• Title/Summary/Keyword: 학술지 선정

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A Study of Nerve Conduction Velocity of Normal Adults (정상성인의 신경전도속도에 관한 연구)

  • Choi, Kyoung-Chan;Hah, Jung-Sang;Byun, Yeung-Ju;Park, Choong-Suh;Yang, Chang-Heon
    • Journal of Yeungnam Medical Science
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    • v.6 no.1
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    • pp.151-163
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    • 1989
  • Nerve conduction studies help delineate the extent and distribution of the neural lesion. The nerve conduction was studied on upper(median, ulnar and radial nerves) and lower(personal, posterior tibial and sural nerves) extremities in 83 healthy subjects 23 to 66 years of age. and normal values were established(Table 1). The mean motor terminal latency (TL) were : median. 3.6(${\pm}0.6$)milliseconds ; ulnar. 2.9(${\pm}0.5$) milliseconds ; radial nerve. 2.3(${\pm}0.4$) milliseconds. Mean motor nerve conduction velocity(MNCV) along distal and proximal segments: median. 61.2(${\pm}9.1$) (W-E) and 57.8(${\pm}13.2$) (E-Ax) meters per second ; ulnar. 63.7(${\pm}9.1$) (W-E) and 50.(${\pm}10.0$) meters per second. Mean sensory nerve conduction velocity(SNCV) : median. 34.7(${\pm}6.7$) (F-W), 63.7(${\pm}7.1$) (W-E) and 62.8(${\pm}12.3$) (E-Ax)meters per second ; ulnar. 38.0(${\pm}6.7$)(F-W), 63.4(${\pm}7.5$) (W-E) and 57.0(${\pm}10.1$) (E-Ax)meters per second ; radial, 45.3(${\pm}6.8$) (F-W) and 64.2(${\pm}11.0$) (W-E) meters per second ; sural nerve, 43.4(${\pm}6.1$) meters per second. The amplitudes of action potential and H-reflex were also standardized. Mean H latency was 28.4(${\pm}3.2$) milliseconds. And. the fundamental principles, several factors altering the rate of nerve conduction and clinical application of nerve stimulation techniques were reviewed.

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Vegetation classification based on remote sensing data for river management (하천 관리를 위한 원격탐사 자료 기반 식생 분류 기법)

  • Lee, Chanjoo;Rogers, Christine;Geerling, Gertjan;Pennin, Ellis
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.6-7
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    • 2021
  • Vegetation development in rivers is one of the important issues not only in academic fields such as geomorphology, ecology, hydraulics, etc., but also in river management practices. The problem of river vegetation is directly connected to the harmony of conflicting values of flood management and ecosystem conservation. In Korea, since the 2000s, the issue of river vegetation and land formation has been continuously raised under various conditions, such as the regulating rivers downstream of the dams, the small eutrophicated tributary rivers, and the floodplain sites for the four major river projects. In this background, this study proposes a method for classifying the distribution of vegetation in rivers based on remote sensing data, and presents the results of applying this to the Naeseong Stream. The Naeseong Stream is a representative example of the river landscape that has changed due to vegetation development from 2014 to the latest. The remote sensing data used in the study are images of Sentinel 1 and 2 satellites, which is operated by the European Aerospace Administration (ESA), and provided by Google Earth Engine. For the ground truth, manually classified dataset on the surface of the Naeseong Stream in 2016 were used, where the area is divided into eight types including water, sand and herbaceous and woody vegetation. The classification method used a random forest classification technique, one of the machine learning algorithms. 1,000 samples were extracted from 10 pre-selected polygon regions, each half of them were used as training and verification data. The accuracy based on the verification data was found to be 82~85%. The model established through training was also applied to images from 2016 to 2020, and the process of changes in vegetation zones according to the year was presented. The technical limitations and improvement measures of this paper were considered. By providing quantitative information of the vegetation distribution, this technique is expected to be useful in practical management of vegetation such as thinning and rejuvenation of river vegetation as well as technical fields such as flood level calculation and flow-vegetation coupled modeling in rivers.

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Long-term Effect of Desferrioxamine to rHuEPO Resistant Anemia in Hemodialysis Patients (혈액 투석 환자에서 나타나는 rHuEPO 저항성 빈혈에 대한 Desferrioxamine의 장기 효과)

  • Lim, Sang-Woo;Jung, Hang-Jae;Bae, Sung-Wha;Do, Jun-Young;Yoon, Kyung-Woo
    • Journal of Yeungnam Medical Science
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    • v.14 no.2
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    • pp.399-414
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    • 1997
  • There are several factors concerning to anemia in chronic renal failure patients. But when rHuEPO is used, most of these factors can be overcome, and the levels of hemoglobin are increased. However, about 10% of the renal failure patients represent rHuEPO-resistant anemia eventhough high dosage of rHuEPO. For these cases, desferrioxamine can be applied to correct rHuEPO resistnacy, and many mechanism of DFO are arguing. So we are going to know whether DFO can be applied to correct anemia of the such patients, how long its effect can be continued. The seven pateients as experimental group(DFO+EPO) who represent refractoriness to rHuEPO and the other seven patients as control group(EPO) were included. Experimental group had lower than 9 g/dL of hemoglobin levels despite high rHuEPO dosage (more than 4000U/Wk) and showed normocytic normochromic anemia. There were no definitve causes of anemia such as hemorrhage or iron deficiency. Control group patients had similar characteristics in age, mean dialysis duration but showed adequate response to rHuEPO. DFO was administered to experimental group for 8 weeks along with rHuEPO(the rHuEPO individual mean dosage had been determined by mean dosage of the previous 6 months. Total mean dosage; 123.5 U/Kg/Wk). After 8 weeks of DFO administration, the hemoglobin and rHuEPO dosage levels were checked for 15 consecutive months. It should be noted that the patients determined their own rHuEPO dosage levels according to hemoglobin levels and economic status. In conrol group, rHuEPO was administered by the same method used in experimental group without DFO through the same period. Fifteen months of observation period after DFO trial were divided as Time I(7 months after DFO trial) and Time II(8 months after Time I). The results are as follows: Before DFO trial, mean hemoglobin level of experimental group was 7.8 g/dL, which is similar level(p>0.05) to control group(mean Hb; 8.2 g/dL). But in experimental group, significantly(p<0.05) higher dosages of rHuEPO(mean; 123.5 U/Kg/Wk) than control group (mean; 41.6 U/Kg/Wk) had been used. It means resistancy to rHuEPO of experimental group. But after DFO trial, the hemoglobin levels of the experimental group were increased significantly(p<0.05), and these effect were continued to Time II.(Time I; mean 8.6g/dL, Time II; mean 8.6g/dL) The effects of DFO to hemoglobin were continued for 15 months after DFO trial with similar degree through Time I, Time II. Also, rHuEPO dosages used in the experimental group were decreased to similar levels of the control group after DFO trial and these effect were also continued for 15 months(Time I; mean 48.1 U/Kg/Wk. Time II; mean 51.8 U/Kg/Wk). In the same period, hemoglobin levels and rHuEPO dosages used in the control group were not changed significantly. Notibly, hemoglobin increment and rHuEPO usage decrement in experimental group were showed maxilly in the 1st month after DFO trial. That is, after the use of DFO, erythopoiesis was enhanced with a reduced rHuEPO dosage. So we think rHuEPO reisistancy can be overcome by DFO therapy. In conclusion, the DFO can improve the anemia caused by chronic renal failure at least over 1 year, and hence, can reduce the dosage of rHuEPO for anemia correction. Additional studies in order to determine the mechanism of DFO on erythropoiesis and careful attention to potential side effects of DFO will be needed.

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