Effects of Lysine Intake during Middle to Late Gestation (Day 30 to 110) on Reproductive Performance, Colostrum Composition, Blood Metabolites and Hormones of Multiparous Sows

Zhang, R.F.,Hu, Q.,Li, P.F.,Xue, L.F.,Piao, X.S.,Li, D.F. Asian Australasian Association of Animal Productio 2011 Animal Bioscience Vol.24 No.8

Lysine intake during gestation has a major impact on subsequent reproductive performance. The objective of this experiment was to determine the effect of lysine intake from mid-gestation until farrowing on the reproductive performance of multiparous sows. On day 30 of gestation, 200 Landrace${\times}$Large White sows were randomly assigned to one of four groups based on body weight and parity (n = 50). The gestation diets contained 0.46, 0.56, 0.65 or 0.74% lysine. Increasing dietary lysine concentration improved sow body condition at farrowing and increased litter weights (p<0.05). Dietary lysine level also had a significant effect on the dry matter (p<0.05) and protein content (p<0.05) of colostrum. Increased lysine intake increased serum insulin concentration (p<0.05) and there was a trend towards increased serum prolactin content (linear, p = 0.07). However, increased lysine tended to decrease blood urea N (quadratic, p = 0.05). These results suggest that higher lysine levels (0.65-0.75%) than those recommended by the National Research Council improved reproductive performance for multiparous gestating sows and this increase may be partially mediated through blood metabolites or metabolic hormone levels.

SRBCTs Subtype Classification Based on Bhattacharyya Distance Gene Selection

Xue-Wei Tian,Zhen-Xing Zhang,Sang-Hong Lee,Jae-Woong Kim,Joon S. Lim 한국콘텐츠학회 2012 ICCC International Digital Design Invitation Exhib Vol.2012 No.12

SRBCTs Subtype Classification Based on Bhattacharyya Distance Gene Selection

Xue-Wei Tian,Zhen-Xing Zhang,Sang-Hong Lee,Jae-Woong Kim,Joon S. Lim 한국콘텐츠학회 2012 한국콘텐츠학회 종합학술대회 논문집 Vol.2012 No.12

Effects of Twisting Parameters on Characteristics of Rotor-Spun Composite Yarns with Spandex

Zhang H.X.,Xue Y.,Wang S.Y. The Korean Fiber Society 2006 Fibers and polymers Vol.7 No.1

Spandex fibers have superior stretch and elastic recovery ability. Composite yarns containing spandex are frequently used to manufacture elastic textile products and accessories. We have developed a composite yarn spinning system that produces different kinds of composite yarns containing spandex on a modified open-end rotor spinning frame. By changing the twisting parameter of composite yarns, we studied the structure and properties of rotor-spun composite yarns with spandex. The results indicate that the twisting parameter has great influence on the structure and properties of rotor-spun composite yarns with spandex. The linear density of spandex filament has influence on the properties of composite yarns too. In comparison with normal rotor-spun yarn, the appearance of composite yarns is clearer, the structure is much tighter, and the properties are improved.

Comparison of HRV Time and Frequency Domain Features for Myocardial Ischemia Detection

전설위(Xue-Wei Tian),장진흥(Zhen-Xing Zhang),이상홍(Sang-Hong Lee),임준식(Joon S. Lim) 한국콘텐츠학회 2011 한국콘텐츠학회논문지 Vol.11 No.3

심박 변이도 (HRV) 분석은 심근허혈 (MI)를 평가하기 위한 편리한 도구이다. HRV에 대한 분석법은 시간 영역과 주파수 영역 분석으로 나눠질 수 있다. 본 논문은 단기간의 HRV 분석에 있어서 웨이블릿 변환을 주파수 영역 분석과 시간 영역 분석 비교하기 위하여 사용하였다. ST-T와 정상 에피소드는 각각 European ST-T 데이터베이스와 MIT-BIH Normal Sinus Rhythm 데이터베이스에서 각각 수집되었다. 한 에피소드는 32개 연속하는 RR 간격으로 나눠질 수 있다. 18개 HRV 특징은 시간과 주파수 영역 분석을 통하여 추출된다. 가종 퍼지소속함수 신경망 (NEWFM)은 추출된 18개의 특징을 이용하여 심근허혈을 진단하였다. 결과는 보여주는 평균 정확도로부터 시간영역과 주파수영역의 특징은 각각 75.29%와 80.93%이다. Heart Rate Variability (HRV) analysis is a convenient tool to assess Myocardial Ischemia (MI). The analysis methods of HRV can be divided into time domain and frequency domain analysis. This paper uses wavelet transform as frequency domain analysis in contrast to time domain analysis in short term HRV analysis. ST-T and normal episodes are collected from the European ST-T database and the MIT-BIH Normal Sinus Rhythm database, respectively. An episode can be divided into several segments, each of which is formed by 32 successive RR intervals. Eighteen HRV features are extracted from each segment by the time and frequency domain analysis. To diagnose MI, the Neural Network with Weighted Fuzzy Membership functions (NEWFM) is used with the extracted 18 features. The results show that the average accuracy from time and frequency domain features is 75.29% and 80.93%, respectively.

Multi-stage approach for structural damage identification using particle swarm optimization

Tang, H.,Zhang, W.,Xie, L.,Xue, S. Techno-Press 2013 Smart Structures and Systems, An International Jou Vol.11 No.1

An efficient methodology using static test data and changes in natural frequencies is proposed to identify the damages in structural systems. The methodology consists of two main stages. In the first stage, the Damage Signal Match (DSM) technique is employed to quickly identify the most potentially damaged elements so as to reduce the number of the solution space (solution parameters). In the second stage, a particle swarm optimization (PSO) approach is presented to accurately determine the actual damage extents using the first stage results. One numerical case study by using a planar truss and one experimental case study by using a full-scale steel truss structure are used to verify the proposed hybrid method. The identification results show that the proposed methodology can identify the location and severity of damage with a reasonable level of accuracy, even when practical considerations limit the number of measurements to only a few for a complex structure.

Taxonomy of fungal complex causing red-skin root of Panax ginseng in China

Lu, Xiao H.,Zhang, Xi M.,Jiao, Xiao L.,Hao, Jianjun J.,Zhang, Xue S.,Luo, Yi,Gao, Wei W. The Korean Society of Ginseng 2020 Journal of Ginseng Research Vol.44 No.3

Background: Red-skin root of Asian ginseng (Panax ginseng) significantly reduces the quality and limits the production of ginseng in China. The disease has long been thought to be a noninfectious physiological disease, except one report that proved it was an infectious disease. However, the causal agents have not been successfully determined. In the present study, we were to reveal the pathogens that cause red-skin disease. Methods: Ginseng roots with red-skin root symptoms were collected from commercial fields in Northeast China. Fungi were isolated from the lesion and identified based on morphological characters along with multilocus sequence analyses on internal transcription spacer, β-tubulin (tub2), histone H3 (his3), and translation elongation factor 1α (tef-1α). Pathogens were confirmed by inoculating the isolates in ginseng roots. Results: A total of 230 isolates were obtained from 209 disease samples. These isolates were classified into 12 species, including Dactylonectria sp., D. hordeicola, Fusarium acuminatum, F. avenaceum, F. solani, F. torulosum, Ilyonectria mors-panacis, I. robusta, Rhexocercosporidium panacis, and three novel species I. changbaiensis, I. communis, and I. qitaiheensis. Among them, I. communis, I. robusta, and F. solani had the highest isolation frequencies, being 36.1%, 20.9%, and 23.9%, respectively. All these species isolated were pathogenic to ginseng roots and caused red-skin root disease under appropriate condition. Conclusion: Fungal complex is the causal agent of red-skin root in P. ginseng.

Multi-stage approach for structural damage identification using particle swarm optimization

H. Tang,W. Zhang,L. Xie,S. Xue 국제구조공학회 2013 Smart Structures and Systems, An International Jou Vol.11 No.1

An efficient methodology using static test data and changes in natural frequencies is proposed to identify the damages in structural systems. The methodology consists of two main stages. In the first stage, the Damage Signal Match (DSM) technique is employed to quickly identify the most potentially damaged elements so as to reduce the number of the solution space (solution parameters). In the second stage, a particle swarm optimization (PSO) approach is presented to accurately determine the actual damage extents using the first stage results. One numerical case study by using a planar truss and one experimental case study by using a full-scale steel truss structure are used to verify the proposed hybrid method. The identification results show that the proposed methodology can identify the location and severity of damage with a reasonable level of accuracy, even when practical considerations limit the number of measurements to only a few for a complex structure.

Neuro-Fuzzy Network-based Depression Diagnosis Algorithm Using Optimal Features of HRV

장진흥(Zhen-Xing Zhang),전설위(Xue-Wei Tian),임준식(Joon S. Lim) 한국콘텐츠학회 2012 한국콘텐츠학회논문지 Vol.12 No.2

본 논문은 가중 퍼지소속함수 기반 신경망 (Neural Network with Weighted Fuzzy Membership functions, NEWFM)과 심박수 변이도(Heart Rate Variability, HRV)를 이용하여 우울증 진단알고리즘을 제안하고 있다. 본 알고리즘에서 사용할 NEWFM의 입력특징을 추출하기 위해서 주파수도메인 특징추출, 시간도메인 특징추출, 웨이블릿변환 특징추출, 포인케어변환 특징추출 방법을 이용하여 22개의 초기 HRV특징들을 추출하였다. 또한 NEWFM에서 제공하는 비중복면적 분산측정법 (Non-overlap Area Distribution Measurement, NADM)에 의해 입력특징의 중요도를 평가하여 22개의 초기특징으로부터 중요도가 가장 높은 6개 최적입력특징을 선택하였다. 이 6개 특징을 이용하여 우울증을 진단한 결과는 95.8%의 정확도를 나타내었다. This paper presents an algorithm for depression diagnosis using the Neural Network with Weighted Fuzzy Membership functions (NEWFM) and heart rate variability (HRV). In the algorithm, 22 different features were initially extracted from the HRV signal by frequency domain, time domain, wavelet transformed, and Poincare transformed feature extraction methods; of these 6 optimal features were selected by significance evaluation using Non-overlap Area Distribution Measurement (NADM) based on NEWFM. The proposed algorithm uses these 6 optimal features to diagnose depression with an accuracy of 95.83%.

Effects of Fermented Potato Pulp on Performance, Nutrient Digestibility, Carcass Traits and Plasma Parameters of Growing-finishing Pigs

Li, P.F.,Xue, L.F.,Zhang, R.F.,Piao, Xiangshu,Zeng, Z.K.,Zhan, J.S. Asian Australasian Association of Animal Productio 2011 Animal Bioscience Vol.24 No.10

A total of 629 Duroc${\times}$Landrace${\times}$Large White crossbred pigs were utilized in three experiments (Exp. 1, 222 pigs weighing $25.6{\pm}2.0\;kg$ BW; Exp. 2, 216 pigs weighing 5$6.2{\pm}4.3\;kg$ BW; Exp. 3, 191 pigs weighing $86.4{\pm}4.6\;kg$ BW) conducted to determine the effects of fermented potato pulp on performance, nutrient digestibility, carcass traits and plasma parameters in growingfinishing pigs. Each experiment lasted 28 d. The pigs were assigned to one of two corn-soybean meal-based diets containing 0 or 5% fermented potato pulp. The inclusion of fermented potato pulp increased weight gain (p<0.05) in experiments 1 and 2 and increased feed intake (p<0.05) in experiment 2. Feed conversion was improved (p<0.05) in experiment 2 and showed a tendency to improve (p<0.10) in experiments 1 and 3 when pigs were fed fermented potato pulp. Fermented potato pulp increased (p<0.05) dry matter digestibility in experiments 1 and 3 and energy digestibility in experiment 2. Feeding fermented potato pulp decreased plasma urea nitrogen (p<0.05) and alanine aminotransferase (p<0.05) in experiments 1 and 2, while plasma aspartate aminotransferase was decreased (p<0.05) in experiment 3. Dietary fermented potato pulp did not affect the carcass characteristics of finishing pigs. Feeding fermented potato pulp reduced (p<0.05) fecal ammonia concentration in all three experiments. In conclusion, feeding growing-finishing pigs diets containing 5% fermented potato pulp improved weight gain and feed conversion without any detrimental effects on carcass traits. The improvements in pig performance appeared to be mediated by improvements in nutrient digestibility.