• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.27-40
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• 2024

This study empirically derives the factors affecting the practice of corporate social responsibility (CSR) of venture firms in Korea from the perspective of Slack Resource Theory and the company's growth strategy, and provides implications for future expansion of venture firm's CSR activities. In Korea, venture firms have grown into important players in the national economy since the late 1990s through social contributions such as economic value creation, job creation, and technological development. As venture companies grow in status, positive relationships with stakeholders and responsibility for environmental and social values are required. Now, CSR is becoming an important strategic choice for SMEs and venture firms. However, until now, CSR-related academic research has mainly focused on large or listed corporations, and there is not much research on SMEs or venture firms. In particular, research on the factors that lead venture companies to make important business decisions of participating in CSR activities is not there yet. This study applied logistic multiple regression analysis using the '2023 Survey on Venture Firms' conducted by the Ministry of SMEs and Startups. As a result of this study, operating profit, which is an available resources of venture companies, and government support, which is a potential resource, have a positive impact on venture firms's CSR activities. Also, business relationships with large corporations and expectation for future cooperation also have a positive impact on CSR activities as the determinants. On the other hand, it was analyzed that in venture firms where ownership and management are not separated, the higher the CEO's shareholding ratio, the more negatively it affects CSR activities. This study contributes academically as the first empirical study on the determinants of CSR activities of venture firms in Korea and provides implications that government policy support and collaboration between large corporations and venture firms are important in order to expand CSR activities of venture firms.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.139-153
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• 2024

The importance of sustainable growth and cost reduction has increased globally, leading to the expansion of outsourcing by companies. Additionally, the spread of the platform economy has brought changes in the way we work, and the online outsourcing market, where tasks are mediated through platforms, is growing. Academically, while research on general outsourcing is actively conducted, studies on online outsourcing are relatively insufficient compared to its actual utilization. This study aims to analyze the factors and performance factors of online outsourcing utilization by startups, to identify the effects and concerns of using online outsourcing from multiple perspectives, and to suggest the roles of various stakeholders for effective utilization and industry development. For the research, a survey was conducted with 281 employees of startups who have experience in using online outsourcing, and the main findings are as follows. First, the enhancement of efficiency, profitability, and innovation through the use of online outsourcing positively affects organizational commitment and job satisfaction of startup members. Especially, the improvement of efficiency due to the use of online outsourcing has a significant effect on enhancing job satisfaction. Second, concerns about the burden of online outsourcing fees or uncertain outcomes negatively affect organizational commitment and job satisfaction. Third, there are perceptual differences in the motivations and performance regarding the utilization of online outsourcing depending on the job position. Practitioners perceive that the use of online outsourcing increases organizational commitment, whereas managers have relatively higher concerns about the uncertainty of outsourced task outcomes and information security. Through this study, the possibility that human resource shortages and employee management issues in startups can be improved through online outsourcing was confirmed. By verifying the influence of various factors of online outsourcing utilization, this study also provides meaningful implications for establishing business strategies for online outsourcing intermediary platform companies and for formulating startup support policies by government and other startup support organizations.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.107-118
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• 2016

The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.

• Korean Journal of Agricultural Science
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• v.15 no.1
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• pp.82-94
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• 1988

This study was performed to obtain the basic data which can be applied to use of foaming mortars. The results obtained were summarized as follows ; 1. The lowest water-cement ratios were shown at the mixing ratio of 1 : 1. But, it was gradually increased in poorer mixing ratio and decreased in more addition of foaming agent. The water-cement ratios were decreased up to 1.6-53.1% by mix-foaming type and 4.4-24.1% by pre-foamed type than cement mortar. 2. The highest bulk densities were shown at the mixing ratio of 1 : 1. But, it was gradually decreased in poorer mixing ratio and more addition of foaming agent. The decreasing rates of bulk densities were increased in richer mixing ratio and more addition of foaming agent. 3. The bulk densities were decreased up to 38.8-55.9% by mix-foaming type and 9.7-23.6% by pre-foamed type than cement mortar. 4. The lowest absorption rates were shown at the mixing ratio of 1 : 1. But, it was gradually increased in poorer mixing ratio and more addition of foaming agent. The increasing rates of absorption rates were increased in richer mixing ratio and more addition of foaming agent. 5. Absorption rates when immersed in 72hours were shown up to 3.41-5.85 times greater by mix-foaming type and 1.05-1.55 times greater by pre-foamed type than those of cement mortar. it was significantly higher at the early stage of immersed time than cement mortar. 6. The highest strengths were shown at the mixing ratio of 1 : 1. But, it was gradually decreased in poorer mixing ratio and more addition of foaming agent. The decreasing rates of strengths were increased in poorer mixing ratio and more addition of foaming agent. 7. The strengths were decreased up to 77.0-92.8% by mix-foaming type and 36.7-74.4% by pre-foamed type than cement mortar. 8. The lowest air contents were shown at the mixing ratio of 1 : 1. But, it was gradually increased in poorer mixing ratio and more addition of foaming agent. The increasing rates of air contents were increased in richer mixing ratio and more addition of foaming agent. 9. Air contents were shown up to 26.0-63.8 times greater by mix-foaming type and 5.8-17.7 times greater by pre-foamed type than those of cement mortar. 10. The correlations between bulk density, absorption rate, compressive strength and air content were highly significant. The multiple regression equations of bulk density, absorption rate, compressive strength, tensile strength, bending strength and air content were computed depending on a function of mixing ratio and addition of foaming agent. They were generally highly significant.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Journal of Preventive Medicine and Public Health
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• v.23 no.3 s.31
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• pp.296-308
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• 1990

The relationship between copper and mercury contents in the scalp hair and chronic schizophrenia was investigated. The samples of scalp hair were collected from 80 male chronic schizophrenic patients at the age from 20 to 29, who were hospitalized in the National Psychiatric Hospital in Seoul. As the control group, 69 males were collected from general population. Hair samples were taken from the napes and the Minnesota Multiple Personality Inventory (MMPI) was performed also. The copper and mercury contents were determined by an atomic absorption spectrophotometer. Significantly higher T-score of MMPI was seen in patients group for Hypochondriasis Scale (Hs), Depression Scale (D), Psychopathic Deviate Scale (Pd), Paranoia Scale (Pa), Psychasthenia Scale (Pt), Schizophrenia Scale (Sc) subscales than control group, and the frequency distribution by T-score was also significantly different between the patient and the control group for above scales. The content of copper in the hair of patient group was significantly lower than the control group. In the case of mercury, the mean value of patient group was significantly higher than control group. Between the value of copper and mercury, statistically significant negative correlation (r=-0.25) was found. When grouped by the T-score of MMPI, there was no difference of copper contents between T-score subgroup at all MMPI scale. But the mercury contents showed significant difference between T-score subgroup at Pt, Sc scale. When compared between the group of above 70 T-score and the group of less than 70, the mercury contents of Pa, Pt, Sc scale of above 70 T-score group were significantly higher than the group of less than 70. In other scales, the mercury content of the above 70 group were higher than the group of less than 70 except Mf scale, although there were no statistscally significances. In D, Pa, Sc scales, as the T-score of MMPI increased, the contents of mercury also increased. When divided into the patient group and the control group, the copper contents of the patient groups were significantly lower than the control group at each T-score scale in most MMPI scales. In the case of mercury, the value of patient group were significantly higher than the control group in the less than 44 scale of D, in the $60{\sim}69$ scale of Pd, in the $45{\sim}59$ scale of Mf, in the $60{\sim}69$ scale of Ma, in the less than 44 of Si. These results suggest that the effects of the deficiency of copper or high intake of mecury on schizophrenia and personality may be of possible value. Thus further studies are necessary to determine whether schizophrenia and personality formation would be attributed to copper deficiency or mercury intake.

• Korean Journal of Animal Reproduction
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• v.23 no.2
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• pp.127-132
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• 1999

This study was carried out to investigate the general characteristics such as volume, sperm concentration, sperm motility, sperm abnormality on whole semen, removed seminal plasma(RSP) semen and fractional semen of small dogs, and the effect of temperature and preservatio time and cryopreservation on motility of whole and removed seminal plasma semen. Multiple ejaculates were collected from small dogs by the digital manipulation of penis. 1. Average sperm concentration, sperm motility and abnormal sperm rates of whole semen and RSP semen were 5.07$\pm$2.32$\times$10$^{6}$ cells/$m\ell$, 95.42$\pm$2.65%, 4.42$\pm$0.157% and 4.69$\pm$3.27~4.25$\pm$3.65$\times$10$^{6}$ cells/$m\ell$, 91.17$\pm$3.85~88.52$\pm$3.85%, 6.57$\pm$0.43~5.54$\pm$0.52%, respectively. 2. Average semen volume per ejaculate, sperm concentration, sperm motility and abnormal sperm rate of 1st fractional semen were 0.92$\pm$0.7$m\ell$, 4.57$\pm$0.78$\times$10$^{6}$ cells/$m\ell$, 10.72$\pm$3.21% and 5.50$\pm$0.70%. Average semen volume per ejaculate, sperm concentration, sperm motility and abnormal sperm rate of 2nd fractional semen were 2. 14$\pm$0.19$m\ell$, 2.01$\pm$0.12$\times$10$^{6}$ cells/$m\ell$, 95.44$\pm$4.21% and 4.31$\pm$0.53%. Average semen volume per ejaculate, sperm concentration, sperm motility and abnormal sperm rate of 3rd fractional semen were 2.66$\pm$0.23$m\ell$, 2.35$\pm$0.21$\times$10$^{6}$ cells/$m\ell$, 90.71$\pm$2.63%, 6.33$\pm$0.91%, respectively. 3. Motility of whole semen and RSP semen were higher at 2$0^{\circ}C$ than at 4$^{\circ}C$ or 37$^{\circ}C$. When preservation temperature was 2$0^{\circ}C$, sperm motility were 98.32% at 1 hr, 92.15% at 5 hrs, 90.23% at 10 hrs 82.08% at 15 hrs 70.07% at 20 hrs 60.02% at 20 hrs 37.19% at 40 hrs respectively. 4. Average sperm motility of frozen 2nd fraction semen and RSP semen were 33.3$\pm$8.7, 54.7$\pm$9.5%, respectively. Sperm motility was significantly higher in frozen 2nd fraction semen and RSP semen compared with control group.

• Korean journal of applied entomology
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• v.16 no.4 s.33
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• pp.199-208
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• 1977

Activities of various hydrolytic enzymes produced by three plant pathogenic fungi, Sclerotium rolfsii Sacc., Sclerotinia sclerotiorum (Lieb.) deBary and Helminthosporium sigmoideum var. irregulare Crallery et Tullius, were measured. Activties and amounts of the enzymes in mycelia, cultural filtrates, and sclerotia(except of sclerotia of H. sigmoideum var. irregulare) were estimated at various pH levels in order to find out optimal pH for their enzymatic activities. Enzymes such as cellulase (ex), invertase, xylanase, $\beta-amylase$, polymethylgalacturonase, polygalacturonase, phosphatase and protease were estimated. Culture solution for production of enzymes was prepared by adding of 10g, D-glucose, 1.3g $NH_4NO_3,\; 0.5g\; MgSO_4,\;7H_2O,\; and\; 1.0g\; KH_2PO_4$ into 1 liter of potato decoction plus 2ml of micro element solution consisting of 0.2mg. Fe, 0.2mg Zn, and 0.1mg Mn as the sulphates into 1 liter of distilled water. All tested mycelia and cultural filtrates were obtained from the cultures incubarted in previous solution for ten days at $25^{\circ}C$, and sclerotia were harvested from PDA plates of 3. days old, The crude enzyme solutions were prepared according to the method of Miyazaki etal. Ten days after incubation, activities of Cx produced by Scl. sclerotiorum were higher than those of the other fung and each of Cx from three fungi showed different pH optima, such as S. rolfsii and Scl. schlerotiorum in acid side (around pH 3.0), H. sigmoideum var. irregulare in neutral side (around pH 6.3). Invertase activities of S. rolfsii were 20 times higher than those of the other fungi in all samples. All tested fungi, however, showed no significant difference between the enzymatic activities of their cultural filtrate and mycelia and the activities in sclerotia of S. rolfsii and Scl. sclerotiorum were hardly recognized. There were multiple peaks on the xylanase activity curves of three fungi in terms of pH values. High activities of the xylanase were revealed in sclerotia of S. rolfsii and Scl. sclerotiorum, and in mycelia of H. sigmoideum var. irregulare. The highest activities of $\beta-amylase$ were shown both in mycelia and cultural filtrate of H. sigmoideum var. irregulae among the tested fungi, and their optimal pH was 6.2 in both mycelia and cultural filtrate. In the S. rofsii and Sel. sclerotiorum, however, the activities of cultural filtrates were higher than those of the other fungi, and optimal pH was 3.0 and 6.2 for cultural filtrate and both mycelia and sclerotia, respectively. Activities of PMG were high in cultural filtrates of all tested fungi, especially in Scl. sclerotiorum and H. sigmoideum var. irregulare. Mycelia of themalso showed the considerable activities. Optimal pH for enzymatic activities were variable with thekind of fungi or with the samples measured. The highest activities of PG were presented by mycelia of S. rolfsii and Scl. sclerotiorum. $9.l\mu /min.\; and\; 9.5\mu g/min.$, respectively. Optimal pH for activity of PG in mycelia was around 4.5 in S. rolfsii and around 3.0 in Scl. sclerotiorum. Phosphatase of S. rolfsii and Scl. sclerotiorum was more active in acid side (optimal PH3. 5) and that of H. sigmoideum var. irregulare showed one peak each in acid, neutral and alkaline side. But the highest peak was at pH 9.5. Protease of all tested fungi was more active at pH 10.0, especially that of the cultural filtrate of H. sigmoideum var. irregualre.