• Title/Summary/Keyword: artificial chemical

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Study on the Extracted Cellulose Powder from Natural Resources for Artificial Diet of Silkworm, Bombyx mori (I) (누에 인공사료의 Cellulose원 개발에 관한 연구(I))

  • 김주읍;박광의;성수일;유재복
    • Journal of Sericultural and Entomological Science
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    • v.19 no.1
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    • pp.5-7
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    • 1977
  • On the purpose of exploiting cellulose resourse which is needed for artificial diet of silkworms, mulberry branch, eastern cotton wood branch, pitch pine pulp, poplar pulp, chaff, sawdust and rice straw were examined. Among the matters above mentioned. mulberry branch and pitch pine pulp were found to be replaceable as cellulose component in the artificial diet. By means of some chemical treatments, it is found that one of the extracted cellulose powder from mulberry branches is more useful in the larval growth.

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Development of Artificial Skin from Chitosan Derivatives

  • Yong-Don Won;Chang-Kook Lee;Beung-Ho Ryu
    • Journal of Life Science
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    • v.9 no.1
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    • pp.17-21
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    • 1999
  • Chitosan derivitives, a sulfated N-acetylchitosan was synthesized, and artificial skin of sulfated N-acetylchitosan and N-carboxyl butyl chitosan were investigated. Sulfated derivatives of chitosan were analyzed by {TEX}${13}^C${/TEX}-NMR and the structure on N-acetyl chitosan 3,6-O-disulfate were confirmed. Rabbits underwent a midline laparotomy followed either by a bilateral peritoneal sidewall abraison(3.0×1.5cm). The injured surface was then covered with 0.2mm thick sulfated N-acetyl chitosan membrane. Sulfated N-acetyl chitosan membrane was found to reduce postsurgical bleeding after abraison of peritoneal surface treated with sulfated N-acetyl chitosan membrane. Sulfated N-acetyl chitosan implanted rabbit showed quick wound healing than N-carboxybutyl chitosan. With a sterilization procedure of chemical sterilization, sulfated N-acetyl chitosan seem to be better substitutes than N-carboxybutyl chitosan.

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Evaluation of Thermal Embrittlement Susceptibility in Cast Austenitic Stainless Steel Using Artificial Neural Network (인공신경망을 이용한 주조 스테인리스강의 열취화 민감도 평가)

  • Kim, Cheol;Park, Heung-Bae;Jin, Tae-Eun;Jeong, Ill-Seok
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.4
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    • pp.460-466
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    • 2004
  • Cast austenitic stainless steel is used for several components, such as primary coolant piping, elbow, pump casing and valve bodies in light water reactors. These components are subject to thermal aging at the reactor operating temperature. Thermal aging results in spinodal decomposition of the delta-ferrite leading to increased strength and decreased toughness. This study shows that ferrite content can be predicted by use of the artificial neural network. The neural network has trained teaming data of chemical components and ferrite contents using backpropagation learning process. The predicted results of the ferrite content using trained neural network are in good agreement with experimental ones.

Electro-active Polymer and Dielectric Elastomer Technology for Haptic Interface, Muscular Enhancement, and Tunable Optical Components (전기가변 고분자 소재를 이용한 응용소자)

  • Yoon, J.W.;Park, S.K.;Mun, S.
    • Electronics and Telecommunications Trends
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    • v.34 no.4
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    • pp.108-116
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    • 2019
  • Electro-active polymers and dielectric elastomers have many intriguing properties that enable smart interfaces and electrically tunable optical systems, such as haptic feedback devices, artificial muscles, and expansion-tunable optical elements. These device classes are of great interest owing to their promising roles in next-generation technologies including virtual or augmented reality, human sensing and muscular enhancement, and artificial skins. In this report, we review basic principles, current state-of-the-art techniques, and future prospects of electro-active and dielectric elastomer technology. We describe chemical and physical properties of the most promising polymer substances, essential elementary architectures for artificial muscle-like functionalities, and their applications to haptic interfaces, muscular enhancement, and focus-tunable optical elements.

A Study for Improving Properties of Antiwashout Underwater Concrete Mixed with Mineral Admixtures (광물질 혼화재를 혼합한 수중불분리성 콘크리트의 물성 향상을 위한 연구)

  • 문한영;신국재;이창수
    • Journal of the Korea Concrete Institute
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    • v.14 no.3
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    • pp.409-419
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    • 2002
  • Nowadays, antiwashout underwater concrete is widely used for constructing underwater concrete structures but they, especially placed in marine environment, can be easily attacked by chemical ions such as SO$\^$2-/$\_$4/ Cl$\^$-/ and Mg$\^$2+/, so the quality and capability of concrete structures go down. In this paper, to solve and improve those matters, flyash and GGBFS(ground granulated blast furnace slag) were used as partial replacements for ordinary portland cement. As results of experiments for fundamental properties of antiwashout underwater concrete containing 10, 20, 30% of flyash and 40, 50, 60 % of GGBFS respectively, setting time, air contents, suspended solids and pH value were satisfied with the "Standard Specification of Antiwashout Admixtures for Concrete" prescribed by KSCE, and also slump flow, efflux time and elevation of head were more improved than that of control concrete. From the compressive strength test, it was revealed that the antiwashout underwater concrete containing mineral admixtures(flyash and GGBFS) is more effective for long term compressive strength than control concrete. An attempt to know how durable when they are under chemical attack has also been done by immersing in chemical solutions that were x2 artificial seawater, 5 % sulphuric acid solution, 10%, sodium sulfate solution and 10% calcium chloride solution. After immersion test for 91days, XRD analysis was carried out to investigate the reactants between cement hydrates and chemical ions and some crystalline such as gypsum ettringite and Fridel′s salt were confirmed.

Comparative Study of Estimation Methods of the Endpoint Temperature in Basic Oxygen Furnace Steelmaking Process with Selection of Input Parameters

  • Park, Tae Chang;Kim, Beom Seok;Kim, Tae Young;Jin, Il Bong;Yeo, Yeong Koo
    • Korean Journal of Metals and Materials
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    • v.56 no.11
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    • pp.813-821
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    • 2018
  • The basic oxygen furnace (BOF) steelmaking process in the steel industry is highly complicated, and subject to variations in raw material composition. During the BOF steelmaking process, it is essential to maintain the carbon content and the endpoint temperature at their set points in the liquid steel. This paper presents intelligent models used to estimate the endpoint temperature in the basic oxygen furnace (BOF) steelmaking process. An artificial neural network (ANN) model and a least-squares support vector machine (LSSVM) model are proposed and their estimation performance compared. The classical partial least-squares (PLS) method was also compared with the others. Results of the estimations using the ANN, LSSVM and PLS models were compared with the operation data, and the root-mean square error (RMSE) for each model was calculated to evaluate estimation performance. The RMSE of the LSSVM model 15.91, which turned out to be the best estimation. RMSE values for the ANN and PLS models were 17.24 and 21.31, respectively, indicating their relative estimation performance. The essential input parameters used in the models can be selected by sensitivity analysis. The RMSE for each model was calculated again after a sequential input selection process was used to remove insignificant input parameters. The RMSE of the LSSVM was then 13.21, which is better than the previous RMSE with all 16 parameters. The results show that LSSVM model using 13 input parameters can be utilized to calculate the required values for oxygen volume and coolant needed to optimally adjust the steel target temperature.

The effect of two artificial salivas on the adhesion of Candida albicans to heat-polymerized acrylic resin

  • Oncul, Burcin;Karakis, Duygu;Al, Funda Dogruman
    • The Journal of Advanced Prosthodontics
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    • v.7 no.2
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    • pp.93-97
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    • 2015
  • PURPOSE. Xerostomia can diminish the quality of life, leads to changes in normal chemical composition of saliva and oral microbiata, and increases the risk for opportunistic infections, such as Candida albicans. Various artificial salivas have been considered for patients with xerostomia. However, the knowledge on the antifungal and antiadhesive activity of artificial saliva substitutes is limited. The aim of the present study was to evaluate influence of two artificial salivas on the adhesion of Candida albicans to the polymethylmethacrylate disc specimens. MATERIALS AND METHODS. Two commercial artificial salivas (Saliva Orthana and Biotene Oral Balance Gel) were selected. 45 polymethylmethacrylate disc specimens were prepared and randomly allocated into 3 groups; Saliva Orthana, Biotene-Oral Balance gel and distilled water. Specimens were stored in the artificial saliva or in the sterile distilled water for 60 minutes at $37^{\circ}C$. Then they were exposed to yeast suspensions including Candida albicans. Yeast cells were counted using ${\times}40$ magnification under a light microscope and data were analysed. RESULTS. Analysis of data indicated statistically significant difference in adhesion of Candida albicans among all experimental groups (P=.000). Findings indicated that Saliva Orthana had higher adhesion scores than the Biotene Oral Balance gel and distilled water (P<.05). CONCLUSION. In comparison of Saliva Orthana, the use of Biotene Oral Balance Gel including lysozyme, lactoferrin and peroxidase may be an appropriate treatment method to prevent of adhesion of Candida albicans and related infections in patients with xerostomia.

Hemodynamic study of Pneumatic Artificial Heart Implanted in Calves (송아지에 이식한 공기구동형 인공심장의 혈역학적 연구)

  • 박표원
    • Journal of Chest Surgery
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    • v.23 no.3
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    • pp.438-451
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    • 1990
  • Pneumatic total artificial heart[TAH] has been clinically applied for the purpose of permanent or temporary use followed by cardiac transplantation in the patients with end stage heart diseases. In spite of the good durability of the pneumatic TAH, thrombus formation, bleeding and infection resulted in death. The Tomasu heart, which is a type of pneumatic TAH, was used in this study. This model is a modified Jarvik heart and consists of atrial cuffs, outflow vascular grafts and thin-layer seamless diaphragm type of ventricles. Cardiac outputs of the left artificial heart were measured by Donovan`s mock circulation under variable conditions of driving parameters, and an experimental artificial heart implantation was performed in 4 calves to observe the changes of hemodynamic parameters in early postoperative period and hematologic and bio-chemical changes in a long-term survival case. In the mock circulation test, cardiac output of the heart was increased with the increase of the left atrial pressure and left driving pressure. Maximum cardiac output was obtained at the heart rate of 120 to 130/min and percent systole of 40 to 45Zo under the condition of a constant left driving pressure of 180mmHg and left atrial pressure of 10mmHg. During the first 24 hours of TAH pumping, driving pressure ranged from 178$\pm$5mmHg to 187$\pm$8mmHg for the left heart and from 58$\pm$6mmHg to 78$\pm$28mmHg for the right heart. The Mean arterial pressure significantly increased between 2 and 8 hours after the start of pumping. The survival time ranged from 27 hours to 46 days. The causes of death were respiratory failure in 2 cases, mechanical valve failure in one, and left ventricular outflow obstruction due to thrombus in a 46-day survival case. This study demonstrated that Tomasu artificial heart operated effectively during the first 24 hours of artificial heart pumping, but thrombus formation around the valve holding area was the main problem in long-term survival case.

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A fault diagnostic system for a chemical process using artificial neural network (인공 신경 회로망을 이용한 화학공정의 이상진단 시스템)

  • 최병민;윤여홍;윤인섭
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10a
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    • pp.131-134
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    • 1990
  • A back-propagation neural network based system for a fault diagnosis of a chemical process is developed. Training data are acquired from FCD(Fault-Consequence Digraph) model. To improve the resolution of a diagnosis, the system is decomposed into 6 subsystems and the training data are composed of 0, 1 and intermediate values. The feasibility of this approach is tested through case studies in a real plant, a naphtha furnace, which has been used to develop a knowledge based expert system, OASYS (Operation Aiding expert SYStem).

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