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To enhance the performance of ultra-high voltage power fittings in severe weather conditions without altering their current structure, the high-strength and toughness aluminum alloys were rationally selected to study the optimization of the die-casting process. This approach aims to improve the overall longevity and function of the power fittings in extreme climates. First of all, the propose of this study is to use the material's strength–toughness product (STP) concept to evaluate the material stability of the power fitting impact resistance and fatigue toughness in order to determine the appropriate material selection. Secondly, the location of the mold's sprue and gate was optimized through finite element simulation to prevent gas volume and flow defects during the casting process. This improves the material's toughness and anti-fatigue failure characteristics of the product. Then, vacuum equipment and a vacuum valve auxiliary system were added based on the existing die-casting machine, and the mold structure was optimized to enable the vacuum die-casting process. Finally, a water-based boron nitride environmentally friendly mold release agent was used to solve demolding difficulties with an A356 aluminum alloy and improve mold lubrication and surface quality. The production of quad-bundled spacers using A356 and vacuum die casting has resulted in parts with a tensile strength of at least 250 MPa and an elongation of no less than 7%. This improvement has laid a foundation for enhancing the operational reliability of existing overhead transmission line fittings. [ABSTRACT FROM AUTHOR]

As a large number of flexible elements such as distributed power and flexible load are connected to microgrids, the economic improvement of microgrids has become an important topic through rational energy distribution. In this paper, an economic scheduling model considering the load demand for a microgrid system under the mechanism of a peak–valley tariff is proposed. A mathematical model of the microgrid components is proposed to determine the exchange power between the microgrid and main network. Meanwhile, an improved War Strategy Optimization (WSO) algorithm is proposed to investigate three scenarios: (i) without batteries, (ii) with batteries and (iii) with batteries and demand response. Additionally, demand response optimization is carried out with the Particle Swarm Optimization (PSO) algorithm and the improved WSO is compared with four other algorithms in scenario (iii). The comparison shows that the improved WSO algorithm has a better optimization performance in solving the proposed scheduling model. [ABSTRACT FROM AUTHOR]

An active distribution network is an important development trend of the power grid with widespread use of the distributed generation. The reliability of the active distribution network is not negligible due to the uninterruptible power supply. In the paper, the reliability evaluation method of the active distribution network is proposed in detail, based on combining the roulette wheel selection and the sequential Monte Carlo algorithm. The uncertainty of both the distribution generation and the load is taken into consideration based on the power probability distribution and the working state in the presented model. Furthermore, the IEEE-RBTS Bus 6 is used to verify the validity of the proposed method. The result shows that the new energy access improves the availability and the reliability of the active distribution network. [ABSTRACT FROM AUTHOR]

The graph stream is defined as rapid edge streams on a huge domain of nodes. Nowadays, graph streams play important roles in network traffic, social networks, and cloud troubleshooting. Therefore, various summary structures for graph streams are proposed to obtain approximate evaluation results. However, these structures either sacrifice accuracy for guaranteed throughput or compromise memory consumption for high precision. In view of the limitations, we propose Cuckoo Matrix. It only uses one adjacency matrix to complete high accuracy queries while assuring large throughput. Meanwhile, Cuckoo Matrix is capable of preserving the connectivity of edges for the purpose of supporting both structural queries and weight-based estimations. The experimental results show that Cuckoo Matrix improves insertion throughput by 25% and reduces memory consumption by 25% compared to the state-of-the-art, which meets the current requirements of graph stream summarization. [ABSTRACT FROM AUTHOR]

The accurate detection of insulators is an important prerequisite for insulator fault diagnosis. To solve the problem of background interference and overlap caused by the axis-aligned bounding boxes in the tilting insulator detection tasks, we construct an improved detection architecture according to the scale and tilt features of the insulators from several perspectives, such as bounding box representation, loss function, and anchor box construction. A new orientation detection method for tilting insulators based on angle regression and priori constraints is put forward in this paper. Ablation tests and comparative validation tests were conducted on a self-built aerial insulator image dataset. The results show that the detection accuracy of our model was increased by 7.98% compared with that of the baseline, and the overall detection accuracy reached 82.33%. Moreover, the detection effect of our method was better than that of the YOLOv5 detection model and other orientation detection models. Our model provides a new idea for the accurate orientation detection of insulators. [ABSTRACT FROM AUTHOR]

Bolts are important components on transmission lines, and the timely detection and exclusion of their abnormal conditions are imperative to ensure the stable operation of transmission lines. To accurately identify bolt defects, we propose a bolt defect identification method incorporating an attention mechanism and wide residual networks. Firstly, the spatial dimension of the feature map is compressed by the spatial compression network to obtain the global features of the channel dimension and enhance the attention of the network to the vital information in a weighted way. After that, the enhanced feature map is decomposed into two one-dimensional feature vectors by embedding a cooperative attention mechanism to establish long-term dependencies in one spatial direction and preserve precise location information in the other direction. During this process, the prior knowledge of the bolts is utilized to help the network extract critical feature information more accurately, thus improving the accuracy of recognition. The test results show that the bolt recognition accuracy of this method is improved to 94.57% compared with that before embedding the attention mechanism, which verifies the validity of the proposed method. [ABSTRACT FROM AUTHOR]

The multi-microgrid is gradually springing up with widespread use of the distributed generation. It is of great meaning to have research on the energy mutual optimization of the multi-microgrid to improve the new energy-consumption capacity. In this paper, a comprehensive economic model of the multi-microgrid is proposed for optimizing the power dispatching, and the source-network-load-storage is taken into account. Different from other studies, the special novelty of this paper is the improved cuckoo search (CS) algorithm which is adopted to optimize the power dispatching of the multi-microgrid. Comparing with the particle swarm optimization (PSO) algorithm, the improved CS algorithm has better performance in solving the proposed model. The optimal power supply strategy is determined by predicting the optimal state of charge of the battery in the model of the multi-microgrid. The model effectiveness of the multi-microgrid is confirmed in the case study of Wangjiazhai area. With this method, the optimal power dispatching is determined. [ABSTRACT FROM AUTHOR]

The computer generation of poetry has been studied for more than a decade. Generating poetry on a human level is still a great challenge for the computer-generation process. We present a novel Transformer-XL based on a classical Chinese poetry model that employs a multi-head self-attention mechanism to capture the deeper multiple relationships among Chinese characters. Furthermore, we utilized the segment-level recurrence mechanism to learn longer-term dependency and overcome the context fragmentation problem. To automatically assess the quality of the generated poems, we also built a novel automatic evaluation model that contains a BERT-based module for checking the fluency of sentences and a tone-checker module to evaluate the tone pattern of poems. The poems generated using our model obtained an average score of 9.7 for fluency and 10.0 for tone pattern. Moreover, we visualized the attention mechanism, and it showed that our model learned the tone-pattern rules. All experiment results demonstrate that our poetry generation model can generate high-quality poems. [ABSTRACT FROM AUTHOR]

Coronary microvascular dysfunction (CMD) refers to a subset of structural and/or functional disorders of coronary microcirculation that lead to impaired coronary blood flow and eventually myocardial ischemia. Amid the growing knowledge of the pathophysiological mechanisms and the development of advanced tools for assessment, CMD has emerged as a prevalent cause of a broad spectrum of cardiovascular diseases (CVDs), including obstructive and nonobstructive coronary artery disease, diabetic cardiomyopathy, and heart failure with preserved ejection fraction. Of note, the endothelium exerts vital functions in regulating coronary microvascular and cardiac function. Importantly, insufficient or uncontrolled activation of endothelial autophagy facilitates the pathogenesis of CMD in diverse CVDs. Here, we review the progress in understanding the pathophysiological mechanisms of autophagy in coronary endothelial cells and discuss their potential role in CMD and CVDs. [ABSTRACT FROM AUTHOR]

In this paper, we use semi-tensor product of quaternion matrices, L -representation of quaternion matrices, and GH -representation of special quaternion matrices such as quaternion (anti)-centrosymmetric matrices to solve the special solutions of quaternion matrix equation. Based on semi-tensor product of quaternion matrices and the structure matrix of the multiplication of quaternion, we propose the vector representation operation conclusion of quaternion matrices, and study the different matrix representations of quaternion matrices. Then the problem of the quaternion matrix equation is transformed into the corresponding problem in the real number fields by using vector representation and L -representation of quaternion matrices, combined with the special structure of (anti)-centrosymmetric matrices, the independent elements are extracted by GH -representation method, so as to reduce the number of variables to be calculated and improve the calculation accuracy. Finally, the effectiveness of the method is verified by numerical examples, and the time comparison with the two existing algorithms is carried out. The algorithm in this paper is also applied in a centrosymmetric color digital image restoration model. [ABSTRACT FROM AUTHOR]

In this paper, we consider the split quaternion matrix equation X − A f (X) B = C , f (X) ∈ { X , X H , X i H , X j H X k H } . The H representation method has the characteristics of transforming a matrix with a special structure into a column vector with independent elements. By using the real representation of split quaternion matrices, H representation method, the Kronecker product of matrices and the Moore-Penrose generalized inverse, we convert the split quaternion matrix equation into the real matrix equation, and derive the sufficient and necessary conditions and the general solution expressions for the (skew) bisymmetric solution of the original equation. Moreover, we provide numerical algorithms and illustrate the efficiency of our method by two numerical examples. [ABSTRACT FROM AUTHOR]

Background The impairment of the inner blood–retinal barrier (iBRB) increases the pathological development of diabetic retinopathy (DR), a severe complication in diabetic patients. Identifying approaches to preserving iBRB integrity and function is a significant challenge in DR. C1q/tumor necrosis factor-related protein-3 (CTRP3) is a newly discovered adipokine and a vital biomarker, predicting DR severity. We sought to determine whether and how CTRP3 affects the pathological development of non-proliferative diabetic retinopathy (NPDR). Methods To clarify the pathophysiologic progress of the blood–retinal barrier in NPDR and explore its potential mechanism, a mouse Type 2 diabetic model of diabetic retinopathy was used. The capillary leakage was assessed by confocal microscope with fluorescent-labeled protein in vivo. Furthermore, the effect of CTRP3 on the inner blood–retinal barrier (iBRB) and its molecular mechanism was clarified. Results The results demonstrated that CTRP3 protects iBRB integrity and resists the vascular permeability induced by DR. Mechanistically, the administration of CTRP3 activates the AMPK signaling pathway and enhances the expression of Occludin and Claudin-5 (tight junction protein) in vivo and in vitro. Meanwhile, CTRP3 improves the injury of human retinal endothelial cells (HRMECs) induced by high glucose/high lipids (HG/HL), and its protective effects are AMPK-dependent. Conclusions In summary, we report, for the first time, that CTRP3 prevents diabetes-induced retinal vascular permeability via stabilizing the tight junctions of the iBRB and through the AMPK-dependent Occludin/Claudin-5 signaling pathway, thus critically affecting the development of NPDR. [ABSTRACT FROM AUTHOR]

Corrosion and crack defects often exist at the same time in pipelines. The interaction impact between these defects could potentially affect the growth of the fatigue crack. In this paper, a crack propagation method is proposed for pipelines with interacting corrosion and crack defects. The finite element models are built to obtain the Stress Intensity Factors (SIFs) for fatigue crack. SIF interaction impact ratio is introduced to describe the interaction effect of corrosion on fatigue crack. Two approaches based on extreme gradient boosting (XGBoost) are proposed in this paper to predict the SIF interaction impact ratio at the deepest point of the crack defect for pipelines with interacting corrosion and crack defects. Crack size, corrosion size and the axial distance between these two defects are the factors that have an impact on the growth of the fatigue crack, and so they are considered as the input of XGBoost models. Based on the synthetic samples from finite element modeling, it has been proved that the proposed approaches can effectively predict the SIF interaction impact ratio with relatively high accuracy. The crack propagation models are built based on the proposed XGBoost models, Paris' law and corrosion growth model. Sensitivity analyses regarding corrosion initial depth and axial distance between defects are performed. The proposed method can support pipeline integrity management by linking the crack propagation model with corrosion size, crack size and the axial distance. The problem of how the interaction between corrosion and crack defects impacts crack defect growth is investigated. [ABSTRACT FROM AUTHOR]

A method that employs the back propagation (BP) neural network is used to predict the growth of corrosion defect in pipelines. This method considers more diversified parameters that affect the pipeline's corrosion rate, including pipe parameters, service life, corrosion type, corrosion location, corrosion direction, and corrosion amount in a three-dimensional direction. The initial corrosion time is also considered, and, on this basis, the uncertainties of the initial corrosion time and the corrosion size are added to the BP neural network model. In this paper, three kinds of pipeline corrosion growth models are constructed: the traditional corrosion model, the corrosion model considering the uncertainties of initial corrosion time and corrosion depth, and corrosion model also considering the uncertainties of corrosion size (length, width, depth). The rationality and effectiveness of the proposed prediction models are verified by three case studies: the uniform model, the exponential model, and the gamma process model. The proposed models can be widely used in the prediction and management of pipeline corrosion. [ABSTRACT FROM AUTHOR]

The traditional set stability of Boolean networks (BNs) refers to whether all the states can converge to a given state subset. Different from the existing results, the set stability investigated in this paper is whether all states in a given initial set can converge to a given destination set. This paper studies the set stability and set stabilization avoiding undesirable sets of BNs and Boolean control networks (BCNs), respectively. First, by virtue of the semi-tensor product (STP) of matrices, the dynamics of BNs avoiding a given undesirable set are established. Then, the set reachability and set stability of BNs from the initial set to destination set avoiding an undesirable set are investigated, respectively. Furthermore, the set stabilization of BCNs from the initial set to destination set avoiding a given undesirable set are investigated. Finally, a design method for finding the time optimal set stabilizer is proposed, and an example is provided to illustrate the effectiveness of the results. [ABSTRACT FROM AUTHOR]

Due to the inconsistency and intermittence of solar energy, concentrated solar power (CSP) cannot stably transmit energy to the grid. Heat storage can maximize the availability of CSP plants. Especially, thermochemical heat storage (TCHS) based on CaO/CaCO3 cycles has broad application prospects due to many advantages, such as high heat storage density, high exothermic temperature, low energy loss, low material price, and good coupling with CSP plants. This paper provided a comprehensive outlook on the integrated system of CaO/CaCO3 heat storage, advanced reactor design, heat storage conditions, as well as the performance of CaO-based materials. The challenges and opportunities faced by current research were discussed, and suggestions for future research and development directions of CaO/CaCO3 heat storage were briefly put forward. [ABSTRACT FROM AUTHOR]

Lithium silicate (Li4SiO4) material can be applied for CO2 capture in energy production processes, such as hydrogen plants, based on sorption-enhanced reforming and fossil fuel-fired power plants, which has attracted research interests of many researchers. However, CO2 absorption performance of Li4SiO4 material prepared by the traditional solid-state reaction method is unsatisfactory during the absorption/regeneration cycles. Improving CO2 absorption capacity and cyclic stability of Li4SiO4 material is a research highlight during the energy production processes. The state-of-the-art kinetic and quantum mechanical studies on the preparation and CO2 absorption process of Li4SiO4 material are summarized, and the recent studies on the effects of preparation methods, dopants, and operating conditions on CO2 absorption performance of Li4SiO4 material are reviewed. Additionally, potential research thoughts and trends are also suggested. [ABSTRACT FROM AUTHOR]

The intermittent and inconsistent nature of some renewable energy, such as solar and wind, means the corresponding plants are unable to operate continuously. Thermochemical energy storage (TES) is an essential way to solve this problem. Due to the advantages of cheap price, high energy density, and ease to scaling, CaO-based material is thought as one of the most promising storage mediums for TES. In this paper, TES based on various cycles, such as CaO/CaCO3 cycles, CaO/Ca(OH)2 cycles, and coupling of CaO/Ca(OH)2 and CaO/CaCO3 cycles, were reviewed. The energy storage performances of CaO-based materials, as well as the modification approaches to improve their performance, were critically reviewed. The natural CaO-based materials for CaO/Ca(OH)2 TES experienced the multiple hydration/dehydration cycles tend to suffer from severe sintering which leads to the low activity and structural stability. It is found that higher dehydration temperature, lower initial sample temperature of the hydration reaction, higher vapor pressure in the hydration reactor, and the use of circulating fluidized bed (CFB) reactors all can improve the energy storage performance of CaO-based materials. In addition, the energy storage performance of CaO-based materials for CaO/Ca(OH)2 TES can be effectively improved by the various modification methods. The additions of Al2O3, Na2Si3O7, and nanoparticles of nano-SiO2 can improve the structural stabilities of CaO-based materials, while the addition of LiOH can improve the reactivities of CaO-based materials. This paper is devoted to a critical review on the development on thermochemical energy storage based on CaO-based materials in the recent years. [ABSTRACT FROM AUTHOR]