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    ๋ธ”๋ก๊ณต์ค‘ํ•ฉ์ฒด ๋งˆ์ด์…€๊ณผ ๋งˆ์ด์…€-๋ฌด๊ธฐ ์กฐํ•ฉ์ฒด์˜ ๊ตฌ์กฐ ๋ฐ ๊ทธ ๋ณ€ํ™”

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ™”ํ•™์ƒ๋ฌผ๊ณตํ•™๋ถ€(์—๋„ˆ์ง€ํ™˜๊ฒฝ ํ™”ํ•™์œตํ•ฉ๊ธฐ์ˆ ์ „๊ณต), 2020. 8. ์ฐจ๊ตญํ—Œ.Self-assembly of block copolymer micelles (BCMs) in selective solvents is well-understood phenomenon after decades of fundamental researches, and yet recent studies with novel block copolymer designs have demonstrated structural and dynamic behaviors of BCMs beyond the classical understanding. Simultaneously, strategies that use BCMs as building blocks for hybrid structures or nanocomposites has received great attention in a couple of decades for the purpose of extraordinary material properties, mimicking the protein-inorganic hybrids ubiquitous in nature. Therefore, it is essential to make connections between the fundamentals of BCM assembly and the design principles of hybrid structures involving BCMs. This dissertation addresses impact of a distinct molecular motif at block copolymers on the structures and dynamics of self-assembled micelles and an illustrative hybrid structure made from the interactions between BCMs and inorganic materials. The underlying theme across the studies is to emphasize the importance of knowledge on the structural evolution of BCMs in making precisely engineered nanomaterials. The first part of this dissertation presents characterization and interpretation of the micellar structures and the relaxation dynamics using diblock copolymers where long fluoroalkyl side-chains are attached to a specific block. The bottlebrush chain architecture causes large stiffness on the fluoroalkyl block, forcing it to be strongly stretched within the core of spherical micelles in a solvent selective to the non-fluoroalkyl block. Unconventional scaling relationships between sizes of the core and the corona and the length of fluoroalkyl block are found, suggesting that this notable stiffness of the core block induces deviation from the classical thermodynamic theory of BCMs. Another consequence of the bottlebrush architecture is the absence of entanglement and the abundance of free volume within the core domain, which facilitates the internal relaxation of chain within the core. As a result, equilibration of the model diblock copolymer is substantially fast, which leads to the rapid preparation of highly monodispersed BCMs. A quantitative measurement of the relaxation kinetics was made using contrast matched small-angle neutron scattering technique, which proves fast chain exchange between BCMs with bottlebrush core block. Hence, the impact of bottlebrush architecture at the core block is found to be significant in that the dependence of BCM structures on its length and the relaxation kinetics are quite different from those of linear, flexible block copolymers. The second part presents hybrid structures involving BCMs, namely, bio-mimicking nanocomposite of BCMs and mineral crystals. Herein, BCMs are allowed to adsorb at the surface of inorganic materials via electrostatic interaction. Such adsorption brings about the occlusion of BCMs in growing mineral crystals, where the occlusion density appears to be important in determining resultant toughening effect of the occluded minerals. Charge density of the corona affects the strength of the BCM adsorption at the mineral surface, whereas Brownian diffusion of BCMs affects the collision frequency at the growing mineral crystals. Thus, by controlling pH and hydrodynamic size of BCMs, the crystals experience from unperturbed growth to partial blockage of growing site (occlusion) to adsorption-induced growth inhibition in the order of increasing adsorption density. These results indicate that BCMs with precisely controlled structure could serve as versatile building blocks for hierarchical nanostructures with unprecedented mechanical properties.์ง€๋‚œ ์ˆ˜์‹ญ ๋…„๊ฐ„์˜ ๊ธฐ์ดˆ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๋ธ”๋ก๊ณต์ค‘ํ•ฉ์ฒด ๋งˆ์ด์…€(Block copolymer micelle; BCM)์˜ ์ž๊ธฐ์กฐ๋ฆฝ์— ๋Œ€ํ•œ ์ดํ•ด๊ฐ€ ์ฆ์ง„๋˜์–ด ์™”์œผ๋‚˜, ์ƒˆ๋กญ๊ฒŒ ๋””์ž์ธ๋œ ๋ธ”๋ก๊ณต์ค‘ํ•ฉ์ฒด๋ฅผ ์ด์šฉํ•œ ์ตœ๊ทผ์˜ ์—ฐ๊ตฌ ์‚ฌ๋ก€๋“ค์€ ๊ธฐ์กด์˜ ์ด๋ก ์œผ๋กœ ์„ค๋ช…๋˜์ง€ ์•Š๋Š” ๊ตฌ์กฐ์  ๋ฐ ๋™์—ญํ•™์  ํŠน์„ฑ์„ ์ง€๋‹ˆ๋Š” BCM์„ ์„ ๋ณด์ด๊ณ  ์žˆ๋‹ค. ํ•œํŽธ, ์ž์—ฐ๊ณ„์—์„œ ๋ฐœ๊ฒฌ๋˜๋Š” ๋‹จ๋ฐฑ์งˆ-๋ฌด๊ธฐ์งˆ ๋ณตํ•ฉ์ฒด๋ฅผ ๋ณธ๋”ฐ, ์šฐ์ˆ˜ํ•œ ๋ฌผ์„ฑ์„ ๊ฐ–๋Š” ์กฐํ•ฉ์ฒด๋‚˜ ๋‚˜๋…ธ๋ณตํ•ฉ์ฒด๋ฅผ ๊ตฌํ˜„ํ•˜๊ธฐ ์œ„ํ•ด BCM์„ ์ด์šฉํ•˜๋Š” ์—ฐ๊ตฌ ์—ญ์‹œ ํ™œ๋ฐœํžˆ ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ, BCM ์ž๊ธฐ์กฐ๋ฆฝ ํ˜„์ƒ์— ๋Œ€ํ•œ ์ง€์‹๊ณผ ๋งˆ์ด์…€ ์œ ๋ž˜ ์กฐํ•ฉ์ฒด์˜ ํ˜•์„ฑ์›๋ฆฌ ๊ฐ„์˜ ์—ฐ๊ด€์„ฑ์„ ๊นŠ์ด ์žˆ๊ฒŒ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” ๋ธ”๋ก๊ณต์ค‘ํ•ฉ์ฒด์˜ ๋…ํŠนํ•œ ๋ถ„์ž๋ชจํ‹ฐํ”„๊ฐ€ ์ž๊ธฐ์กฐ๋ฆฝ๋œ ๋งˆ์ด์…€์˜ ๊ตฌ์กฐ์™€ ๋™์—ญํ•™์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ ๋ฐ BCM๊ณผ ๋ฌด๊ธฐ์งˆ ๊ฐ„์˜ ์ƒํ˜ธ์ž‘์šฉ์— ์˜ํ•œ ์กฐํ•ฉ๊ตฌ์กฐ์˜ ์˜ˆ์‹œ๋ฅผ ๋‹ค๋ฃฌ๋‹ค. ์ด๋Ÿฌํ•œ ์—ฐ๊ตฌ๋“ค์„ ๊ด€ํ†ตํ•˜์—ฌ, ์ •ํ™•ํžˆ ์ œ์–ด๋œ ๋‚˜๋…ธ์†Œ์žฌ๋ฅผ ์œ„ํ•ด BCM์˜ ๊ตฌ์กฐ๋ณ€ํ™”์— ๋Œ€ํ•œ ์ง€์‹์„ ํ™œ์šฉํ•˜๋Š” ๊ฒƒ์˜ ์ค‘์š”์„ฑ์„ ๊ฐ•์กฐํ•˜๊ณ ์ž ํ•œ๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์˜ ์ฒซ ๋ถ€๋ถ„์—์„œ๋Š” ํ•œ ์ชฝ ๋ธ”๋ก์— ๊ธด ํ”Œ๋ฃจ์˜ค๋ฅด์•Œํ‚ฌ ๊ณ์‚ฌ์Šฌ์ด ๋‹ฌ๋ฆฐ ์ด์ค‘๋ธ”๋ก๊ณต์ค‘ํ•ฉ์ฒด์˜ ๋งˆ์ด์…€ ๊ตฌ์กฐ์™€ ์™„ํ™” ๋™์—ญํ•™์„ ์†Œ๊ฐœํ•œ๋‹ค. ํ”Œ๋ฃจ์˜ค๋ฅด์•Œํ‚ฌ ๊ณ๊ฐ€์ง€์— ์˜ํ•œ ๋ณ‘์†”(Bottlebrush)ํ˜• ์‚ฌ์Šฌ๊ตฌ์กฐ๋Š” ๋ธ”๋ก์— ์ƒ๋‹นํ•œ ์‚ฌ์Šฌ ๊ฒฝ๋„(Stiffness)๋ฅผ ์ˆ˜๋ฐ˜ํ•˜๋ฉฐ, ๋ธ”๋ก๊ณต์ค‘ํ•ฉ์ฒด ์ž๊ธฐ์กฐ๋ฆฝ์„ ํ†ตํ•ด ๋ถˆ์šฉ์„ฑ ์šฉ๋งค ์ƒ์—์„œ ๊ตฌํ˜• ๋งˆ์ด์…€์˜ ๋‚ดํ•ต์„ ์ด๋ฃฐ ๋•Œ์˜ ํ”Œ๋ฃจ์˜ค๋ฅด์•Œํ‚ฌ ์‚ฌ์Šฌ์€ ๊ทธ ๊ฒฝ๋„๋กœ ์ธํ•ด ๊ฐ•ํ•˜๊ฒŒ ์‹ ์žฅ(Stretching)๋œ๋‹ค. ๋˜ํ•œ, ํ”Œ๋ฃจ์˜ค๋ฅด์•Œํ‚ฌ ์‚ฌ์Šฌ์˜ ๊ธธ์ด์— ๋”ฐ๋ฅธ ๋งˆ์ด์…€์˜ ๋‚ดํ•ต๊ณผ ์ฝ”๋กœ๋‚˜(Corona) ํฌ๊ธฐ์˜ ์Šค์ผ€์ผ๋ง ๊ด€๊ณ„์‹์€ ๊ณ ์ „์ ์ธ ์—ด์—ญํ•™์  ์ด๋ก ์—์„œ ๋ฒ—์–ด๋‚œ ๊ฒƒ์œผ๋กœ ๊ด€์ฐฐ๋˜๋ฉฐ, ์ด๋Ÿฌํ•œ ๋น„์ „ํ˜•์„ฑ์€ ๋ถˆ์šฉ์„ฑ ๋ณ‘์†”ํ˜• ๋ธ”๋ก์˜ ์‚ฌ์Šฌ ๊ฒฝ๋„๋กœ๋ถ€ํ„ฐ ์œ ๋ž˜ํ•˜์˜€๋‹ค. ๋ณ‘์†”ํ˜• ์‚ฌ์Šฌ๊ตฌ์กฐ์˜ ์‚ฌ์Šฌ ๊ฒฝ๋„๋กœ๋ถ€ํ„ฐ ์œ ๋ž˜ํ•˜๋Š” ๋˜ ๋‹ค๋ฅธ ๊ฒฐ๊ณผ๋Š” ์‚ฌ์Šฌ ์–ฝํž˜(Entanglement)์ด ๊ฑฐ์˜ ์—†๊ณ  ์ž์œ ๋ถ€ํ”ผ(Free volume)๊ฐ€ ํฌ๋‹ค๋Š” ์ ์ธ๋ฐ, ์ด๋กœ ์ธํ•ด ๋ณ‘์†”ํ˜• ์‚ฌ์Šฌ์€ ์„ ํ˜• ์‚ฌ์Šฌ์— ๋น„ํ•ด ์‹ ์†ํ•œ ๋™์—ญํ•™์  ํŠน์„ฑ์„ ๋ณด์ด๋ฉฐ ๋‚ดํ•ต ๋‚ด๋ถ€์—์„œ์˜ ์™„ํ™”(Relaxation) ์—ญ์‹œ ๋น ๋ฅด๋‹ค. ๋”ฐ๋ผ์„œ, ๋ณธ ๋ณ‘์†”ํ˜• ๋ธ”๋ก๊ณต์ค‘ํ•ฉ์ฒด ์‹œ์Šคํ…œ์˜ ํ‰ํ˜• ์ด๋™ ์‹œ๊ฐ„์€ ๋งค์šฐ ์‹ ์†ํ•˜์—ฌ ์งง์€ ์‹œ๊ฐ„ ์•ˆ์— ๊ท ์ผํ•œ BCM์„ ์ œ์ž‘ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋‹จ์ฐจ๋งž์ถค(Contrast-matched) ์†Œ๊ฐ ์ค‘์„ฑ์ž ์‚ฐ๋ž€๊ธฐ๋ฒ•์„ ์ด์šฉํ•ด ์™„ํ™” ๋™์—ญํ•™์„ ์ •๋Ÿ‰์ ์œผ๋กœ ์ธก์ •ํ•œ ๊ฒฐ๊ณผ, ์‹ค์ œ๋กœ ๋ณ‘์†”ํ˜• ์‚ฌ์Šฌ์ด ๋‚ดํ•ต์„ ์ด๋ฃจ๋Š” BCM์˜ ์‚ฌ์Šฌ ๊ตํ™˜์ด ๋น ๋ฆ„์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•ด, ๋ณ‘์†”ํ˜• ์‚ฌ์Šฌ์ด ๋‚ดํ•ต์„ ์ด๋ฃจ๋Š” ์ž๊ธฐ์กฐ๋ฆฝ์ฒด๋Š” ๊ทธ ๊ตฌ์กฐ์  ๊ฑฐ๋™๊ณผ ์™„ํ™” ๋™์—ญํ•™์ด ์‹ ์ถ•์„ฑ ์žˆ๋Š” ์„ ํ˜• ๋ธ”๋ก๊ณต์ค‘ํ•ฉ์ฒด์˜ ๊ทธ๊ฒƒ๊ณผ ๋งค์šฐ ์ƒ์ดํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋‘ ๋ฒˆ์งธ ๋ถ€๋ถ„์—์„œ๋Š” BCM์„ ์ˆ˜๋ฐ˜ํ•œ ์กฐํ•ฉ๊ตฌ์กฐ์˜ ์˜ˆ์‹œ๋กœ BCM๊ณผ ๊ด‘๋ฌผ(Mineral) ๊ฒฐ์ •์˜ ์ž์—ฐ๋ชจ์‚ฌ ๋‚˜๋…ธ๋ณตํ•ฉ์ฒด๋ฅผ ์†Œ๊ฐœํ•œ๋‹ค. BCM์€ ์ •์ „๊ธฐ์  ์ƒํ˜ธ์ž‘์šฉ์„ ํ†ตํ•ด ๋ฌด๊ธฐ์งˆ์˜ ํ‘œ๋ฉด์— ํก์ฐฉํ•˜๋ฉฐ, ํก์ฐฉ๋œ BCM์€ ๋‚˜์•„๊ฐ€ ์„ฑ์žฅํ•˜๋Š” ๊ด‘๋ฌผ ๊ฒฐ์ • ๋‚ด๋ถ€์— ํ•จ์ž…๋  ์ˆ˜ ์žˆ๊ณ , ์ด๋ ‡๊ฒŒ ์œ ๊ธฐ์งˆ์ด ํ•จ์ž…๋œ ๊ด‘๋ฌผ์€ ํ•จ์ž… ๋ฐ€๋„์— ๋”ฐ๋ผ ํŒŒ์‡„๊ฐ•๋„(Fracture Toughness)๊ฐ€ ์ฆ๊ฐ•๋œ๋‹ค. BCM์˜ ์ฝ”๋กœ๋‚˜ ์ „ํ•˜ ๋ฐ€๋„์— ์˜ํ•ด BCM ํก์ฐฉ ์„ธ๊ธฐ๊ฐ€ ๋‹ฌ๋ผ์ง€๋Š” ํ•œํŽธ, BCM์˜ ๋ธŒ๋ผ์šดํ™•์‚ฐ์€ ์„ฑ์žฅ ์ค‘์ธ ๊ด‘๋ฌผ ๊ฒฐ์ •๊ณผ์˜ ์ถฉ๋Œ๋นˆ๋„์— ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค. ๋”ฐ๋ผ์„œ, pH์™€ BCM์˜ ์ˆ˜๋™์—ญํ•™์ (Hydrodynamic) ํฌ๊ธฐ๋ฅผ ์กฐ์ ˆํ•จ์— ๋”ฐ๋ผ, ๊ฒฐ์ •์€ ํก์ฐฉ ๋ฐ€๋„๊ฐ€ ์ฆ๊ฐ€ํ•˜๋Š” ์ˆœ์„œ๋Œ€๋กœ (1) ๋ฐฉํ•ด๋ฐ›์ง€ ์•Š๋Š” ์ƒํƒœ์˜ ์„ฑ์žฅ๊ณผ (2) ์„ฑ์žฅ์ง€์ ์˜ ๋ถ€๋ถ„์ ์ธ ๋ด‰์‡„์™€ ๊ทธ๋กœ ์ธํ•œ ํ•จ์ž…์„ ๊ฑฐ์ณ (3) ์™„์ „ํ•œ ์„ฑ์žฅ ์–ต์ œ๋ฅผ ๊ฒช๋Š”๋‹ค. ์ด๋Ÿฌํ•œ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š”, ์ •๋ฐ€ํ•œ ๊ตฌ์กฐ ์ œ์–ด๋ฅผ ๊ฑฐ์นœ BCM์„ ๋‹ค์ธต์  ์กฐํ•ฉ๊ตฌ์กฐ๋ฅผ ๋งŒ๋“ค๊ธฐ ์œ„ํ•œ ๋‹จ์œ„์†Œ์žฌ๋กœ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ์ „๋ก€ ์—†๋Š” ๋ฌผ์„ฑ์„ ์ง€๋‹ˆ๋Š” ๋‚˜๋…ธ์†Œ์žฌ๋ฅผ ๊ตฌํ˜„ํ•  ์ˆ˜ ์žˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค.Chapter 1. Introduction ........................................................................... 1 1.1. Historical Background ........................................................................ 1 1.2. Motivation of Research ...................................................................... 9 Chapter 2. Structures of Bottlebrush Fluoroalkyl Block Copolymer Micelles 11 2.1. Introduction ...................................................................................... 11 2.2. Experimental Section ....................................................................... 14 2.3. Results and Discussion ..................................................................... 23 2.3.1. Preparation and Characterization of PF-b-PC Block Copolymer Micelles ..................... 23 2.3.2. Effect of PF Core Block Stiffness on the Structure of Block Copolymer Micelles .............. 27 2.4. Summary .......................................................................................... 34 Chapter 3. Chain Exchange Kinetics of Block Copolymer Micelles with Bottlebrush Core Block ... 35 3.1. Introduction ...................................................................................... 35 3.2. Experimental Section ....................................................................... 38 3.3. Results and Discussion ..................................................................... 47 3.3.1. Relaxation dynamics of bottlebrush polymer PF.................. 47 3.3.2. Dynamics of chain exchange in block copolymer micelles with bottlebrush core block .............. 51 3.4. Summary .......................................................................................... 58 Chapter 4. Nanocomposite Formation through Interactions Between Block Copolymer Micelles and Crystallizing Minerals ............................ 59 4.1. Introduction ...................................................................................... 59 4.2. Experimental Section ....................................................................... 62 4.3. Results .............................................................................................. 70 4.3.1. Nucleation and growth of CaSO4โ€ข0.5H2O crystals in evaporating droplets ................ 70 4.3.2. Anisotropic adsorption and growth retardation of PAA .......................................... 72 4.3.3. Adsorption and occlusion of PS-b-PAA BCMs ................... 83 4.4. Discussion ........................................................................................ 91 4.4.1. Mechanisms of diffusion-limited adsorption of PAA and PS-b-PAA BCMs for the retardation of crystal growth ....................... 91 4.4.2. Effect of structures of macromolecular additives on the retardation of crystal growth ........................................................... 92 4.5. Summary .......................................................................................... 94 Conclusions ................................................................................ 95 Bibliography ......................................................................... 98 ๊ตญ๋ฌธ ์ดˆ๋ก .......................................................................... 103Docto

    A study on broadband source localization in ocean acoustic waveguide

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    In SONAR(Sound Navigation and Ranging), passive localization of sound sources in range and depth are important issues. It has long been known that multi-modal dispersion in a shallow water waveguide degrades the performance of localization by conventional plane-wave beamforming. This is due to the advent of spurious effects unique to the waveguide environment, such as multiple peaks and beam spreading in the beam output. Attempts, on the other hand, have been made to localize sources in ocean waveguides by exploiting multi-modal interference using methods such as matched field processing(MFP). Apart from being computationally expensive, MFP techniques require accurate knowledge of the wave propagation environment. They are susceptible to large systematic errors from mismatch when adequate environmental information is not available. The range of a source in a ocean waveguide can sometimes also be estimated by the simpler waveguide invariant method, which employs only incoherent processing of acoustic intensity data as a function of range and bandwidth. It is convenient to apply the concept of waveguide invariant . This has earlier been shown to be useful for explaining interference patterns of broadband signals. In this thesis we proposed that instantaneous and computationally inexpensive source range estimation method. The proposed method requires neither a priori knowledge of environmental parameters nor multiple modes in the received field. In the proposed method we introduced a concept of the slope of modal interference patterns show that the information of source range. So, we analyzed the single sensor spectrogram then compare the ratio of between source range and positioned sensors. Then we estimated the trajectory of moving source and demonstrated the results of computer simulation. This thesis is organized as follows : Section 2 overviews the underwater acoustic propagation model. In Section 3, array invariant source range estimating method is described. In Section 4, the proposed method is described, and simulation results are discussed. Finally Section 5 gives conclusions and future works.์ œ 1 ์žฅ ์„œ๋ก  = 1 ์ œ 2 ์žฅ ์ˆ˜์ค‘ ์ŒํŒŒ ์ „๋‹ฌ ๋ชจ๋ธ๋ง = 4 2.1 ์ˆ˜์ค‘ ์ŒํŒŒ ์ „๋‹ฌ ํŠน์„ฑ = 4 2.2 ์ฑ„๋„ ์ „๋‹ฌ ํ•จ์ˆ˜ ์ถ”์ • = 9 ์ œ 3 ์žฅ ๋ฐฐ์—ด ๋ถˆ๋ณ€์„ฑ ์ด๋ก ์— ๊ธฐ๋ฐ˜ํ•œ ์Œ์› ๊ฑฐ๋ฆฌ ์ถ”์ • ๊ธฐ๋ฒ• = 14 3.1 ๋ฐฐ์—ด ๋ถˆ๋ณ€์„ฑ ์ด๋ก  = 14 3.2 ๋ชจ์˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ ๊ฒฐ๊ณผ ๋ถ„์„ = 20 ์ œ 4 ์žฅ ์ŠคํŽ™ํŠธ๋กœ๊ทธ๋žจ์˜ ๊ฐ„์„ญํŒจํ„ด์„ ์ด์šฉํ•œ ๊ฑฐ๋ฆฌ์ถ”์ • ๊ธฐ๋ฒ• = 29 4.1 ๋ชจ๋“œ ๊ฐ„์„ญ๊ณผ ์Œํ–ฅ ๋„ํŒŒ๊ด€ ๋ถˆ๋ณ€ ์ด๋ก  = 29 4.2 ์Œ์›์˜ ๊ฑฐ๋ฆฌ์— ๋”ฐ๋ฅธ ๊ฐ„์„ญ ํŒจํ„ด = 34 4.3 ์ œ์•ˆ๋œ ๊ฑฐ๋ฆฌ ์ถ”์ • ์•Œ๊ณ ๋ฆฌ์ฆ˜ = 37 4.4 ๊ฑฐ๋ฆฌ ์ถ”์ • ๊ฒฐ๊ณผ ๋ถ„์„ = 40 ์ œ 5 ์žฅ ๊ฒฐ๋ก  = 45 ์ฐธ๊ณ  ๋ฌธํ—Œ = 4

    2018-2019๋…„ Uganda Malaria Indicator Survey ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•˜์—ฌ

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    ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ: ์šฐ๊ฐ„๋‹ค๋Š” ๋ง๋ผ๋ฆฌ์•„ ๋ฐœ์ƒ๋ฅ  ์ „ ์„ธ๊ณ„ 3์œ„, ์‚ฌ๋ง๋ฅ  7์œ„๋กœ ๋ง๋ผ๋ฆฌ์•„๋กœ ์ธํ•œ ์งˆ๋ณ‘๋ถ€๋‹ด์ด ๋†’์€ ๊ตญ๊ฐ€์ด๋‹ค. ์šฐ๊ฐ„๋‹ค ์ •๋ถ€์™€ ๋ณด๊ฑด๋ถ€๋Š” ๋ง๋ผ๋ฆฌ์•„ ์œ ๋ณ‘๋ฅ ์„ ๊ฐ์†Œ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ์‚ด์ถฉ ๋ชจ๊ธฐ์žฅยท๋ฐฉ์ถฉ๋ง ์ด์šฉ, ์‹ค๋‚ด ์ž”๋ฅ˜ ์Šคํ”„๋ ˆ์ด ์‚ฌ์šฉ๊ณผ ๊ฐ™์€ ๋ง๋ผ๋ฆฌ์•„ ํ†ต์ œํ”„๋กœ๊ทธ๋žจ ์ •์ฑ…์„ ์‹œํ–‰ํ•˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์šฐ๊ฐ„๋‹ค์˜ ๊ธฐํ›„์™€ ์ง€ํ˜•์ด ์ง€์—ญ๋ณ„๋กœ ์ƒ์ดํ•œ ํŠน์ง•์„ ๊ฐ€์ง€๊ณ  ์žˆ๊ณ  ๋ง๋ผ๋ฆฌ์•„๋Š” ๊ธฐํ›„์™€ ํ™˜๊ฒฝ์  ์š”์ธ์— ์˜ํ–ฅ์„ ๋งŽ์ด ๋ฐ›๋Š” ์งˆ๋ณ‘์ด๋ฏ€๋กœ ์šฐ๊ฐ„๋‹ค์˜ ๋ง๋ผ๋ฆฌ์•„ ์ •์ฑ…์€ ์‚ฌํšŒ๊ฒฝ์ œ์ , ์ธ๊ตฌํ•™์  ์š”์ธ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ธฐํ›„ํ™˜๊ฒฝ๊ณผ ๊ฐ™์€ ์ง€์—ญ์  ์š”์ธ๋„ ํ•จ๊ป˜ ๊ณ ๋ คํ•ด์•ผ ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ์—ฐ๊ตฌ๋ชฉํ‘œ: ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฐœ์ธ ์ˆ˜์ค€๊ณผ ์ง€์—ญ ์ˆ˜์ค€์˜ ๊ณ„์ธต์  ์ž๋ฃŒ๋กœ ๊ตฌ๋ถ„๋œ 2018-2019 ์šฐ๊ฐ„๋‹ค ๋ง๋ผ๋ฆฌ์•„ ์ง€ํ‘œ์กฐ์‚ฌ์ž๋ฃŒ(MIS)๋ฅผ ์ด์šฉํ•˜์—ฌ ๋‹ค์ˆ˜์ค€ ๋ถ„์„์„ ์‹ค์‹œํ•˜๊ณ  ๋ง๋ผ๋ฆฌ์•„ ํ†ต์ œํ”„๋กœ๊ทธ๋žจ๊ณผ ๋ง๋ผ๋ฆฌ์•„ ์‹ ์†์ง„๋‹จ๊ฒ€์‚ฌ๊ฒฐ๊ณผ์˜ ์—ฐ๊ด€์„ฑ์„ ํŒŒ์•…ํ•˜๊ณ ์ž ํ•œ๋‹ค. ์—ฐ๊ตฌ๋ฐฉ๋ฒ•: ์šฐ๊ฐ„๋‹ค 57๊ฐœ ๋„์‹œ ์ง‘๋ฝ(cluster)๊ณผ 174๊ฐœ์˜ ์‹œ๊ณจ ์ง‘๋ฝ์— ๊ฑฐ์ฃผํ•˜๋Š” 15-49์„ธ ์—ฌ์„ฑ 1,942๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ์ˆ˜ํ–‰ํ•˜๋Š” ๋‹จ๋ฉด์—ฐ๊ตฌ์ด๋‹ค. ๊ฒฐ๊ณผ๋ณ€์ˆ˜๋Š” ๋ง๋ผ๋ฆฌ์•„ ์‹ ์†์ง„๋‹จ๊ฒ€์‚ฌ๊ฒฐ๊ณผ(โ€˜์–‘์„ฑโ€™, โ€˜์Œ์„ฑโ€™)์ธ ๋ฒ”์ฃผํ˜• ๋ณ€์ˆ˜์ด๋ฉฐ ๊ฐœ์ธ์ˆ˜์ค€๊ณผ ์ง€์—ญ์ˆ˜์ค€์˜ ์œ„๊ณ„์  ์ž๋ฃŒ๋ผ๋Š” ์ ์„ ๊ณ ๋ คํ•˜์—ฌ ๋‹ค์ˆ˜์ค€ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„ (Multilevel Logistic Regression)์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ํ†ต๊ณ„์  ๊ฒ€์ฆ๋ฐฉ๋ฒ•์œผ๋กœ ๊ธฐ์ดˆํ†ต๊ณ„๋ถ„์„, ์นด์ด์ œ๊ณฑ๋ถ„์„, ์ƒ๊ด€๋ถ„์„, ์ผ๋ฐ˜ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„, ๋‹ค์ˆ˜์ค€ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ์ข…์†๋ณ€์ˆ˜๋Š” ๋ง๋ผ๋ฆฌ์•„ ์‹ ์†์ง„๋‹จ๊ฒ€์‚ฌ๊ฒฐ๊ณผ์ด๋ฉฐ, ๋…๋ฆฝ๋ณ€์ˆ˜๋Š” ๊ฐœ์ธ์ˆ˜์ค€(์—ฐ๋ น, ์ข…๊ต, ๋ฌธ๋งน๋ฅ , ๋ง๋ผ๋ฆฌ์•„ ์ง€์‹, ๋ง๋ผ๋ฆฌ์•„ ๋ฉ”์‹œ์ง€ ๋…ธ์ถœ์—ฌ๋ถ€, 12๊ฐœ์›” ์ด๋‚ด ์‚ด์ถฉ ์Šคํ”„๋ ˆ์ด ์‚ฌ์šฉ์—ฌ๋ถ€, ์ทจ์นจ์šฉ ๋ชจ๊ธฐ์žฅ ์†Œ์œ , LLIN ๋ชจ๊ธฐ์žฅ ์‚ฌ์šฉ, ๋นˆํ˜ˆ์ˆ˜์ค€, ๋ฐœ์—ด์—ฌ๋ถ€, ๊ฒฝ์ œ์  ์ˆ˜์ค€, ์–ด๋จธ๋‹ˆ์˜ ๊ต์œก์ˆ˜์ค€, ๊ฐ€์กฑ์ˆ˜, ํ™”์žฅ์‹ค ์œ ํ˜•, ์‹์ˆ˜์›, ๊ฑฐ์ฃผ์ง€)๊ณผ ์ง€์—ญ์ˆ˜์ค€(์‹์ƒ์ง€์ˆ˜, ์ง€ํ‘œ์˜จ๋„, ๊ฐ•์šฐ๋Ÿ‰, ITN ๋ณด๊ธ‰๋ฅ , ์ธ๊ตฌ๋ฐ€๋„, ์ง€์—ญ๋ณ„ ํ‰๊ท ๊ต์œก์ˆ˜์ค€)์œผ๋กœ ๊ตฌ๋ถ„ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์— ํ™œ์šฉํ•œ ํ”„๋กœ๊ทธ๋žจ์€ SAS 9.4์ด๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ: ๋ง๋ผ๋ฆฌ์•„ ์‹ ์†์ง„๋‹จ๊ฒ€์‚ฌ๊ฒฐ๊ณผ๊ฐ€ ์–‘์„ฑ์œผ๋กœ ๋‚˜ํƒ€๋‚œ ์‚ฌ๋žŒ์€ ์ „์ฒด ์—ฐ๊ตฌ๋Œ€์ƒ์ž 1942๋ช… ์ค‘ 417๋ช…(16.98%)์ด์—ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ์ฃผ ๋ณ€์ˆ˜์ธ ๋ง๋ผ๋ฆฌ์•„ ํ†ต์ œํ”„๋กœ๊ทธ๋žจ ๋ณ€์ˆ˜์ธ โ€˜12๊ฐœ์›” ์ด๋‚ด ์‹ค๋‚ด ์‚ด์ถฉ ์Šคํ”„๋ ˆ์ด ์‚ฌ์šฉ์—ฌ๋ถ€โ€™์™€ โ€˜LLIN ๋ชจ๊ธฐ์žฅ ์‚ฌ์šฉ์—ฌ๋ถ€โ€™๊ฐ€ ์œ ์˜์ˆ˜์ค€ 95%์—์„œ ๊ฒฐ๊ณผ๋ณ€์ˆ˜์™€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ๊ด€๊ณ„๋ฅผ ๊ฐ–๋Š” ๋ณ€์ˆ˜๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค[IRS= OR:0.23, 95%CI=0.12-0.46, LLIN: OR=0.68, 95%CI=0.47-0.99]. ๊ทธ ์™ธ ๊ฐœ์ธ ๋ณ€์ˆ˜ ์ค‘ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ๋ณ€์ˆ˜๋Š” ๊ฐœ์ธ ์ˆ˜์ค€์—์„œ ๊ฒฝ์ œ์  ์ˆ˜์ค€ [โ€˜๋‚ฎ์Œโ€™: OR=0.56, 95%CI=0.35-0.90, โ€˜๋†’์Œโ€™: OR=0.33, 95%CI=0.17-0.68, โ€˜๋งค์šฐ ๋†’์Œโ€™: OR=0.12, 95%CI=0.03-0.44], ์–ด๋จธ๋‹ˆ์˜ ๊ต์œก์ˆ˜์ค€ [โ€˜์ค‘๋“ฑ๊ต์œกโ€™ OR=0.48, 95%CI=0.24-0.96], ๋ฐœ์—ด์—ฌ๋ถ€[OR=2.02 95%CI=1.37-2.97], ๋นˆํ˜ˆ์ˆ˜์ค€[โ€˜๊ฒฝ์ฆโ€™: OR=1.70 95%CI=1.13-2.55, โ€˜๋ณดํ†ตโ€™: OR=3.85, 95%CI=2.58-5.75, โ€˜์ค‘์ฆโ€™ OR=7.14, 95%CI=2.33-21.86]๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ์ง€์—ญ ์ˆ˜์ค€์—์„œ ์ง€ํ‘œ์˜จ๋„ [OR=128, 95%CI=1.09-1.49], ๊ฐ•์ˆ˜๋Ÿ‰[OR=1.02, 95%CI=1.01-1.03], ITN ๋ณด๊ธ‰๋ฅ [OR=1.77, 95%CI=1.19-2.64]์ด ๊ฒฐ๊ณผ๋ณ€์ˆ˜์ธ ๋ง๋ผ๋ฆฌ์•„ ์‹ ์†์ง„๋‹จ๊ฒ€์‚ฌ๊ฒฐ๊ณผ์— ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ๊ด€๊ณ„๋ฅผ ๊ฐ–๋Š” ๋ณ€์ˆ˜๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๋ก : ๋ถ„์„์— ํฌํ•จ๋˜์—ˆ๋˜ ์ฃผ์š” ๋ณ€์ˆ˜์ธ ๋ง๋ผ๋ฆฌ์•„ ํ†ต์ œ ํ”„๋กœ๊ทธ๋žจ ์ค‘ ์‹ค๋‚ด ์‚ด์ถฉ ์Šคํ”„๋ ˆ์ด์™€ LLIN ๋ชจ๊ธฐ์žฅ ์‚ฌ์šฉ์ด ์œ ์˜์ˆ˜์ค€ 95%์—์„œ ์œ ์˜ํ•œ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์ธ ์ด์œ ๋Š” ์šฐ๊ฐ„๋‹ค ์ •๋ถ€์˜ ์ง€์†์ ์ธ ๊ด€์‹ฌ๊ณผ ์ค‘์žฌ๊ฐœ์ž… ์„ฑ๊ณต์ด๋ผ๊ณ  ์—ฌ๊ฒจ์ง„๋‹ค. PRECEDE ์ง„๋‹จ๋‹จ๊ณ„ ์ค‘ ์—ญํ•™์  ์ง„๋‹จ์š”์ธ์ธ โ€˜๋นˆํ˜ˆ์ˆ˜์ค€โ€™๊ณผ โ€˜๋ฐœ์—ด์—ฌ๋ถ€โ€™๊ฐ€ ๋งค์šฐ ๋†’์€ ์—ฐ๊ด€์„ฑ์„ ๋ณด์˜€๋Š”๋ฐ ๊ทธ ์ค‘ ๋นˆํ˜ˆ์ด ์‹ฌํ•ด์งˆ์ˆ˜๋ก ๋ง๋ผ๋ฆฌ์•„ ๊ฒ€์‚ฌ๊ฒฐ๊ณผ๊ฐ€ ์–‘์„ฑ์œผ๋กœ ๋‚˜ํƒ€๋‚  ์˜ค์ฆˆ๋Š” ์•ฝ 7๋ฐฐ๋‚˜ ์ฆ๊ฐ€ํ–ˆ๋‹ค. ๋”ฐ๋ผ์„œ, ์ •๋ถ€๋Š” ์šฐ๊ฐ„๋‹ค์˜ ๊ฐ€์ž„๊ธฐ ์—ฌ์„ฑ์„ ๋Œ€์ƒ์œผ๋กœ ๋ฐœ์—ด๊ณผ ๋นˆํ˜ˆ๊ณผ ๊ฐ™์€ ๋Œ€ํ‘œ์ ์ธ ์ž„์ƒ ์ฆ์ƒ์— ๋Œ€ํ•ด ๊ต์œกํ•˜๊ณ  ๊ฐ์—ผ ์˜ˆ๋ฐฉ๋ฒ•์œผ๋กœ ๋ง๋ผ๋ฆฌ์•„ ํ†ต์ œํ”„๋กœ๊ทธ๋žจ ์ด์šฉ ํ™•๋Œ€๋ฅผ ์œ„ํ•œ ์ค‘์žฌ๊ฐœ์ž…์ „๋žต ์ˆ˜๋ฆฝ์˜ ํ•„์š”์„ฑ์„ ์‹œ์‚ฌํ•œ๋‹ค.Objectives: Malaria infection is still a high burden of disease in Uganda and has remained a leading public health problem in the country. In this regard, the main purpose of this study was to identify and examine associative factors that have influenced the result of a rapid diagnostics test in Uganda using 2018-2019 Malaria Indicator Survey(UMIS). This study, therefore, aimed to investigate the prevalence and factors associated with RDT result on individual and environmental level in Uganda. Methods: This study used the Malaria Indicator Survey for 2018-2019 provided and collected by the United States Agency for International Development (USAIDS). The outcome variable was malaria rapid diagnostic test survey results(negative or positive) and the main explanatory variable was as follows: Individual level includes age, literacy, motherโ€™s education, religion, malaria knowledge, heard/seen message about malaria, wealth, members of household, type of toilet facility, source of drinking water, residence, fever, anemia level, IRS, use LLIN, own mosquito net and Environmental level consists of rainfall, land surface temperature, enhanced vegetation index, population density, ITN coverage, average motherโ€™s education level. A multilevel logistic regression model was conducted using SAS 9.4 and to identify individual and community level determinants of RDT result during lactation. Results: From the findings of this study, the vulnerability of an Ugandan woman to malaria infection decreased as โ€˜Has dwelling been sprayed against mosquitoes in the last 12 monthsโ€™ and โ€˜Use LLINโ€™. Other major significant factors were: the presence of anemia and fever history in women, wealth level, motherโ€™s education level. Also, land surface temperature, ITN coverage, rainfall was significantly associated with the increased risk of malaria disease and infection. Conclusion: Individuals with wealth conditions, education level, fever and anemia level are positively associated with malaria infection. Improving malaria control programs such as spraying anti-malaria to the house and LLIN are effective means of reducing the risk of malaria. Since Female household members are vulnerable groups to the risk of malaria, infectious disease management and announcement of prevention methods against malaria has been essential to design improved strategic intervention for the reduction of malaria epidemic in Uganda.์ œ1์žฅ ์„œ๋ก  1 ์ œ1์ ˆ ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ๋ฐํ•„์š”์„ฑ 1 1. ๋ง๋ผ๋ฆฌ์•„์งˆ๋ณ‘๊ฐœ์š” 1 2. ๋ง๋ผ๋ฆฌ์•„ ์ „ ์„ธ๊ณ„ํ˜„ํ™ฉ 2 3. ๋ง๋ผ๋ฆฌ์•„ ์ฃผ์š” ํ†ต์ œํ”„๋กœ๊ทธ๋žจ๊ณผ ๋ชฉํ‘œ 3 4. ๋‹ค์ˆ˜์ค€ ๋ถ„์„์˜ ํ•„์š”์„ฑ 5 ์ œ2์ ˆ ์—ฐ๊ตฌ๋ชฉ์  7 ์ œ2์žฅ ์„ ํ–‰๋ฌธํ—Œ ๊ณ ์ฐฐ 8 ์ œ1์ ˆ ๋ง๋ผ๋ฆฌ์•„ ํ†ต์ œํ”„๋กœ๊ทธ๋žจ๊ณผ ๊ฑด๊ฐ•๊ฒฐ๊ณผ 8 ์ œ2์ ˆ ๋ง๋ผ๋ฆฌ์•„ ๊ฐ์—ผ๊ณผ ๋‹ค์ˆ˜์ค€ ๋ถ„์„ 9 ์ œ3์ ˆ ๋ง๋ผ๋ฆฌ์•„ ๊ฐ์—ผ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์š”์ธ 11 ์ œ3์žฅ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 16 ์ œ1์ ˆ ์—ฐ๊ตฌ์ž๋ฃŒ ๋ฐ ๋Œ€์ƒ 16 1. ์—ฐ๊ตฌ์ง€์—ญ 16 2. ์—ฐ๊ตฌ์ž๋ฃŒ 18 3. ์—ฐ๊ตฌ๋Œ€์ƒ 20 ์ œ2์ ˆ ์—ฐ๊ตฌ๋ณ€์ˆ˜ 22 1. ์ข…์†๋ณ€์ˆ˜ 23 2. ๋…๋ฆฝ๋ณ€์ˆ˜ 23 ์ œ3์ ˆ ๋ถ„์„๋ฐฉ๋ฒ• 27 ์ œ4์ ˆ ์œค๋ฆฌ์  ๊ณ ๋ ค 31 ์ œ4์žฅ ์—ฐ๊ตฌ๊ฒฐ๊ณผ 32 ์ œ1์ ˆ ๋‹ค์ˆ˜์ค€ ๋ถ„์„ ๊ฒฐ๊ณผ 32 1. ๊ธฐ์ดˆํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ 32 2. ์—ฐ๊ตฌ๋Œ€์ƒ์ž์˜ ํŠน์„ฑ์— ๋”ฐ๋ฅธ ๋ง๋ผ๋ฆฌ์•„ ์‹ ์†์ง„๋‹จ๊ฒ€์‚ฌ๊ฒฐ๊ณผ์˜ ๊ด€๊ณ„ 39 3. ์ƒ๊ด€๋ถ„์„ ๊ฒฐ๊ณผ 43 4. ๊ฐœ์ธ์ˆ˜์ค€ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„๊ฒฐ๊ณผ 46 5. ๋‹ค์ˆ˜์ค€ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ 49 1) ๋‹ค์ˆ˜์ค€ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ 49 2) ๋ง๋ผ๋ฆฌ์•„ ์‹ ์†์ง„๋‹จ๊ฒ€์‚ฌ๊ฒฐ๊ณผ์™€ ์ง€์—ญ๊ฐ„ ์ฐจ์ด ๋ถ„์„ 54 ์ œ5์žฅ ๊ฒฐ๋ก  ๋ฐ ๊ณ ์ฐฐ 56 ์ œ1์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ๊ณ ์ฐฐ 56 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ์˜์˜ ๋ฐ ํ•œ๊ณ„ 58 ์ œ3์ ˆ ๊ฒฐ๋ก  ๋ฐ ์ œ์–ธ 60 ์ฐธ๊ณ ๋ฌธํ—Œ 62 Abstract 70์„

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