The visual implementation of 3-dimensional national environment is focused by the requirement and importance in the fields such as, national development plan, telecommunication facility deployment plan, railway construction, construction engineering, spatial city development, safety and disaster prevention engineering. The currently used DEM system using contour lines, which embodies national geographic information based on the 2-D digital maps and facility information has limitation in implementation in reproducing the 3-D spatial city. Moreover, this method often neglects the altitude of the rail way infrastructure which has narrow width and long length. There it is needed to apply laser measurement technique in the spatial target object to obtain accuracy. Currently, the LiDAR data which combines the laser measurement skill and GPS has been introduced to obtain high resolution accuracy in the altitude measurement. In this paper, we first investigate the LiDAR based researches in advanced foreign countries, then we propose data a generation scheme and an algorithm for the optimal manage and synthesis of railway facility system in our 3-D spatial terrain information. For this object, LiDAR based height data transformed to DEM, and the realtime unification of the vector via digital image mapping and raster via exactness evaluation is transformed to make it possible to trace the model of generated 3-dimensional railway model with long distance for 3D tract model generation.
In this study design information was separately defined form general product information and thus factors reflected in product design ion the basis of values and roles were extracted. The following is a classification of 5 different types of design factors divided according to their disposition. ·Innovation factor - element which previously did not exist or element related with explicit reformation ·Open factor - active element which not only improves current performance but also induces new functions through understanding of usage situations and new possibilities. ·Anterior factor - element which prolongs and develops the early development requirements of products through C.I. and P.I. related elements and characteristics of previous models and design strategy. Self-evidence factor - element related with function visualization through product structure which may make possible the consolidation of shape and function. Rigid factor - element, based on the human factors engineering, related with the safety and efficiency of users. This classification was obtained by defining major characteristics of products considering the target consumer and market characteristics. In this classification factor structuring design process which efficiently deducted a differentiated final product by synthesizing factors of higher importance as dominant factors was proposed. With this kind of factor structuring process, product differentiation may be achieved by bestowing individual characteristics to each product by combining design dominant factors associated with the product for a specific purpose from the stages of product concept development. Moreover, this may be used as an approach to actively correspond to the various and specific demands of the comsumer.
In this paper, I would like to explore the possibility that the nature of place assimilation can be captured in terms of the OCP within the Optimality Theory (Mccarthy & Prince 1999. 1995; Prince & Smolensky 1993). In derivational models, each assimilatory process would be expressed through a different autosegmental rule. However, what any such model misses is a clear generalization that all of those processes have the effect of avoiding a configuration in which two consonantal place nodes are adjacent across a syllable boundary, as illustrated in (1):(equation omitted) In a derivational model, it is a coincidence that across languages there are changes that have the result of modifying a structure of the form (1a) into the other structure that does not have adjacent consonantal place nodes (1b). OT allows us to express this effect through a constraint given in (2) that forbids adjacent place nodes: (2) OCP(PL): Adjacent place nodes are prohibited. At this point, then, a question arises as to how consonantal and vocalic place nodes are formally distinguished in the output for the purpose of applying the OCP(PL). Besides, the OCP(PL) would affect equally complex onsets and codas as well as coda-onset clusters in languages that have them such as English. To remedy this problem, following Mccarthy (1994), I assume that the canonical markedness constraint is a prohibition defined over no more than two segments, $\alpha$ and $\beta$: that is, $^{*}\{{\alpha, {\;}{\beta{\}$ with appropriate conditions imposed on $\alpha$ and $\beta$. I propose the OCP(PL) again in the following format (3) OCP(PL) (table omitted) $\alpha$ and $\beta$ are the target and the trigger of place assimilation, respectively. The '*' is a reminder that, in this format, constraints specify negative targets or prohibited configurations. Any structure matching the specifications is in violation of this constraint. Now, in correspondence terms, the meaning of the OCP(PL) is this: the constraint is violated if a consonantal place $\alpha$ is immediately followed by a consonantal place $\bebt$ in surface. One advantage of this format is that the OCP(PL) would also be invoked in dealing with place assimilation within complex coda (e.g., sink [si(equation omitted)k]): we can make the constraint scan the consonantal clusters only, excluding any intervening vowels. Finally, the onset clusters typically do not undergo place assimilation. I propose that the onsets be protected by certain constraint which ensures that the coda, not the onset loses the place feature.
Among poly aromatic hydrocarbons, dioxin and PCBs are the most controversial environmental pollutants in our modern life. These pollutants are known as human carcinogens, and liver is the most sensitive target in animal cancer models. Specific aims of the study were focused on the mechanism of carcinogenesis in hepatocytes and the structure-activity relation among these diverse environmental chemicals. Because key mechanisms of dioxin-induced carcinogenesis in human epithelial cell model are the alteration of signal transduction pathway and PKC isoforms, the alteration of the signal transduction pathways and other factors associated with carcinogenesis were studied. Rat hepatocytes cultured under the sandwich protocols were exposed with the various concentration of dioxins and PCBs, and signal transduction pathway, protein kinase C isoforms, oxidant stress, and apoptotic nuclei were evaluated. Since it is important to understand the structure-activity relation among these chemicals to properly assess the carcinogenic potentials, the study analyzed the parameters associated with carcinogenic processes, based on their structural characteristics. In addition, signal transduction pathways and PKC isoforms involved in inhibition of UV-induced apoptosis were also analyzed to elaborate the tumor promotion mechanism of these chemicals. Induction of apoptosis by UV irradiation was optimal at $60\;J/m^2$ in primary hepatocyte in culture. Compared to non coplanar PCBs such as PCB 114 and PCB 153, coplanar PCBs such as PCB 77 and PCB126 showed a stronger inhibition of apoptosis induced by UV irradiation. Production of reactive oxygen species (ROS) was more stimulated by non-coplanar PCBs than coplanar PCBs with the most potent induction of ROS by chlorinated non-coplanar PCB. As compared to the level of induction by PCB126, non-coplanar PCB153 showed a higher increase of intracellular concentrations. Besides the alteration of intracellular calcium concentration, translocation of PKC from cytosolic fraction to membrane fraction was clearly observed upon the exposure of non-coplanar PCB. Taken together, the present study demonstrated that there is a potent structure-activity relationship among PCB congeners and the mechanism of PAH-induced carcinogenesis is structure-specific. The study suggested that more diverse pathways of PAH-induced carcinogenesis should be taken into account beyond the boundary of Ah receptor dogma to assess the health impact of PAH with more accuracy.
To cope with the limits of conventional O-D trip matrix collecting methods, several approaches have been developed. One of them is bilevel Programming method Proposed by Yang(1995), which uses Sensitivity Analysis Based(SAB) algorithm to solve Generalized Least Square(GLS) problem. However, the SAB a1gorithm has revealed two critical short-comings. The first is that when there exists a significant difference between target O-D matrix and true O-D matrix, SAB algorithm may not produce correct solution. This stems from the heavy dependance on the historical O-D information, in special when gravel Patterns are dramatically changed. The second is the assumption of iterative linear approximation to original Problem. Because of the approximation, SAB algorithm has difficulty in converging to Perfect Stackelberg game condition. So as to avoid the Problems. we need a more robust and stable solution method. The main purpose of this Paper is to show the problem of the dependency of Previous models and to Propose an alternative solution method to handle it. The Problem of O-D matrix estimation is intrinsically nonlinear and nonconvex. thus it has multiple solutions. Therefore it is necessary to require a method for searching globa1 solution. In this paper, we develop a solution algorithm combined with genetic algorithm(GA) , which is widely used as probabilistic global searching method To compare the efficiency of the algorithm, SAB algorithm suggested by Yang et al. (1992,1995) is used. From the results of numerical example, the Proposed algorithm is superior to SAB algorithm irrespective of travel patterns.
Background : Cyclooxygenase is the main target enzyme for the nonsteroidal anti inflammatory drugs (NSAIDs) that have been shown to suppress carcinogenesis in both experimental models and epidemiological studies. COX-2 plays an important role in solid tumor growth, invasiveness and angiogenesis, through, in part, the synthesis of prostaglandins, such as prostaglandin E2 (PGE2). In this study, the prognostic significance of an increase in COX-2 expression in lung cancer samples was evaluated. Material and Methods : The expression of COX-2, by immunohistochemistry, was studied in paraffin-embedded tumor blocks obtained from 84 patients(male 67, female 17, with a mean age of 63, ranging from 34 to 84 years) who had undergone surgery at Wonkwang University Hospital, between 1997 and 2002. For the evaluation of the relationships between COX-2 expression, and the clinical stage, metastasis to lymph nodes and survival, those cases showing the respective antigen expression in >10% of the tumor cells were considered positive. Result : Of the 84 patients, 61 (73%) exhibited more than 10% COX-2 immunoreactivities in the tumor and normal cells, whereas the remaining 23 showed no increase in the expression of COX-2. There was no significant relationship between the increased expression of COX-2 and the disease stage(p=0.1002) or cell type(p=0.152). The median survival was longer for the patients with a negative, compared to positive, COX-2 expression(36 compared to 24 months, p<0.05). The two year-survival rate was also higher in the patients with a negative COX-2 expression (78%) than those with a positive expression (47%, Kaplan-Meier, Log Rank, p < 0.05). Conclusion : The median survival was longer in the patients with a negative, compared to positive, COX-2 expression was longer than those with positive COX-2, having undergone complete resection due to primary non-small cell lung cancer.
High dynamic range (HDR) images represent a far wider numerical range of exposures than common digital images. Thus it can accurately store intensity levels of light found in the specific scenes generated by light sources in the real world. Although a kind of professional HDR cameras which support fast accurate capturing has been developed, high costs prevent from employing those in general working environments. The common method to produce a HDR image with lower cost is to take a set of photos of the target scene with a range of exposures by general purpose cameras, and then to transform them into a HDR image by commercial softwares. However, the method needs complicate and accurate camera calibration processes. Furthermore, creating HDR environment maps which are used to produce high quality imaging contents includes delicate time-consuming manual processes. In this paper, we present an automatic HDR panorama environment map generating system which was constructed to make the complicated jobs of taking pictures easier. And we show that our system can be effectively applicable to photo-realistic compositing tasks which combine 3D graphic models with a 2D background scene using image-based lighting techniques.
Objective: Average daily gain (ADG) is an important target trait of pig breeding programs. We aimed to identify single nucleotide polymorphisms (SNPs) and genomic regions that are associated with ADG in the Duroc pig population. Methods: We performed a genome-wide association study involving 390 Duroc boars and by using the PorcineSNP60K Beadchip and two linear models. Results: After quality control, we detected 3,5971 SNPs, which included seven SNPs that are significantly associated with the ADG of pigs. We identified six quantitative trait loci (QTL) regions for ADG. These QTLs included four previously reported QTLs on Sus scrofa chromosome (SSC) 1, SSC5, SSC9, and SSC13, as well as two novel QTLs on SSC6 and SSC16. In addition, we selected six candidate genes (general transcription factor 3C polypeptide 5, high mobility group AT-hook 2, nicotinamide phosphoribosyltransferase, oligodendrocyte transcription factor 1, pleckstrin homology and RhoGEF domain containing G4B, and ENSSSCG00000031548) associated with ADG on the basis of their physiological roles and positional information. These candidate genes are involved in skeletal muscle cell differentiation, diet-induced obesity, and nervous system development. Conclusion: This study contributes to the identification of the casual mutation that underlies QTLs associated with ADG and to future pig breeding programs based on marker-assisted selection. Further studies are needed to elucidate the role of the identified candidate genes in the physiological processes involved in ADG regulation.
Objectives: Notopterygium incisum(N. incisum) and Saposhnikovia divaricata(S. divaricata) have been clinically used in traditional oriental medicine for treatment of inflammatory diseases. Also, a herbal mixture prepared with N. incisum and S. divaricata has been strongly linked to the anti-inflammatory effect. In this study, we evaluate the synergistic anti-inflammatory effect of N. incisum and S. divaricata. Methods: For evaluating the anti-inflammatory activity of a herbal mixture of N. incisum and S. divaricata in vivo, we measured the changed ear thickness in 12-O-tetradecanoyl-phorbol-13-acetate(TPA)-induced mouse ear edema model after topical application of herbal mixture. In addition, the levels of markers for inflammation, such as tumore necrosis factor (TNF)-${\alpha}$, interleukin (IL)-1${\beta}$, and nitric oxide(NO), were determined by ELISA assay in lipopolysaccharide-stimulated Raw 264.7 cells. Results: We reported that water extracts of N. incisum and S. divaricata combination significantly inhibited the mouse ear edema induced by TPA. Moreover, the water extracts of N. incisum and S. divaricata combination exhibited synergistic effects in down-regulating IL-1${\beta}$ level, but not TNF-${\alpha}$ and NO. Conclusions: These results suggest that combined treatment of N. incisum and S. divaricata, based on seven methods in prescription compatibility, has a synergistic effect in down-regulating inflammatory response both in vivo and in vitro models. Especially, it seems that IL-1${\beta}$ is a one of main target of the mixture of N. incisum and S. divaricata on anti-inflammatory activity.
Kim, Donghyun;Kim, Jungwook;Kwak, Jaewon;Necesito, Imee V.;Kim, Jongsung;Kim, Hung Soo
Journal of Wetlands Research
/
v.22
no.2
/
pp.106-112
/
2020
Wetlands play an important function and role in hydrological, environmental, and ecological, aspects of the watershed. Water level in wetlands is essential for various analysis such as for the determination of wetland function and its effects on the environment. Since several wetlands are ungauged, research on wetland water level prediction are uncommon. Therefore, this study developed a water level prediction model using multiple regression analysis, principal component regression analysis, artificial neural network, and DNN to predict wetland water level. Geumjeong-Mountain Wetland located in Yangsan-city, Gyeongsangnam-do province was selected as the target area, and the water level measurement data from April 2017 to July 2018 was used as the dependent variable. On the other hand, hydrological and meteorological data were used as independent variables in the study. As a result of evaluating the predictive power, the water level prediction model using DNN was selected as the final model as it showed an RMSE value of 6.359 and an NRMSE value of 18.91%. This research study is believed to be useful especially as a basic data for the development of wetland maintenance and management techniques using the water level of the existing unmeasured points.
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