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
Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.
Purpose: This study was conducted to examine the concentration of nutrients in transitional breast milk from Korean lactating mothers and to evaluate daily intakes of their infants based on the Dietary Reference Intakes for Koreans 2010 (KDRIs 2010). Methods: Breast milk samples were collected at 5~15 days postpartum from 100 healthy lactating Korean mothers. Macro- and micro-nutrients, and immunoglobulin (Igs) concentrations in breast milk were analyzed. Results: The mean energy, protein, fat, and carbohydrate concentrations in breast milk were
The purposes of this study were to investigate supporting status and subsidy for school food service and to analyze the perception of school food service officials at the educational board on using rice bread to the school food service menu. The questionnaire was developed by content analysis, situation analysis, in-depth interview and checked by the school food service officials at the educational board. The questionnaires were responded by 33 officials (respondent rate: 86.8%) during September 1 to October 26 in 2007. The major findings of this study were as follows: First, most of the respondents were women (93.9%), and worked an average of 104.36 months at school-related work. The metropolitan & provincial office of education had prevalently jurisdiction over 272.3 rural and self-operation type of elementary schools, 115.50 rural and self-operation type of middle schools and 73.0 rural and self-operation type of high schools. In the case of the district office of education, 23.3 urban and self-operation type of elementary schools, 11.6 urban and self-operation type of middle schools and 5.3 urban and contracted type of high schools were averagely managed. Second, all the respondents supported meal cost for low-income group and 50.5% provided reimbursement for organic environmental agricultural products. The highest subsidy was 16.8 billion won as meal cost for low-income group in metropolitan & provincial office and 1,050 million won as labor cost in district office. Third, the experience of performing policies for using rice was relatively lower than perception of rice bread application to school food service menu. Fourth, the advantages of using rice bread were acceleration of consuming rice (32.0%), excellence of nutrition (24.0%) and promotion of healthy image (22.7%). On the other hand, the difficulties of using rice bread were lack of facilities (72.7%), higher cost compared to wheat bread (54.5%), limitation of menu application and cooking method (15.7% each). Fifth, the opinion of utilizing rice and that of applying rice bread were significantly correlated (p<0.001). Desirability and willingness were correlated with reality for applying rice bread to the school food service menu (p<0.001). Also, comparative analysis between divided groups by perception of utilizing rice showed that willingness and experience were significantly different.
To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.
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.
Studies were carried out 1) to define the shape and size of sampling quadrat and its number of observations for weed experiments, 2) to characterize the growth and community of major summer weeds under upland condition and 3) to investigate the factors influencing competition between weeds and soybeans under weed-free and weedy conditions in early and late season cultures. No significant difference was noted among different shapes of quadrat (regular, rectangular, band, and circular) in the sampling efficiency of weeds. The results also suggested that the minimum size of quadrat was 0.25
The purpose of this paper is to explore the relations between financial constraints and dividend smoothing of innovative small and medium sized enterprises(SMEs) listed on Korea Securities Market and Kosdaq Market of Korea Exchange. The innovative SMEs is defined as the firms with high level of R&D intensity which is measured by (R&D investment/total sales) ratio, according to Chauvin and Hirschey (1993). The R&D investment plays an important role as the innovative driver that can increase the future growth opportunity and profitability of the firms. Therefore, the R&D investment have large, positive, and consistent influences on the market value of the firm. In this point of view, we expect that the innovative SMEs can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. And also, we expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Aivazian et al.(2006) exert that the financial unconstrained firms with the high accessibility to capital market can adjust dividend payment faster than the financial constrained firms. We collect the sample firms among the total SMEs listed on Korea Securities Market and Kosdaq Market of Korea Exchange during the periods from January 1999 to December 2007 from the KIS Value Library database. The total number of firm-year observations of the total sample firms throughout the entire period is 5,544, the number of firm-year observations of the dividend firms is 2,919, and the number of firm-year observations of the non-dividend firms is 2,625. About 53%(or 2,919) of these total 5,544 observations involve firms that make a dividend payment. The dividend firms are divided into two groups according to the R&D intensity, such as the innovative SMEs with larger than median of R&D intensity and the noninnovative SMEs with smaller than median of R&D intensity. The number of firm-year observations of the innovative SMEs is 1,506, and the number of firm-year observations of the noninnovative SMEs is 1,413. Furthermore, the innovative SMEs are divided into two groups according to level of financial constraints, such as the financial unconstrained firms and the financial constrained firms. The number of firm-year observations of the former is 894, and the number of firm-year observations of the latter is 612. Although all available firm-year observations of the dividend firms are collected, deletions are made in the case of financial industries such as banks, securities company, insurance company, and other financial services company, because their capital structure and business style are widely different from the general manufacturing firms. The stock repurchase was involved in dividend payment because Grullon and Michaely (2002) examined the substitution hypothesis between dividends and stock repurchases. However, our data structure is an unbalanced panel data since there is no requirement that the firm-year observations data are all available for each firms during the entire periods from January 1999 to December 2007 from the KIS Value Library database. We firstly estimate the classic Lintner(1956) dividend adjustment model, where the decision to smooth dividend or to adopt a residual dividend policy depends on financial constraints measured by market accessibility. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between current payout rato and target payout ratio each year. In the Lintner model, dependent variable is the current dividend per share(DPSt), and independent variables are the past dividend per share(DPSt-1) and the current earnings per share(EPSt). We hypothesized that firms adjust partially the gap between the current dividend per share(DPSt) and the target payout ratio(Ω) each year, when the past dividend per share(DPSt-1) deviate from the target payout ratio(Ω). We secondly estimate the expansion model that extend the Lintner model by including the determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory. In the expansion model, dependent variable is the current dividend per share(DPSt), explanatory variables are the past dividend per share(DPSt-1) and the current earnings per share(EPSt), and control variables are the current capital expenditure ratio(CEAt), the current leverage ratio(LEVt), the current operating return on assets(ROAt), the current business risk(RISKt), the current trading volume turnover ratio(TURNt), and the current dividend premium(DPREMt). In these control variables, CEAt, LEVt, and ROAt are the determinants suggested by the residual dividend theory and the agency theory, ROAt and RISKt are the determinants suggested by the dividend signaling theory, TURNt is the determinant suggested by the transactions cost theory, and DPREMt is the determinant suggested by the catering theory. Furthermore, we thirdly estimate the Lintner model and the expansion model by using the panel data of the financial unconstrained firms and the financial constrained firms, that are divided into two groups according to level of financial constraints. We expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, because the former can finance more easily the investment funds through the market accessibility than the latter. We analyzed descriptive statistics such as mean, standard deviation, and median to delete the outliers from the panel data, conducted one way analysis of variance to check up the industry-specfic effects, and conducted difference test of firms characteristic variables between innovative SMEs and noninnovative SMEs as well as difference test of firms characteristic variables between financial unconstrained firms and financial constrained firms. We also conducted the correlation analysis and the variance inflation factors analysis to detect any multicollinearity among the independent variables. Both of the correlation coefficients and the variance inflation factors are roughly low to the extent that may be ignored the multicollinearity among the independent variables. Furthermore, we estimate both of the Lintner model and the expansion model using the panel regression analysis. We firstly test the time-specific effects and the firm-specific effects may be involved in our panel data through the Lagrange multiplier test that was proposed by Breusch and Pagan(1980), and secondly conduct Hausman test to prove that fixed effect model is fitter with our panel data than the random effect model. The main results of this study can be summarized as follows. The determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory explain significantly the dividend policy of the innovative SMEs. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between the current payout ratio and the target payout ratio each year. In the core variables of Lintner model, the past dividend per share has more effects to dividend smoothing than the current earnings per share. These results suggest that the innovative SMEs maintain stable and long run dividend policy which sustains the past dividend per share level without corporate special reasons. The main results show that dividend adjustment speed of the innovative SMEs is faster than that of the noninnovative SMEs. This means that the innovative SMEs with high level of R&D intensity can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. The other main results show that dividend adjustment speed of the financial unconstrained SMEs is faster than that of the financial constrained SMEs. This means that the financial unconstrained firms with high accessibility to capital market can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Futhermore, the other additional results show that dividend adjustment speed of the innovative SMEs classified by the Small and Medium Business Administration is faster than that of the unclassified SMEs. They are linked with various financial policies and services such as credit guaranteed service, policy fund for SMEs, venture investment fund, insurance program, and so on. In conclusion, the past dividend per share and the current earnings per share suggested by the Lintner model explain mainly dividend adjustment speed of the innovative SMEs, and also the financial constraints explain partially. Therefore, if managers can properly understand of the relations between financial constraints and dividend smoothing of innovative SMEs, they can maintain stable and long run dividend policy of the innovative SMEs through dividend smoothing. These are encouraging results for Korea government, that is, the Small and Medium Business Administration as it has implemented many policies to commit to the innovative SMEs. This paper may have a few limitations because it may be only early study about the relations between financial constraints and dividend smoothing of the innovative SMEs. Specifically, this paper may not adequately capture all of the subtle features of the innovative SMEs and the financial unconstrained SMEs. Therefore, we think that it is necessary to expand sample firms and control variables, and use more elaborate analysis methods in the future studies.
This project was a service-cum-research effort with a quasi-experimental study design to examine the health benefits of an integrated Family Planning (FP)/Maternal & Child health (MCH) Service approach that provides crucial factors missing in the present on-going programs. The specific objectives were: 1) To test the effectiveness of trained nurse/midwives (MW) assigned as change agents in the Health Sub-Center (HSC) to bring about the changes in the eight FP/MCH indicators, namely; (i)FP/MCH contacts between field workers and their clients (ii) the use of effective FP methods, (iii) the inter-birth interval and/or open interval, (iv) prenatal care by medically qualified personnel, (v) medically supervised deliveries, (vi) the rate of induced abortion, (vii) maternal and infant morbidity, and (viii) preinatal & infant mortality. 2) To measure the integrative linkage (contacts) between MW & HSC workers and between HSC and clients. 3) To examine the organizational or administrative factors influencing integrative linkage between health workers. Study design; The above objectives called for quasi-experimental design setting up a study and control area with and without a midwife. An active intervention program (FP/MCH minimum 'package' program) was conducted for a 2 year period from June 1982-July 1984 in Seosan County and 'before and after' surveys were conducted to measure the change. Service input; This study was undertaken by the Soonchunhyang University in collaboration with WHO. After a baseline survery in 1981, trained nurses/midwives were introduced into two health sub-centers in a rural setting (Seosan county) for a 2 year period from 1982 to 1984. A major service input was the establishment of midwifery services in the existing health delivery system with emphasis on nurse/midwife's role as the link between health workers (nurse aids) and village health workers, and the referral of risk patients to the private physician (OBGY specialist). An evaluation survey was made in August 1984 to assess the effectiveness of this alternative integrated approach in the study areas in comparison with the control area which had normal government services. Method of evaluation; a. In this study, the primary objective was first to examine to what extent the FP/MCH package program brought about changes in the pre-determined eight indicators (outcome and impact measures) and the following relationship was first analyzed; b. Nevertheless, this project did not automatically accept the assumption that if two or more activities were integrated, the results would automatically be better than a non-integrated or categorical program. There is a need to assess the 'integration process' itself within the package program. The process of integration was measured in terms of interactive linkages, or the quantity & quality of contacts between workers & clients and among workers. Intergrative linkages were hypothesized to be influenced by organizational factors at the HSC clinic level including HSC goals, sltrurture, authority, leadership style, resources, and personal characteristics of HSC staff. The extent or degree of integration, as measured by the intensity of integrative linkages, was in turn presumed to influence programme performance. Thus as indicated diagrammatically below, organizational factors constituted the independent variables, integration as the intervening variable and programme performance with respect to family planning and health services as the dependent variable: Concerning organizational factors, however, due to the limited number of HSCs (2 in the study area and 3 in the control area), they were studied by participatory observation of an anthropologist who was independent of the project. In this observation, we examined whether the assumed integration process actually occurred or not. If not, what were the constraints in producing an effective integration process. Summary of Findings; A) Program effects and impact 1. Effects on FP use: During this 2 year action period, FP acceptance increased from 58% in 1981 to 78% in 1984 in both the study and control areas. This increase in both areas was mainly due to the new family planning campaign driven by the Government for the same study period. Therefore, there was no increment of FP acceptance rate due to additional input of MW to the on-going FP program. But in the study area, quality aspects of FP were somewhat improved, having a better continuation rate of IUDs & pills and more use of effective Contraceptive methods in comparison with the control area. 2. Effects of use of MCH services: Between the study and control areas, however, there was a significant difference in maternal and child health care. For example, the coverage of prenatal care was increased from 53% for 1981 birth cohort to 75% for 1984 birth cohort in the study area. In the control area, the same increased from 41% (1981) to 65% (1984). It is noteworthy that almost two thirds of the recent birth cohort received prenatal care even in the control area, indicating that there is a growing demand of MCH care as the size of family norm becomes smaller 3. There has been a substantive increase in delivery care by medical professions in the study area, with an annual increase rate of 10% due to midwives input in the study areas. The project had about two times greater effect on postnatal care (68% vs. 33%) at delivery care(45.2% vs. 26.1%). 4. The study area had better reproductive efficiency (wanted pregancies with FP practice & healthy live births survived by one year old) than the control area, especially among women under 30 (14.1% vs. 9.6%). The proportion of women who preferred the 1st trimester for their first prenatal care rose significantly in the study area as compared to the control area (24% vs 13%). B) Effects on Interactive Linkage 1. This project made a contribution in making several useful steps in the direction of service integration, namely; i) The health workers have become familiar with procedures on how to work together with each other (especially with a midwife) in carrying out their work in FP/MCH and, ii) The health workers have gotten a feeling of the usefulness of family health records (statistical integration) in identifying targets in their own work and their usefulness in caring for family health. 2. On the other hand, because of a lack of required organizational factors, complete linkage was not obtained as the project intended. i) In regards to the government health worker's activities in terms of home visiting there was not much difference between the study & control areas though the MW did more home visiting than Government health workers. ii) In assessing the service performance of MW & health workers, the midwives balanced their workload between 40% FP, 40% MCH & 20% other activities (mainly immunization). However,
This experiment was designed to explore the specific functional interrelations between the vestibular semicircular canals and the extraocular muscles which may disclose the neural organization, connecting the vestibular canals and each ocular motor nuclei in the brain system, for vestibuloocular reflex mechanism. In urethane anesthetized rabbits, a fine wire insulated except the cut cross section of its tip was inserted into the canals closely to the ampullary receptor organs through the minute holes provided on the osseous canal wall for monopolar stimulation of each canal nerve. All extraocular muscles of both eyes were ligated and cut at their insertio, and the isometric tension and EMG responses of the extraocular muscles to the vestibular canal nerve stimulation were recorded by means of a physiographic recorder. Upon stimulation of the semicircular canal nerve, direction if the eye movement was also observed. The experimental results were as follows. 1) Single canal nerve stimulation with high frequency square waves (240 cps, 0. 1 msec) caused excitation of three extraocular muscles and inhibition of remaining three muscles in the bilateral eyes; stimulation of any canal nerve of a unilateral labyrinth caused excitation (contraction) of the superior rectus, superior oblique and medial rectus muscles and inhibition (relaxation) of the inferior rectus, inferior oblique and lateral rectos muscles in the ipsilateral eye, and it caused the opposite events in the contralateral eye. 2) By the overlapped stimulation of triple canal nerves of a unilateral labyrinth, unidirectional (excitatory or inhibitory) summation of the individual canal effects on a given extraocular muscles was demonstrated, and this indicates that three different canals of a unilateral vestibular system exert similar effect on a given extraocular muscles. 3) Based on the above experimental evidences, a simple rule by which one can define the vestibular excitatory and inhibitory input sources to all the extraocular muscles is proposed; the superior rectus, superior oblique and medial rectus muscles receive excitatory impulses from the ipsilateral vestibular canals, and the inferior rectus, inferior oblique and lateral rectus muscles from the contralateral canals; the opposite relationship applies for vestibular inhibitory impulses to the extraocular muscles. 4) According to the specific direction of the eye movements induced by the individual canal nerve stimulation, an extraocutar muscle exerting major role (a muscle of primary contraction) and two muscles of synergistic contraction could be differentiated in both eyes. 5) When these experimental results were compared to the well known observations of Cohen et al. (1964) made in the cats, extraocular muscles of primary contraction were the same but those of synergistic contraction were partially different. Moreover, the oblique muscle responses to each canal nerve excitation appeared to be all identical. However, the responnes of horizontal (medial and lateral) and vertical (superior and inferior) rectus muscles showed considerable differences. By critical analysis of these data, the author was able to locate theoretical contradictions in the observations of Cohen et al. but not in the author's results. 6) An attempt was also made to compare the functional observation of this experiment to the morphological findings of Carpenter and his associates obtained by degeneration experiments in the monkeys, and it was able to find some significant coincidence between there two works of different approach. In summary, the author has demonstrated that the well known observations of Cohen et al. on the vestibulo-ocular interrelation contain important experimental errors which can he proved by theoretical evaluation and substantiated by a series of experiments. Based on such experimental evidences, a new rule is proposed to define the interrelation between the vestibular canals and the extraocular muscles.