Cholinergic innervation of the hippocampus is known to be correlated with learning and memory. The cholinergic agonist carbachol (CCh) modulate synaptic plasticity and produced long-term synaptic depression (LTD) in the hippocampus. However, the exact mechanisms by which the cholinergic system modifies synaptic functions in the hippocampus have yet to be determined. This study introduces an acetylcholine receptor-mediated LTD that requires internalization of alpha-amino-3-hydroxy-5-methylisoxazole-4-propionate (AMPA) receptors on the postsynaptic surface and their intracellular mechanism in the hippocampus. In the present study, we showed that the application of the cholinergic agonist CCh reduced the surface expression of GluA2 on synapses and that this reduction was prevented by the M1 muscarinic acetylcholine receptor antagonist pirenzepine in primary hippocampal neurons. The interaction between GluA2 and the glutamate receptor-interacting protein 1 (GRIP1) was disrupted in a hippocampal slice from a rat upon CCh simulation. Under the same conditions, the binding of GluA2 to adaptin-α, a protein involved in clathrin-mediated endocytosis, was enhanced. The current data suggest that the activation of LTD, mediated by the acetylcholine receptor, requires the internalization of the GluA2 subunits of AMPA receptors and that this may be controlled by the disruption of GRIP1 in the PDZ ligand domain of GluA2. Therefore, we can hypothesize that one mechanism underlying the LTD mediated by the M1 mAChR is the internalization of the GluA2 AMPAR subunits from the plasma membrane in the hippocampal cholinergic system.
Groundwater flow in fractured rock masses is controlled by combined effects of fracture networks, state of geostafic stresses and crossflow between fractures and rock matrix. Furthermore the scaie dependent, anisotropic properties of hydraulic parameters results mainly from irregular paftems of fracture system, which can not be evaluated properly with the methods available at present. The basic assumpfion of discrete fracture network model is that groundwater flows only along discrete fractures and the flow paths in rock mass are determined by geometric paftems of interconnected fractures. The characteristics of fracture distribution in space and fracture hydraulic parameters are represented as the probability density functions by stochastic simulation. The discrete fracture network modelling was aftempted to characterize the groundwater flow in the vicinity of existing large cavems located in Wonjeong-ri, Poseung-myon, Pyeungtaek-kun. The fracture data of $1\textrm{km}^2$ area were analysed. The result indicates that the fracture sets evaluated from an equal area projection can be grouped into 6 sets and the fracture sizes are distributed in longnormal. The conductive fracture density of set 1 shows the highest density of 0.37. The groundwater inflow into a carvem was calculated as 29ton/day with the fracture transmissivity of $10^{-8}\textrm{m}^2/s$. When the fracture transmissivity increases in an order, the inflow amount estimated increases dramatically as much as fold, i.e 651 ton/day. One of the great advantages of this model is a forward modelling which can provide a thinking tool for site characterization and allow to handle the quantitative data as well as qualitative data.
Two-Photon Fluorescence (TPF) experiment measures temporal width of an amplified short laser pulse which has passed through a four-pass Nd: glass amplifier, after selecting a single pulse from pulse train Q-switched and mode-locked(QSML) in Nd:YLF master oscillator. Determination of pulsewidth and pulseshape was also made with detection of autocorrelation trace of CW mode-locked pulse train by using noncollinear type I Second Harmonic Generation (SHG) method. The observed TPF track showed various patterns, depending on pulse-selecting position in QSML pulse train. That is, autocorrelation of a pulse extracted at front of the train displayed smooth pulse shape, while one from the trailing part of the train created many sharp spikes and substructure in the pulse. By TPF method, pulsewidth was measured to be 44.4 ps with contrast ratio of 2.86 which enabled us to find out energy fraction of a pulse to total energy, (sum of pulse and background); we obtain the value of 0.62. Pulsewidth of 46.6ps was also acquired in another SHG experiment with the help of only mode-locked pulse train. On the other hand, we confirmed that shape of the pulse is close to $sech^2$ one as a result of fitting the SHG autocorrelation signal with various functions. With simulation using this $sech^2$ type of pulse, pulsewidth reduction of the beam, having passed through four-pass amplifier, was also verified.
Yun, Sang Yeop;Jung, Ho Chul;Lee, In-Beum;Chang, Kun Soo
제어로봇시스템학회:학술대회논문집
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1991.10b
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pp.1639-1645
/
1991
Because of the important role LD converters play in the production of high quality steel, various dynamic models have been attempted in the past by many researchers not only to understand the complex chemical reactions that take place in the converter process but also to assist the converter operation itself using computers. And yet no single dynamic model was found to be completely satisfactory because of the complexity involved with the process. The process indeed involves dynamic energy and mass balances at high temperatures accompanied by complex chemical reactions and transport phenomena in the molten state. In the present study, a mathematical model describing the dynamic behavior of LD converter process has been developed. The dynamic model describes the time behavior of the temperature and the concentrations of chemical species in the hot metal bath and slag. The analysis was greatly facilitated by dividing the entire process into three zones according to the physical boundaries and reaction mechanisms. These three zones were hot metal (zone 1), slag (zone 2) and emulsion (zone 3) zones. The removal rate of Si, C, Mn and P and the rate of Fe oxidation in the hot metal bath, and the change of composition in the slag were obtained as functions of time, operating conditions and kinetic parameters. The temperature behavior in the metal bath and the slag was also obtained by considering the heat transfer between the mixing and the slag zones and the heat generated from chemical reactions involving oxygen blowing. To identify the unknown parameters in the equations and simulate the dynamic model, Hooke and Jeeves parttern search and Runge-Kutta integration algorithm were used. By testing and fitting the model with the data obtained from the operation of POSCO #2 steelmaking plant, the dynamic model was able to predict the characteristics of the main components in the LD converter. It was possible to predict the optimum CO gas recovery by computer simulation
The objective of this study is to evaluate the impacts on the domestic timber supply potential of forest resources management policies such as the extention of forest management infrastruture and setting aside more forest lands for the provision of environmental goods. To this end, the domestic timber supply functions were estimated using time series data for the period 1970-1990 and were used to predict the future trends in timber production in the Republic of Korea. For this purpose, a set of scenarios based on the forest road density and forest inventory growth were designed for the next 40 years. The timber supply behavior in Korea was found to be different by species group : domestic supply of softwood roundwood is inelastic with respect to its ovum price while that of hardwood elastic. The effect of forest road construction on the domestic timber production seems to be insignificant yet. The model simulation aided by policy scenarios revealed that the future timber supply potential will be largely restricted if the policy option with emphasis on the provision of environmental goods from the forest resources were adopted.
Asynchronous transfer mode is flexible to support multimedia communication services using asynchronous time-sharing and statistical multimedia techniques to the existing data communication area, ATM ABR service controls network traffic using feedback information on the network congestion situation in order to guarantee the demanded service qualities and the available cell rates, In this paper we apply the control method using queue length prediction to the formation of feedback information for more efficient ABR traffic control. If backward node receive the longer delayed feedback information on the impending congestion, the switch can be already congested from the uncontrolled arriving traffic and the fluctuation of queue length can be inefficiently high in the continuing time intervals, The feedback control method proposed in this paper predicts the queue length in the switch using the slope of queue length prediction function and queue length changes in time-series, The predicted congestion information is backward to the node, NLMS and neural network are used as the predictive control functions, and they are compared from performance on the queue length prediction. Simulation results show the efficiency of the proposed method compared to the feedback control method without the prediction, Therefore, we conclude that the efficient congestion and stability of the queue length controls are possible using the prediction scheme that can resolve the problems caused from the longer delays of the feedback information.
We consider a linear calibration problem, $y_i = $$\alpha + \beta (x_i - x_0) + \epsilon_i$, $i=1, 2, {\cdot}{\cdot},n$$y_f = \alpha + \beta (x_f - x_0) + \epsilon, $ where we observe $(x_i, y_i)$'s for the controlled calibration experiments and later we make inference about $x_f$ from a new observation $y_f$. The objective of the calibration design problem is to find the optimal design $x = (x_i, \cdots, x_n$ that gives the best estimates for $x_f$. We compare Kim(1989)'s Bayesian design which minimizes the expected value of the posterior variance of $x_f$ and some optimal designs from literature. Kim suggested the Bayesian optimal design based on the analysis of the characteristics of the expected loss function and numerical must be equal to the prior mean and that the sum of squares be as large as possible. The designs to be compared are (1) Buonaccorsi(1986)'s AV optimal design that minimizes the average asymptotic variance of the classical estimators, (2) D-optimal and A-optimal design for the linear regression model that optimize some functions of $M(x) = \sum x_i x_i'$, and (3) Hunter & Lamboy (1981)'s reference design from their paper. In order to compare the designs which are optimal in some sense, we consider two criteria. First, we compare them by the expected posterior variance criterion and secondly, we perform the Monte Carlo simulation to obtain the HPD intervals and compare the lengths of them. If the prior mean of $x_f$ is at the center of the finite design interval, then the Bayesian, AV optimal, D-optimal and A-optimal designs are indentical and they are equally weighted end-point design. However if the prior mean is not at the center, then they are not expected to be identical.In this case, we demonstrate that the almost Bayesian-optimal design was slightly better than the approximate AV optimal design. We also investigate the effects of the prior variance of the parameters and solution for the case when the number of experiments is odd.
Han, Daegun;Kim, Deokhwan;Kim, Jungwook;Jung, Jeawon;Lee, Jongso;Kim, Hung Soo
Journal of Wetlands Research
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v.21
no.spc
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pp.90-97
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2019
In recent years, flood due to the consecutive storm events have been occurred and property damage and casualties are in increasing trend. This study calls the consecutively occurred storm events as a mega rainfall scenario and the discharge by the scenario is defined as a mega flood discharge. A mega rainfall scenario was created on the assumption that 100-year frequency rainfall events were consecutively occurred in the Gyeongancheon stream basin. The SSARR (Streamflow Synthesis and Reservoir Regulation) model was used to estimate the mega flood discharge using the scenario in the basin. In addition, in order to perform more reasonable runoff analysis, the parameters were estimated using the SCE_UA algorithm. Also, the calibration and verification were performed using the objective functions of the weighted sum of squared of residual(WSSR), which is advantageous for the peak discharge simulation and sum of squared of residual(SSR). As a result, the mega flood discharge due to the continuous occurrence of 100-year frequency rainfall events in the Gyeongan Stream Basin was estimated to be 4,802㎥/s, and the flood discharge due to the 100-year frequency single rainfall event estimated by "the Master Plan for the Gyeongancheon Stream Improvement" (2011) was 3,810㎥/s. Therefore, the mega flood discharge was found to increase about 992㎥/s more than the single flood event. The results of this study can be used as a basic data for Comprehensive Flood Control Plan of the Gyeongan Stream basin.
Journal of the military operations research society of Korea
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v.2
no.1
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pp.127-143
/
1976
The purpose of this thesis is to study the optimal arrangement of aircraft instrument panels through the human factors approach. Human factors engineering is the process of effectively fitting the human component to the machine component in any man-machine system. The human factors. are especially important to an aircraft pilot who must constantly shift his attention between the instrument panel within the cockpit and the surrounding area of the aircraft. The preliminary part of this study is to find the general patterns of the Korean pilot's eye movements during their various flying maneuvers, and which instruments require the most attention while in flight. It is assumed that all pilots have a general pattern of eye movement when observing the aircraft instrument panel and that an optimum arrangement would be to minimize the eye travel distance between instruments. In this thesis the arrangements of instruments is taken to be the independent variable and the eye travel distance between instruments the dependent variable. la order to compile the information necessary for this study, sixty Korean Air Force pilots were interviewed and requested to complete information forms. These information forms listed various flying maneuvers and listed each instrument used on the instrument panel. The compilation of the information on these completed forms listed the instruments most frequently used by the pilots. The second part of this study was to determine the optimum instrument arrangement. It was necessary to study the various number of possible arrangements of instruments depending upon the number of instruments involved. Therefore, these instruments are grouped by two major functions, The flight instruments were subdivided into three groups, and the engineering instruments were subdivided into six groups. With this subdivision we arrive at the possible number of arrangements of 4,320. Through the simulation method, total eye travel distance for each of these 4,320 arrangements is calculated and the arrangement which appears to be of optimum distance between the most frequently used aircraft instruments is determined. The results of this study indicate that the optimum distance between instruments would be 33,028cm and that the corresponding distance of the instrument panel now being used is 34,288cm. Therefore, an increased efficiency of $3.8\%$ would be realized if the existing aircraft instrument panel were re-arranged according to layout proposed in this thesis.
In hydrologic modeling, prediction uncertainty generally stems from various uncertainty sources associated with model structure, data, and parameters, etc. This study aims to assess the parameter uncertainty effect on hydrologic prediction results. For this objective, a distributed rainfall-sediment yield-runoff model, which consists of rainfall-runoff module for simulation of surface and subsurface flows and sediment yield module based on unit stream power theory, was applied to the mesoscale mountainous area (Cheoncheon catchment; 289.9 $km^2$). For parameter uncertainty evaluation, the model was calibrated by a multi-objective optimization algorithm (MOSCEM) with two different objective functions (RMSE and HMLE) and Pareto optimal solutions of each case were then estimated. In Case I, the rainfall-runoff module was calibrated to investigate the effect of parameter uncertainty on hydrograph reproduction whereas in Case II, sediment yield module was calibrated to show the propagation of parameter uncertainty into sedigraph estimation. Additionally, in Case III, all parameters of both modules were simultaneously calibrated in order to take account of prediction uncertainty in rainfall-sediment yield-runoff modeling. The results showed that hydrograph prediction uncertainty of Case I was observed over the low-flow periods while the sedigraph of high-flow periods was sensitive to uncertainty of the sediment yield module parameters in Case II. In Case III, prediction uncertainty ranges of both hydrograph and sedigraph were larger than the other cases. Furthermore, prediction uncertainty in terms of spatial distribution of erosion and deposition drastically varied with the applied model parameters for all cases.
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