The author intended to investigate external and internal changes in the cone structure, changes in water content, sugar, fat and protein during the period of seed maturation which bears a proper germinability. The experimental results can be summarized as in the following. 1. Male flowers 1) Pollen-mother cells occur as a mass from late in April to early in May, and form pollen tetrads through meiosis early and middle of May. Pollen with simple nucleus reach maturity late in May. 2) Stamen number of a male flower is almost same as the scale number of cone and is 69-102 stamens. One stamen includes 5800-7300 pollen. 3) The shape is round and elliptical, both of a pollen has air-sac with
The studies were carried out to disclose the physical and chemical properties of sericin fraction obtained from silk cocoon shells and its characteristics of swelling and solubility. The following results were obtained. 1. The physical and chemical properties of sericin fraction. 1) In contrast to the easy water soluble sericin, the hard soluble sericin contains fewer amino acids include of polar side radical while the hard soluble amino acid sach as alanine and leucine were detected. 2) The easy soluble amino acids were found mainly on the outer part of the fibroin, but the hard soluble amino acids were located in the near parts to the fibroin. 3) The swelling and solubility of the sericin could be hardly assayed by the analysis of the amino acid composition, and could be considered to tee closely related to the compound of the sericin crystal and secondary structure. 4) The X-ray patterns of the cocoon filament were ring shape, but they disappeared by the degumming treatment. 5) The sericin of tussah silkworm (A. pernyi), showed stronger circular patterns in the meridian than the regular silkworm (Bombyx mori). 6) There was no pattern difference between Fraction A and B. 7) X-ray diffraction patterns of the Sericin 1, ll and 111 were similar except interference of 8.85A (side chain spacing). 8) The amino acids above 150 in molecular weight such as Cys. Tyr. Phe. His. and Arg. were not found quantitatively by the 60 minutes-hydrolysis (6N-HCI). 9) The X-ray Pattern of 4.6A had a tendency to disappear with hot-water, ether, and alcohol treatment. 10) The partial hydrolysis of sericin showed a cirucular interference (2A) on the meridian. 11) The sericin pellet after hydrolysis was considered to be peptides composed with specific amino acids. 12) The decomposing temperature of Sericin 111 was higher than that of Sericin I and II. 13) Thermogram of the inner portioned sericin of the cocoon shell had double endothermic peaks at 165
Background: The dysfunction of multiple organs is found to be caused by reactive oxygen species as a major modulator of microvascular injury after hemorrhagic shock. Hemorrhagic shock, one of many causes inducing acute lung injury, is associated with increase in alveolocapillary permeability and characterized by edema, neutrophil infiltration, and hemorrhage in the interstitial and alveolar space. Aggressive and rapid fluid resuscitation potentially might increased the risk of pulmonary dysfunction by the interstitial edema. Therefore, in order to improve the pulmonary dysfunction induced by hemorrhagic shock, the present study was attempted to investigate how to reduce the inflammatory responses and edema in lung. Material and Method: Male Sprague-Dawley rats, weight 300 to 350 gm were anesthetized with ketamine(7 mg/kg) intramuscular Hemorrhagic Shock(HS) was induced by withdrawal of 3 mL/100 g over 10 min. through right jugular vein. Mean arterial pressure was then maintained at
The purpose of this study was to investigate the health status of preschool children using the questionnaires about dietary behaviors and anthropometric indices. And also nutritional status was investigated using questionnaires for 24-hr recall method. The study was conducted in 145 children aged 3 to 6 years and questionnaires for dietary behaviors and dietary intakes were performed by mothers of children in Ulsan. Just nine percent of children were graded as good in terms of having healthy eating habits, this means that the nutrition education for the dietary behaviors should be more focused on preschool children. With regard to the frequency of food intake, children consumed green & yellow vegetables less frequently, meanwhile consumed high protein source food (meat, egg and bean) and milk and its product more frequently. Children almost never consumed fried foods as often as 1-2 times a weak. In assessment of the health status, children have the highest prevalence of colds and allergy, but lower prevalence of clinical symptoms due to the nutritional deficiency. The mean height was
Background : Pulmonary aspergillomas usually arise from colonization and proliferation of Aspergillus in preexisting cavitary lung disease of any cause. About 15% of patients with tuberculous pulmonary cavities were found to have aspergilloma. We analyzed the clinical features and course of 91 patients with pulmonary aspergilloma. Method : During the ten-year period from June 1986 to May 1996, 91 patients whose condition was diagnosed as pulmonary aspergilloma at 4 university hospitals in Taegu city were reviewed. All patients fulfilled one of the following criteria : 1) histologic evidence of aspergilloma within abnormal air space in tissue sections, or 2) a positive Aspergillus serum precipitin test with the radiologic finding of a fungus ball. The histological diagno-sis was established in 81 patients(89.0%) and clinical diagnosis in 10 patients(11.0%). Results : 1) The age range was 22 to 65 years, with an average of 45 years. A male and female ratio was 1.7 : 1 (57 men and 34 women). 2) Hemoptysis was far the most frequent symptom(89%), followed by cough, dyspnea, weakness, weight loss, fever, chest pain. 3) In all but 14 cases(15.4%) there had been associated conditions. Pulmonary tuberculosis was far the most frequent underlying condition found(74.7%), followed by bronchiectasis (6.6%), cavitary neoplasm(2.2%), pulmonary sequestration(1.1%). 4) The involved area was usually in the upper lobes; the right upper lobe was involved in 39(42.9%), the left upper lobe in 31(34.1%), the left lower lobe in 13(14.3%), the right lower lobe in 7(7.7%), and the right middle lobe in 1(1.1%). 5) On standard chest roent geno gram the classic "bell-like" image of a fungus ball was found in 62.6% of the subjects. On CT scan, 88.1% of the subjects in which they were done. 6) The surgical therapy was undertaken in 76 patients, and medical therapy in 15 patients, including 4 patients with intracavitary instillation of amphotericin B. 7) The surgical modality was lobectomy in 55 patients(72.4%), segmentectomy in 16 patients(21.1%), pneumonectomy in 4 patients(5.3%), wedge resection in 1 patient(1.3%). The mortality rate was 3.9% (3 patients) ; 2 patients died of sepsis and 1 died of hemoptysis. The postoperative complications were encountered in 6 patients (7.9%), including each one patient with respiratory failure, bleeding, bronchopleural fistula, empyema, and vocal cord paralysis. 8) In the follow-up cases, each 2 patients of 71 patients with surgical treatment and 10 patients with medical treatment had recurrent hemoptysis. Conclusion : During follow-up of the chronic pulmonary disease with abnormal air space, if the standard chest roentgenograms are insufficient to detect a fungus ball, computed tomographic scan and serum precipitin test are likely to aid the diagnosis of patients with suspected pulmonary aspergilloma. A reasonable recommendation for management of a patient with aspergilloma would be to reserve surgical resection for those patients who have had severe, recurrent hemoptysis. And a well controlled cooperative study to the medical treatment such as intracavitary antifungal therapy is further needed.
The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.
The sprig of Jinryungtang Gagambang has been used for curing as a traditional medicine without any experimental evidence to support the rational basis for their clinical use. This experiment was carried out to evaluate the possible therapeutic or antitumoral effects of Jinryungtang Gagambang extract against cancer, and to study some mechanisms responsible for its effect. The cytotoxic and antitumor effects were evaluated on human cell liens (A549, hep3B, Caki-1, Sarcoma 180) after exposure to Jinryungtang Gagambang extract using in ILS, colony forming efficency and SRB assay which were regarded as a valuable method for cytotoxic and antitumor effects of unknown compound on tumor cell lines. The results obtained in this studies were as follows. 1. As a result of exposure to Jinryungtang Gagambang extract, the proliferation of A549, hep3B, Caki-1, good correlations were shown from the results of SRB assay and those of clogenetic assay. 2. The oral administration of Jinryungtang Gagambang extract showed significant effects of increase of MST(mean survival time) and ILS(increased life span) depending on the increasing concentration. 3. Against squamous cell carcinoma induced by MCA, Jinryungtang Gagambang decreased not only the frequency of tumor production but also the number and weight of tumors per tumor bearing mice(TBM). Jinryungtang Gagambang also significantly suppressed the development of 3LL cell-implanted tumors by frequency and their size, and some developed tumors were regressed by the continuous treatment of Jinryungtang Gagambang extract into TBM. 4. Jinryungtang Gagambang extract also increased NK cell activities. According to the above results, it could be suggested that Jinryungtang Gagambang extract has prominent antiutmor effect.
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.