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Lipase Supplementation before a High-Fat Meal Reduces Perceptions of Fullness in Healthy Subjects
( Max E Levine ),( Sara Yanchis Koch ),( Kenneth L Koch ) 대한소화기학회 2015 Gut and Liver Vol.9 No.4
Background/Aims: Postprandial symptoms of fullness and abdominal discomfort are common after fatty meals. Gastric lipases hydrolyze 10% to 20% of dietary triglycerides during the stomach trituration period of digestion. The aim of this study was to evaluate the effects of acid-resistant lipase on upper gastrointestinal symptoms, including fullness and bloating, as well as on gastric myoelectrical activity after healthy subjects ingested a high-fat, liquid meal. Methods: This study utilized a double-blind, placebo-controlled, crossover design with 16 healthy volunteers who ingested either a capsule containing 280 mg of acid-resistant lipase or a placebo immediately before a fatty meal (355 calories, 55% fat). Participants rated their stomach fullness, bloating, and nausea before and at timed intervals for 60 minutes after the meal. Electrogastrograms were obtained to assess the gastric myoelectrical activity. Results: Stomach fullness, bloating, and nausea increased significantly 10 minutes after ingestion of the fatty meal (p<0.01), whereas normal gastric myoelectrical activity decreased and tachygastria increased (p<0.05). With lipase, reports of stomach fullness were significantly lower compared with placebo (p<0.05), but no effect on gastric myoelectrical activity or other upper gastrointestinal symptoms was observed. Conclusions: The high-fat meal induced transient fullness, bloating, nausea, and tachygastria in healthy individuals, consistent with postprandial distress syndrome. Acid-resistant lipase supplementation significantly decreased stomach fullness. (Gut Liver 2015;9:464-469)
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Gong, Jinxia,Xie, Da,Jiang, Chuanwen,Zhang, Yanchi The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.1
A stochastic optimal power flow (S-OPF) model considering uncertainties of load and wind power is developed based on chance constrained programming (CCP). The difficulties in solving the model are the nonlinearity and probabilistic constraints. In this paper, a limit relaxation approach and an iterative learning control (ILC) method are implemented to solve the S-OPF model indirectly. The limit relaxation approach narrows the solution space by introducing regulatory factors, according to the relationship between the constraint equations and the optimization variables. The regulatory factors are designed by ILC method to ensure the optimality of final solution under a predefined confidence level. The optimization algorithm for S-OPF is completed based on the combination of limit relaxation and ILC and tested on the IEEE 14-bus system.
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A New Solution for Stochastic Optimal Power Flow
Jinxia Gong,Da Xie,Chuanwen Jiang,Yanchi Zhang 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.1
A stochastic optimal power flow (S-OPF) model considering uncertainties of load and wind power is developed based on chance constrained programming (CCP). The difficulties in solving the model are the nonlinearity and probabilistic constraints. In this paper, a limit relaxation approach and an iterative learning control (ILC) method are implemented to solve the S-OPF model indirectly. The limit relaxation approach narrows the solution space by introducing regulatory factors, according to the relationship between the constraint equations and the optimization variables. The regulatory factors are designed by ILC method to ensure the optimality of final solution under a predefined confidence level. The optimization algorithm for S-OPF is completed based on the combination of limit relaxation and ILC and tested on the IEEE 14-bus system.
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Lu, Lingling,Wang, Xi,Liao, Lijuan,Wei, Yanpeng,Huang, Chenguang,Liu, Yanchi Techno-Press 2015 Smart Structures and Systems, An International Jou Vol.15 No.2
An optimal sensor placement (OSP) method based on structural subsection technique (SST) and model reduction technique was proposed for modal identification of truss structures, which was conducted using genetic algorithm (GA). The constraints of GA variables were determined by SST in advance. Subsequently, according to model reduction technique, the optimal group of master degrees of freedom and the optimal objective function value were obtained using GA in a case of the given number of sensors. Correspondingly, the optimal number of sensors was determined according to optimal objective function values in cases of the different number of sensors. The proposed method was applied on a scaled jacket offshore platform to get its optimal number of sensors and the corresponding optimal sensor layout. Then modal kinetic energy and modal assurance criterion were adopted to evaluate vibration energy and mode independence property. The experiment was also conducted to verify the effectiveness of the selected optimal sensor layout. The results showed that experimental modes agreed reasonably well with numerical results. Moreover the influence of the proposed method using different optimal algorithms and model reduction technique on optimal results was also compared. The results showed that the influence was very little.
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Chenguang Huang,Lingling Lu,Lijuan Liao,Yanpeng Wei,Yanchi Liu,Xi Wang 국제구조공학회 2015 Smart Structures and Systems, An International Jou Vol.15 No.2
An optimal sensor placement (OSP) method based on structural subsection technique (SST) and model reduction technique was proposed for modal identification of truss structures, which was conducted using genetic algorithm (GA). The constraints of GA variables were determined by SST in advance. Subsequently, according to model reduction technique, the optimal group of master degrees of freedom and the optimal objective function value were obtained using GA in a case of the given number of sensors. Correspondingly, the optimal number of sensors was determined according to optimal objective function values in cases of the different number of sensors. The proposed method was applied on a scaled jacket offshore platform to get its optimal number of sensors and the corresponding optimal sensor layout. Then modal kinetic energy and modal assurance criterion were adopted to evaluate vibration energy and mode independence property. The experiment was also conducted to verify the effectiveness of the selected optimal sensor layout. The results showed that experimental modes agreed reasonably well with numerical results. Moreover the influence of the proposed method using different optimal algorithms and model reduction technique on optimal results was also compared. The results showed that the influence was very little.
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