• Title/Summary/Keyword: discrete data

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Novel two-stage hybrid paradigm combining data pre-processing approaches to predict biochemical oxygen demand concentration (생물화학적 산소요구량 농도예측을 위하여 데이터 전처리 접근법을 결합한 새로운 이단계 하이브리드 패러다임)

  • Kim, Sungwon;Seo, Youngmin;Zakhrouf, Mousaab;Malik, Anurag
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1037-1051
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    • 2021
  • Biochemical oxygen demand (BOD) concentration, one of important water quality indicators, is treated as the measuring item for the ecological chapter in lakes and rivers. This investigation employed novel two-stage hybrid paradigm (i.e., wavelet-based gated recurrent unit, wavelet-based generalized regression neural networks, and wavelet-based random forests) to predict BOD concentration in the Dosan and Hwangji stations, South Korea. These models were assessed with the corresponding independent models (i.e., gated recurrent unit, generalized regression neural networks, and random forests). Diverse water quality and quantity indicators were implemented for developing independent and two-stage hybrid models based on several input combinations (i.e., Divisions 1-5). The addressed models were evaluated using three statistical indices including the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and correlation coefficient (CC). It can be found from results that the two-stage hybrid models cannot always enhance the predictive precision of independent models confidently. Results showed that the DWT-RF5 (RMSE = 0.108 mg/L) model provided more accurate prediction of BOD concentration compared to other optimal models in Dosan station, and the DWT-GRNN4 (RMSE = 0.132 mg/L) model was the best for predicting BOD concentration in Hwangji station, South Korea.

Business Relationships and Structural Bonding: A Study of American Metal Industry (산업재 거래관계와 구조적 결합: 미국 금속산업의 분석 연구)

  • Han, Sang-Lin;Kim, Yun-Tae;Oh, Chang-Yeob;Chung, Jae-Moon
    • 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.

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The Effects of Sentiment and Readability on Useful Votes for Customer Reviews with Count Type Review Usefulness Index (온라인 리뷰의 감성과 독해 용이성이 리뷰 유용성에 미치는 영향: 가산형 리뷰 유용성 정보 활용)

  • Cruz, Ruth Angelie;Lee, Hong Joo
    • Journal of Intelligence and Information Systems
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    • v.22 no.1
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    • pp.43-61
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    • 2016
  • Customer reviews help potential customers make purchasing decisions. However, the prevalence of reviews on websites push the customer to sift through them and change the focus from a mere search to identifying which of the available reviews are valuable and useful for the purchasing decision at hand. To identify useful reviews, websites have developed different mechanisms to give customers options when evaluating existing reviews. Websites allow users to rate the usefulness of a customer review as helpful or not. Amazon.com uses a ratio-type helpfulness, while Yelp.com uses a count-type usefulness index. This usefulness index provides helpful reviews to future potential purchasers. This study investigated the effects of sentiment and readability on useful votes for customer reviews. Similar studies on the relationship between sentiment and readability have focused on the ratio-type usefulness index utilized by websites such as Amazon.com. In this study, Yelp.com's count-type usefulness index for restaurant reviews was used to investigate the relationship between sentiment/readability and usefulness votes. Yelp.com's online customer reviews for stores in the beverage and food categories were used for the analysis. In total, 170,294 reviews containing information on a store's reputation and popularity were used. The control variables were the review length, store reputation, and popularity; the independent variables were the sentiment and readability, while the dependent variable was the number of helpful votes. The review rating is the moderating variable for the review sentiment and readability. The length is the number of characters in a review. The popularity is the number of reviews for a store, and the reputation is the general average rating of all reviews for a store. The readability of a review was calculated with the Coleman-Liau index. The sentiment is a positivity score for the review as calculated by SentiWordNet. The review rating is a preference score selected from 1 to 5 (stars) by the review author. The dependent variable (i.e., usefulness votes) used in this study is a count variable. Therefore, the Poisson regression model, which is commonly used to account for the discrete and nonnegative nature of count data, was applied in the analyses. The increase in helpful votes was assumed to follow a Poisson distribution. Because the Poisson model assumes an equal mean and variance and the data were over-dispersed, a negative binomial distribution model that allows for over-dispersion of the count variable was used for the estimation. Zero-inflated negative binomial regression was used to model count variables with excessive zeros and over-dispersed count outcome variables. With this model, the excess zeros were assumed to be generated through a separate process from the count values and therefore should be modeled as independently as possible. The results showed that positive sentiment had a negative effect on gaining useful votes for positive reviews but no significant effect on negative reviews. Poor readability had a negative effect on gaining useful votes and was not moderated by the review star ratings. These findings yield considerable managerial implications. The results are helpful for online websites when analyzing their review guidelines and identifying useful reviews for their business. Based on this study, positive reviews are not necessarily helpful; therefore, restaurants should consider which type of positive review is helpful for their business. Second, this study is beneficial for businesses and website designers in creating review mechanisms to know which type of reviews to highlight on their websites and which type of reviews can be beneficial to the business. Moreover, this study highlights the review systems employed by websites to allow their customers to post rating reviews.

Principle and Recent Advances of Neuroactivation Study (신경 활성화 연구의 원리와 최근 동향)

  • Kang, Eun-Joo
    • Nuclear Medicine and Molecular Imaging
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    • v.41 no.2
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    • pp.172-180
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    • 2007
  • Among the nuclear medicine imaging methods available today, $H_2^{15}O-PET$ is most widely used by cognitive neuroscientists to examine regional brain function via the measurement of regional cerebral blood flow (rCBF). The short half-life of the radioactively labeled probe, $^{15}O$, often allows repeated measures from the same subjects in many different task conditions. $H_2^{15}O-$ PET, however, has technical limitations relative to other methods of functional neuroimaging, e.g., fMRI, including relatively poor time and spatial resolutions, and, frequently, insufficient statistical power for analysis of individual subjects. However, recent technical developments, such as the 3-D acquisition method provide relatively good image quality with a smaller radioactive dosage, which in turn results in more PET scans from each individual, thus providing sufficient statistical power for the analysis of individual subject's data. Furthermore, the noise free scanner environment $H_2^{15}O$ PET, along with discrete acquisition of data for each task condition, are important advantages of PET over other functional imaging methods regarding studying state-dependent changes in brain activity. This review presents both the limitations and advantages of $^{15}O-PET$, and outlines the design of efficient PET protocols, using examples of recent PET studies both in the normal healthy population, and in the clinical population.

A Study on the Resilience Process of Persons with Disabilities (중도장애인의 레질리언스(Resilience) 과정에 관한 연구)

  • Kim, Mi-Ok
    • Korean Journal of Social Welfare
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    • v.60 no.2
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    • pp.99-129
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    • 2008
  • This study analyzed the resilience process of persons with disabilities using the grounded theory approach. To conduct this study, the researcher conducted in-depth interviews with 8 persons with disabilities. In data analysis, this study identified 393 concepts on the resilience process of persons with disabilities and the concepts were categorized into 45 sub-categories and 18 primary categories. In the paradigm model on the resilience process of persons with disabilities, it was identified that casual conditions included 'unawareness of disability before being disability', 'extreme pain', 'repressing psychological pain', and the contingent conditions were 'dis-empowerment by staying in home', 'isolation by himself with difficulty in accepting the disability', 'experience of frustration from social barriers with prejudice against persons with disabilities'. Also, it was identified that the resilience process could be dependent on the type and the degree of the disability, the gender, and the length of time being disability. In spite of the casual and contingent conditions, the central way in which persons with disabilities could acquire resilience was identified as 'enhancement of the power of positive thinking'. The control conditions which accelerate or retard central phenomenon were 'the awareness of not being alone through family, friends, neighborhood and the social system' externally and 'finding purpose in life through religion and help from other persons with disabilities', internally. The action/interactional sequences enhanced the efforts, self searching and active acting, and as a result, persons with disabilities could find comfort in life, participate in society and change the perspective of disability in society. The core categories of resilience process in persons with disabilities were a belief in affirmation and choice of life by initiative. In the process analysis, stages developed in the following: 'pain', 'strangeness', 'reflection', 'daily life'. This stage was more continuous and causal than discrete and complete. In this process, the types of resilience of persons with disabilities are divided into 'existence reflection', 'course development', 'implicit endeavor', and 'active execution'. This study showed the details of the paradigm models, the process and types with an in-depth understanding of the resilience process of persons with disabilities using grounded theory as well as theory construction and policy and clinical involvement on the study of persons with disabilities.

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Speech Recognition Using Linear Discriminant Analysis and Common Vector Extraction (선형 판별분석과 공통벡터 추출방법을 이용한 음성인식)

  • 남명우;노승용
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.4
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    • pp.35-41
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    • 2001
  • This paper describes Linear Discriminant Analysis and common vector extraction for speech recognition. Voice signal contains psychological and physiological properties of the speaker as well as dialect differences, acoustical environment effects, and phase differences. For these reasons, the same word spelled out by different speakers can be very different heard. This property of speech signal make it very difficult to extract common properties in the same speech class (word or phoneme). Linear algebra method like BT (Karhunen-Loeve Transformation) is generally used for common properties extraction In the speech signals, but common vector extraction which is suggested by M. Bilginer et at. is used in this paper. The method of M. Bilginer et al. extracts the optimized common vector from the speech signals used for training. And it has 100% recognition accuracy in the trained data which is used for common vector extraction. In spite of these characteristics, the method has some drawback-we cannot use numbers of speech signal for training and the discriminant information among common vectors is not defined. This paper suggests advanced method which can reduce error rate by maximizing the discriminant information among common vectors. And novel method to normalize the size of common vector also added. The result shows improved performance of algorithm and better recognition accuracy of 2% than conventional method.

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An Intelligent Intrusion Detection Model Based on Support Vector Machines and the Classification Threshold Optimization for Considering the Asymmetric Error Cost (비대칭 오류비용을 고려한 분류기준값 최적화와 SVM에 기반한 지능형 침입탐지모형)

  • Lee, Hyeon-Uk;Ahn, Hyun-Chul
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.157-173
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    • 2011
  • As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

THE CURRENT STATUS OF BIOMEDICAL ENGINEERING IN THE USA

  • Webster, John G.
    • Proceedings of the KOSOMBE Conference
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    • v.1992 no.05
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    • pp.27-47
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    • 1992
  • Engineers have developed new instruments that aid in diagnosis and therapy Ultrasonic imaging has provided a nondamaging method of imaging internal organs. A complex transducer emits ultrasonic waves at many angles and reconstructs a map of internal anatomy and also velocities of blood in vessels. Fast computed tomography permits reconstruction of the 3-dimensional anatomy and perfusion of the heart at 20-Hz rates. Positron emission tomography uses certain isotopes that produce positrons that react with electrons to simultaneously emit two gamma rays in opposite directions. It locates the region of origin by using a ring of discrete scintillation detectors, each in electronic coincidence with an opposing detector. In magnetic resonance imaging, the patient is placed in a very strong magnetic field. The precessing of the hydrogen atoms is perturbed by an interrogating field to yield two-dimensional images of soft tissue having exceptional clarity. As an alternative to radiology image processing, film archiving, and retrieval, picture archiving and communication systems (PACS) are being implemented. Images from computed radiography, magnetic resonance imaging (MRI), nuclear medicine, and ultrasound are digitized, transmitted, and stored in computers for retrieval at distributed work stations. In electrical impedance tomography, electrodes are placed around the thorax. 50-kHz current is injected between two electrodes and voltages are measured on all other electrodes. A computer processes the data to yield an image of the resistivity of a 2-dimensional slice of the thorax. During fetal monitoring, a corkscrew electrode is screwed into the fetal scalp to measure the fetal electrocardiogram. Correlations with uterine contractions yield information on the status of the fetus during delivery To measure cardiac output by thermodilution, cold saline is injected into the right atrium. A thermistor in the right pulmonary artery yields temperature measurements, from which we can calculate cardiac output. In impedance cardiography, we measure the changes in electrical impedance as the heart ejects blood into the arteries. Motion artifacts are large, so signal averaging is useful during monitoring. An intraarterial blood gas monitoring system permits monitoring in real time. Light is sent down optical fibers inserted into the radial artery, where it is absorbed by dyes, which reemit the light at a different wavelength. The emitted light travels up optical fibers where an external instrument determines O2, CO2, and pH. Therapeutic devices include the electrosurgical unit. A high-frequency electric arc is drawn between the knife and the tissue. The arc cuts and the heat coagulates, thus preventing blood loss. Hyperthermia has demonstrated antitumor effects in patients in whom all conventional modes of therapy have failed. Methods of raising tumor temperature include focused ultrasound, radio-frequency power through needles, or microwaves. When the heart stops pumping, we use the defibrillator to restore normal pumping. A brief, high-current pulse through the heart synchronizes all cardiac fibers to restore normal rhythm. When the cardiac rhythm is too slow, we implant the cardiac pacemaker. An electrode within the heart stimulates the cardiac muscle to contract at the normal rate. When the cardiac valves are narrowed or leak, we implant an artificial valve. Silicone rubber and Teflon are used for biocompatibility. Artificial hearts powered by pneumatic hoses have been implanted in humans. However, the quality of life gradually degrades, and death ensues. When kidney stones develop, lithotripsy is used. A spark creates a pressure wave, which is focused on the stone and fragments it. The pieces pass out normally. When kidneys fail, the blood is cleansed during hemodialysis. Urea passes through a porous membrane to a dialysate bath to lower its concentration in the blood. The blind are able to read by scanning the Optacon with their fingertips. A camera scans letters and converts them to an array of vibrating pins. The deaf are able to hear using a cochlear implant. A microphone detects sound and divides it into frequency bands. 22 electrodes within the cochlea stimulate the acoustic the acoustic nerve to provide sound patterns. For those who have lost muscle function in the limbs, researchers are implanting electrodes to stimulate the muscle. Sensors in the legs and arms feed back signals to a computer that coordinates the stimulators to provide limb motion. For those with high spinal cord injury, a puff and sip switch can control a computer and permit the disabled person operate the computer and communicate with the outside world.

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Compositional Variation of Arsenopyrites in Arsenic and Polymetallic Ores from the Ulsan Mine, Republic of Korea, and their Application to a Geothermometer (울산광산산(蔚山鑛山産) 유비철석(硫砒鐵石)의 조성변화(組成變化) 및 지질온도계(地質溫度計)에 대(對)한 적용(適用))

  • Choi, Seon-Gyu;Chung, Jae-Ill;Imai, Naoya
    • Economic and Environmental Geology
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    • v.19 no.3
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    • pp.199-218
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    • 1986
  • Arsenopyrite in arsenic and polymetallic ores from calcic Fe-W skarn deposit of the Ulsan mine, Republic of Korea, has been investigated by means of electron microprobe analysis and X-ray diffractometry. As a result, it is revealed that the Ulsan arsenopyrite may be classified into the following three species with different generation on the basis of its mode of occurrence, chronological order during polymetallic mineralization and chemical composition; arsenopyrites I, II and III. 1) Arsenopyrite I-(Ni, Co)-bearing species belonging to the oldest generation, which has crystallized together with (Ni, Co)-arsenides and -sulpharsenides in the early stage of polymetallic mineralization. In rare cases, it contains a negligible amount of antimony. It occurs usually as discrete grains with irregular outline, showing rarely subhedral form, and is diffused in skarn zone. The maximum contents of nickel and cobalt are 10.04 Ni and 2.45 Co (in weight percent). Occasionally, it shows compositional zoning with narrow rim of lower (Ni+Co) content. 2) Arsenopyrite II-arsenian species, in which (Ni+Co) content is almost negligible, may occur widely in arsenic ores, and its crystallization has followed that of arsenopyrite I. It usually shows subhedral to euhedral form and is closely associated with $l{\ddot{o}}llingite$, bismuth, bismuthinite, chalcopyrite, sphalerite, bismuthian tennantite, etc. It is worthy of note that arsenopyrite II occasionally contains particles consisting of both bismuth and bismuthinite. 3) Arsenopyrite III-(Ni, Co)-free, S-excess and As-deficient species is close to the stoichiometric composition, FeAsS. It occurs in late hydrothermal veins, which cut clearly the Fe-W ore pipe and the surrounding skarn zone. It shows euhedral to subhedral form, being extremely coarse-grained, and is closely associated with pyrite, "primary" monoclinic pyrrhotite, galena, sphalerite, etc. Among three species of the Ulsan arsenopyrite, arsenopyrite I does not serve as a geothermometer, because (Ni+Co) content always exceeds 1 weight percent. In spite of the absence of Fe-S minerals as sulphur-buffer assemblage, the presence of $Bi(l)-Bi_2S_3$ sulphur-buffer enables arsenopyrite II to apply successfully to the estimation of either temperature and sulphur fugacity, the results are, $T=460{\sim}470^{\circ}C$, and log $f(S_2)=-7.4{\sim}7.0$. With reference to arsenopyrite III, only arsenopyrite coexisting with pyrite and "primary" monoclinic pyrrhotite may serve to restrict the range of both temperature and sulphur fugacity, $T=320{\sim}440^{\circ}C$, log $f(S_2)=-9.0{\sim}7.0$. These temperature data are consistent with those obtained by fluid inclusion geothermometry on late grandite garnet somewhat earlier than arsenopyrite II. At the beginning of this paper, the geological environments of the ore formation at Ulsan are considered from regional and local geologic settings, and physicochemical conditions are suspected, in particular the formation pressure (lithostatic pressure) is assumed to be 0.5kb (50MPa). The present study on arsenopyrite geothermometry, however, does not bring about any contradictions against the above premises. Thus, the following genetical view on the Ulsan ore deposit previously advocated by two of the present authors (Choi and Imai) becomes more evident; the ore deposit was formed at shallow depth and relatively high-temperature with steep geothermal gradient-xenothermal conditions.

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Effect of NMDA Receptor Antagonist on Local Cerebral Glucose Metabolic Rate in Focal Cerebral Ischemia (국소뇌허혈에서 NMDA 수용체 길항제가 국소 뇌포도당 대사율에 미치는 영향)

  • Kim, Sang-Eun;Hong, Seung-Bong;Yoon, Byung-Woo;Bae, Sang-Kyun;Choi, Chang-Woon;Lee, Dong-Soo;Chung, June-Key;Roh, Jae-Kyu;Lee, Myung-Chul;Koh, Chang-Soon
    • The Korean Journal of Nuclear Medicine
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    • v.29 no.3
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    • pp.294-306
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    • 1995
  • There has recently been increasing interest in the use of NMDA receptor antagonists as potential neuroprotective agents for the treatment of ischemic stroke. To evaluate the neuroprotective effect of the selective non-competitive NMDA receptor antagonist MK-801 in focal cerebral ischemia, local cerebral glucose utilization (ICGU) was examined in 15 neuroanatomically discrete regions of the conscious rat brain using the 2-deoxy-D[$^{14}C$] glucose quantitative autoradiographic technique 24 hr after left middle cerebral artery occlusion (MCAO). Animals received MK-801 (5 mg/kg i.v.) or saline vehicle before (20-30 min) or after (30 min) MCAO. Both pretreatment and posttreatment of MK-801 increased occluded/non-occluded ICGU ratio in 7 and 5 of the 15 regions measured, respectively (most notably in cortical structures). Following MK-801 pretreatment, there was evidence of widespread increases in ICGU not only in the non-occluded hemisphere (12 of the 15 areas studied) but also in the occluded hemisphere (13 of the 15 areas studied), while MK-801 postreatment did not significantly increase ICGU both in the normal and occluded hemispheres. These data indicate that MK-801 has a neuroprotective effect in focal cerebral ischemia and demonstrate that MK-801 provides widespread alterations of glucose utilization in conscious animals.

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