The international development community is off-track from meeting targets for alleviating global malnutrition. Meanwhile, there is growing consensus across scientific disciplines that fish plays a crucial role in food and nutrition security. However, this ‘fish as food’ perspective has yet to translate into policy and development funding priorities. We argue that the traditional framing of fish as a natural resource emphasizes economic development and biodiversity conservation objectives, whereas situating fish within a food systems perspective can lead to innovative policies and investments that promote nutrition-sensitive and socially equitable capture fisheries and aquaculture. This paper highlights four pillars of research needs and policy directions toward this end. Ultimately, recognizing and working to enhance the role of fish in alleviating hunger and malnutrition can provide an additional long-term development incentive, beyond revenue generation and biodiversity conservation, for governments, international development organizations, and society more broadly to invest in the sustainability of capture fisheries and aquaculture.
We describe an iodometric titration
method for the determination
of ascorbic acid using a microfluidic paper-based analytical device
(μPAD). The ascorbic acid was detected by measuring the length
of the blue band formed in a straight paper channel delimited by wax.
This analytical method was designed as a laboratory experiment for
undergraduates majoring in chemical education. The main objectives
of this practice are to introduce μPAD into a preservice teacher’s
classroom, motivating their passion of learning chemistry, and implementing
green chemistry education. Finally, we hope this novel microscale
chemistry experiment could be introduced into the chemistry classroom
at high schools by these preservice teachers after graduation. A total
of 145 preservice chemistry teachers performed this experiment in
the fifth semester. They completed this experiment within 3 h; positive
feedback from these students indicated that the learning objectives
and instructional aims were met.
Artificial intelligence is widely used in mathematical modeling. The technical means in mathematical modeling are more and more diversified, especially the application of artificial intelligence algorithm greatly promotes the development of mathematical modeling. In recent years, because of its great influence on the fuel consumption, output power and exhaust performance of automobiles, the control strategy has become a research hotspot and focus in automobile R&D industry. Therefore, based on the relevant research results in recent years, after studying and analyzing the typical control strategies of hybrid vehicles, this paper finally puts forward the energy management strategy of hybrid vehicles based on model predictive control (MPC), and strives to contribute to the academic research of energy management strategies of hybrid vehicles.
Aiming at the impact of the uncertainty of source load on the optimal scheduling in an integrated energy system (IES), in this paper, based on hybrid resolution modeling and hybrid instruction cycle scheduling technology, three time scales of day-ahead, intra-day rolling and real-time feedback optimization scheduling models are established, respectively, with the objectives of the economic optimal daily operation of the system, the minimum sum of the operation cost of energy purchase and wind curtailment penalty cost in the rolling control time domain, and the minimum adjustment amount of equipment output power. Then, the chaotic gravitational search algorithm (CGSA) is used to solve the problem, and the composite coordination optimization operation strategy of IES with mixed time scales based on CGSA is proposed. In the example, the comparison between the multi-timescale scheduling plan and the actual output, the comparison of the system scheduling results under different strategies and the comparison of different optimization algorithms show that the proposed optimization operation strategy is beneficial to optimize the energy flow distribution, reduce the system operation cost, improve the IES economy and optimization speed.
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