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Commencing with the dynamic characteristic optimization of frequency regulation of wind energy storage systems， this study delves into a coordinated frequency regulation strategy between energy storage systems （ESS） and wind farms， taking into account the state of charge （SOC）. Firstly， it investigates the strategy of differential inertia support using variable-ratio speed regulation of the doubly-fed induction generator （DFIG） under varying wind speeds. Subsequently， a two-tiered coordinated control approach is employed to determine the power command to synchronize distributed energy storage with wind farm frequency regulation. Then， with the energy storage SOC as a state variable， a strategy for allocating frequency regulation power commands is proposed based on a consensus algorithm. This strategy considers the disparities in energy storage SOC and power regulation capabilities， facilitating power allocation for distributed energy storage based on SOC status. Finally， the efficacy of the proposed strategy is validated through simulation. The findings demonstrate that this strategy effectively coordinates distributed energy storage with wind farms to provide frequency response， swiftly recovering the operation mode of maximum power point tracking （MPPT） of wind turbines and thereby averting secondary frequency disturbances in the system.

This article explores the application of digital information technology in music education, especially in teaching traditional music. Taking the intersection of conventional music culture and applied teaching practice, the article utilizes advanced algorithmic techniques - Support Vector Machines and Apriori Association Rule Algorithm - to construct an innovative model of emotional cognition and stylistic categorization of traditional music. This model integrates standard music emotion cognition and style classification into modern informationized music teaching. To verify the model’s effectiveness, the researchers selected 500 pieces of traditional Chinese music as samples, trained and tested using the constructed model, and compared it with other algorithmic models. The test results show that the model outperforms BP neural networks and Linear neural networks regarding emotion perception. Specifically, the model shows efficient performance with mean square error (MSE) and correlation coefficient (CC) averages of 0.0099 and 90.50% on the test set, respectively. In addition, the model has the shortest processing time and is lower than the IM-Apriori algorithm regarding space consumption, showing its efficiency and resource-saving advantages. The model’s accuracy ranges from 75.23% to 90.06% in classifying traditional music. In summary, the model proposed in this paper improves the accuracy and efficiency of emotional cognition and style classification of conventional music and provides essential technical support for effectively integrating traditional music into modern informative music teaching.

Optimal control based on the exact synchronization of linear ordinary differential equations can provide conditions for the existence of optimal control of long-time lag network stability. In this paper, we first generalize network control systems, time lag systems, and modern control system stability theory to discuss long-time lag network stability analysis and control problems. The numerical solution method for solving ordinary differential equations with boundary conditions is proposed by combining the numerical solution method for initial value problems of differential equations and the iterative method for solving nonlinear equations. Finally, the fixed-time synchronization problem of complex networks with time-varying time lags under periodic intermittent control is studied. Two intermittent control strategies are designed based on the linear ordinary differential equation algorithm, and the convergence analysis of the synchronization error and the synchronization criterion are given. Numerical values show that the synchronization error converges to zero (< 1.0e − 5) in 0.32s, while the convergence times are 0.55s and 0.90s. The fixed times of the three methods are calculated to be T* = 0.52, T1 = 0.71 and T2 = 1.32, respectively, and the synchronization error system converges faster under the method in the paper. The numerical simulation results verify the effectiveness of linear ordinary differential equations in controlling the stability of long-time lag networks.

Background As population aging progresses, the prevalence of multimorbidity and polypharmacy is increasing in older adults, which may increase the risk of potentially inappropriate medication, causing adverse health outcomes. Objective To systematically assess the prevalence and associated factors of potentially inappropriate medication in community-dwelling Chinese older adults, in order to provide a reference for developing relevant intervention strategies. Methods In June 2022, we searched databases of CNKI, CQVIP, Wanfang Data, SinoMed, PubMed, EmBase, and Web of Science from inception to June 2022 for studies on potentially inappropriate medication in community-dwelling older adults in China. Two reviewers independently selected studies, extracted data and assessed the quality of included studies according to the Agency for Healthcare Research and Quality methodology checklist. Meta-analysis was conducted using Stata 12.0. Results A total of 24 studies were included, including two with high quality and 22 with moderate quality. Meta-analysis showed that the pooled prevalence of potentially inappropriate medication was 34.8%〔95%CI (31.3%, 38.3%) 〕in community-dwelling older adults in China. Pooled estimates showed 75 years or above〔OR (95%CI) =1.261 (1.074, 1.481) 〕, five or more comorbidities〔OR (95%CI) =3.287 (1.405, 7.691) 〕, and taking five or more medications〔OR (95%CI) =1.800 (1.305, 2.481) 〕or taking 10 or more medications〔OR (95%CI) =4.380 (2.612, 7.347) 〕were associated factors of potentially inappropriate medication. Conclusion Potentially inappropriate medication is common in community-dwelling older adults in China, whose risk is associated with older age, multimorbidity and polypharmacy. Prevention and management of potentially inappropriate medication should be paid attention to individuals with the above characteristics.

To help people solve unsolved problems in everyday life and solve the complexity of life, this paper proposes an artificial intelligence algorithm and establishes a mathematical model for simulation experiments. The results show that the artificial intelligence algorithm can search the optimal solution in a short time, with a success rate of 95.87%. Under the same conditions, relative to other algorithms, it can not only improve the success rate of the optimal solution, but also the search solution has very significant advantages.

Razor clams, belonging to the Pharidae and Solenidae families, are ecologically and economically important; however, very little research has been conducted on the Pharidae family. The genus Novaculina is a marine-derived freshwater lineage, and Novaculina chinensis is a rare freshwater species of the Pharidae family. In order to understand the phylogenetic relationships of N. chinensis, we sequenced the mitochondrial genome of the genus Novaculina, which is 16,262 bp in length and consists of 12 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), and 2 ribosomal RNA genes (rRNAs). The phylogenetic relationships of 69 Imparidentian mitochondrial genomes (mitogenomes) indicated that N. chineisis is closely related to Sinonovacula constricta of the order Adapedonta. Our study also found that the Ka/Ks ratios of 12 protein-coding genes in the Pharidae family are lower than one, indicating the occurrence of negative purification selection. Morphological observations of the siphons of N. chinensis, Novaculina myanmarensis, and Novaculina gangetica indicate that N. chinensis may be the ancestral clade of the genus Novaculina, which has not been proposed in previous studies. Our study provides useful molecular information on the phylogenetic and evolutionary relationships of Pharidae and also contributes to the conservation and management of the germplasm resources of N. chinensis. [ABSTRACT FROM AUTHOR]

With the advancement of the industrial Internet of Things era, and the use of renewable energy technologies, smart grid has become the main form of power grid, and data has become a key link. The problem of data islands is common, and the data value, especially the commercial value, has yet to be tapped. This phenomenon is particularly prominent in power grid enterprises. Therefore, a data management model and method for power grid enterprises are proposed. The model aims at data asset management of power grid enterprises, reveals the process of extracting, modeling, analyzing and value mining of power grid data based on big data BI technology, and puts forward a practical and easy-to-land data asset management method, which really solves the problems of how to collect, store, manage and use data. Finally, taking the linkage between power marketing data and power grid planning in a certain area of Hangzhou, Zhejiang Province as a specific scenario, the BI analysis conclusion of relevant marketing data is displayed, which realizes the echo of conventional application and advanced application, reduces investment practically, improves economic benefits, and demonstrates the feasibility and scientificity of the method. [ABSTRACT FROM AUTHOR]