• Korean Journal of Agricultural Science
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• v.20 no.2
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• pp.133-144
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• 1993

Calli were induced on microtuber disks of potato(S.tuberosum) infected with three binary vectors transconjugated with C58, A281 and LBA 4404 of Agrobacterium tumefaciens and pBI121. The frequency inducing callus was the highest by infection of C121 carrying pC58 and pBI121, and shoots were differentiated on the calli without any hormonal application. Transformed calli were selected by their resistance to kanamycin and identified by GUS activity. The frequency of callus formation by infection of binary vector strain was affected according to the hormonal application.

• Journal of Korean Society of Forest Science
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• v.98 no.6
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• pp.696-702
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• 2009

Yellow poplar (Liriodendron tulipifera L.) is an insect-pollinated tree species with large, perfect flower, and its seed sets average only about 10 percent naturally. In its controlled pollination, pollination bags are usually taken to prevent unwanted pollination, but bagging is an expensive and time-consuming process. Therefore, this study was conducted to determine the need of pollination bag by estimating how much unintended pollination would occur when different cross methods were applied. Five different pollination methods were applied as follows: 1) natural open pollination (i.e. insect pollination) as a reference, 2) self-pollination; no removing reproductive organs with bagging, 3) open pollination; emasculated(removing sepal, petal and stamen) without bagging, 4) controlled pollination; emasculated with bagging and 5) controlled pollination; emasculated without bagging. Very low value of full seed rate (0.2%) was observed in method 3, it was suggested that removing stamen and petal restrict the activity of pollen vectors like bee. Difference in the full seed rate between method 4 and method 5 was not significant (27.9% versus 24.0%, respectively). Consequently, controlled pollination without bagging might be an alternative method for extensive breeding and mass production of seeds in yellow poplar.

• Journal of Life Science
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• v.22 no.8
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• pp.1018-1023
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• 2012

Snail is a zinc finger transcription factor that induces epithelial-to-mesenchymal transition (EMT), which promotes tumor invasion and metastasis by repressing E-cadherin expression. In addition, Snail restricts the cellular apoptotic response to apoptotic stimuli or survival factor withdrawal; however, its molecular mechanism remains largely unknown. In this study, we have investigated the mechanism underlying Snail-mediated chemoresistance to 5-fluorouracil (5-FU), one of the most widely used anti-cancer drugs. When Snail was overexpressed by doxycycline (DOX) in MCF-7 #5 cells, it inhibited 5-FU-induced apoptotic cell death and switched the cell death mode to necrosis. Snail expression, either by DOX treatment in MCF-7 #5 cells or by the transfection of Snail expression vectors pCR3.1-Snail-Flg, phosphorylation-resistant pCR3.1-S104, and 107A Snail-Flg in MCF-7 cells specifically induced PTEN down-regulation/inactivation and Akt/PKB activation, without affecting ERK1/2 activity. In addition, Snail prominently suppressed 5-FU-induced increases in p53 levels. These findings demonstrate that Snail switches 5-FU-induced apoptosis to necrosis through the activation of Akt/PKB and the down-regulation of p53 levels.

• Journal of Microbiology and Biotechnology
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• v.22 no.3
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• pp.390-399
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• 2012

Endoglucanase gene egIV was cloned from Trichoderma viride AS 3.3711, an important cellulose-producing fungus, by using an RT-PCR protocol. The egIV cDNA is 1,297 bp in length and contains a 1,035 bp open reading frame encoding a 344 amino acid protein with an estimated molecular mass of 35.5 kDa and isoelectronic point (pI) of 5.29. The expression of gene egIV in T. viride AS 3.3711 could be induced by sucrose, corn straw, carboxymethylcellulose (CMC), or microcrystalline cellulose, but especially by CMC. The transcripts of egIV were regulated under these substrates, but the expression level of the egIV gene could be inhibited by glucose and fructose. Three recombinant vectors, pYES2-xegIV, $pYES2M{\alpha}$-egIV, and $pYES2M{\alpha}$-xegIV, were constructed to express the egIV gene in Saccharomyces cerevisiae H158. The CMCase activity of yeast transformants $IpYES2M{\alpha}$-xegIV was higher than that of transformant IpYES2-xegIV or $IpYES2M{\alpha}$-egIV, with the highest activity of 0.13 U/ml at induction for 48 h, illustrating that the modified egIV gene could enhance CMCase activity and that $MF{\alpha}$ signal peptide from S. cerevisiae could regulate exogenous gene expression more effectively in S. cerevisiae. The recombinant EGIV enzyme was stable at pH 3.5 to 7.5 and temperature of $35^{\circ}C$ to $65^{\circ}C$. The optimal reaction condition for EGIV enzyme activity was at the temperature of $55^{\circ}C$, pH of 5.0, 0.75 mM $Ba^{2+}$, and using CMC as substrate. Under these conditions, the highest activity of EGIV enzyme in transformant $IpYES2M{\alpha}$-xegIV was 0.18 U/ml. These properties would provide technical parameters for utilizing cellulose in industrial bioethanol production.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.372-383
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• 2006

Among the approaches to image database management, content-based image retrieval (CBIR) is viewed as having the best support for effective searching and browsing of large digital image libraries. Typical CBIR systems allow a user to provide a query image, from which low-level features are extracted and used to find 'similar' images in a database. However, there exists the semantic gap between human visual perception and low-level representations. An effective methodology for overcoming this semantic gap involves relevance feedback to perform feature re-weighting. Current approaches to feature re-weighting require the number of components for a feature representation to be the same for every image in consideration. Following this assumption, they map each component to an axis in the n-dimensional space, which we call the metric space; likewise the feature representation is stored in a fixed-length vector. However, with the emergence of features that do not have a fixed number of components in their representation, existing feature re-weighting approaches are invalidated. In this paper we propose a feature re-weighting technique that supports features regardless of whether or not they can be mapped into a metric space. Our approach analyses the feature distances calculated between the query image and the images in the database. Two-sided confidence intervals are used with the distances to obtain the information for feature re-weighting. There is no restriction on how the distances are calculated for each feature. This provides freedom for how feature representations are structured, i.e. there is no requirement for features to be represented in fixed-length vectors or metric space. Our experimental results show the effectiveness of our approach and in a comparison with other work, we can see how it outperforms previous work.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.439-448
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• 1996

Extraction and selection of the informative features play a central role in pattern recognition. This paper describes a modified back-propagation algorithm that performs selection of the informative features and trains a neural network simultaneously. The algorithm is mainly composed of three repetitive steps : training, connection pruning, and input unit elimination. Afer initial training, the connections that have small magnitude are first pruned. Any unit that has a small number of connections to the hidden units is deleted,which is equivalent to excluding the feature corresponding to that unit.If the error increases,the network is retraned,again followed by connection pruning and input unit elimination.As a result,the algorithm selects the most im-portant features in the measurement space without a transformation to another space.Also,the selected features are the most-informative ones for the classification,because feature selection is tightly coupled with the classifi-cation performance.This algorithm helps avoid measurement of redundant or less informative features,which may be expensive.Furthermore,the final network does not include redundant parameters,i.e.,weights and biases,that may cause degradation of classification performance.In applications,the algorithm preserves the most informative features and significantly reduces the dimension of the feature vectors whiout performance degradation.

• Parasites, Hosts and Diseases
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• v.59 no.5
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• pp.531-536
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• 2021

The prevalence and intensity of Opisthorchis viverrini metacercariae (OvMc) were investigated in fish from 3 southern administrative regions along the Mekong River in Cambodia, i.e., Phnom Penh, Takeo, and Kandal Provinces from 2017 to 2020. A total of 295 freshwater fish (24 species) were transported to our laboratory with ice and examined using the artificial digestion method. In Phnom Penh, among 4 fish species positive for OvMc, 9 (23.7%) of 38 specimens examined were infected, and their intensity of infection averaged 4.3 metacercariae per infected fish. In Takeo Province, among 10 fish species positive for OvMc, 24 (38.1%) out of 63 fish examined were infected, and their intensity of infection was av. 14.4 metacercariae per infected fish. In particular, all of 3 Osteochilus schlegelii fish examined were infected, and their infection intensity was high, 34.7 metacercariae per fish. In Kandal Province, among 6 fish species positive for OvMc, 46 (90.2%) out of 51 specimens examined were infected, and their infection intensity was 24.0 metacercaraie per infected fish. All fish of Systomus orphoides (n=17), Barbonymus altus (n=14), and Rasbora aurotaenia (n=2) were infected, and their intensity of infection averaged 37.7, 21.6, and 18.5 metacercariae per fish, respectively. Metacercariae of Haplochis yokogawai, Haplorchis taichui, and Centrocestus formosanus were detected in fish from Takeo and Kandal Provinces. From these results, it has been confirmed that a variety of fish species from Phnom Penh, Takeo, and Kandal Provinces are commonly infected with OvMc, and preventive measures to avoid human O. viverrini infection should be performed in Cambodia.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.39-48
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• 2022

The main purpose of the work is to analyze modern innovative educational practices in the field of culture and art and their effectiveness in the context of the spread of digitalization trends. The study used general scientific theoretical methods of analysis, synthesis, analogy, comparative, induction, deduction, reductionism, and a number of others, allowing you to fully understand the pattern of modern modernization processes in a long historical development and demonstrate how the rejection of the negativity of progress allows talented artists to realize their own potential. The study established the advantages and disadvantages of involving innovative technologies in the educational process on the example of European experience and outlined possible ways of implementing digitalization processes in Ukrainian institutions of higher education, formulated the main difficulties encountered by teachers and students in the use of technological innovation in the pandemic. The rapid development of digital technologies has had a great impact on the sphere of culture and art, both visual, scenic, and musical in all processes: creation, reproduction, perception, learning, etc. In the field of art education, there is a synthesis of creative practices with digital technologies. In terms of music education, these processes at the present stage are provided with digital tools of specially developed software (music programs for composition and typing of musical text, recording, and correction of sound, for quality listening to the whole work or its fragments) for training programs used in institutional education and non-institutional learning as a means of independent mastering of the theory and practice of music-making, as well as other programs and technical tools without which contemporary art cannot be imagined. In modern stage education, the involvement of video technologies, means of remote communication, allowing realtime adjustment of the educational process, is actualized. In the sphere of fine arts, there is a transformation of communicative forms of interaction between the teacher and students, which in the conditions of the pandemic are of two-way communication with the help of information and communication technologies. At this stage, there is an intensification of transformation processes in the educational industry in the areas of culture and art.

• Korea Trade Review
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• v.48 no.3
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• pp.69-88
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• 2023

This study analyzes the dynamic characteristics of cargo volume (demand), ship fleet (supply), and freight rate (price) of container, dry bulk, and tanker shipping markets by using the VAR and VECM models. This analysis is expected to enhance the statistical understanding of market dynamics, which is perceived by the actual experiences of market participants. The common statistical patterns, which are all shown in the three shipping markets, are as follows: 1) The Granger-causality test reveals that the past increase of fleet variable induces the present decrease of freight rate variable. 2) The impulse-response analysis shows that cargo shock increases the freight rate but fleet shock decreases the freight rate. 3) Among the three cargo, fleet, and freight rate shocks, the freight rate shock is overwhelmingly largest. 4) The comparison of adjR² reveals that the fleet variable is most explained by the endogenous variables, i.e., cargo, fleet, and freight rate in each of shipping markets. 5) The estimation of co-integrating vectors shows that the increase of cargo increases the freight rate but the increase of fleet decreases the freight rate. 6) The estimation of adjustment speed demonstrates that the past-period positive deviation from the long-run equilibrium freight rate induces the decrease of present freight rate.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.