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Fluctuations in the output power of photovoltaic (PV) under climate changes such as variations in temperature and radiation is an important challenge for these resources. Therefore, it is very important to keep the output power of solar systems constant without any fluctuation at their maximum power point in the event of climate change. The aim of this paper is to suggest a maximum power point tracking (MPPT) method to cancel the output power oscillation of PV systems in severEe weather conditions, especially under radiation and temperature changes. In order to find the optimal parameters of the MPPT controller, the improved shuffled frog-leaping algorithm (ISFLA) and fuzzy controller are used. In addition, to fine-tune the member functions (MFs) of FLC, the combination of the fuzzy logic controller (FLC) and the ISFLA algorithm are employed. The ISFLA is an effective solution to cope with the stochastic behavior of the PV system under changing the radiation and ambient temperature. A storage system is also used to provide more stability and reliability for the system. Simulation results show that the recommended scheme provides excellent tracking efficiency from 98.1 to 99.6%. The case study under partial shading conditions also confirms the 16% improvement in the efficiency of the proposed method and more stability compared to the conventional P&O MPPT controller. [ABSTRACT FROM AUTHOR]

Based on the existing literature, this paper analyzed and explored the factors that affect the efficiency of resource allocation, and evaluated the current situation of resource allocation in various fields. It is found that with the emergence of the new pattern of China's economic development, the economic growth rate has slowed down, and the method of large-scale production driving economic growth is no longer applicable to the current economic situation. Nowadays, when structural transformation and upgrading have entered a new stage, to achieve the optimization of resource allocation efficiency, it is necessary to start from three aspects; improving information transparency, upgrading industrial structure, and planning government intervention. Through the adaptation analysis of blockchain technology and the existing problems in optimizing resource allocation efficiency, it explored the feasibility of blockchain technology to optimize resource allocation efficiency, and promote economical, efficient and high-quality development. [ABSTRACT FROM AUTHOR]

Power systems have been accommodating solar energy to a large extent, particularly when it comes to photovoltaic (PV) systems. In this regard, a number of parameters, including temperature and solar irradiance, have a significant impact on the power output of such systems. Maximum power point tracking (MPPT) strategies have been devised and deployed in PV systems as a successful remedy to boost efficiency in response to varying climate parameters. Accordingly, a promoted MPPT strategy is designed in this paper deploying the incremental conductance (INC) method optimized by employing the grasshopper optimization algorithm (GOA)-based adaptive neuro-fuzzy inference system (ANFIS). This technique includes two stages: specifying the optimal values of voltage by deploying the GOA taking into consideration various scenarios of temperature and solar irradiance. Afterward, the ANFIS would give the optimal value of the voltage by using solar irradiance on PV panels. It is noteworthy that the INC technique would initialize at this value and seek the maximum power point (MPP). One of the merits associated with using the ANFIS-based INC technique is the smaller dataset needed for the training purpose. In this regard, in case the ANFIS does not specify the definite point, the INC approach would do it. Simulations are performed to validate the usefulness of the suggested GOA-ANFIS-based INC MPPT technique and compared with conventional MPPT schemes. [ABSTRACT FROM AUTHOR]

Background Mortality increases during heat waves have been reported worldwide. The magnitude of these increases can vary within regions according to sociodemographic and urban landscape characteristics. The objectives of this study were to explore this variation and its determinants, and to identify the most heat-vulnerable areas by mapping heat vulnerability. Methods We conducted a time-stratified case-crossover analysis using daily mortality in the Barcelona metropolitan area during the warm seasons of 1999-2006. Temperature data on the date of death were assigned to each individual, which were assigned to their census tract of residence. Eight census tract-level variables on socioeconomic or built environment characteristics were obtained from the census. Residence surrounding greenness was obtained from satellite data. The relative risk (RR) of mortality after three consecutive hot days (defined as those exceeding the 95th percentile of maximum temperature) was calculated via conditional logistic regression. Effect modification was examined by including interaction terms. Results Analyses were based on 52 806 deaths. The effect of three consecutive hot days was a 30% increase in all-cause mortality (RR=1.30, 95% CI 1.24 to 1.38). Heterogeneity of this effect was observed across census tracts. The effect of heat on mortality was higher in the census tracts with a large percentage of old buildings (RR=1.21, 95% CI 1.00 to 1.46), manual workers (RR=1.25, 95% CI 0.96 to 1.64) and residents perceiving little surrounding greenness (RR=1.29, 95% CI 1.01 to 1.65). After three consecutive hot days, mortality doubled in the most heat-vulnerable census tracts. Conclusions Sociodemographic and urban landscape characteristics are associated to mortality risk during heat waves and are useful to build heat vulnerability maps. [ABSTRACT FROM AUTHOR]

With the rapid development of Internet technology, the importance of blockchain technology has become increasingly prominent. Faced with this situation, extensive research has been carried out at home and abroad. Through the analysis of relevant literature on blockchain in recent years, it is found that there are many research results of blockchain technology in medical care, finance, education, etc., but its application in the field of resource allocation efficiency is rare. From the existing studies on the influencing factors of resource allocation efficiency in China, it is found that there are significant differences in resource allocation efficiency between China and some developed countries or between various provinces and cities of China. [ABSTRACT FROM AUTHOR]

The resin infiltration stage during the resin transfer molding process is complicated, which involves the edge effect, resin curing reaction and heat transfer phenomenon. In this paper, considering the edge effect, the integrated investigation on curing reaction, physical property, two-dimensional resin flow and three-dimensional temperature distribution is implemented in theory and numerical simulation. And then the evolution of coupling physical fields, such as resin temperature, curing degree and resin viscosity, is analyzed numerically. The present study is helpful for understanding the complex relationships among a variety of parameters during the reactive filling process. [ABSTRACT FROM AUTHOR]