75 research outputs found

    Optimization ACE inhibition activity in hypertension based on random vector functional link and sine-cosine algorithm

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    Bioactive peptides from protein hydrolysates with antihypertensive properties have a great effect in health, which warrants their pharmaceutical use. Nevertheless, the process of their production may affect their efficacy. In this study, we investigate the inhibitory activities of various hydrolysates on angiotensin-converting enzyme (ACE) in relation to the chemical diversity of corresponding bioactive peptides. This depends on the enzyme specificity and process conditions used for the production of hydrolysates. In order to mitigate the uncontrolled chemical alteration in bioactive peptides, we propose a computational approach using the random vector functional link (RVFL) network based on the sine-cosine algorithm (SCA) to find optimal processing parameters, and to predict the ACE inhibition activity. The SCA is used to determine the optimal configuration of RVFL, improving the prediction performance. The experimental results show that the performance measures of the proposed model are better than the state-of-the-art methods

    Cadmium contamination and dietary exposure assessment in rice in Nanning City

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    Objective To understand the content of cadmium (Cd) in rice and evaluate the potential health risk to local residents. Methods Total of 886 rice samples were collected from Nanning City during 2015-2019, and the content of Cd in rice was determined by inductively coupled plasma-mass spectrometry (ICP-MS). The health risk assessment model recommended by the United States Environmental Protection Agency was used to assess the health risk of local residents. Results The detection rate of Cd in 886 rice samples was 94.92% (841/886), and the violation rate was 19.19% (170/886). The content of Cd range from 1.50 to 915.00 μg/kg, of which mean and median were 126.85 and 79.00 μg/kg, respectively. The dietary Cd exposure of people aged 6-17 was higher than that of people aged 18 and above. The dietary exposure to Cd was 12.43-23.95 μg/kg BW for people aged 18 and above, and the target hazard quotient (THQ) was below 1; however, the dietary exposure of Cd was 15.42-29.80 μg/kg BW for people aged 6-17, with THQ between 0.62 and 1.19. In Mashan, Shanglin and Longan, the THQ of people aged 6-17 was greater than 1. Conclusion There was a certain contamination of Cd in rice in this city, and might pose potential health risks to the people aged 6-17. Therefore, it is necessary to strengthen the monitoring and control of the contamination

    An improved quantum-behaved particle swarm optimization method for short-term combined economic emission hydrothermal scheduling

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    a b s t r a c t This paper presents a modified quantum-behaved particle swarm optimization (QPSO) for short-term combined economic emission scheduling (CEES) of hydrothermal power systems with several equality and inequality constraints. The hydrothermal scheduling is formulated as a bi-objective problem: (i) minimizing fuel cost and (ii) minimizing pollutant emission. The bi-objective problem is converted into a single objective one by price penalty factor. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability. In this study, heuristic strategies are proposed to handle the equality constraints especially water dynamic balance constraints and active power balance constraints. A feasibility-based selection technique is also employed to meet the reservoir storage volumes constraints. To show the efficiency of the proposed method, different case studies are carried out and QPSO-DM is compared with the differential evolution (DE), the particle swarm optimization (PSO) with same heuristic strategies in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed method is capable of yielding higher-quality solutions stably and efficiently in the short-term hydrothermal scheduling than any other tested optimization algorithms

    Mining association rules using clustering

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