• Proceedings of the Korean Journal of Food and Nutrition Conference
• /
• 2000.12a
• /
• pp.29-34
• /
• 2000

산업 발달에 따라 날로 많은 식품들이 새롭게 개발되어지고 있다. 또한 이와 병행해서 식품으로 인한 알레르기 발생 빈도도 날로 증가하고 있으며 그 증상 또한 점차 심화되고 있는 것이 세계적인 추세이다. 우리나라도 예외는 아니어서 일반 알레르기 환자뿐 아니라 식품으로 인한 알레르기 환자들이 점차 증가됨이 보고되어지고 있다. 농산물 시장의 수입개방이후 우리나라에는 많은 해외 농산물이 수입되어지고 있으며 그 중 작년 한해의 경우 총 수입 농산물의 10%를 넘는 유전자 재조합 농산물이 우리나라에 수입되어진 것으로 통계 보고되어졌다. 이러한 관점에서 알레르기 환자의 증가와 새로운 식품 (특히 유전자 재조합 식품)의 증가에는 서로 관련성이 있을 것으로 추측되어지고 있어 (새로운) 식품에 대한 알레르기성의 예측과 관리가 필요한 실정이다. 이에 몇몇 발표된 유전자 재조합 식품에 관련된 알레르기성 검사 논문들과 실험실에서 이루어진 연구 결과들을 중심으로 유전자 재조합 식품의 알레르기 위험성에 대해 알아보고자 한다. 일반적으로 식품의 단백질이 알레르겐(allergen)으로 작용하기 위해서는 먼저 소화효소에 의해 분해되어지고 장에서 흡수되어져서 immunopotent cell에 의해 process 되어 immune system에 present 되어져야 한다. 따라서 단백질로 인한 알레르기 반응은 그 단백질의 자연적 형태 뿐만이 아니라 소화 효소에 분해된 단편들의 구조 또는 다른 알레르겐 단백질과의 유사 구조로 인한 교차 반응에 의해 발생함을 기억해야 한다. 식품 단백질 중 어떤 단백질이 알레르겐으로 작용하는가에 대한 특이성 조사에 많은 관심이 집중되어지고 있지만 아직까지는 대략 다섯 개 정도의 일반적인 특성으로서 요약되어질 수 있다. 그러나 이러한 대략의 특성에 적용되지 않는 식품 알레르겐도 많음을 잊어서는 안 될 것이다. 알레르겐으로 작용하는 식품 단백질의 일반적 특성 1. 좋은 수용성 2. 식품내에 많은 부분을 차지하는 주 단백질이 주 알레르겐으로 작용 3. 단백질내에 하나 이상의 IgE-binding site 존재 4. 위장액에 대한 저항성 5. 10～70 kDa 크기 유전자 재조합 기술이란 말 그대로 유전자를 인위적으로 새롭게 조합하는 기술로 이전의 기술로는 불가능했던 유전적 변형을 농작물과 동물에 가능하게 했으며 이로 인해 유전적으로 변형된 식용 동식물의 개발이 가능하게 되었다. 새로운 유전인자를 개체에 삽입함으로 새로운 단백질이 발현 될수 있고 그로 인해 1) 해충과 질병에 대한 저항성 증가, 2) 화학 제초제에 대한 새로운 저항성 부여, 3) 식품의 저장성 향상, 4) 식품의 영향적 보충/향상 등의 이점을 얻을 수 있다 (표 1). 세계적으로 유전자 재조합 된 새로운 농산물의 재배는 날로 증가추세에 있으며 그 중에서 가장 많은 부분을 차지하는 농산물로 soybean을 들 수 있으며 (표 2) soybean을 중심으로 그 알레르기성의 변화가 연구 조사된 몇 가지 예를 살펴보고자 한다. (표 3)에 요약된 soybean중 첫 번째 경우는 재초제에 대한 저항성을 높여주기 위해 Agrobacterium에 존재하는 EPSPS라는 단백질을 콩에서 발현하도록 찬 유전자 재조합 된 콩의 경우이다. 이 콩의 경우에는 첫째. 이전된 새로운 단백질 EPSPS가 다른 여러 식물에 이미 존재하고 있는 단백질로서 우리가 이미 이러한 식품을 섭취할 때 이 단백질도 같이 섭취해오고 있었다는 점, 둘째. 이 단백질이 소화액 분해 실험에서 짧은 시간내에 분해가 되었다는 점, 셋째. 재조합 된 콩과 자연 콩이 성분 분석에서 차이를 나타내지 않았다는 점, 네 번째. 쥐를 통한 다양섭취 실험에서 아무런 이상 반응이 없었다는 점등의 결과를 기준으로 알레르기에 대한 개별 검사 없이 안전한 콩으로 결론짓고 있다. 영양성을 높이기 위해 Brazil nut에서 methionine 함량이 풍부한 2s albumine을 콩에서 발현하도록 한 두 번째 유전자 재조합 콩의 경우 이전된 단백질 때문에 Brazil nut에 알레르기 반응을 일으키는 알레르기 환자들을 조사한 결과 역시 재조합 된 콩에도 알레르기 반응을 일으켰다는 보고이다. Brazil nut에서 콩으로 이전된 단백질이 Brazil nut에서의 알레르기성을 그대로 유지한 점을 볼 때 새로운 단백질이 어디에서 유래하는가가 중요함을 잘 보여준 연구이다 세 번째 콩의 경우 역시 영양성을 높여주기 위해 corn에서 10 kDa과 HSZ 단백질을 콩에서 발현하도록 유전자 재조합했는데 이 콩의 경우는 알레르기 환자들이 유전자 재조합 된 콩과 자연 콩에 반응의 차이를 나타내지 않았다는 결과 보고이다. 위의 세 실험 결과들을 종합해 볼 때 무엇보다도 새롭게 발현된 단백질이 원래 어떤 성질을 갖고 있으며 어디에서 유래했는지가 알레르기성 조사에 중요한 역할을 한다 할 수 있겠다. 또한 유전자 재조합된 식품들은 알레르기 환자들을 위해 표기되어져야 할 것인데 이를 위한 알레르기성 검사 실험은 공공단체를 통해 이루어져야 할 것이며 환자들마다 알레르겐으로 작용하는 단백질의 인식부위(epitope)가 다를 수 있기 때문에 적어도 10명 이상의 알레르기 환자들이 조사되어져서 검사가 이루어져야 할 것이다. 환자들의 혈청을 통한 in vitro 실험에서는 ELISA, RAST, immunoblotting과 같은 검사 방법들이 적용될 수 있고, 그 결과가 음성인 경우에 그 다음 단계로 in vivo 실험에서는 직접 환자의 피부반응검사 (skin prick test)나 DBPCFC (double-blind placebo-controlled food challenge) 검사 방법을 통해 확인되어져서 이 모든 경우가 음성인 경우와 하나라도 양성인 경우를 구별하여 식품에 표기함으로 알레르기 환자들의 유전자 재조합 식품에 대한 안전성이 보장되어져야 할 것이다.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.24 no.3
• /
• pp.245-252
• /
• 2004

Experiment was carried out to find the fertilizing effects of 8 different application rates of swine compost fermented with sawdust(SCS) including Chemical fertilizer(CF) on forage yield and soil chemical characteristics of mixed pastures sown in Sep. 1993 at National Livestock Research Institute, RDA., in Suwon during low years. It was arranged in a randomized complete block design with three replicates. Dry matter yield were shown at similar among treatments except Control and $50\%$ SCS of standard amount plot. In botanical composition, the legume and weeds percentages of each treatment were increased as advancing year. The final year's legume percentage were high in line with SCS fertilizing plots($39\%{\sim}43\%$), SCS + CF plots($30\%{\sim}41\%$) and CF plot($32\%$). In productions of TDN, NE and crude protein yield, SCS or SCS($75\%$) + CF($25\%$) were nearly same comparing those of CF, respectively. Phosphate, potassium, magnesium contents and K/(Ca + Mg) except calcium contents of those SCS fertilizing plots in plant were generally high with comparing CF. Those contents were proportional according to the fertilizing amount These result indicate the possibility to substitute chemical fertilizer for SCS($75\%$, 25ton/ha) + CF, $25\%$) as manure-N 210 kg/ha, but might be considered accumulation phosphate in the soil.

• Journal of Food Hygiene and Safety
• /
• v.35 no.4
• /
• pp.291-303
• /
• 2020

Marine organism-derived toxins have negative effects not only on human health but also in aquaculture, fisheries, and marine ecosystems. However, traditional analytical methods are insufficient in preventing this threat. In this paper, we reviewed new rapid methods of toxin detection, which have been improved by adopting diverse types of nanomaterials and technologies. Moreover, we herein describe the main strategies for toxin detection and their related sensing performance. Notably, to popularize and commercialize these newly developed technologies, simplifying the process of pre-treating real samples real samples is very important. As part of these efforts, numerous studies have reported pretreatment methods based on the antibody-immobilized magnetic nanoparticles, and some cases have applied nanoparticles to enhance the sensing performance by utilizing the intrinsic catalytic activity. Furthermore, some reports have introduced fluorescent nanoparticles, such as quantum dots, to represent the lower detection limits of conventional enzyme-based colorimetric methods and lateral flow assays. Some studies using electrochemical measurements based on aptamer-nanoparticle complexes have also been announced. In addition, as the response to new toxins generated by changes in the marine environment is still lacking, further research on diagnostic and detection is also greatly needed for these kinds of marine toxins and their derivatives.

• Computational Structural Engineering
• /
• v.7 no.3
• /
• pp.95-103
• /
• 1994

The safety related components in the nuclear power plant should be designed to withstand the seismic load. Among these components the integrity of reactor internals under earthquake load is important in stand points of safety and economics, because these are classified to Seismic Class I components. So far the modelling methods of reactor internals have been investigated by many authors. In this paper, the dynamic behaviour of reactor internals of Yong Gwang 1&2 nuclear power plants under SSE(Safe Shutdown Earthquake) load is analyzed by using of the simpled Global Beam Model. For this, as a first step, the characteristic analysis of reactor internal components are performed by using of the finite element code ANSYS. And the Global Beam Model for reactor internals which includes beam elements, nonlinear impact springs which have gaps in upper and lower positions, and hydrodynamical couplings which simulate the fluid-filled cylinders of reactor vessel and core barrel structures is established. And for the exciting external force the response spectrum which is applied to reactor support is converted to the time history input. With this excitation and the model the dynamic behaviour of reactor internals is obtained. As the results, the structural integrity of reactor internal components under seismic excitation is verified and the input for the detailed duel assembly series model could be obtained. And the simplicity and effectiveness of Global Beam Model and the economics of the explicit Runge-Kutta-Gills algorithm in impact problem of high frequency interface components are confirmed.

• Korean Journal of Environment and Ecology
• /
• v.27 no.1
• /
• pp.11-21
• /
• 2013

We tried to find out the core feeding site of the Red-crowned Crane(Grus japonensis) in Cheorwon, Korea by using analysis techniques which are MCP(minimum convex polygon), KDE(kernel density estimation), LoCoH(local nearest-neighbor convex-hull). And, We discussed the difference and meaning of result among analysis methods. We choose the data of utilization distribution from distribution map of Red-crowned Crane in Cheorwon, Korea at $17^{th}$ February 2012. Extent of the distribution area was $140km^2$ by MCP analysis. Extents of core feeding area of the Red-crowned Crane were $33.3km^2$($KDE_{1000m}$), $25.7km^2$($KDE_{CVh}$), $19.7km^2$($KDE_{LSCVh}$), according to the 1000m, CVh, LSCVh in value of bandwidth. Extent, number and shape complexity of the core area has decreased, and size of each core area have decreased as small as the bandwidth size(default:1000m, CVh: 554.6m, LSCVh: 329.9). We would suggest the CVh value in KDE analysis as a proper bandwidth value for the Red-crowned crane's core area zoning. Extent of the distribution range and core area have increased and merged into the large core area as a increasing of k value in LoCoH analysis. Proper value for the selecting core area of Red-crowned Crane's distribution was k=24, and extent of the core area was $18.2km^2$, 16.5% area of total distribution area. Finally, the result of LoCoH analysis, we selected two core area, and number of selected core area was smaller than selected area of KDE analysis. Exact value of bandwidth have not been used in studies using KDE analysis in most articles and presentations of the Korea. As a result, it is needed to clarify the exact using bandwidth value in KDE studies.

• Cartoon and Animation Studies
• /
• s.36
• /
• pp.189-215
• /
• 2014

Since the launching of in 1963, a large amount of outstanding cartoons had been produced in China by the year 1980. During this period of time, international reputation was achieved with the extremely full expression and characteristic stories originated from Chinese culture. Decades of cartoons were produced ever year benefiting from support of the government in the last years. However, the quality and in fluence power dropped down comparing with the increasing productivity. The outward followed by examples of successful international box office most of the animation made in China. These cartoons did not obtain admitting internationally, or disclose any traditional speciality of China, although the domestic box office is considered to be fairly successful. The key factors to the successful cases should be analysed and researched rather than simply estimating, in order to achieve both artistic and commercial success. Factor of humor, as a key element of a successful cartoon is proposed in this thesis. Prior to the discussion, a general definition of humor factor is described through Henri Bergson's comedy concept, based on which the key factors of humor will be analysed. A classification system would be derived and introduced as a tool for the analysis of humor factors. According to Henri Bergson, Humor is determined by circumstance, language and character factors. Humor factors are divided into visual, scene and acoustic factors in this research taking the Speciality of cartoon media into consideration. It is the speciality that, in addition to the visual and language factors, multiple acoustic elements are also introduced in such a presentation pattern. This classification system would be considerably applicable to the analysis of humor factors in Chinese cartoons. In this study, around the year 2000 to share the Chinese animation masterpiece were analyzed by selecting and , and . This discussion about key factors of humor is likely to be beneficial to the development of Chinese Cartoons in the future.

• Archives of design research
• /
• v.19 no.2 s.64
• /
• pp.73-80
• /
• 2006

The main purpose of this study is to help develop the productional system of the three dimensional digital animation domestically. Many 30 digital animation projects are being developed and finished with foreign computer graphics technology. However, the 3D animation market in Korea is not as good as the ones in other countries. One of the most significant problems is the lack of a program of study in Korea concerning productional systems used to create 3D animation. We previously imported an advanced productional system from the U.S., which was adaptable to big projects, and consequently, expanded the international digital animation market. Now, we need to develop a new production system which is fully adaptable to the Korean market. A non-sequential system of 3D digital animation tailored for small projects is more adaptable to domestic industry than the sequential system known as the 'Pipeline system.' A non-sequential system is good for small productions that are trying to create animation on a limited budget. The workers in this system can learn to make animation fast and effectively. They can also learn how to discuss with the others in order to avoid duplication of action. In contrast, in the Pipeline System, many workers repeat confirmation steps during the process for the same animations. The benefit of the non-sequential system is that the worker's interest and education can speed up production, because he/she can quickly learn every step of the animation process instead of just doing a particular job which does not allow him/her to observe the other steps involved. The 'animatic' step is the most important in the non-sequential system. The final animation is produced from the animatic. It is developed from scratch through to the final product but only after the agreement of all the workers, including a director.

• Journal of Intelligence and Information Systems
• /
• v.22 no.2
• /
• pp.127-142
• /
• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.

• Journal of Oral Medicine and Pain
• /
• v.31 no.1
• /
• pp.27-36
• /
• 2006

The cases of unidentified individual remains submitted to Forensic dentistry section in National Institute of Scientific Investigation, Korea were analyzed to study the application of forensic dental identification into individual identification in the period 2002-2005. The identification cases of unidentified remains were 405 out of 493, which accounted about 82% of whole cases. The incidence of submission of skeletons at least including the skull was increased from 58% in 2002 to 80% in 2005. The numbers of cases for the full examinations were 4 times more than that for age estimation in 2005. Twenty-four cases were submitted for skull to photographic superimposition and 15 out of 24 cases were examined, and the other 9 cases were examined by DNA analysis only. The submitted cases for dental comparison were 23 cases, 9 cases were positively identified, 4 cases were possible, 7 cases were excluded, and 3 cases ended up with insufficient evidences. The proportion of positive identification by dental methods was increased gradually from 9% in 2002 to 46% in 2005. Forensic dental identification has become important and useful because the availability of dental records and radiographs has been increasing. Compared to DNA analysis, forensic dental identification has several advantages such as no needs for high cost equipments and low expenses. And the interpretation of results is straightforward and speedy. These advantages are based on using primary their own dental records of the individuals rather than secondary DNA reference samples from family members. The application of the forensic dental identification to unidentified individual remains will be increased because the dental comparison can complement the limitation of DNA analysis and skull to photographic superimposition in many cases. In order to obtain positive identifications of unidentified remains, a close collaboration between the police and forensic scientists is important. The systemic approach including legislation to preserve dental records of unidentified remains and missing persons for the identification of unidentified remains should be needed.

• Journal of Food Hygiene and Safety
• /
• v.34 no.1
• /
• pp.1-12
• /
• 2019

The health benefits associated with consumption of fresh produce have been clearly demonstrated and encouraged by international nutrition and health authorities. However, since fresh produce is usually minimally processed, increased consumption of fresh fruits and vegetables has also led to a simultaneous escalation of foodborne illness cases. According to the report by the World Health Organization (WHO), 1 in 10 people suffer from foodborne diseases and 420,000 die every year globally. In comparison to other processed foods, fresh produce can be easily contaminated by various routes at different points in the supply chain from farm to fork. This review is focused on the identification and characterization of possible sources of foodborne illnesses from chemical, biological, and physical hazards and the applicable methodologies to detect potential contaminants. Agro-chemicals (pesticides, fungicides and herbicides), natural toxins (mycotoxins and plant toxins), and heavy metals (mercury and cadmium) are the main sources of chemical hazards, which can be detected by several methods including chromatography and nano-techniques based on nanostructured materials such as noble metal nanoparticles (NMPs), quantum dots (QDs) and magnetic nanoparticles or nanotube. However, the diversity of chemical structures complicates the establishment of one standard method to differentiate the variety of chemical compounds. In addition, fresh fruits and vegetables contain high nutrient contents and moisture, which promote the growth of unwanted microorganisms including bacterial pathogens (Salmonella, E. coli O157: H7, Shigella, Listeria monocytogenes, and Bacillus cereus) and non-bacterial pathogens (norovirus and parasites). In order to detect specific pathogens in fresh produce, methods based on molecular biology such as PCR and immunology are commonly used. Finally, physical hazards including contamination by glass, metal, and gravel in food can cause serious injuries to customers. In order to decrease physical hazards, vision systems such as X-ray inspection have been adopted to detect physical contaminants in food, while exceptional handling skills by food production employees are required to prevent additional contamination.