• 제목/요약/키워드: Distinct Weights

검색결과 46건 처리시간 0.026초

A Plasmid of Lactococcus lactis subsp. lactis ML8 Linked with Lactose Metabolism and Extracellular Proteinase

  • LEE, JONG-HOON;HYONG JOO LEE
    • Journal of Microbiology and Biotechnology
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    • 제6권6호
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    • pp.381-385
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    • 1996
  • Three distinct plasmids, with approximate molecular weights of 1, 4.5, and 33 megadaltons, were found in Lactococcus lactis subsp. lactis (L. lactis) ML8. Slow acid-producing mutants of L. lactis ML8, isolated by plasmid curing with acriflavine treatment, lacked the 33-megadalton plasmids. The plasmid-cured mutant showed lactose-negative (Lac) characteristics and the alteration of extracellular proteinase pattern. The possible involvement of extracellular proteinase with the 33-megadalton plasmid is highlighted in this research.

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카제인-알긴산 혼합물의 유화특성 (Emulsion Properties of Casein-Alginate Mixtures)

  • 황재관;최문정;김종태
    • 한국식품영양과학회지
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    • 제26권6호
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    • pp.1102-1108
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    • 1997
  • Proteins and polysaccharides confer distinct functional properties in food systems. This research was attempted to improve emulsion properties of casein by protein-polysaccharide conjugation, in which alginates with various molecular weights were employed as polysaccharide sources. Casein-alginate mixtures were conjugated by the amino-carbonyl or Maillard reaction at 6$0^{\circ}C$ and 79% relative humidity. The resulting casein-alginate conjugates were tested for their emulsion activity and emulsion stabilizing properties. In general, the emulsion stability of casein-alginate mixture greatly increased due to the amino-carbonyl reaction between casein and alginates, whose magnitude depended on the molecular weight of alginate, weight ratio of casein to alginate and incubation time. It was also found that thermal stability and pH stability were markedly improved by the casein-alginate conjugation.

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Phenotypic characterization of Hanwoo (native Korean cattle) cloned from somatic cells of a single adult

  • Yang, Byoung-Chul;Lee, Seung-Hwan;Hwang, Seong-Soo;Lee, Hwi-Cheul;Im, Gi-Sun;Kim, Dong-Hoon;Lee, Dong-Kyeong;Lee, Kyung-Tai;Jeon, Ik-Soo;Oh, Sung-Jong;Park, Soo-Bong
    • BMB Reports
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    • 제45권1호
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    • pp.38-43
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    • 2012
  • We investigated phenotypic differences in Hanwoo cattle cloned from somatic cells of a single adult. Ten genetically identical Hanwoo were generated by somatic cell nuclear transfer from a single adult. Weights at birth, growing pattern, horn and noseprint patterns were characterized to investigate phenotypic differences. The weights of clones at 6 and 12 months were slightly heavier than that of the donor. A horn pattern analysis revealed that seven clones had exactly the same horn pattern as the donor cow, whereas three were different. Although similarities such as general appearance can often be used to identify individual cloned animals, no study has characterized noseprint patterns for this end. A noseprint pattern analysis of all surviving clones showed that all eight animals had distinct noseprints. Four were similar to the donor, and the remaining four had more secondary-like characteristics.

전략적 중요도를 고려한 연관규칙의 발견: WARM (Association Rule Discovery Considering Strategic Importance: WARM)

  • 최덕원
    • 정보처리학회논문지D
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    • 제17D권4호
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    • pp.311-316
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    • 2010
  • 본 논문은 가중치를 고려한 연관규칙탐사 알고리즘(WARM)을 제시한다. 각 전략적 요소항목에 가중치를 부여하는 것과, 각 전략요소 항목별로 원시 자료값을 정규화하는 것이 이 논문에서 제시하는 알고리즘의 중요한 내용을 구성하고 있다. 본 논문은 TSAA 알고리즘을 확장 발전 시킨 연구로서 전략적 중요도를 반영하는 항목으로는 각 품목의 이익기여도, 마케팅 가치, 고객만족도 등을 사용하였다. 한 대형할인점의 실제 거래자료를 사용하여 알고리즘의 성능을 검사하였으며, Apriori, TSAA 및 WARM의 세 가지 알고리즘을 사용한 탐사결과를 비교 분석하였다. 분석의 결과 세 가지 알고리즘은 연관분석 행태에 있어서 각각 독특한 탐사행태를 보이는 것으로 나타났다.

앉은 자세와 선 자세에서의 인체 관절 동작의 지각 불편도 Ranking (Ranking of Perceived Joints Discomfort in Sitting and Standing Postures)

  • 신승헌;기도형;김형수
    • 대한산업공학회지
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    • 제23권4호
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    • pp.779-791
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    • 1997
  • The purpose of this study is to measure a perceived joint discomfort in the seated and standing position, and to provide ranking systems of perceived joint discomfort. Nineteen mole subjects with no history of musculo-skeletal disorders participated in the experiment. Their physical characteristics were: age $-25.4{\pm}2.7$years, stature $-171.9{\pm}6.0cm$, and body weight $-67.1{\pm}7.0kg$. The results showed that the perceived joint discomforts were different depending upon the joints involved in motion and their movement directions (degree of freedom of motions), which implied that the human body motions and their degrees of freedom should be classified into several distinct classes that need to be assigned different weights of postural stress. Therefore, three ranking systems based on the perceived joint discomforts were suggested, which were classified by the degree of freedom of motions and joints, by only degree of freedom motions, and by joints involved in motion, respectively. In the seated position, the hip movement was the most stressful, the bock was the second, and the shoulder was the third. Likewise, in the standing postures, the hip was the most, the bock was the second, and the ankle was the third. It was expected that these joint motion ranking systems could be used by practitioners of health and safety to improve the comfort of working postures in industry.

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Comparison of Two Meta-Analysis Methods: Inverse-Variance-Weighted Average and Weighted Sum of Z-Scores

  • Lee, Cue Hyunkyu;Cook, Seungho;Lee, Ji Sung;Han, Buhm
    • Genomics & Informatics
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    • 제14권4호
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    • pp.173-180
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    • 2016
  • The meta-analysis has become a widely used tool for many applications in bioinformatics, including genome-wide association studies. A commonly used approach for meta-analysis is the fixed effects model approach, for which there are two popular methods: the inverse variance-weighted average method and weighted sum of z-scores method. Although previous studies have shown that the two methods perform similarly, their characteristics and their relationship have not been thoroughly investigated. In this paper, we investigate the optimal characteristics of the two methods and show the connection between the two methods. We demonstrate that the each method is optimized for a unique goal, which gives us insight into the optimal weights for the weighted sum of z-scores method. We examine the connection between the two methods both analytically and empirically and show that their resulting statistics become equivalent under certain assumptions. Finally, we apply both methods to the Wellcome Trust Case Control Consortium data and demonstrate that the two methods can give distinct results in certain study designs.

사람 재인식을 위한 개선된 PersonNet (Advanced PersonNet for Person Re-Identification)

  • 박성현;강석훈
    • 전기전자학회논문지
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    • 제23권4호
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    • pp.1166-1174
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    • 2019
  • 이 논문에서는 사람 재식별 모델인 PersonNet의 성능을 개선하는 방법을 제안하고 실험한다. 특징점 추출을 위해 인셉션 레이어를 접목하여, 기존 32개의 특징점을 154개로 증가시켜 강화하였다. 또한, PersonNet에서 사용하는 CND 방식을 수정하여 비대칭성을 완화하였고, 보행자 이미지의 특징점을 3부분으로 나누어 가중치를 적용한 방법을 적용하여 특징을 더 뚜렷하게 파악하도록 하였다. 성능 평가를 위해 CUHK01, CUHK03 그리고 Market-1501 3가지의 데이터베이스를 사용하였고 실험 결과 27~31% 성능이 개선되었다.

Purification and Characterization of Phytoferritin

  • Oh, Suk-Heung;Cho, Sung-Woo;Kwon, Tae-Ho;Yang, Moon-Sik
    • BMB Reports
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    • 제29권6호
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    • pp.540-544
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    • 1996
  • Ferritins from germinated pumpkin seeds were isolated by ammonium sulfate precipitation (0.55 saturation), ion-exchange chromatography on DEAE-cellulose, and gel filtration chromatographies on Sephacryl S-300 and Sephadex G-100. Pumpkin ferritin contains less iron than soybean ferritin. Pumpkin ferritin cross-reacted with anti-soybean ferritin antiserum made in rabbit, and showed two distinct antibody reactive bands, both of equal intensity. The pumpkin ferritins corresponding to the two bands were separable by centrifugation in a sucrose gradient (20~50%). The molecular weights of the native pumpkin ferritins based on the estimation of sucrose gradient centrifugation, gel filtration on Sephacryl S-300 and non-denaturing polyacrylamide gel electrophoresis appeared to be: 530~580 KD (the large molecular weight pumpkin ferritin) and 330-360 KD (the small molecular weight pumpkin ferritin) The large molecular weight pumpkin ferritin contains less iron. Both pumpkin ferritins cross-reacted with anti-soybean ferritin antibody with a spur formation suggesting partial antigenic recognition.

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Irreversible Thermoinactivation Mechanisms of Subtilisin Carlsberg

  • Dong Uk Kim
    • Bulletin of the Korean Chemical Society
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    • 제10권6호
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    • pp.600-604
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    • 1989
  • In order to find the rational methods for improving the thermal stability of subtilisin Carlsberg, the mechanisms of irreversible thermoinactivation of the enzyme were studied at $90^{\circ}C.$ At pH 4, the main process was hydrolysis of peptide bond. This process followed first order kinetics, yielding a rate constant of $1.26\;{\times}\;10^{-1}h^{-1}$. Hydrolysis of peptide bond of PMS-subtilisin occurred at various sites, which produced new distinct fragments of molecular weights of 27.2 KD, 25.9 KD, 25.0 KD, 22.3 KD, 19.0 KD, 17.6 KD, 16.5 KD, 15.7 KD, 15.0 KD, 13.7 KD, and 12.7 KD. Most of the new fragments originated from the acidic hydrolysis at the C-side of aspartic acid residues. However 25.0 KD, 15.7 KD, and 13.7 KD which could not be removed in purification steps stemmed from the autolytic cleavage of subtilisin. The minor process at pH 4 was deamidation at asparagine and/or glutamine residues and some extend of aggregation was also observed. However, the aggregation was main process at pH 7 with a first order kinetic constant of $16 h^{-1}.$ At pH 9, the main process seemed to be combination of deamidation and cleavage of peptide bond.

A Computer-Aided Diagnosis of Brain Tumors Using a Fine-Tuned YOLO-based Model with Transfer Learning

  • Montalbo, Francis Jesmar P.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권12호
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    • pp.4816-4834
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    • 2020
  • This paper proposes transfer learning and fine-tuning techniques for a deep learning model to detect three distinct brain tumors from Magnetic Resonance Imaging (MRI) scans. In this work, the recent YOLOv4 model trained using a collection of 3064 T1-weighted Contrast-Enhanced (CE)-MRI scans that were pre-processed and labeled for the task. This work trained with the partial 29-layer YOLOv4-Tiny and fine-tuned to work optimally and run efficiently in most platforms with reliable performance. With the help of transfer learning, the model had initial leverage to train faster with pre-trained weights from the COCO dataset, generating a robust set of features required for brain tumor detection. The results yielded the highest mean average precision of 93.14%, a 90.34% precision, 88.58% recall, and 89.45% F1-Score outperforming other previous versions of the YOLO detection models and other studies that used bounding box detections for the same task like Faster R-CNN. As concluded, the YOLOv4-Tiny can work efficiently to detect brain tumors automatically at a rapid phase with the help of proper fine-tuning and transfer learning. This work contributes mainly to assist medical experts in the diagnostic process of brain tumors.