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    ๋ธ”๋ ˆ์ด์ €๋“ค์˜ ์ „ํŒŒ/๊ฐ๋งˆ์„  ์ƒ๊ด€๊ด€๊ณ„

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ๋ฌผ๋ฆฌยท์ฒœ๋ฌธํ•™๋ถ€(์ฒœ๋ฌธํ•™์ „๊ณต), 2021.8. Sascha Trippe.Relativistic jets in Active Galactic Nuclei (AGN) are one of the most powerful, persistent sources of energy in the Universe. Investigation of AGN jets is valuable and promising as they play an important role in not only the fields of high-energy astrophysics, but also the evolution of galaxies and clusters. Radio-loud AGNs with their relativistic jets directed toward us (e.g., with a viewing angle of โˆผ5 degrees), are classified as blazars. One of the well-known characteristics of blazars is strong ฮณ-ray emission originating from their relativistic jets. Because the spatial res- olution of high-energy telescopes is inadequate, however, our understanding of the high-energy emission is limited and thus the production site of blazar ฮณ-ray flares is a matter of active de- bate. To explore the high-energy emission processes and its origin, I studied several individual blazars that recently showed strong ฮณ-ray emission: BL Lacertae, OT 081 (1749+096), 3C 273, and 0716+714. In these studies, I analyzed their multi-wavelength (radio-to-ฮณ-ray) light curves and Very Long Baseline Interferometry (VLBI) datasets on both the time-domain and image- plane to investigate the variations in emission, structure, and kinematics of the jets during a number of ฮณ-ray flaring periods. The blazar BL Lacertae which is the prototypical BL Lac object (a subclass of blazar), was explored using VLBI datasets obtained from the Korean VLBI Network (KVN). Properties of the radio jet are presented with light curves of the radio core (i.e., the VLBI core seen by the KVN) at 22, 43, 86, and 129 GHz. Our observations covered the decaying part of a strong radio flare. The timescales (ฯ„) of the exponential decays show the following relationship: ฯ„ โˆ ฮฝโˆ’0.2 , with ฮฝ being observing frequency. This is much shallower than the one expected from opacity effects (i.e., the core shift). Simultanous multi-frequency observations of the KVN allow us to perform spectral analysis of the radio emission. The spectral indices versus time and radio frequency, support the models of recollimation shocks (Marscher et al. 2008) and the generalized shock evolution (Valtaoja et al. 1992). OT 081 is a blazar with a compact radio jet. In many VLBI images, the source shows a simple point-like feature without any notable extended structures. It had been consistently bright at radio wavelengths (e.g., a few Jy), but without noteworthy strong ฮณ-ray outbursts. However, there was a historically strong ฮณ-ray outburst in 2016 in this source. To investigate this phenomenon, multi-waveband data were used: KVN and OVRO (radio), ASAS-SN (opti- cal), Swift-XRT (X-ray), and Fermi-LAT (ฮณ-ray). It was revealed that the 2016 ฮณ-ray outburst is highly correlated with emission at lower frequencies from radio to X-ray. By using VLBA observations, we found that this ฮณ-ray event was accompanied by the emergence of a moving polarized knot from the radio core which propagates further downstream of the flow. Combin- ing all the evidence, we conclude that the radio core is the origin of the ฮณ-ray outburst. Blazars can be divided into two subclasses: flat-spectrum radio quasars (FSRQ) and BL Lac objects, based on the presence/absence of broad optical emission lines. Recent studies sup- ported that ฮณ-rays of FSRQs originate from a region beyond the broad-line region (BLR), sug- gesting distances of a few parsecs from the central engine where the radio core is thought to be located. Motivated by this, I investigated two recent ฮณ-ray outbursts of the FSRQ 3C 273 which is one of the most powerful and famous blazars. Analysis were done with data obtained from the ALMA, VLBA, and Fermi-LAT. In order to check the correlation between radio and ฮณ-ray emission, the discrete correlation function (DCF) was employed. Our results indicate that the compact features (i.e., multiple standing shocks) are responsible for the observed ฮณ-ray outbursts in the jet of 3C 273. 0716+714 is known to have extreme variability over the entire electromagnetic spectrum. Our preliminary findings of an unusual anti-correlation between radio and ฮณ-ray emission in this source, lead us to start a detailed study of the radio/ฮณ-ray connection in the jet of 0716+714. Archival multi-frequency data (i.e., SMA, Metsรคhovi, OVRO, Fermi-LAT, and VLBA) were employed and the correlation analysis between the datasets was performed using the techniques of modeling and simulating the light curves. As a result, we found three significant radio-to- ฮณ-ray correlations: two anti-correlations and one positive correlation. We also analyzed VLBA datasets to investigate the parsec-scale jet activity during the ฮณ-ray flares. With all the evidence, we constrain the origin of the ฮณ-ray flares in the jet and suggest internal-shock interactions induced by the passage of a moving disturbance through the radio core as the mechanism behind the observed correlated behaviors. Physics of the relativistic jets in blazars is tricky and complicated due to the extreme physical conditions and various scenarios/possibilities. More detailed observations of the jets with high-resolution VLBI arrays, are currently the best way to resolve the issues of the jet physics. This thesis presents new observational data and results on the nature of blazar ฮณ-ray flares and contributes to the scientific community by supplying the wealth of information for the cases of four remarkable blazars. The individual studies presented in this thesis, conclude as follow: (1) blazar ฮณ-ray flares have multiple emission regions in the jets (i.e., subpc/pc-scales distances from the central black hole) and (2) the propagation of shocks/disturbances along the jet in the subpc/pc-scale regions, causes ฮณ-ray flares (particularly when they pass through the standing shock features; e.g., the radio core).ํ™œ๋™์„ฑ์€ํ•˜ํ•ต (AGN)๋“ค์˜ ์ƒ๋Œ€๋ก ์  ์ œํŠธ๋Š” ์šฐ์ฃผ์—์„œ ๊ฐ€์žฅ ๊ฐ•๋ ฅํ•˜๋ฉฐ ์˜์†์ ์ธ ์—๋„ˆ์ง€ ์†Œ์Šค๋“ค ์ค‘์— ํ•˜๋‚˜์ด๋‹ค. ๊ณ ์—๋„ˆ์ง€ ์ฒœ์ฒด๋ฌผ๋ฆฌ๋ถ„์•ผ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์€ํ•˜์™€ ์„ฑ๋‹จ์˜ ์ง„ํ™”์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•จ์— ๋”ฐ๋ผ, AGN ์ œํŠธ๋“ค์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ๊ฐ€์น˜์žˆ์œผ๋ฉฐ ์ „๋„์œ ๋งํ•˜๋‹ค. ์ „ํŒŒ์—์„œ ๋ฐ์€ AGN (radio-loud AGN)๋“ค ์ค‘, ๊ทธ๋“ค์˜ ์ œํŠธ๊ฐ€ ๋ป—์–ด๋‚˜๊ฐ€๋Š” ์ถ•๊ณผ ์šฐ๋ฆฌ์˜ ์‹œ์„ ๋ฐฉํ–ฅ ์‚ฌ์ด์˜ ๊ฐ๋„๊ฐ€ ๋งค์šฐ ์ž‘์€ (์•ฝ 5๋„ ์ด๋‚ด) AGN๋“ค์€ ๋ธ”๋ ˆ์ด์ € (Blazar)๋กœ์จ ๋ถ„๋ฅ˜๋œ๋‹ค. Blazar๋“ค์˜ ๋Œ€ํ‘œ์ ์ธ ํŠน์ง• ์ค‘ ํ•˜๋‚˜๋Š” ๊ทธ๋“ค์˜ ์ œํŠธ๋กœ๋ถ€ํ„ฐ ๋‚˜์˜ค๋Š” ๊ฐ•๋ ฅํ•œ ๊ฐ๋งˆ์„  ๋ฐฉ์ถœ์ด๋‹ค. ํ•˜์ง€๋งŒ ๊ณ ์—๋„ˆ์ง€ ๋ง์›๊ฒฝ๋“ค์˜ ๊ณต๊ฐ„๋ถ„ํ•ด๋Šฅ์ด ์ถฉ๋ถ„ํ•˜์ง€ ๋ชปํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ๊ทธ๋Ÿฌํ•œ ๊ณ ์—๋„ˆ์ง€ ๋น› ๋ฐฉ์ถœ์— ๋Œ€ํ•œ ์šฐ๋ฆฌ์˜ ์ดํ•ด๋Š” ์ œํ•œ๋˜์–ด ์žˆ๊ณ , ์ด์— ๋”ฐ๋ผ Blazar ๊ฐ๋งˆ์„  ํญ๋ฐœ์˜ ๊ธฐ์›์€ ํ˜„์žฌ ํ™œ๋ฐœํ•œ ๋…ผ์Ÿ ์ค‘์— ์žˆ๋‹ค. ๊ทธ๋Ÿฌํ•œ ๊ณ ์—๋„ˆ์ง€ ๋น›์˜ ๋ฐฉ์ถœ๊ธฐ์ž‘๊ณผ ๊ธฐ์›์„ ํƒ๊ตฌํ•˜๊ธฐ ์œ„ํ•ด์„œ, ๋ณธ ์ €์ž๋Š” ์ตœ๊ทผ ๊ฐ•ํ•œ ๊ฐ๋งˆ์„  ๋ฐฉ์ถœ์„ ๋ณด์ธ ๋ช‡ ๊ฐœ์˜ ๊ฐœ๋ณ„ Blazar๋“ค์„ ์—ฐ๊ตฌํ•˜์˜€๋‹ค: BL Lacertae, OT 081 (1749+096), 3C 273, ๊ทธ๋ฆฌ๊ณ  0716+714. ์ด ์—ฐ๊ตฌ๋“ค์—์„œ ๋ณธ ์ €์ž๋Š” ๊ฐ๋งˆ์„  ํญ๋ฐœ ๊ธฐ๊ฐ„ ๋™์•ˆ์— ์ œํŠธ๋“ค์˜ ๋น›, ๊ตฌ์กฐ, ๊ทธ๋ฆฌ๊ณ  ์šด๋™ํ•™์ด ์–ด๋–ป๊ฒŒ ๋ณ€ํ™”ํ•˜๋Š”์ง€๋ฅผ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ, ์ด๋ฅผ ์œ„ํ•ด ๊ทธ๋“ค์˜ ๋‹คํŒŒ์žฅ (์ „ํŒŒ-๊ฐ๋งˆ์„ ) ๋ณ€๊ด‘๊ณก์„  ๋ฐ ์ตœ์žฅ๊ธฐ์„  ๊ฐ„์„ญ๊ณ„ (VLBI) ๋ฐ์ดํ„ฐ๋“ค์„ ์‹œ๊ฐ„๋„๋ฉ”์ธ๊ณผ ์ด๋ฏธ์ง€๋ฉด ์œ„์—์„œ ๋ถ„์„ํ•˜์˜€๋‹ค. Blazar์˜ ํ•œ ์œ ํ˜•์ธ BL Lac object์— ์†ํ•˜๋ฉฐ, ๋˜ํ•œ ํ•ด๋‹น ํƒ€์ž…์˜ ์›ํ˜•์ด๊ธฐ๋„ ํ•œ BL Lacertae๊ฐ€ ํ•œ๊ตญ VLBI ๊ด€์ธก๊ธฐ์ธ KVN๋ฅผ ์ด์šฉํ•ด ์—ฐ๊ตฌ๋˜์–ด์กŒ๋‹ค. 22, 43, 86, ๊ทธ๋ฆฌ๊ณ  129 GHz์—์„œ ์–ป์–ด์ง„ ์ „ํŒŒ์ฝ”์–ด์˜ ๋ณ€๊ด‘๊ณก์„ ์„ ์ด์šฉํ•˜์—ฌ ์–ป์–ด์ง„ ์ œํŠธ์˜ ํŠน์„ฑ๋“ค์ด ๋‚˜ํƒ€๋‚ด์–ด์กŒ๋‹ค. ์šฐ๋ฆฌ์˜ ๊ด€์ธก๋ฐ์ดํ„ฐ๋Š” ํ•˜๋‚˜์˜ ๊ฐ•๋ ฅํ•œ ์ „ํŒŒ ํญ๋ฐœ์˜ ๊ฐ์‡„ ๋ถ€๋ถ„์„ ํฌํ•จํ•œ๋‹ค. ์ง€์ˆ˜ํ•จ์ˆ˜์  ๊ฐ์‡„์˜ ์‹œ๊ฐ„๊ทœ๋ชจ (tau) ๋“ค์€ ๋‹ค์Œ์˜ ๊ด€๊ณ„์‹์„ ๋”ฐ๋ฅธ๋‹ค: tau ๋น„๋ก€ nu^-0.2, nu๋Š” ๊ด€์ธก์ฃผํŒŒ์ˆ˜๋ฅผ ๋‚˜ํƒ€๋‚ธ๋‹ค. ์ด๋Š” ๋ถˆํˆฌ๋ช…๋„ ํšจ๊ณผ (Core shift)๋กœ๋ถ€ํ„ฐ ์˜ˆ์ƒ๋˜๋Š” ๊ฒฐ๊ณผ์— ๋น„ํ•ด ๋งค์šฐ ์–•๋‹ค. KVN์˜ ๋‹ค์ฃผํŒŒ์ˆ˜ ๋™์‹œ๊ด€์ธก์€ ์ „ํŒŒ ๋ฐฉ์ถœ ๋น›์— ๋Œ€ํ•œ ๋ถ„๊ด‘ํ•™์  ๋ถ„์„์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•ด์ค€๋‹ค. ์‹œ๊ฐ„๊ณผ ์ „ํŒŒ ์ฃผํŒŒ์ˆ˜์— ๋Œ€ํ•œ ๋ถ„๊ด‘์ง€์ˆ˜ (Spectral index)์˜ ๋ณ€ํ™”๋Š” Recollimation shock ๋ชจ๋ธ๊ณผ Generalized shock ๋ชจ๋ธ๋“ค์„ ์ง€์ง€ํ•œ๋‹ค. OT 081์€ ์กฐ๋ฐ€ํ•˜๊ณ  ์†Œํ˜•์ธ ์ œํŠธ๋ฅผ ์ง€๋‹Œ Blazar์ด๋‹ค. ๋งŽ์€ VLBI ์ด๋ฏธ์ง€๋“ค์—์„œ ํ•ด๋‹น ์ œํŠธ๋Š” ๋ฐ”๊นฅ์ชฝ์œผ๋กœ ์—ฐ์žฅ๋œ ๋ˆˆ์— ๋„๋Š” ๊ตฌ์กฐ๋“ค ์—†์ด ๋‹จ์ˆœํ•œ ํฌ์ธํŠธ์™€ ๊ฐ™์€ ํ˜•ํƒœ์˜ ๊ตฌ์กฐ๋ฅผ ๋ณด์—ฌ์ค€๋‹ค. ์ด ์†Œ์Šค๋Š” ์ฃผ๋ชฉํ•  ๋งŒํ•œ ๊ฐ๋งˆ์„  ํญ๋ฐœ์—†์ด ์ „ํŒŒ์—์„œ ์ง€์†์ ์œผ๋กœ ๋ฐ์•„์™”์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ 2016๋…„๋„์— ์ด ํƒ€๊ฒŸ์†Œ์Šค์— ๋Œ€ํ•ด์„œ ์—ญ์‚ฌ์ ์œผ๋กœ ๊ฐ•๋ ฅํ•œ ๊ฐ๋งˆ์„  ํญ๋ฐœ์ด ๋ฐœ์ƒํ•˜์˜€์—ˆ๋‹ค. ์ด ํ˜„์ƒ์„ ์กฐ์‚ฌํ•˜๊ธฐ ์œ„ํ•ด, ๋‹คํŒŒ์žฅ ๋ฐ์ดํ„ฐ๋“ค์ด ์‚ฌ์šฉ๋˜์—ˆ๋‹ค: KVN๊ณผ OVRO (์ „ํŒŒ), ASAS-SN (๊ด‘ํ•™), Swift-XRT (์—‘์Šค์„ ), ๊ทธ๋ฆฌ๊ณ  Fermi-LAT (๊ฐ๋งˆ์„ ). 2016 ๊ฐ๋งˆ์„  ํญ๋ฐœ์ด ๋‚ฎ์€ ์ฃผํŒŒ์ˆ˜๋Œ€ (์ „ํŒŒ๋ถ€ํ„ฐ ์—‘์Šค์„ ๊นŒ์ง€)์˜ ๋ฐฉ์ถœ ๋น›๋“ค๊ณผ ์ƒ๋‹นํ•œ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์Œ์ด ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. VLBA ๊ด€์ธก๋ฐ์ดํ„ฐ๋ฅผ ์ด์šฉํ•จ์œผ๋กœ์จ, ์šฐ๋ฆฌ๋Š” ๋˜ํ•œ ์ด ๊ฐ๋งˆ์„  ํญ๋ฐœ์ด ์ „ํŒŒ์ฝ”์–ด๋กœ๋ถ€ํ„ฐ ๋‚˜์™€ ์ œํŠธ์˜ ํ•˜๋ฅ˜๋กœ ์ „ํŒŒ/์ด๋™ํ•ด๋‚˜๊ฐ€๋Š” ํŽธ๊ด‘ ์ปดํฌ๋„ŒํŠธ (Knot)์˜ ์ถœํ˜„์„ ์ˆ˜๋ฐ˜ํ–ˆ์—ˆ์Œ์„ ์ฐพ์•˜๋‹ค. ์ด๋Ÿฌํ•œ ๋ชจ๋“  ์ฆ๊ฑฐ๋“ค์„ ์กฐํ•ฉํ•ด๋ด„์œผ๋กœ์จ, ์šฐ๋ฆฌ๋Š” ์ „ํŒŒ์ฝ”์–ด๊ฐ€ ๊ฐ๋งˆ์„  ํญ๋ฐœ์˜ ๊ธฐ์›์ด๋ผ ๊ฒฐ๋ก ์ง€์—ˆ๋‹ค. Blazar๋“ค์€ ๋‘ ๊ฐ€์ง€ ์œ ํ˜•์œผ๋กœ ๋‚˜๋‰˜์–ด ์งˆ ์ˆ˜ ์žˆ๋‹ค: ๋„“์€ ๊ด‘ํ•™ ๋ฐฉ์ถœ์„ ์˜ ์กด์žฌ/๋ถ€์žฌ์— ๋”ฐ๋ผ, Flat-Spectrum Radio Quasar (FSRQ) ๊ทธ๋ฆฌ๊ณ  BL Lac object. ๊ทผ๋ž˜์˜ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋“ค์€ FSRQ๋“ค๋กœ๋ถ€ํ„ฐ ๋‚˜์˜ค๋Š” ๊ฐ๋งˆ์„ ๋“ค์ด Broad-Line Region (BLR) ๋„ˆ๋จธ์˜ ์ง€์—ญ์—์„œ ๊ธฐ์›ํ•จ์„ ์‹œ์‚ฌํ–ˆ์—ˆ๋‹ค. ์ด๋Š” ์ „ํŒŒ์ฝ”์–ด๊ฐ€ ์œ„์น˜ํ•ด ์žˆ์„ ๊ฒƒ์œผ๋กœ ์—ฌ๊ฒจ์ง€๋Š”, ์ค‘์•™์˜ ๋ธ”๋ž™ํ™€๋กœ๋ถ€ํ„ฐ ๋ช‡ ํŒŒ์„น (parsec) ๋–จ์–ด์ง„ ๊ฑฐ๋ฆฌ๋ฅผ ์•”์‹œํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์•„์ด๋””์–ด์— ์ฐฉ์•ˆํ•˜์—ฌ, ๋ณธ ์ €์ž๋Š” ๊ฐ€์žฅ ๊ฐ•ํ•˜๋ฉฐ ์œ ๋ช…ํ•œ Blazar๋“ค ์ค‘ ํ•˜๋‚˜์ธ 3C 273 (FSRQ)๋กœ๋ถ€ํ„ฐ ๋ฐœ์ƒํ•œ ์ตœ๊ทผ์˜ ๋‘ ๊ฐ๋งˆ์„  ํญ๋ฐœ๋“ค์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ๋ถ„์„์€ ALMA, VLBA, ๊ทธ๋ฆฌ๊ณ  Fermi-LAT ๋ฐ์ดํ„ฐ๋“ค์„ ์ด์šฉํ•˜์—ฌ ์ˆ˜ํ–‰๋˜์–ด์กŒ๋‹ค. ์ „ํŒŒ์™€ ๊ฐ๋งˆ์„  ๋ณ€๊ด‘๊ณก์„  ์‚ฌ์ด์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด, Discrete Correlation Function (DCF)๊ฐ€ ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. ์šฐ๋ฆฌ์˜ ๊ฒฐ๊ณผ๋“ค์€ ๋งค์šฐ ์กฐ๋ฐ€ํ•œ Multiple standing shock๋“ค์ด 3C 273์˜ ์ œํŠธ ์•ˆ์—์„œ ๊ด€์ธก๋œ ๊ฐ๋งˆ์„  ํญ๋ฐœ๋“ค์˜ ๊ธฐ์›์ž„์„ ๋‚˜ํƒ€๋‚ธ๋‹ค. 0716+714๋Š” ๋ชจ๋“  ์ „์ž๊ธฐํŒŒ ์˜์—ญ์—์„œ ๊ทน์ ์ธ ๋ณ€๊ด‘์„ฑ์„ ๋ณด์ด๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์šฐ๋ฆฌ์˜ ์‚ฌ์ „์กฐ์‚ฌ๊ฒฐ๊ณผ๋กœ ๋ฐํ˜€์ง„ ํ•ด๋‹น ์†Œ์Šค์—์„œ์˜ ์ „ํŒŒ์™€ ๊ฐ๋งˆ์„  ๋ฐฉ์ถœ ๋น› ์‚ฌ์ด์˜ ์—ญ์ƒ๊ด€๊ด€๊ณ„ (anti-correlation)๋Š” ์šฐ๋ฆฌ๊ฐ€ 0716+714 ์ œํŠธ ์•ˆ์—์„œ ์ „ํŒŒ/๊ฐ๋งˆ์„  ์—ฐ๊ด€์„ฑ์— ๋Œ€ํ•œ ์ž์„ธํ•œ ์—ฐ๊ตฌ๋ฅผ ๊ฐœ์‹œํ•˜๊ฒŒ ๋˜๋Š” ๋™๊ธฐ๊ฐ€ ๋˜์—ˆ๋‹ค. ๊ธฐ๋ก ๋ณด๊ด€๋œ (archival) ๋‹คํŒŒ์žฅ ๋ฐ์ดํ„ฐ๋“ค (SMA, Metsahovi, OVRO, Fermi-LAT, ๊ทธ๋ฆฌ๊ณ  VLBA)์ด ์‚ฌ์šฉ๋˜์—ˆ์œผ๋ฉฐ, ๋ฐ์ดํ„ฐ๋“ค ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„์€ ๋ณ€๊ด‘๊ณก์„ ๋“ค์˜ ๋ชจ๋ธ๋ง๊ณผ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ด์šฉํ•ด ์ˆ˜ํ–‰๋˜์–ด์กŒ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ์šฐ๋ฆฌ๋Š” ์„ธ ๊ฐœ์˜ ์ค‘๋Œ€ํ•œ ์ „ํŒŒ/๊ฐ๋งˆ์„  ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์ฐพ์•˜๋‹ค: ๋‘ ๊ฐœ์˜ ์—ญ์ƒ๊ด€๊ด€๊ณ„๋“ค๊ณผ ํ•˜๋‚˜์˜ ์–‘์  ์ƒ๊ด€๊ด€๊ณ„. ์šฐ๋ฆฌ๋Š” ๋˜ํ•œ ๊ฐ๋งˆ์„  ํญ๋ฐœ๋“ค์ด ๋ฐœ์ƒํ•˜๋Š” ๋™์•ˆ ํŒŒ์„น ๊ทœ๋ชจ์—์„œ์˜ ์ œํŠธ๊ฐ€ ์–ด๋– ํ•œ ํ™œ๋™์„ฑ์„ ๋ณด์ด๋Š”์ง€๋ฅผ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด VLBA ๋ฐ์ดํ„ฐ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ๋“ค๋กœ๋ถ€ํ„ฐ ์–ป์–ด์ง„ ๋ชจ๋“  ์ฆ๊ฑฐ๋ฅผ ํ† ๋Œ€๋กœ ์šฐ๋ฆฌ๋Š” ์ œํŠธ ๋‚ด์—์„œ ๊ฐ๋งˆ์„  ํญ๋ฐœ๋“ค์˜ ๊ธฐ์›์„ ํ•œ์ •ํ•˜๊ณ , ๊ด€์ธก๋œ ์ƒ๊ด€๊ด€๊ณ„๋“ค์˜ ๋ฐฐ๊ฒฝ๊ธฐ์ž‘์œผ๋กœ์จ ์ด๋™ํ•˜๋Š” ์„ญ๋™์ด ์ „ํŒŒ์ฝ”์–ด๋ฅผ ์ง€๋‚˜๋ฉด์„œ ์œ ๋ฐœ๋˜๋Š” Internal-shock interaction์„ ์ œ์•ˆํ•œ๋‹ค. ๊ทน์ ์ธ ๋ฌผ๋ฆฌ์  ์ƒํƒœ์™€ ๋‹ค์–‘ํ•œ ์‹œ๋‚˜๋ฆฌ์˜ค ๋ฐ ๊ฐ€๋Šฅ์„ฑ๋“ค ๋•Œ๋ฌธ์—, Blazar์˜ ์ƒ๋Œ€๋ก ์  ์ œํŠธ๋“ค์— ๋Œ€ํ•œ ๋ฌผ๋ฆฌ๋Š” ๋ณต์žกํ•˜๋ฉฐ ๊นŒ๋‹ค๋กญ๋‹ค. ๊ณ ๋ถ„ํ•ด๋Šฅ VLBI ์–ด๋ ˆ์ด๋“ค์„ ํ†ตํ•œ ์ œํŠธ์˜ ์ž์„ธํ•œ ๊ด€์ธก์€ ํ˜„์žฌ ์ œํŠธ๋ฌผ๋ฆฌ์—์„œ์˜ ์Ÿ์ ๋“ค์„ ํ•ด๊ฒฐํ•  ๊ฐ€์žฅ ์ข‹์€ ๋ฐฉ๋ฒ•์ด๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์€ Blazar ๊ฐ๋งˆ์„  ํญ๋ฐœ๋“ค์˜ ํŠน์„ฑ์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ๊ด€์ธก์  ๋ฐ์ดํ„ฐ์™€ ๊ฒฐ๊ณผ๋“ค์„ ๋ณด์—ฌ์ฃผ๋ฉฐ, 4๊ฐœ์˜ ์ฃผ๋ชฉํ•  ๋งŒํ•œ Blazar๋“ค์˜ ๊ฒฝ์šฐ๋“ค์— ๋Œ€ํ•˜์—ฌ ํ’๋ถ€ํ•œ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•จ์œผ๋กœ์จ ํ•™๊ณ„์— ๊ธฐ์—ฌํ•œ๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์— ์ˆ˜๋ก๋œ ๊ฐœ๋ณ„ ์—ฐ๊ตฌ๋“ค์€ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๊ฒฐ๋ก ์„ ๋‚ด๋ฆฐ๋‹ค: (1) Blazar์˜ ๊ฐ๋งˆ์„  ํญ๋ฐœ๋“ค์€ ์ œํŠธ ๋‚ด์—์„œ ๋‹ค์ค‘ ๋ฐฉ์ถœ ์˜์—ญ์„ ๊ฐ€์ง„๋‹ค (์ค‘์•™ ๋ธ”๋ž™ํ™€๋กœ๋ถ€ํ„ฐ subpc/pc ๊ทœ๋ชจ์˜ ๊ฑฐ๋ฆฌ) ๊ทธ๋ฆฌ๊ณ  (2) subpc/pc ๊ทœ๋ชจ์˜ ๊ฑฐ๋ฆฌ์—์„œ ์ œํŠธ์˜ ํ•˜๋ฅ˜๋ฅผ ๋”ฐ๋ผ ์ „ํŒŒํ•ด๋‚˜๊ฐ€๋Š” Shock/์„ญ๋™๋“ค์˜ ์ด๋™์ด ๊ฐ๋งˆ์„  ํญ๋ฐœ์„ ์œ ๋ฐœํ•œ๋‹ค (ํŠน๋ณ„ํžˆ ๊ทธ๋“ค์ด Standing shock ๊ตฌ์กฐ๋“ค์„ ์ง€๋‚˜๊ฐˆ ๋•Œ).I. Introduction 1 1.1 Radio jets in Active Galactic Nuclei (AGN) 1 1.1.1 Active Galactic Nuclei 1 1.1.2 Formation of AGN jets 3 1.1.3 Jet structures and evolution 6 1.1.4 Beaming effects 13 1.1.5 Importance in astrophysics 16 1.2 Multi-waveband observations of AGN 18 1.2.1 Very Long Baseline Interferometry 18 1.2.2 Fermi-LAT 25 1.3 High energy gamma-ray emission in blazars 28 1.3.1 Nonthermal emission 28 1.3.2 The radio/ฮณ-ray connection 32 1.4 Thesis outline 37 II. The Millimeter-Radio Emission of BL Lacertae During Two ฮณ-Ray Outbursts 39 2.1 Introduction 40 2.2 Observation and Data reduction 41 2.3 Results 45 2.3.1 Radio morphology of BL Lac seen by the KVN 46 2.3.2 Radio Light Curves 48 2.3.3 Spectral Indices and Spectrum of the Core 51 2.4 Discussion 53 2.4.1 Variability and Cooling Time Scales 55 2.4.2 Shock Evolution in The Core Region 59 2.4.3 The Radio-ฮณ-Ray Connection 60 2.5 Summary 63 III. Exploring The Nature of The 2016 ฮณ-Ray Emission in The Blazar 1749+096 65 3.1 Introduction 66 3.2 Observations and Data 67 3.2.1 KVN 22/43/86/129 GHz & VLBA 43 GHz 67 3.2.2 OVRO 15 GHz 68 3.2.3 ASAS-SN 69 3.2.4 Swift-XRT 69 3.2.5 Fermi-LAT 69 3.3 Results and Analysis 71 3.3.1 Multi-waveband light curves 71 3.3.2 Multi-wavelength flux correlations 72 3.3.3 LAT ฮณ-ray photon indices 75 3.3.4 Linear polarization at 43 GHz 77 3.3.5 Flux evolution near the core 79 3.4 Discussion 82 3.4.1 ฮณ-ray activity 82 3.4.2 Multi-wavelength correlations 83 3.4.3 Origin of the ฮณ-ray outburst 83 3.4.4 The enhanced ฮณ-ray emission in 2016 October 86 3.5 Summary 86 IV. Investigating The Connection between ฮณ-Ray Activity and The Relativistic Jet in 3C 273 during 2015โ€“2019 89 4.1 Introduction 90 4.2 Observations 91 4.2.1 Fermi-LAT 91 4.2.2 ALMA band3 92 4.2.3 VLBA 43 GHz 92 4.3 Results 94 4.3.1 Light curves 94 4.3.2 Photon indices from weekly and monthly ฮณ-ray light curves 97 4.3.3 Correlation between the radio and ฮณ-ray light curves 99 4.3.4 Parsec-scale jet near the 43 GHz core 102 4.3.5 Polarization 106 4.4 Discussion 108 4.4.1 Positional variations of the stationary components 108 4.4.2 2016 ฮณ-ray outburst 109 4.4.3 2017 ฮณ-ray outburst 112 4.4.4 ฮณ-ray spectra 114 4.5 Summary 115 V. Radio and ฮณ-Ray Activity in The Jet of The Blazar S5 0716+714 117 5.1 Introduction 118 5.2 Observations 120 5.2.1 cm-wavelength data 120 5.2.2 SMA 230 GHz (1.3 mm) 120 5.2.3 ฮณ-ray flux 120 5.3 Results 121 5.3.1 Radio and ฮณ-ray light curves 121 5.3.2 Correlation analysis 121 5.3.2.1 Long-term correlation with the 37 GHz data 121 5.3.2.2 Optimization of the probable time ranges 125 5.3.2.3 DCF curves over the T1, T2, and T3 periods 136 5.3.3 Jet kinematics 140 5.4 Discussion 149 5.4.1 Internal shock interactions 149 5.4.2 Frequency dependence in the time lags 151 5.4.3 Timing of the knot ejections in T1 and T2 153 5.4.4 Location of the ฮณ-ray production site 154 5.4.5 Evolution of the parsec scale jet 155 5.5 Summary 157 VI. Conclusion 161 Bibliography 167 Appendix 183 A Appendices for Chapter4 183 A.1 Gaussian model-fit parameters 183 ์š”์•ฝ 189 ๊ฐ์‚ฌ์˜ ๊ธ€ 193๋ฐ•

    ๊ธ์ •์  ์‚ฌ๊ฑด์— ๋Œ€ํ•œ ์ถ”์ƒ์ -๊ตฌ์ฒด์  ๋ฐ˜์ถ”๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ๋ณธ ์—ฐ๊ตฌ๋Š” ์ถ”์ƒ์  ๋ฐ˜์ถ” ์ง‘๋‹จ๊ณผ ๊ตฌ์ฒด์  ๋ฐ˜์ถ” ์ง‘๋‹จ์—์„œ ์‹ฌ๋ฆฌ์  ์›ฐ๋น™์˜ ์ค‘์š”ํ•œ ์ง€ํ‘œ์ธ ๊ธ์ •์ ์ธ ๋ฏธ๋ž˜ ์˜ˆ์ธก์ด ์–ด๋–ค ์ฐจ์ด๋ฅผ ๋ณด์ด๋Š”์ง€๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•œ ๋ชฉ์ ์œผ๋กœ ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋งŒ 18์„ธ ์ด์ƒ ์„ฑ์ธ 268๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ์˜จ๋ผ์ธ ์„ค๋ฌธ์กฐ์‚ฌ๋ฅผ ์‹ค์‹œํ•˜๊ณ  ์Šคํฌ๋ฆฌ๋‹ ๊ณผ์ •์„ ๊ฑฐ์ณ ์šฐ์šธํ•˜์ง€ ์•Š์€ ์ƒํƒœ๋กœ ํŒ๋ณ„๋œ 83๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ZOOMํ”„๋กœ๊ทธ๋žจ์„ ์ด์šฉํ•ด ๋น„๋Œ€๋ฉด ์‹คํ—˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์˜จ๋ผ์ธ ์‚ฌ์ „ ์ธก์ •์„ ๋งˆ์นœ ์ฐธ์—ฌ์ž๋Š” ์ถ”์ƒ์  ๋ฐ˜์ถ” ์ง‘๋‹จ๊ณผ ๊ตฌ์ฒด์  ๋ฐ˜์ถ” ์ง‘๋‹จ์— ๋ฌด์„  ๋ฐฐ์ •๋œ ํ›„ ์—ฐ๊ตฌ์ž์™€ ์ผ๋Œ€์ผ๋กœ ๋ฐ˜์ถ” ์กฐ์ž‘ ๋ฉด๋‹ด์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ์กฐ์ž‘ ๋ฉด๋‹ด์ด ์™„๋ฃŒ๋œ ํ›„ ์‚ฌํ›„ ๋ฐ˜์ถ” ๊ฒ€์‚ฌ๋ฅผ ์‹ค์‹œํ•ด ๋ฐ˜์ถ”์˜ ์กฐ์ž‘์ด ์œ ์˜ํ•˜๊ฒŒ ์ผ์–ด๋‚ฌ๋Š”์ง€ ํ™•์ธํ•˜์˜€๋‹ค. ๋ฐ˜์ถ”๊ฒ€์‚ฌ ์™„๋ฃŒ ํ›„ ์ฐธ๊ฐ€์ž๋Š” ๊ธ์ •์  ๋ฏธ๋ž˜ ์˜ˆ์ธก ์ˆ˜์ค€์„ ํ‰์ •ํ•˜์˜€๋‹ค. ๋ถˆ์„ฑ์‹คํ•œ ์‘๋‹ต์„ ํ•œ 6๋ช…์„ ์ œ์™ธํ•œ 77๋ช…์˜ ์ž๋ฃŒ๊ฐ€ ์ตœ์ข… ๋ถ„์„์— ์‚ฌ์šฉ๋˜์—ˆ์œผ๋ฉฐ ์ง‘๋‹จ ๊ฐ„ ๋™์งˆ ์„ฑ ๊ฒ€์‚ฌ๋ฅผ ์œ„ํ•ด ๋…๋ฆฝํ‘œ๋ณธ t-๊ฒ€์ •์„ ์‹ค์‹œํ•˜์˜€๊ณ  ๊ธ์ •๋ฐ˜์ถ” ์„ฑํ–ฅ์ด ๊ธ์ •์  ๋ฏธ๋ž˜ ์˜ˆ์ธก์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์„ฑ๋ณ„, ์ง‘๋‹จ, ๊ธ์ •์ •์„œ ๋ณ€ํ™”๋Ÿ‰, ๊ธ์ •๋ฐ˜์ถ”๋ฅผ ๋ณ€์ธ์œผ๋กœ ํ•˜๋Š” ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ๋˜ํ•œ ๊ธ์ •์  ๋ฏธ๋ž˜ ์˜ˆ์ธก์ด ์ง‘๋‹จ ๊ฐ„ ์–ด๋–ค ์ฐจ์ด๋ฅผ ๋ณด์ด๋Š”์ง€ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ๋…๋ฆฝํ‘œ๋ณธ t-๊ฒ€์ •์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ๋จผ์ € ๊ธ์ •๋ฐ˜์ถ”๊ฐ€ ๊ธ์ •์  ๋ฏธ๋ž˜ ์˜ˆ์ธก์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„์œผ๋กœ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ, ๊ธ์ •๋ฐ˜์ถ”๊ฐ€ ๊ธ์ •์  ๋ฏธ๋ž˜ ์˜ˆ์ธก์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์œ ์ผํ•œ ๋ณ€์ธ์ž„์ด ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์šฐ์šธํ•˜์ง€ ์•Š์€ ์ผ๋ฐ˜์ธ๋“ค์€ ๊ธ์ •์ ์ธ ์ž๊ธฐ ์ž์งˆ ํ˜น์€ ๊ธ์ •์ •์„œ ๊ฒฝํ—˜์— ๋Œ€ํ•ด ๋ฐ˜๋ณต์ ์œผ๋กœ ์‚ฌ๊ณ ํ•˜๋Š” ๊ฒฝํ–ฅ์ด ๋†’์„์ˆ˜๋ก ๊ธ์ •์ ์ธ ๋ฏธ๋ž˜๊ฐ€ ์˜ฌ ๊ฐ€๋Šฅ์„ฑ์„ ๋†’๊ฒŒ ํ‰๊ฐ€ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ์ถ”์ƒ์  ๋ฐ˜์ถ” ์ง‘๋‹จ๊ณผ ๊ตฌ์ฒด์  ๋ฐ˜์ถ” ์ง‘๋‹จ์˜ ๊ธ์ •์  ๋ฏธ๋ž˜ ์˜ˆ์ธก์„ ๋น„๊ตํ•œ ๊ฒฐ๊ณผ ์ถ”์ƒ์  ๋ฐ˜์ถ” ์ง‘๋‹จ์—์„œ ๊ธ์ •์  ๋ฏธ๋ž˜ ์˜ˆ์ธก ์ˆ˜์ค€์ด ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋†’์€ ๊ฒƒ์ด ๋ฐํ˜€์กŒ๋‹ค. ๋‘ ์ง‘๋‹จ์ด ์„œ๋กœ ๋…๋ฆฝ์ ์ด๊ณ  ๋™์งˆ์ ์œผ๋กœ ๊ตฌ์„ฑ๋˜์–ด์žˆ๋‹ค๋Š” ๊ฒƒ ๋˜ํ•œ ํ™•์ธ๋˜์–ด ๋‹ค๋ฅธ ์š”์ธ๋“ค์ด ์•„๋‹Œ ์ง‘๋‹จ ๊ฐ„ ๋ฐ˜์ถ”๋ฐฉ์‹์˜ ์ฐจ์ด๊ฐ€ ๊ธ์ •์  ๋ฏธ๋ž˜ ์˜ˆ์ธก์— ์œ ์˜๋ฏธํ•œ ์ฐจ์ด๋ฅผ ๋งŒ๋“ค์–ด๋ƒˆ๋‹ค๋Š” ๊ฒƒ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ง€๊ธˆ๊นŒ์ง€ ํฌ๊ฒŒ ๊ด€์‹ฌ์„ ๋ฐ›์ง€ ๋ชปํ–ˆ๋˜ ๊ธ์ •์ •์„œ ๋ฐ˜์‘์–‘์‹, ํŠนํžˆ ๊ธ์ • ๋ฐ˜์ถ”์˜ ๊ฐœ์ธ์ฐจ์™€ ๊ธ์ •์ ์ธ ๋ฏธ๋ž˜ ์˜ˆ์ธก์„ ์‹คํ—˜์ ์œผ๋กœ ์—ฐ๊ตฌํ–ˆ๋‹ค๋Š” ์˜์˜๊ฐ€ ์žˆ๋‹ค. ๋˜ํ•œ ๋ฐ˜์ถ”์˜ ์ฒ˜๋ฆฌ๋ฐฉ์‹์ด๋ก ์„ ๋ถ€์ •์  ์ƒํ™ฉ์— ๋Œ€ํ•œ ๋ฐ˜์ถ”๊ฐ€ ์•„๋‹Œ, ๊ธ์ •์  ๋ฐ˜์ถ”์—์„œ ํ™•์ธํ–ˆ๋‹ค๋Š” ํ•™์ˆ ์  ์˜์˜๊ฐ€ ์žˆ์œผ๋ฉฐ ์‹ค์ œ ์ƒ๋‹ด ์žฅ๋ฉด์—์„œ ๊ธ์ •์ •์„œ ๊ฒฝํ—˜์„ ํ™œ์šฉํ•ด ๋‚ด๋‹ด์ž์˜ ์‹ฌ๋ฆฌ์  ์›ฐ๋น™์„ ๋„๋ชจํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ–ˆ๋‹ค๋Š” ์ƒ๋‹ด ์‹ค์ œ์  ์˜์˜๊ฐ€ ์žˆ๋‹ค. ์ฃผ์š”์–ด: ๊ธ์ •์  ๋ฏธ๋ž˜ ์˜ˆ์ธก, ๊ธ์ • ๋ฐ˜์ถ”, ๋ฐ˜์ถ”๋ฐฉ์‹, ์ถ”์ƒ์  ๋ฐ˜์ถ”, ๊ตฌ์ฒด์  ๋ฐ˜์ถ”This study was conducted with the aim of verifying the difference in positive future prediction, an important indicator of psychological well-being, in abstract and concrete rumination groups. An online survey was conducted on 268 adults aged 18 and older, and a non-face-to-face experiment was conducted on 83 people who were determined not depressed through the screening process. After completing online pre-measurements, participants were assigned to either the abstract rumination group or the concrete rumination group, which the researcher then conducted a one-on-one rumination manipulation interview. After the manipulation interview was completed, a posterior rumination test was conducted to verify that the significance of the rumination manipulation. After the completion of the rumination test, participants rated the level of positive future prediction. Data from 77 people, excluding six who responded insincerely, were used for the final analysis. Independent sample t-tests were conducted for homogeneity tests between groups, and multiple regression analyses were conducted with gender, group, positive affect, and positive rumination. An independent sample t-test was also conducted to determine how positive future predictions differ between groups. First of all, a multi-regression analysis of the impact of positive reflection on positive future prediction confirmed that positive reflection is the only variable that affects positive future prediction. This confirmed that the higher the tendency of ordinary people to think repeatedly about positive self-qualities or positive emotional experiences, the higher the possibility of predicting a positive future. Furthermore, a comparison of the positive future predictions of the abstract rumination group and the concrete rumination group revealed significantly higher levels of positive future prediction in the abstract rumination group. It has also been confirmed that the two groups are independent and homogeneous from each other, indicating that difference in rumination methods between groups, rather than other factors, have created a significant difference in positive future predictions. The results of this study is significant in that it sheds light on the difference between positive rumination and positive future prediction, twon important factors which have not received much attention so far. There is also an academic significance in that the processing-mode theory of rumination was identified in positive rumination, not in reflection on negative situation. This study also presented a method of promoting the psychological well-being of clients by utilizing positive affect experience in actual counseling scenes. Keywords: Positive Future Prediction, Positive Rumination, Processing Mode Theory, Abstract Rumination, Concrete RuminationI. ์„œ ๋ก  1 1. ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ ๋ฐ ๋ชฉ์  1 2. ์—ฐ๊ตฌ ๋ฌธ์ œ ๋ฐ ์—ฐ๊ตฌ ๊ฐ€์„ค 6 II. ์ด๋ก ์  ๋ฐฐ๊ฒฝ 8 1. ๊ธ์ •์  ๋ฏธ๋ž˜ ๊ธฐ๋Œ€์™€ ์‹ฌ๋ฆฌ์  ์›ฐ๋น™ 8 2. ๋ฐ˜์ถ” 10 1) ๋ฐ˜์ถ”์˜ ์ •์˜ 10 2) ์ ์‘์  ๋ฐ˜์ถ”์™€ ๋ถ€์ ์‘์  ๋ฐ˜์ถ” 11 3. ๋ฐ˜์ถ”์™€ ๋ฏธ๋ž˜์˜ˆ์ธก 14 1) ๋ถ€์ •์  ์ƒํ™ฉ์— ๋Œ€ํ•œ ๋ฐ˜์ถ”์™€ ๋ฏธ๋ž˜์˜ˆ์ธก 14 2) ๊ธ์ •์  ์ƒํ™ฉ์— ๋Œ€ํ•œ ๋ฐ˜์ถ”์™€ ๋ฏธ๋ž˜์˜ˆ์ธก 15 III. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 21 1. ์—ฐ๊ตฌ ๋Œ€์ƒ 21 2. ์—ฐ๊ตฌ ๋„๊ตฌ 22 3. ์‹คํ—˜ ์ ˆ์ฐจ 27 4. ๋ถ„์„ ๋ฐฉ๋ฒ• 29 IV. ์—ฐ๊ตฌ๊ฒฐ๊ณผ 30 1. ๊ฒฐ๊ณผ๋ถ„์„์„ ์œ„ํ•œ ์ž๋ฃŒ๊ฒ€ํ†  30 2. ๊ธ์ •์  ๋ฏธ๋ž˜์˜ˆ์ธก์— ๊ธ์ •๋ฐ˜์ถ”๊ฐ€ ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 32 3. ๋ฐ˜์ถ”๋ฐฉ์‹์— ๋”ฐ๋ฅธ ๊ธ์ •์  ๋ฏธ๋ž˜์˜ˆ์ธก ์ฐจ์ด 33 โ…ค. ๋…ผ ์˜ 35 1. ์š”์•ฝ ๋ฐ ๋…ผ์˜ 35 2. ์—ฐ๊ตฌ์˜ ์˜์˜ ๋ฐ ์‹œ์‚ฌ์  38 3. ์—ฐ๊ตฌ์˜ ์ œํ•œ์  ๋ฐ ํ›„์†์—ฐ๊ตฌ ์ œ์–ธ 40 ์ฐธ๊ณ ๋ฌธํ—Œ 42 ๋ถ€๋ก 51 Abastract 76์„

    A Primary Study on the Development of Evaluation Model for Marine Traffic Safety Assessment

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    Collision between Xing Guang No.7 and Neo Blue which happened in front of the Incheon lock gate indicates that Korean coastal water is classified as dangerous area due to heavy traffic in confined waters. This may lead to severe accident such as collision, grounding, sinking and environmental pollution. According to the Marine Traffic Safety Law, revised in 2009, Marine Traffic Safety Diagnosis System is introduced to secure the safe navigation, prevent the marine accident and to maximize the efficiency of the port. The diagnosis system aims to investigate, measure and evaluate the effect of the various development project such as the construction of bridge and/or piers, etc. and to reflect the diagnostic results for the safe navigation. In the process of this system, the most important part is the marine traffic safety assessment, and evaluation model is required in order to implement the assessment. However, the evaluation model used in Korea is highly limited, and these models are made in foreign countries such as Japan. There are some problems to apply these models to Korean coastal waters. So the development of the proper evaluation model for Korea is required as early as possible. The purpose of this research is implementing marine traffic assessment of Korean coastal waters by using ES(Environmental Stress) model which is formal assessment model for marine traffic flow simulation in the Diagnosis System and IWRAP(IALA Waterway Risk Assessment Program) recommended by IALA, and analyze the results for the basic reference to develop independent evaluation model.์ œ 1 ์žฅ ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 1.2 ์—ฐ๊ตฌ์˜ ๋ฐฉ๋ฒ• 2 ์ œ 2 ์žฅ ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์ง„๋‹จ์ œ๋„์˜ ๊ฐœ๋…๊ณผ ์ ˆ์ฐจ 4 2.1 ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์ง„๋‹จ์˜ ์šฉ์–ด ์ •์˜ 4 2.1.1 ํ•ด์ƒ๊ตํ†ต์˜ ๊ฐœ๋… 4 2.1.2 ์•ˆ์ „์˜ ๊ฐœ๋… 4 2.1.3 ์ง„๋‹จ์˜ ๊ฐœ๋… 5 2.2 ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์ง„๋‹จ์ œ๋„ 6 2.2.1 ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์ง„๋‹จ์˜ ๊ฐœ๋… 6 2.2.2 ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์ง„๋‹จ ์ ˆ์ฐจ 9 ์ œ 3 ์žฅ ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์„ฑ ํ‰๊ฐ€ ์ ˆ์ฐจ ๋ฐ ํ‰๊ฐ€๋ชจ๋ธ ์กฐ์‚ฌ 11 3.1 ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์„ฑ ํ‰๊ฐ€์˜ ๊ฐœ๋… 11 3.2 ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์„ฑ ํ‰๊ฐ€ ์ ˆ์ฐจ 12 3.2.1 ํ•ด์ƒ๊ตํ†ตํ˜„์ƒ ํŒŒ์•… 13 3.2.2 ํ•ด์ƒ๊ตํ†ตํ˜„์ƒ ๊ธฐ์ˆ  13 3.2.3 ํ•ด์ƒ๊ตํ†ตํ˜„์ƒ ์˜ˆ์ธก 14 3.2.4 ํ•ด์ƒ๊ตํ†ตํ˜„์ƒ ์žฌํ˜„ 14 3.2.5 ํ•ด์ƒ๊ตํ†ตํ˜„์ƒ ํ‰๊ฐ€ 15 3.3 ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์„ฑ ํ‰๊ฐ€๋ชจ๋ธ 16 3.3.1 IWRAP 16 3.3.2 ES Model 22 3.3.3 PAWSA 26 3.3.4 FSA 30 3.3.5 US Model 35 3.3.6 ์ผ๋ณธ์˜ ์•ˆ์ „๋Œ€์ฑ… ํ‰๊ฐ€ ๊ฐ€์ด๋“œ๋ผ์ธ 36 3.3.7 ๊ธฐํƒ€ ํ‰๊ฐ€๋ชจ๋ธ 39 3.3.8 ์ข…ํ•ฉ ๋ถ„์„ 40 ์ œ 4 ์žฅ IWRAP ๋ฐ ES Model์„ ํ™œ์šฉํ•œ ์šธ์‚ฐํ•ญ ํ•ด์—ญ ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์„ฑ ํ‰๊ฐ€ 42 4.1 ๊ธฐ์ดˆ ์ž๋ฃŒ ์กฐ์‚ฌ 42 4.1.1 ์ž์—ฐ ํ™˜๊ฒฝ 42 4.1.2 ํ•ญํ–‰ ํ™˜๊ฒฝ 44 4.2 IWRAP์„ ์ด์šฉํ•œ ์šธ์‚ฐํ•ญ ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์„ฑ ํ‰๊ฐ€ 46 4.2.1 Leg ์ง€์ • 46 4.2.2 ๊ตํ†ต๋Ÿ‰ ๋ฐ ๋ถ„์‚ฐ์น˜ ์ž…๋ ฅ 48 4.2.3 ๊ธฐํƒ€ ๋ณ€์ˆ˜ ์ž…๋ ฅ 57 4.2.4 ์•ˆ์ „์„ฑ ํ‰๊ฐ€ ๊ฒฐ๊ณผ ๋ถ„์„ 58 4.3 ES Model์„ ์ด์šฉํ•œ ์šธ์‚ฐํ•ญ ํ•ด์ƒ๊ตํ†ต ์•ˆ์ „์„ฑ ํ‰๊ฐ€ 60 4.4 ํ•ด์–‘์‚ฌ๊ณ  ํ†ต๊ณ„์ž๋ฃŒ ๋น„๊ต ๋ถ„์„ 62 ์ œ 5 ์žฅ ๊ฒฐ ๋ก  6

    Detection of Intestinal Protozoa in Korean Patients Using BD MAX Enteric Parasite Panel and Seegene Allplex Gastrointestinal Parasite Assay

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    Background: Intestinal protozoan infection is one of the main causes of gastrointestinal diseases. Protozoa are usually detected by direct smear microscopy, concentration techniques, or special stains; however, these techniques are labor-intensive and require well-trained technicians. Therefore, molecular techniques involving polymerase chain reaction (PCR) have been developed to satisfy the need for unbiased and rapid ana lytical methods with high sensitivity and specificity. In this study, the BD MAXTM Enteric Parasite Panel (EPP) (Becton, Dickinson and Company, USA), designed to detect Cryptosporidium parvum and/or hominis, Giardia lamblia, and Entamoeba histolytica, and the AllplexTM Gastrointestinal Para site Assays (AGPA) (Seegene Inc., Korea), designed to detect Cryptosporidium species, G. lamblia, E. histolytica, Blastocystis hominis, Dientamoe ba fragilis, and Cyclospora cayetanensis were compared to determine whether any of these assays could become a useful tool for detecting intes tinal protozoan infections in Korea. Methods: We investigated 295 fecal samples using EPP and AGPA. Then we confirmed the positive results with the conventional and nested PCR. Consistent detection by conventional PCR, nested PCR, and one of the multiplex panels was considered โ€œtrue positive.โ€ Results: Out of 295 samples, 17 were true positives for B. hominis and 2 were true positives for E. histolytica. EPP detected parasites in only two samples owing to its design; however, its true positive detection rate was 100% (2/2). AGPA detected parasites in 24 samples with 79.2% (19/24) true positives. Conclusions: The incidence of protozoan, especially B. hominis, infection may be more prevalent than expected. AGPA could be an effective tool for screening protozoan infections.ope

    A Case Report of Transfusion-associated Circulatory Overload

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    Transfusion-associated circulatory overload (TACO) is recently becoming more important than transfusion-related acute lung injury (TRALI) in terms of the number of patients with definite diagnosis as well as its prognosis. In order to diagnose TACO, it is helpful to recognize early the symptoms suspicious of transfusion reaction through electronic medical record system and computer network, and this will be of help for obtaining samples for brain natriuretic peptide (BNP) measurement before and after the onset of transfusion reaction. We report a case in which a transfusion reaction was diagnosed as TACO. A 62-year-old woman was admitted to the emergency room due to bleeding tendency. Two fresh frozen plasma units and one unit of leukocyte-reduced red blood cells were transfused. Blood pressure increased during transfusion, and the chest X-ray showed findings suggestive of newly developed pulmonary edema. N-terminal prohormone of BNP (NT-proBNP) test was carried out using the specimens in refrigerated storage. Compared with the NT-proBNP level measured 12 hours before the transfusion, that measured 6 hours after the transfusion was markedly increased (>48 fold of pre-transfusion level). As a result, this case was diagnosed with TACO.ope

    Determination of Colistin Resistance by Simple Disk Diffusion Test Using Modified Mueller-Hinton Agar

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    Background: Colistin has become a last-resort antibiotic for the management of multidrug-resistant gram-negative bacteria. The disk diffusion test is cheap and easy to perform but may be unreliable for colistin susceptibility testing due to poor diffusion of the large colistin molecule. An improved agar diffusion test would increase the reliability of colistin susceptibility testing. This study aimed to modify Muller-Hinton agar (MHA) to improve colistin diffusion in agar. Methods: MHA was modified by reducing the agar concentration from 100% to 30% and supplementing with protamine. We tested 60 gram-negative clinical isolates of Pseudomonas aeruginosa (N=27) and Acinetobacter calcoaceticus-baumannii complex (N=33). Disk diffusion test results were interpreted based on minimum inhibitory concentrations determined by broth microdilution. Results: The modified MHA yielded the best performance metrics, including 94.7% sensitivity, 100% specificity, and an area under the curve of 0.995 (95% confidence interval, 0.982-1.000), P<0.001, at a cut-off point of 13 mm. Conclusions: A reduction of the agar concentration from 100% to 30% and the addition of protamine improved colistin diffusion in agar and allowed routine colistin susceptibility testing in a clinical microbiology laboratory, but should be handled with caution.ope

    Evaluation of the Analytical Performance of Atellica CH 930 Automated Chemistry Analyzer

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    Background: Recently, a new automated chemistry analyzer, Atellica CH930 (Siemens, Germany), was introduced. It automatically measures internal quality control (QC) materials according to a pre-determined schedule. For this purpose, the instrument has space for storage of QC materials. We evaluated the analytical performance of chemistry items by using the Atellica system. Methods: The precision of 29 items was evaluated with three levels of QC materials with two storage methods. We stored the QC materials in the dedicated storage space in the instrument during the precision evaluation period. In addition, we aliquoted and stored the materials in the refrigerator, and then loaded the material in a timely manner. Linearity, carry-over, and agreement with current methods were also evaluated. Results: The within-laboratory coefficient of variation (CV) of most items, except for total CO2 (tCO2), was within 5.0% in both QC storage methods without significant differences in CV between storage methods. The CV of tCO2 was 5.2%, 5.8%, and 5.1% at three different levels when the QC materials were stored in a dedicated space in the instrument. The linearity was acceptable, showing <5% nonlinearity. Although good agreement was observed for most items, some items, such as calcium, total bilirubin, aspartate transaminase, and chloride, showed unequivalent results. Conclusions: Atellica CH930 showed acceptable precision, linearity, and agreement in routine chemistry items. The automatic QC function using the storage device has no problem with stability or precision. It can reduce the manual process, allowing technicians to focus on reviewing the QC results and reporting reliable results.ope

    A Case of Panagglutination on Antibody Identification in a Multiple Myeloma Patient Receiving Daratumumab

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    Herein, we report a patient showing panagglutination in the unexpected antibody identification test after the administration of daratumumab. The patient was a 66-year-old woman who had undergone multiple cycles of chemotherapy and autologous peripheral blood stem cell transplantation for treating multiple myeloma; however, despite treatment, she had relapsed. Therefore, daratumumab, on clinical trials in Korea, started to be administered. After administration of daratumumab, the result of antibody screening test was positive, on the contrary to the result prior to the administration. Moreover, all positive reactions were shown in the antibody identification to the panel cells. After destroying CD38 antigens on the surface of RBCs using DTT, negative results were obtained. Daratumumab?a novel therapeutic human CD38 monoclonal antibody that can be used as targeted immunotherapy?is an FDA-approved drug for treating multiple myeloma. Because CD38 is expressed not only on myeloma cells, but also on red blood cells (RBCs), the use of daratumumab might lead to RBC agglutinations, and thereby resulting in false-positive results on the pre-transfusion tests. Therefore, caution is needed in case of a patient receiving daratumumab. Furthermore, additional test using DTT is required, especially when panagglutination was shown in the antibody identification test, as in this case.ope

    A Structural Model of the Relationship between Perceptions of Organizational Politics and Organizational Commitment with Organizational Cynicism as a Mediator: Exploring the Negative Factors Affecting the Organizational Commitment of Local Government Employees

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    ์กฐ์ง๋ชฐ์ž…์€ ์กฐ์ง์˜ ๊ฒฝ์Ÿ์šฐ์œ„๋ฅผ ํ™•๋ณดํ•˜๊ธฐ ์œ„ํ•œ ์ค‘์š” ์ˆ˜๋‹จ์œผ๋กœ ์ธ์‹๋˜๋ฉด์„œ ์ด์˜ ๋‹ค์–‘ํ•œ ์˜ํ–ฅ๋ณ€์ธ๋“ค์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ด๋ฃจ์–ด์ ธ ์™”์ง€๋งŒ ๋ถ€์ •์  ์˜ํ–ฅ์š”์ธ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ์†Œ์ˆ˜์— ๋ถˆ๊ณผํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์กฐ์ง์ •์น˜์ง€๊ฐ ๋ฐ ์กฐ์ง๋ƒ‰์†Œ์ฃผ์˜๊ฐ€ ์กฐ์ง๋ชฐ์ž…์˜ ๋ถ€์ •์  ์˜ํ–ฅ๋ณ€์ˆ˜๋กœ ๊ธฐ๋Šฅํ•  ๊ฒƒ์œผ๋กœ ๊ฐ€์ •ํ•˜์—ฌ, ์ด ๋“ค ์˜ํ–ฅ ๋ฐ ๊ฒฐ๊ณผ ๋ณ€์ธ๋“ค๊ฐ„์˜ ๊ตฌ์กฐ์  ๊ด€๊ณ„๋ฅผ ์‹ค์ฆ์ ์œผ๋กœ ๋ถ„์„ํ•˜๋Š” ๋ฐ ๋ชฉ์ ์„ ๋‘”๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๊ฒฝ๋‚จ์ง€์—ญ ๊ด€๋ฃŒ 221๋ช…์„ ๋ถ„์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ, ์กฐ์ง์ •์น˜์ง€๊ฐ๊ณผ ์กฐ์ง๋ƒ‰์†Œ์ฃผ์˜๋Š” ์กฐ์ง๋ชฐ์ž…(๊ฐ€์น˜ ๋ฐ ๊ทผ์†๋ชฐ์ž…)์˜ ๋ถ€์ •์  ์˜ํ–ฅ๋ณ€์ธ์œผ๋กœ ๊ธฐ๋Šฅํ•œ๋‹ค๋Š” ๊ฒƒ์ด ํ™•์ธ๋˜์—ˆ์œผ๋ฉฐ, ํŠนํžˆ, ์กฐ์ง๋ƒ‰์†Œ์ฃผ์˜๋Š” ์˜ํ–ฅ๋ณ€์ธ๊ณผ ๊ฒฐ๊ณผ๋ณ€์ธ์„ ๋ถ€๋ถ„ ๋งค๊ฐœํ•˜๋Š” ๊ธฐ๋Šฅ๋„ ์กด์žฌํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ํ–‰์ • ์„œ๋น„์Šค์˜ ์งˆ์  ์ œ๊ณ ๋ฅผ ์œ„ํ•ด์„œ๋Š” ๊ด€๋ฃŒ๋“ค์˜ ์ž๋ฐœ์ ์ด๊ณ  ํ—Œ์‹ ์ ์ธ ๋…ธ๋ ฅ์— ๋ถ€์ •์ ์œผ๋กœ ์ž‘์šฉํ•˜๋Š” ์กฐ์ง์ •์น˜์ง€๊ฐ๊ณผ ์กฐ์ง๋ƒ‰์†Œ์ฃผ์˜์™€ ๊ฐ™์€ ์š”์ธ๋“ค์„ ๋ฐฐ์ œํ•  ์ˆ˜ ์žˆ๋Š” ์กฐ์ง ๋ถ„์œ„๊ธฐ ํ˜•์„ฑ์ด ์ „์ œ๋˜์–ด์•ผ ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๊ฒฝํ—˜์ ์œผ๋กœ ์ž…์ฆํ•˜์˜€๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๋ฅผ ๊ฐ€์ง„๋‹ค
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