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The high-altitude, low-oxygen environment of the Qinghai-Tibet Plateau poses significant challenges for the introduction of superior livestock breeds. However, local plateau species have adapted to thrive and reproduce under these harsh conditions. Understanding the molecular mechanisms behind plateau animals’ adaptation to low-oxygen environments is essential for breeding livestock suited to high-altitude regions. Tibetan pigs, which have undergone long-term natural selection and artificial breeding, have developed the ability to survive and reproduce in hypoxic environments. In this study, we conducted whole-genome resequencing of 30 Tibetan pigs from high-altitude regions and 30 Diannan small-ear pigs from low-altitude areas, to identify candidate genes that support Tibetan pigs’ adaptation to hypoxic conditions through selection signal analysis. Additionally, we performed transcriptome sequencing on five tissues (heart, liver, spleen, lung, and bone marrow) from both Tibetan pigs and Diannan small-ear pigs to identify genes with significant differential expression between the two breeds. We then integrated the genomic and transcriptomic data by examining the expression of candidate genes identified in selection signal analysis across different tissues. The selection signal analysis identified 10 genes—HES4, ANGPT1, HIF3A, SPHK2, PCK2, RCN3, HIGD2A, DNM2, IRF9, and SRF—that were under positive selection in the Tibetan pig population and are associated with hypoxia adaptation. When combined with transcriptome data, we found that five of these genes—HIF3A, RCN3, HIGD2A, PCK2, and IRF9—exhibited differential expression. Through an integrated approach of selection signal and transcriptome analysis, we identified five key functional genes that contribute to the adaptation of Tibetan pigs to hypoxic environments. These findings offer new insights into the adaptability of plateau animals.

Abstract As one of the most widespread renewable energy sources, wind energy is now an important part of the power system. Accurate and appropriate wind speed forecasting has an essential impact on wind energy utilisation. However, due to the stochastic and uncertain nature of wind energy, more accurate forecasting is necessary for its more stable and safer utilisation. This paper proposes a Legendre multiwavelet‐based neural network model for non‐linear wind speed prediction. It combines the excellent properties of Legendre multi‐wavelets with the self‐learning capability of neural networks, which has rigorous mathematical theory support. It learns input‐output data pairs and shares weights within divided subintervals, which can greatly reduce computing costs. We explore the effectiveness of Legendre multi‐wavelets as an activation function. Meanwhile, it is successfully being applied to wind speed prediction. In addition, the application of Legendre multi‐wavelet neural networks in a hybrid model in decomposition‐reconstruction mode to wind speed prediction problems is also discussed. Numerical results on real data sets show that the proposed model is able to achieve optimal performance and high prediction accuracy. In particular, the model shows a more stable performance in multi‐step prediction, illustrating its superiority.

Abstract Satellite electrical power supply system requires higher redundancy and reliability. The failure of the secondary power supply of the power distribution unit will directly lead to the unavailability of the load. The matrix switch can connect multiple secondary power supplies to multiple loads to improve the fault tolerance of the distribution unit. As the number of redundant switches increases, the process of fault reconstruction becomes more complex. In this paper, a matrix switch fault reconstruction method based on 0–1 integer programming is proposed. This method can reconstruct the matrix switch for different fault modes to meet the electrical power supply and protection requirements of the load. Compared with the general fault countermeasure, this method has independent decision‐making ability, can be expanded by modifying a few parameters, and can be integrated into the management of the whole satellite power supply system. A 500‐W satellite power supply system experimental platform was built, and a matrix distribution switch unit prototype meeting the requirements of integration and low volume was manufactured. The experimental results verify the effectiveness of the reconstruction strategy when dealing with multiple faults in different locations.

In recent years, DC fault arc detection has been an electrical engineering research hotspot. At present, most proposed detection methods do not analyze the effects of fault arc electrical characteristics on both line current and supply voltage. Therefore, this study extensively analyzes variations of the line current and supply voltage because of DC arc faults based on the volt-ampere characteristics of DC arc faults. Then, a DC series arc fault detection method is proposed that comprehensively uses information on line current and supply voltage. An experimental platform for DC fault arc generation and detection was established using a DC-DC converter and a photovoltaic power supply as DC power supplies, and the proposed method was confirmed by experiments using this platform. Experimental results demonstrate that the proposed method can effectively distinguish arc faults and has the characteristics of clear physical meaning while maintaining a low amount of calculation.

Since each branch of the multiterminal DC circuit system relies on the DC circuit breaker for breaking and fault isolation, the prohibitive cost and huge volume of the Hybrid DC Circuit Breaker (HCB) limit its development and broad application in multiterminal flexible DC systems. Multiport hybrid DC circuit breaker (MP-HDCCB) based on device and branch sharing reduces the configuration cost of the circuit breaker to a certain extent. In order to further reduce the cost of MP-HDCCB, a novel MP-HDCCB topology based on hybrid switching devices is proposed, adopting full controlled switching devices to achieve rapidity of breaking fault current, and using semi-controlled switching devices in series to withstand the transient interruption voltage (TIV), so as to reduce the construction cost and technical difficulty. In this paper, the working principle and fault breaking strategy of the topology are introduced in detail, then the parameters of the major circuit are analyzed theoretically, and the parameter design of each branch is given. In the end, the rationality and validity of the proposed topology is tested and verified by simulations and experimental tests.

Owing to the shortcomings of existing series arc fault detection methods, based on a summary of arc volt⁻ampere characteristics, the change rule of the line current and the relationship between the voltage and current are deeply analyzed and theoretically explained under different loads when series arc faults occur. A series arc fault detection method is proposed, and the software flowchart and principles of the applied hardware implementation are given. Finally, a prototype of an arc fault detection device (AFDD) with a rated voltage of 220 V and a rated current of 40 A is developed. The prototype was tested according to experimental methods provided by the Chinese national standard, GB/T 31143-2014. The experimental results show that the proposed detection method is simple and practical, and can be implemented using a low-cost microprocessor. The proposed method will provide good theoretical guidance in promoting the research and development of an AFDD.