Functional Coefficient Moving Average Model with Applications to forecasting Chinese CPI

This article establishes the functional coefficient moving average model (FMA), which allows the coefficient of the classical moving average model to adapt with a covariate. The functional coefficient is identified as a ratio of two conditional moments. Local linear estimation technique is used for estimation and asymptotic properties of the resulting estimator are investigated. Its convergence rate depends on whether the underlying function reaches its boundary or not, and asymptotic distribution could be nonstandard. A model specification test in the spirit of Hardle-Mammen (1993) is developed to check the stability of the functional coefficient. Intensive simulations have been conducted to study the finite sample performance of our proposed estimator, and the size and the power of the test. The real data example on CPI data from China Mainland shows the efficacy of FMA. It gains more than 20% improvement in terms of relative mean squared prediction error compared to moving average model

Association analysis of alpha-amylase (AMY) and cathepsin L (CTSL) SNPs with growth traits in giant tiger shrimp Penaeus monodon

Alpha-amylase (AMY) and cathepsin-L (CTSL) were selected as candidate genes for SNP discovery for growth traits of P. monodon. Six SNPs were found in AMY and three in CTSL in P. monodon. Association analyses for the candidate SNPs with important economic traits were performed in populations. That allele A at CTLS-213 SNP, AA, and GA, tended to be associated with increased body weight. Shrimps with genotype GG had significantly smaller CL, CW, and CH values than those with GT and TT genotypes (P < 0.05). While CTLS-820 SNP was found to be significantly associated with CH and FSL (P <0.05). These SNPs will be valid for marker-assisted selection breeding programs in P. monodon

Effects of replacing dietary fishmeal with zymolytic black soldier fly larvae on the growth performance of the mud crab (<em>scylla paramamosain</em>) larvae

Black soldier fly have been shown to be one of the optimal alternatives to fishmeal, but there are few reports on the effects of zymolytic black soldier fly larvae (ZBSFL) on the growth and digestion of crustaceans. An 8-week feeding trial was conducted to evaluate the effects of different replacement levels of ZBFLS on growth performance, body composition, and digestive enzyme activity of the mud crab larvae. Four diets were formulated by replacing fishmeal with 0%, 5%, 10% and 15% ZBSFL in the basal diet. Crab larvae were randomly divided into four groups of three replicates each and fed twice daily. The results showed that the SR of crab larvae was higher than that of the no-substitution group when the substitution rate reached 5% (P < 0.05). There was no significant change in SR when the substitution rate was further increased. Weight growth rate and Specific growth rate were similar, both highest at 10% substitution ratio. The crude protein content of whole crab larvae gradually increased as the proportion of FM substituted by ZBSFL increased. The lipid content of whole crab larvae in the 5% substitution ratio group was significantly higher than that in all other groups (P < 0.05). Meanwhile. The activities of amylase, protease and lipase gradually increased. In this experiment, when the percentage of ZBSFL substitution for FM reached 10%, its growth performance was optimal, with higher SR, less negative effects and more balanced indicators in all aspects. When the substitution rate was further increased, it might increase the digestive burden of the crab and negatively affect its growth

2020 roadmap on solid-state batteries

Li-ion batteries have revolutionized the portable electronics industry and empowered the electric vehicle (EV) revolution. Unfortunately, traditional Li-ion chemistry is approaching its physicochemical limit. The demand for higher density (longer range), high power (fast charging), and safer EVs has recently created a resurgence of interest in solid state batteries (SSB). Historically, research has focused on improving the ionic conductivity of solid electrolytes, yet ceramic solids now deliver sufficient ionic conductivity. The barriers lie within the interfaces between the electrolyte and the two electrodes, in the mechanical properties throughout the device, and in processing scalability. In 2017 the Faraday Institution, the UK's independent institute for electrochemical energy storage research, launched the SOLBAT (solid-state lithium metal anode battery) project, aimed at understanding the fundamental science underpinning the problems of SSBs, and recognising that the paucity of such understanding is the major barrier to progress. The purpose of this Roadmap is to present an overview of the fundamental challenges impeding the development of SSBs, the advances in science and technology necessary to understand the underlying science, and the multidisciplinary approach being taken by SOLBAT researchers in facing these challenges. It is our hope that this Roadmap will guide academia, industry, and funding agencies towards the further development of these batteries in the future

Variation of bacterial communities in black tiger shrimp (Penaeus monodon) with different growth performances

The intestinal bacteria of aquatic animals are closely related to their health and growth status. Penaeus monodon has become an important aquaculture species in the world because of its high nutritional value and market to demand. However, knowledge of bacterial communities on the growth phenotype of P. monodon is still limited. In this research, the bacterial community were comprehensively analyzed by using Miseq sequencing technology and bioinformatics. The results indicated that 29 phyla and 468 genera were identified by the taxonomic sequence. The data showed that the composition of microbial community was statistically different to fast-growing shrimps and slow-growing shrimps. There were significant differences in intestinal bacteria at the genus level. Lactococcus, Limnothrix, and Arthrospira had more abundance in the gut of fast-growing shrimps, which may promote the growth of P. monodon by affecting enzyme activities and improving immune response. Nautella, Shimia, Pseudoalteromonas, Aliiroseovarius, Albimonas, Tessaracoccus had more abundance in the gut of slow-growing shrimps. Nautella had the ability to express virulence by stimulated by environmental factors, thereby increasing the susceptibility to infection, which may have a negative impact on healthy growth of shrimps. Pseudoalteromonas, Aliiroseovarius and Shimia were related to the pathogenicity of shrimp, which may be an important factor affecting the growth of shrimp. Overall, this study demonstrates that the bacterial community associated with P. monodon was variation on different growth performance. These results can provide information on microbiome characteristics involved in the asynchronous growth of shrimp

Optimal Allocation of Generalized Power Sources in Distribution Network Based on Multi-Objective Particle Swarm Optimization Algorithm

Optimal allocation of generalized power sources in distribution network is researched. A simple index of voltage stability is put forward. Considering the investment and operation benefit, the stability of voltage and the pollution emissions of generalized power sources in distribution network, a multi-objective optimization planning model is established. A multi-objective particle swarm optimization algorithm is proposed to solve the optimal model. In order to improve the global search ability, the strategies of fast non-dominated sorting, elitism and crowding distance are adopted in this algorithm. Finally, tested the model and algorithm by IEEE-33 node system to find the best configuration of GP, the computed result shows that with the generalized power reasonable access to the active distribution network, the investment benefit and the voltage stability of the system is improved, and the proposed algorithm has better global search capability

Multi-Objective Low-Carbon Economic Dispatch Considering Demand Response with Wind Power Integrated Systems

The generation cost, carbon emissions and customers’ satisfaction are considered in this paper. On the basis of this, the multi-objective and low-carbon economic dispatch model with wind farm, this considers demand response, is established. The model user stochastic programming theory to describe the uncertainty of the wind power and converts it into an equivalent deterministic model by using distribution function of wind power output, optimizes demand side resources to adjust the next day load curve and to improve load rate and absorptive capacity of wind power, introduce customers’ satisfaction to ensure that the scheduling scheme satisfies customer and integrate the resources of source and load to unify coordination wind farm access to network and to meet the requirements of energy saving and emission reduction. The search process of artificial fish school algorithm introducing Tabu search and more targeted search mechanism, an multi-objective improved artificial fish school algorithm is proposed to solve this model. Using the technique for order preference by similarity to ideal solution (TOPSIS) to sort the Pareto frontier, the optimal scheduling scheme is determined. Simulation results verify the rationality and validity of the proposed model and algorithm

The Foraging Window for Greater White-Fronted Geese (<i>Anser albifrons</i>) Is Consistent with the Growth Stage of <i>Carex</i>

Food resources are key limiting factors for migratory waterbirds, and the foraging strategies adopted by herbivorous waterbirds are affected by food availability in wetland habitats. The greater white-fronted goose (Anser albifrons) is mainly dependent on Carex in the lower and middle Yangtze River floodplain. Exploring the relationship between the growth conditions of Carex and the foraging strategies adopted by wintering greater white-fronted geese has important ecological implications for habitat protection and management. In this study, scan sampling and focal animal sampling were used to record the foraging behaviors of greater white-fronted geese wintering at Shengjin Lake, and the plant height and water content of Carex were surveyed simultaneously. The relationship between plant characteristics and foraging behaviors was tested using a linear regression equation. The results showed that Carex had two growth periods at Shengjin Lake, and the pecking rate and foraging time budget of greater white-fronted geese were higher during these two periods. Plant characteristics were positively correlated with goose foraging behaviors. The strategic adjustment of the foraging behaviors adopted by wintering greater white-fronted geese was consistent with the growth stage of Carex, which is the optimal foraging window for greater white-fronted geese. During the foraging windows, geese changed their foraging strategies to obtain more energy in order to guarantee successful wintering and migration