1,534 research outputs found
Large Margin Object Tracking with Circulant Feature Maps
Structured output support vector machine (SVM) based tracking algorithms have
shown favorable performance recently. Nonetheless, the time-consuming candidate
sampling and complex optimization limit their real-time applications. In this
paper, we propose a novel large margin object tracking method which absorbs the
strong discriminative ability from structured output SVM and speeds up by the
correlation filter algorithm significantly. Secondly, a multimodal target
detection technique is proposed to improve the target localization precision
and prevent model drift introduced by similar objects or background noise.
Thirdly, we exploit the feedback from high-confidence tracking results to avoid
the model corruption problem. We implement two versions of the proposed tracker
with the representations from both conventional hand-crafted and deep
convolution neural networks (CNNs) based features to validate the strong
compatibility of the algorithm. The experimental results demonstrate that the
proposed tracker performs superiorly against several state-of-the-art
algorithms on the challenging benchmark sequences while runs at speed in excess
of 80 frames per second. The source code and experimental results will be made
publicly available
๋๋ฌผ๋ชจ๋ธ์ ์ด์ฉํ ์น์ฃผ์ผ ํ์ก/์น์์ฐ๊ตฌ์ก ์ง๋จ๋ง์ปค์ ๋ฐ๊ตด๊ณผ์ธ๊ท ์์ง ํน์์ ์ด์ฉํ ์น์ฃผ์ผ ๋๋ฌผ๋ชจ๋ธ
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ์น์ํ๋ํ์ ์น์๊ณผํ๊ณผ, 2021. 2. ์ต์๋.๋ฐฐ๊ฒฝ
์น์ฃผ ์งํ์ ์ฌ๋์ ๊ตฌ๊ฐ์์ ํํ๊ฒ ์์ฃผ ๋ฐ์ํ๋ ์งํ์ผ๋ก ์น์ ์กฐ์ง์๋ง ์ํฅ์ ๋ฏธ์น๋ ์น์์ผ๊ณผ ์น์ฃผ ์ธ๋, ์น์กฐ๊ณจ ๋ฐ ๋ฐฑ์
์ง์ ํฌํจํ๋ ๊น์ ์น์ฃผ ์กฐ์ง์ ์ํฅ์ ๋ฏธ์น๋ ์น์ฃผ์ผ์ ๋ ๊ฐ์ง ์ฃผ์
์ ํ์ ์ง๋ณ์ ํฌํจํ๋ค. ์น์ฃผ์ผ์ ๋ค์ธ์ฑ ์งํ์ด๋ผ๋ ์ฌ์ค์ด ์๋ ค์ ธ ์๋ค. ๊ทธ ์ค ์น์ ์ฐํ ์๋ฌผ๋ง์ ์ธ๊ท ๊ณผ ๊ทธ ๋์ฌ ์ฐ๋ฌผ์ ์น์ฃผ์ผ์ ๋ฐ์์ ํ์ ์ธ์์ด์ง๋ง ์ถฉ๋ถํ์ง๋ ์๋ค. ๋ถ๊ฐ์ ์ผ๋ก ์์ฃผ์ ๊ตญ์ ์๊ทน ์ธ์์ ์ ์ ์ธ์๊ฐ ์ธ๊ท ์ธ์์ ์๋ก ์ํฅ์ ์ฃผ๊ณ ๋ฐ์ผ๋ฉฐ ์์ฉํ๋ค. ์น์ฃผ์ผ์ ๋ฐ๋ณ ๊ธฐ์ ์ ๋ช
ํํ ํ๊ธฐ ์ํด์๋ ๋ค์ํ ์์ธ ๊ฐ์ ์ํธ์์ฉ์ ๋ํ ์ ๋ฐ์ ์ธ ์ดํด๊ฐ ํ์ํ๋ค. ์ด ๋
ผ๋ฌธ์ ์น์ฃผ์ผ์ ๋ฐ๋ณ ๊ธฐ์ ์์ ๋ณ์์ฑ ๋ฏธ์๋ฌผ์ ์ง์์ ์ธ ๊ฐ์ผ์ ์ญํ ๊ณผ ์น์ฃผ์ผ์ ์ง๋จํ๊ธฐ์ํ ํ์ก ๋ฐ ์น์์ด๊ตฌ์ก์ ๋ฐ์ด์ค๋ง์ปค ๋ถ์์ ์ด์ ์ ๋ง์ถ๊ณ ์๋ค.
๋ฐฉ๋ฒ
๋น๊ธ๊ฒฌ ๋ชจ๋ธ์์ ์ด 15 ๋ง๋ฆฌ์ ๋น๊ธ์ ๋์กฐ๊ตฐ(๊ฒฐ์ฐฐ ์์), ์ 1๊ตฐ(6 ๊ฐ ์น์์ ๊ฒฐ์ฐฐ) ๋ฐ ์ 2๊ตฐ(12 ๊ฐ ์น์์ ๊ฒฐ์ฐฐ)์ ์ธ๊ตฐ์ผ๋ก ๋๋์๋ค. ์คํ ๊ธฐ๊ฐ์ ์น์ฃผ์ผ ์ ๋ 8 ์ฃผ์ ์น๋ฃ 4 ์ฃผ๋ก ๊ตฌ์ฑ๋์๋ค. ์น์ฃผ์ผ์ ์์์ ํ๊ฐ์ ํ์ก ์ฑ์ทจ๋ 4 ์ฃผ๋ง๋ค ์ํํ์๋ค. ํ์ก ๋ฐ ์น์์ด๊ตฌ์ก ๋ด S100A8, S100A9, S100A8/A9 ๋ฐ ๋งคํธ๋ฆญ์ค ๋ฉํ๋กํ๋กํ
์์ (MMP)-9์ ์์ค์ ํจ์๊ฒฐํฉ๋ฉด์ญํก์ฐฉ๋ถ์์ผ๋ก ์ธก์ ํ์๋ค.
์ธ๊ท ๊ฐ์ ์์ง์ ์นจ๊ฐ ๋ถ์ ๋ฐ ๊ณต์ด์ ๋ ์ด์ ์ค์บ๋ ํ๋ฏธ๊ฒฝ์ผ๋ก ๋ถ์ํ์๋ค. ๊ณต์ด์ ๋ ์ด์ ์ค์บ๋ ํ๋ฏธ๊ฒฝ๊ณผ 3D ์ธํฌ ํ์๊ธฐ๋ฅผ ์ฌ์ฉํ์ฌ ์ธ๊ท ์ด ์์ฅ๊ตฌ๊ฐ์ํผ์ธํฌ IMOK (Murine Oral Keratinocyte) ์ ์นจ์
ํ๋ ๊ฒ์ ๊ด์ฐฐํ์๋ค.
์์ฅ๋ชจ๋ธ์ 6 ์ฃผ๋ น์ C57BL/6 ์์ปท ์์ฅ 80๋ง๋ฆฌ๋ฅผ ์ฌ์ฉํ์๋ค. ๋ชจ๋ ์์ฅ์ Streptococcus danieliae (Sd) 2 x 10 ^ 9 ์ธํฌ๋ฅผ 1ํ ๊ฒฝ๊ตฌํฌ์ฌ ํ 5๊ฐ ๊ทธ๋ฃน์ผ๋ก ๋๋์๋ค. ์ด์ด์ Fusobacterium. nucleatum Subsp. animalis KCOM 1280 (Fna), Porphyromonas. gingivalis 33277 (Pg33277), P. gingivalis KUMC-P4 (PgP4), ๋๋ PgP4 + Fna๋ฅผ 2% ์นด๋ฅด๋ณต์๋ฉํธ ์
๋ฃฐ๋ก์ค๋ฅผ ํจ์ ํ๋ 100 ฮผL PBS์ ์์ด 2 ์ผ ๊ฐ๊ฒฉ์ผ๋ก 6 ํ ๊ตฌ๊ฐ ํฌ์ฌํ์๋ค. ๋์กฐ๊ตฐ์ PBS๋ง์ผ๋ก 2% ์นด๋ฅด๋ณต์๋ฉํธ์
๋ฃฐ๋ก์ค์ค๋ฅผ ๋ฐ์๋ค. ์ฒซ ์ ์ข
ํ 5 ์ฃผ ๋๋ 8 ์ฃผ ํ์ ์์ฅ๋ฅผ ์๋ฝ์ฌ์ํค๊ณ ์กฐ์ง๊ณผ ํ์ฒญ์ ์ฑ์ทจํ์๋ค. ์์
์ ์น์กฐ๊ณจ ์์ค์ ์ปดํจํฐ ๋จ์ธต์ดฌ์์ผ๋ก ์ธก์ ํ์๊ณ , ํ์
๊ณจ์ ํค๋งํก์ค๋ฆฐ๊ณผ ์์ค์ ์ผ๋ก ์ผ์ํ๊ณ P. gingivalis-, F. nuleatum-, S. danieliae- ํน์ด์ ํ์นจ์๋ฅผ ์ฌ์ฉํ์ฌ in situ hybridization์ ์ํํ์๋ค. ์์ฅ ๊ตฌ๊ฐ์์ ์ป์ ์ธ๊ท ์ DNA๋ฅผ ์ด์ฉํ์ฌ, Sd, Fna, Pg์ ์์ qPCR๋ก ๋ถ์ ํ์๋ค. ํ์ก ๋ฐ ํ์ฒญ ๋ด ๋ฐํ
๋ฆฌ์์ ๋ํ IgG ๋ฐ IgA ํญ์ฒด์ ์์ค์ ํจ์๊ฒฐํฉ๋ฉด์ญํก์ฐฉ๋ถ์์ ์ฌ์ฉํ์ฌ ์ธก์ ํ์๋ค.
๊ฒฐ๊ณผ
๋น๊ธ๊ฒฌ ๋ชจ๋ธ์์ ์คํ๊ตฐ์ ๋ชจ๋ ๋๋ฌผ๊ณผ ๋์กฐ๊ตฐ์ ๋ ๋ง๋ฆฌ๊ฐ ์น์ฃผ์ผ์ ์ผ์ผ์ผฐ๊ณ ์ฑ๊ณต์ ์ผ๋ก ์น๋ฃ ๋์๋ค. ๋ณธ ์ฐ๊ตฌ์์ ์ํํ ๋ชจ๋ ํ์ก ๋ฐ์ด์ค๋ง์ปค(S100A8, S100A9, S100A8/A9, MMP-9)๋ ์ง๋จ ๋ฅ๋ ฅ์ด ๋์์ผ๋ฉฐ(c index โฅ 0.944) ๋จ์ผ ์น์์์ ์น์ฃผ์ผ์ด ๋ฐ์ํ ๋๋ฌผ๋ ์๋ณํ ์ ์์๋ค.
์ํํ ์น์ฃผ์ผ P.gingivalis ๊ท ์ฃผ ์ฉ ํ์์์ ๋ถ๋ฆฌ๋ ๊ท ์ฃผ PgP4๊ฐ Sd์ ๊ฐ์ฅ ๊ฐํ ๊ณต์คํฉ์ ๋ณด์๋ค. IMOK ์ธํฌ๋ก์ ๋ฐํ
๋ฆฌ์ ์นจ์
์ Sd์ ๋นํด PgP4, Pg33227 ๋ฐ Fna์ ์ํด ๋๊ฒ ๊ด์ฐฐ๋์๋ค. ์์ฅ๋ชจ๋ธ์์ ๋์กฐ์ค๊ณผ ๋น๊ตํด PgP4 ๊ทธ๋ฃน๊ณผ Fna + PgP4 ๊ทธ๋ฃน์ด ์ ์ํ๊ฒ ์ฆ๊ฐ๋ ์น์กฐ๊ณจ ์์ค์ ๋ณด์๋ค. Fna์ Pg๋ ๊ตฌ๊ฐํฌ์ฌ ํ 5์ฃผ์ฐจ๋ณด๋ค 8์ฃผ์ฐจ์ ์ฆ๊ฐํ ๊ฒ์ผ๋ก ๋ณด์ ์์ฅ ๊ฐ์ ์ฑ๊ณต์ ์ผ๋ก ์ง๋ฝํ์๊ณ ํฅ์ฒด ๋ฐ์์ ์ ๋ํ์๋ค. PgP4 ๊ทธ๋ฃน์ ์น์์กฐ์ง์ Pg๋ฟ ์๋๋ผ Sd์ ๋์ ์นจํฌ๋ฅผ ๋ณด์๋ค.
๊ฒฐ๋ก
ํ์ก S100A8, S100A9, S100A8/A9 ๋ฐ MMP-9๋ ๊ฐ์ ์น์ฃผ์ผ ์ง๋จ์ ์ฌ์ฉํ ์ ์์ง๋ง, ์ด๋ค์ ํ์ก ์์น์ ์ํฅ์ ๋ฏธ์น ์ ์๋ ๋ค๋ฅธ ์งํ์ ์ฃผ์ํด์ผ ํ๋ค.
P. gingivalis KUMC-P4๊ท ์ฃผ๋ ์์ฅ์ ๊ตฌ๊ฐ ์์ฃผ๊ท ์ธ S. danieliae์ ์์ง๋์ด IMOK ์ธํฌ๋ก ์นจํฌํ๋ ๋ฅ๋ ฅ์ด ๊ฐํด C57BL/6 ๋ง์ฐ์ค์์ ์๋นํ ์น์กฐ๊ณจ ํ๊ดด๋ฅผ ์ ๋ํ์๋ค.Background
Periodontal diseases are highly prevalent in the human oral cavity. There are two major types of periodontal diseases: gingivitis that only affects gingival tissue and periodontitis that affects deep periodontal tissues, composing of cementum, periodontal ligament, and alveolar bone. Periodontitis is a multifactorial disease. Among the involved factors, the bacteria and their metabolites of dental biofilms are the indispensable initiating factors for periodontitis, but it is not sufficient.
The occurrence of periodontitis is also affected by other factors, including local and systemic factors that positively or negatively interact with each other. To clarify the pathogenesis of periodontitis, it is necessary to grasp the interactions among various factors.
This paper focuses on the role of persistent infection of pathogenic microorganisms in the pathogenesis of periodontal disease, and the power of biomarkers in saliva and gingival crevicular fluid to screen periodontitis.
Methods
In a beagle dog model, a total of 15 beagles were divided into three groups: the control group (without ligature), the first group (ligature on 6 teeth) and the second group (ligature on 12 teeth). The experimental period was consisted of 8 weeks of periodontitis induction and 4 weeks of treatment. Clinical measurements and saliva sampling were performed every 4 weeks. The levels of S100A8, S100A9, S100A8/A9 and matrix metalloproteinase (MMP)-9 were measured using enzyme-linked immunosorbent assay (ELISA).
The coaggregation between clinical isolate bacteria was analyzed by a sedimentation assay and confocal laser scanning microscopy. The invasion of bacteria into Murine Oral Keratinocyte (IMOK) cells was observed using a confocal laser scanning microscop and a 3D cell explorer.
In a murine model, a total of 80 female six-week-old C57BL/6 mice were randomly divided into five groups (n=16 per group). 2 x 10^9 cells of murine oral commensal bacteria Streptococcus. danieliae DSM 26621 were gavaged before grouping. Mice were orally gavaged with total 2 x 10^9 cells of F. nucleatum Subsp. animalis KCOM 1280 (Fna), P. gingivalis ATCC 33277 (Pg33277), P. gingivalis KUMC-P4 (PgP4), or PgP4+Fna in 100 ยตL PBS plus 2% carboxymethyl cellulose every 2 days total six times. The sham group received 2% carboxymethyl cellulose in PBS alone. Mice were euthanized five or eight weeks after the first inoculation. Alveolar bone loss in the hemi-maxillae were measured by micro-CT. The mandibular molars were stained with hematoxylin and eosin and in situ hybridization using P. gingivalis-, F. nuleatum-, S. danieliae-specific probes. Using the genomic DNA of bacteria obtained from the oral cavity of mice, the copy numbers, Sd, Fna, and Pg were analyzed by qPCR. The levels of IgG and IgA antibodies against bacteria in saliva and sera were measured by ELISA.
Result
All dog animals in the experimental groups and the two control animals suffered from periodontitis and were successfully treated. All salivary biomarkers of periodontitis had high diagnostic ability (Area under curve, AUC index โฅ 0.944) and could identify animals with periodontitis on a single tooth. The saliva S100A8/A9 levels returned to healthy states, while the levels of S100A8, S100A9 and MMP-9 in periodontitis stability were still significantly higher than healthy levels.
The clinically isolated strain PgP4 showed the strongest coaggregation with S. danieliae. Increased bacterial invasion into IMOK cells were observed by PgP4, Pg33227, and Fna. The alveolar bone levels significantly decreased in the PgP4 group at both time points (weeks 5 and 8) and in the Fna+PgP4 group at week 8 compared with the Sham group. The bacteria invasion to gingival tissues were significantly increased in the PgP4 group.
Conclusion
Salivary S100A8, S100A9, S100A8/A9, and MMP-9 may be used for the screening of periodontitis in dogs, but with caution of other conditions that can affect their levels in saliva.
Porphyromonas gingivalis KUMC-P4, which had strong ability to coaggregate with the major murine oral flora S. danieliae and invade into IMOK cells, induced significant alveolar bone destruction in C57BL/6 mice.Chapter โ
. Background 1
1. Periodontal tissue and periodontitis 1
1.1. Periodontal tissue 1
1.2. Periodontitis: Definition, and epidemiology 3
2. Etiology of periodontitis 4
3. Pathophysiology 5
3.1. Bacterial communities in periodontitis 5
3.2. Immune response of periodontal host 9
3.3. Saliva and gingival crevicular fluid 12
4. Histopathology 13
5. Diagnosis and treatment 14
6. Salivary biomarker 16
7 Periodontitis animal models 17
Chapter โ
ก. Periodontitis: beagle dog model 19
1. Introduction 20
2. Aim of study 23
3. Methods and materials 24
4. Results 32
5. Discussion 48
Chapter III. Periodontitis: murine model 55
1. Introduction 56
2. Aim of study 61
3. Methods and materials 62
4. Results 81
5. Discussion 102
Chapter IV. Conclusion 106
Chapter V. References 107Docto
The Development of Chinese Feminism on Weibo
Developed from Western feminism(s), Chinese feminism is based on a belief in gender equality. This paper unwraps a brief history of the development of Chinese feminism through the aspects of Confucianism and communism, which reinforced patriarchy as the dominant ideology in the society. Under the influence of Confucianism, the traditional culture in China considers women as reproductive tools, and believes that men are superior to women. The patriarchy essentially undermines the development of Chinese feminism that has influenced not only the imbalanced gender distribution in modern society, but also peopleโs perspectives on Chinese feminism. However, compared to their predecessors, who passively accepted the patriarchy taught them by society, modern Chinese are more critical of patriarchy, and eager to challenge the traditional culture. Chinese feminism has made great progress toward gender equality, which can be shown through peopleโs perspectives on social media. This paper will select Weibo, one of the most popular social media platforms in China, and two case studies, focused on โleftover womenโ and rape culture, to further analyze how peopleโs views have changed in terms of Chinese feminism on Weibo
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