Objective: According to market demand, meat duck breeding mainly includes 2 breeding directions: lean Pekin duck (LPD) and fat Pekin duck (FPD). The aim of the present study was to compare carcass and meat quality traits between 2 strains, and to provide basic data for guidelines of processing and meat quality improvement. Methods: A total of 62 female Pekin ducks (32 LPDs and 30 FPDs) were slaughtered at the age of 42 days. The live body weight and carcass traits were measured and calculated. Physical properties of breast muscle were determined by texture analyzer and muscle fibers were measured by paraffin sections. The content of inosine monophosphate (IMP), intramuscular fat (IMF) and fatty acids composition were measured by high-performance liquid chromatography, Soxhlet extraction method and automated gas chromatography respectively. Results: The results showed that the bodyweight of LPDs was higher than that of FPDs. FPDs were significantly higher than LPDs in subcutaneous fat thickness, subcutaneous fat weight, subcutaneous fat percentage, abdominal fat percentage and abdominal fat shear force (p<0.01). LPDs were significantly higher than FPDs in breast muscle thickness, breast muscle weight, breast muscle rate and breast muscle shear force (p<0.01). The muscle fiber average area and fiber diameter of LPDs were significantly higher than those of FPDs (p<0.01). The muscle fiber density of LPDs was significantly lower than that of FPDs (p<0.01). The IMF of LPDs in the breast muscle was significantly higher than that in the FPDs (p<0.01). There was no significant difference between the 2 strains in IMP content (p>0.05). The polyunsaturated fatty acid content of LPDs was significantly higher than that of FPDs (p<0.01), and FPDs had higher saturated fatty acid and monounsaturated fatty acid levels (p<0.05). Conclusion: Long-term breeding work resulted in vast differences between the two strains Pekin ducks. This study provides a reference for differences between LPD and FPD that manifest as a result of long-term selection.
Objective: The intestinal microbiota plays an important role in host physiology, metabolism, immunity, and behavior. And host genetics could influence the gut microbiota of hybrid animals. The three-way cross model is commonly utilized in commercial pig production; however, the use of this model to analyse the gut microbial composition is rarely reported. Methods: Two three-way hybrid pigs were selected, with Saba pigs as the starting maternal pig: Duroc× (Berkshire×Saba) (DBS) pig, Berkshire×(Duroc×Saba) (BDS) pig. One hundred pigs of each model were reared from 35 days (d) to 210 d. The body weight or feed consumption of all pigs were recorded and their feed/gain (F/G) ratio was calculated. On day 210, 10 pigs from each three-way cross were selected for slaughter, and cecal chyme samples were collected for 16S rRNA gene sequencing. Results: The final body weight (FBW) and average daily gain (ADG) of DBS pigs were significantly higher than those of BDS pigs (p<0.05), while the F/G ratios of DBS pigs were significantly lower than those of BDS pigs (p<0.05). The dominant phyla in DBS and BDS pigs were Bacteroidetes (55.23% vs 59%, respectively) and Firmicutes (36.65% vs 34.86%, respectively) (p>0.05). At the genus level, the abundance of Prevotella, Roseburia, and Anaerovibrio in DBS pigs was significantly lower than in BDS pigs (p<0.01). The abundance of Eubacterium, Clostridium XI, Bacteroides, Methanomassiliicoccus, and Parabacteroides in DBS pigs was significantly higher than in BDS pigs (p<0.05). The FBWs and ADGs were positively correlated with Bacteroides, ClostridiumXI, and Parabacteroides but negatively correlated with the Prevotella, Prevotella/Bacteroides (P/B) ratio, Roseburia, and Anaerovibrio. Conclusion: These results indicated that host genetics affect the cecal microbiota composition and the porcine gut microbiota is associated with growth performance, thereby suggesting that gut microbiota composition may be a useful biomarker in porcine genetics and breeding.
Canever, Jaquelini Betta;Barbosa, Rafael Inacio;Hendler, Ketlyn Germann;Neves, Lais Mara Siqueira das;Kuriki, Heloyse Uliam;Aguiar, Aderbal Silva Junior;Fonseca, Marisa de Cassia Registro;Marcolino, Alexandre Marcio
The Korean Journal of Pain
/
v.34
no.3
/
pp.250-261
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2021
Background: Complex regional pain syndrome type I (CRPS-I) consists of disorders caused by spontaneous pain or induced by some stimulus. The objective was to verify the effects of photobiomodulation (PBM) using 830 nm wavelength light at the affected paw and involved spinal cord segments during the warm or acute phase. Methods: Fifty-six mice were randomized into seven groups. Group (G) 1 was the placebo group; G2 and G3 were treated with PBM on the paw in the warm and acute phase, respectively; G4 and G5 treated with PBM on involved spinal cord segments in the warm and acute phase, respectively; G6 and G7 treated with PBM on paw and involved spinal cord segments in the warm and acute phase, respectively. Edema degree, thermal and mechanical hyperalgesia, skin temperature, and functional quality of gait (Sciatic Static Index [SSI] and Sciatic Functional Index [SFI]) were evaluated. Results: Edema was lower in G3 and G7, and these were the only groups to return to baseline values at the end of treatment. For thermal hyperalgesia only G3 and G5 returned to baseline values. Regarding mechanical hyperalgesia, the groups did not show significant differences. Thermography showed increased temperature in all groups on the seventh day. In SSI and SFI assessment, G3 and G7 showed lower values when compared to G1, respectively. Conclusions: PBM irradiation in the acute phase and in the affected paw showed better results in reducing edema, thermal and mechanical hyperalgesia, and in improving gait quality, demonstrating efficacy in treatment of CRPS-I symptoms.
Objective: The present study was conducted to investigate the effects of lycopene on growth performance, abdominal fat deposition, serum lipids levels, activities of hepatic lipid metabolism related enzymes and genes expression in broiler chickens. Methods: A total of 256 healthy one-day-old male Arbor Acres broiler chicks were randomly divided into four groups with eight replicates of eight birds each. Birds were fed basal diet supplemented with 0 (control), 100, 200, and 400 mg/kg lycopene, respectively. Results: Dietary 100 mg/kg lycopene increased the body weight at 21 day of age compared to the control group (p<0.05). Compared to the basal diet, broilers fed diet with 100 mg/kg lycopene had decreased abdominal fat weight, and broilers fed diet with 100 and 200 mg/kg lycopene had decreased abdominal fat percentage (p<0.05). Compared to control, diets with 100, 200, and 400 mg/kg lycopene reduced the levels of total triglyceride and total cholesterol in serum, and diets with 100 and 200 mg/kg lycopene reduced the level of serum low density lipoprotein cholesterol (p<0.05). The activity of fatty acid synthase (FAS) in 400 mg/kg lycopene treated broilers and the activity of acetyl-CoA carboxylase (ACC) in 100, 200, and 400 mg/kg lycopene treated broilers were lower than those fed basal diet (p<0.05). Lycopene increased the mRNA abundance of adenosine monophosphate activated protein kinase α (AMPK-α), whereas decreased the mRNA abundance of sterol regulatory element-binding protein 1, FAS, and ACC compared to the control group (p<0.05). Conclusion: Dietary lycopene supplementation can alleviate abdominal fat deposition and decrease serum lipids levels, possibly through activating the AMPK signaling pathway, thereby regulating lipid metabolism such as lipogenesis. Therefore, lycopene or lycopene-rich plant materials might be added to poultry feed to regulate lipid metabolism.
KSCE Journal of Civil and Environmental Engineering Research
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v.40
no.6
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pp.613-622
/
2020
The South Korean government plans for a 37 % reduction in CO2 emissions against business as usual by 2030. Subsequently, the Ministry of Land, Infrastructure and Transport declared a 26.9 % reduction target in greenhouse gas emissions from buildings by 2020 and established the Green Standard for Energy and Environmental Design (G-SEED) to help improve the environmental performance of buildings. Construction companies often work with consulting firms to prepare for G-SEED certification. In the process, owing to inefficient data sharing and work connections, it is difficult to achieve economic efficiency and obtain certification. The objective of this study was to develop an economic model to assist contractors in achieving the required G-SEED scores for materials and resources. To do this, we automated the process for material comparison and selection on the basis of an analysis of actual consulting data, and developed a model that selects material alternatives that can meet the required scores at a minimum cost. Information on materials is input by applying a genetic algorithm to the optimization of alternatives. When the model was applied to actual data, the construction cost could be lowered by 79.3 % compared with existing methods. The economical material selection model is expected to not only reduce construction costs for owners desiring G-SEED certification but also shorten the project design time.
Objective : The purpose of this study was to examine the roles and practices of occupational therapists in public health centers based on their working experience of occupational therapists who are working in these facilities. Methods : We used Giorgi's descriptive phenomenological research method. Six occupational therapists were interviewed, and their recorded data were analyzed using Claizzi's thematic analysis. Results : As a result, 4 categories, 16 themes, and 24 elements were elicited. The major roles of occupational therapists in public health centers were the evaluation of clients, home-visit occupational therapy, management of dementia programs and community connection projects. Interventions that are needed to create a healthy community include case and program management, compensatory approaches, and healthy lifestyle interventions. The difficulties experienced by occupational therapists include their limited number job insecurity, performance-oriented administrative policy, and the lack of communication among professionals. Occupational therapists require education in health management and practice in public health centers to build their capacities. Conclusion : The results of this study could be used for guidelines for occupational therapists who work in community healthcare centers, as well as basic training for competent occupational therapists in the community.
Journal of Korea Society of Industrial Information Systems
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v.25
no.6
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pp.33-45
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2020
This paper aims to look at the perspective that the latest cutting-edge technologies are predicting individual diseases in the actual medical environment in a situation where various types of wearable devices are rapidly increasing and used in the healthcare domain. Through the process of collecting, processing, and transmitting data by merging clinical data, genetic data, and life log data through a user-participating wearable device, it presents the process of connecting the learning model and the feedback model in the environment of the Deep Neural Network. In the case of the actual field that has undergone clinical trial procedures of medical IT occurring in such a high-tech medical field, the effect of a specific gene caused by metabolic syndrome on the disease is measured, and clinical information and life log data are merged to process different heterogeneous data. That is, it proves the objective suitability and certainty of the deep neural network of heterogeneous data, and through this, the performance evaluation according to the noise in the actual deep learning environment is performed. In the case of the automatic encoder, we proved that the accuracy and predicted value varying per 1,000 EPOCH are linearly changed several times with the increasing value of the variable.
In this paper, spatially-adaptive denormalization (SPADE) based U-Net is proposed to detect changes by using high-resolution satellite images. The proposed network is to preserve spatial information using SPADE. Change detection methods using high-resolution satellite images can be used to resolve various urban problems such as city planning and forecasting. For using pixel-based change detection, which is a conventional method such as Iteratively Reweighted-Multivariate Alteration Detection (IR-MAD), unchanged areas will be detected as changing areas because changes in pixels are sensitive to the state of the environment such as seasonal changes between images. Therefore, in this paper, to precisely detect the changes of the objects that consist of the city in time-series satellite images, the semantic spatial objects that consist of the city are defined, extracted through deep learning based image segmentation, and then analyzed the changes between areas to carry out change detection. The semantic objects for analyzing changes were defined as six classes: building, road, farmland, vinyl house, forest area, and waterside area. Each network model learned with KOMPSAT-3A satellite images performs a change detection for the time-series KOMPSAT-3 satellite images. For objective assessments for change detection, we use F1-score, kappa. We found that the proposed method gives a better performance compared to U-Net and UNet++ by achieving an average F1-score of 0.77, kappa of 77.29.
Objective : The purpose of this study was to analyze the effects of simultaneous dual-task training to assess executive function in older adults. Methods : We searched the PubMed, EMBASE, Cochrane, Web of Science, and RISS databases of publicated studies in the past decade. Seven studies were selected based on the inclusion and exclusion criteria. Qualitative assessment and meta-analysis were performed for the seven studies. Results : A randomized controlled trial design was used in the selected studies, and PEDro Scores above seven were obtained. The Trial Making Test (TMT) evaluated the effects of dual-task training on executive function in four studies. The Color Trail Test (CTT) was used in two studies, and Stroop test was used in three studies. The effect size for total executive function was 0.38, which was small. The effect sizes for TMT and CTT were 0.37. Stroop Test was 0.34, demonstrating that their effect sizes were also small. Only significant effects in total executive function, TMT, and CTT showed significant effects (all p<0.05). Conclusion : This study confirmed that dual-task training was effective in improving executive function in older adults. To improve the effectiveness of dual-task training, the difficulty of the dual-task training should be considered. It is also necessary to implement assessments that can evaluate performance under dual-task conditions as well as conventional test tools for executive function. In the future, dual-task training could be used as an appropriate intervention for executive function in older adults to delay the onset of dementia.
Yim, Sunjin;Kim, Sungchul;Kim, Inhwan;Park, Jae-Woo;Cho, Jin-Hyoung;Hong, Mihee;Kang, Kyung-Hwa;Kim, Minji;Kim, Su-Jung;Kim, Yoon-Ji;Kim, Young Ho;Lim, Sung-Hoon;Sung, Sang Jin;Kim, Namkug;Baek, Seung-Hak
The korean journal of orthodontics
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v.52
no.1
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pp.3-19
/
2022
Objective: The purpose of this study was to investigate the accuracy of one-step automated orthodontic diagnosis of skeletodental discrepancies using a convolutional neural network (CNN) and lateral cephalogram images with different qualities from nationwide multi-hospitals. Methods: Among 2,174 lateral cephalograms, 1,993 cephalograms from two hospitals were used for training and internal test sets and 181 cephalograms from eight other hospitals were used for an external test set. They were divided into three classification groups according to anteroposterior skeletal discrepancies (Class I, II, and III), vertical skeletal discrepancies (normodivergent, hypodivergent, and hyperdivergent patterns), and vertical dental discrepancies (normal overbite, deep bite, and open bite) as a gold standard. Pre-trained DenseNet-169 was used as a CNN classifier model. Diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis, t-stochastic neighbor embedding (t-SNE), and gradient-weighted class activation mapping (Grad-CAM). Results: In the ROC analysis, the mean area under the curve and the mean accuracy of all classifications were high with both internal and external test sets (all, > 0.89 and > 0.80). In the t-SNE analysis, our model succeeded in creating good separation between three classification groups. Grad-CAM figures showed differences in the location and size of the focus areas between three classification groups in each diagnosis. Conclusions: Since the accuracy of our model was validated with both internal and external test sets, it shows the possible usefulness of a one-step automated orthodontic diagnosis tool using a CNN model. However, it still needs technical improvement in terms of classifying vertical dental discrepancies.
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