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The integration of high-penetration renewable energy sources is playing an increasingly important role in the frequency regulation of the power system. However, due to the varying output characteristics and response speeds of different renewable distributed energy resources (DERs), the overall response from the collective output of these distributed energy resources may not meet expected requirements and could have adverse effects on the grid. One drawback of traditional distributed coordinated control is its high communication requirements. This paper proposes using digital twin (DT) technology for the coordinated control of distributed energy resources, which can minimize the communication needs between various distributed energy resources while achieving coordinated control. Verification of the frequency support coordinated control strategy based on digital twin technology shows that it can effectively enhance the individual output characteristics and overall response of each distributed energy resource, providing effective support for grid frequency. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disorder characterized by progressive damage to both upper and lower motor neurons. Genetic factors are known to play a crucial role in ALS, as genetic studies not only advance our comprehension of disease mechanisms but also help unravel the complex phenotypes exhibited by patients. To gain further insights into the genetic landscape of ALS in the Chinese population and explore genotype–phenotype correlations among individuals, we conducted whole-genome sequencing to screen genes in 34 Chinese familial ALS (FALS) probands lacking the most common ALS-associated genes. Within this cohort, we identified a rare heterozygous missense mutation in the N-terminal domain of KIF5A (c.86A>G) in one of the probands. This finding is significant as mutations in the KIF5A gene have been implicated in ALS in European cohorts since 2018, predominantly characterized by C-terminal mutations. Analysis of the clinical phenotype within this familial lineage revealed a delayed onset of symptoms, an extended survival duration, and initial manifestations in both upper limbs. These observations underscore the clinical heterogeneity observed in ALS patients harboring KIF5A mutations. In conclusion, our study contributes to the growing body of evidence linking KIF5A to ALS and enhances our understanding of the intricate genetic landscape of this disease. [ABSTRACT FROM AUTHOR]

With the continuous improvement in production efficiency and quality of life, the requirements of electrical equipment for power quality are also increasing. Accurate detection of various power quality disturbances is an effective measure to improve power quality. However, in practical applications, the dataset is often contaminated by noise, and when the dataset is not sufficient, the computational complexity is too high. Similarly, in the recognition process of artificial neural networks, the local optimum often occurs, which ultimately leads to low recognition accuracy for the trained model. Therefore, this article proposes a power quality disturbance classification strategy based on the variational mode decomposition (VMD) and improved support vector machine (SVM) algorithms. Firstly, the VMD algorithm is used for preprocessing disturbance denoising. Next, based on the analysis of typical fault characteristics, a multi-SVM model is used for disturbance classification identification. In order to improve the recognition accuracy, the improved Grey Wolf Optimization (IGWO) algorithm is used to optimize the penalty factor and kernel function parameters of the SVM model. The results of the final case study show that the classification accuracy of the proposed method can reach over 98%, and the recognition accuracy is higher than that of the other models. [ABSTRACT FROM AUTHOR]

With the development of smart grids and new power systems, the combination of non-intrusive load identification technology and smart home technology can provide users with the operating conditions of home appliances and equipment, thus reducing home energy loss and improving users' ability to demand a response. This paper proposes a non-intrusive load decomposition model with a parallel multiscale attention mechanism (PMAM). The model can extract both local and global feature information and fuse it through a parallel multiscale network. This improves the attention mechanism's ability to capture feature information over long time periods. To validate the model's decomposition ability, we combined the PMAM model with four benchmark models: the Long Short-Term Memory (LSTM) recurrent neural network model, the Time Pooling-based Load Disaggregation Model (TPNILM), the Extreme Learning Machine (ELM), and the Load Disaggregation Model without Parallel Multi-scalar Attention Mechanisms (UNPMAM). The model was trained on the publicly available UK-DALE dataset and tested. The models' test results were quantitatively evaluated using a confusion matrix. This involved calculating the F1 score of the load decomposition. A higher F1 score indicates better model decomposition performance. The results indicate that the PMAM model proposed in this paper maintains an F1 score above 0.9 for the decomposition of three types of electrical equipment under the same household user, which is 3% higher than that of the other benchmark models on average. In the cross-household test, the PMAM also demonstrated a better decomposition ability, with the F1 score maintained above 0.85, and the mean absolute error (MAE) decreased by 5.3% on average compared with that of the UNPMAM. [ABSTRACT FROM AUTHOR]

In nature, some fish can adhere tightly to the surface of stones, aquatic plants, and even other fish bodies. This adhesion behavior allows these fish to fix, eat, hide, and migrate in complex and variable aquatic environments. The adhesion function is realized by the special mouth and sucker tissue of fish. Inspired by adhesion fish, extensive research has recently been carried out. Therefore, this paper presents a brief overview to better explore underwater adhesion mechanisms and provide bionic applications. Firstly, the adhesion organs and structures of biological prototypes (e.g., clingfish, remora, Garra, suckermouth catfish, hill stream loach, and goby) are presented separately, and the underwater adhesion mechanisms are analyzed. Then, based on bionics, it is explained that the adhesion structures and components are designed and created for applications (e.g., flexible gripping adhesive discs and adhesive motion devices). Furthermore, we offer our perspectives on the limitations and future directions. [ABSTRACT FROM AUTHOR]

Water electrolysis is a clean, non-polluting way of producing hydrogen that has seen rapid development in recent years. It offers the possibility of resolving the issue of excessive carbon emissions in conventional hydrogen production methods. In addition, waste heat recovery in hydrogen fuel cells can significantly increase the efficiency of energy use. Thus, to combine the electric power system, the hydrogen energy system, and the district heating system, this research suggests a novel optimal multi-energy complementary electricity–hydrogen–heat model. Rooftop photovoltaics, energy storage batteries, electric boilers, and hydrogen energy systems made up of hydrogen generation, hydrogen storage, and hydrogen fuel cells are all included in the suggested model. Furthermore, the electricity–hydrogen–heat system can be connected successfully using waste heat recovery in hydrogen fuel cells to create a coordinated supply of heat and power. In this work, the waste heat of hydrogen fuel cells is taken into account to increase the efficiency of energy use. To show the effectiveness of the suggested optimal multi-energy complementary model, many case studies have been conducted. [ABSTRACT FROM AUTHOR]

With the wide application of the gas-power system, gas-power coupling equipment such as gas turbines are gradually becoming widely used, and the problem of insufficient system reserve capacity needs to be solved. In order to improve the operational flexibility of the gas-power system, this paper combines the source side, the load side, and the energy storage side to propose a multi-type backup system, and constructs the source-load-storage multiple reserve capacity system of the gas-power system. Through the participation of gas turbine, steam turbine, interruptible load, and energy storage battery to provide reserve capacity, it can fully cope with the output fluctuation of the load side and source side and realize the coordinated operation of multiple resources to provide reserve capacity. In addition, the coordination of gas turbines and steam turbines can further improve the operation flexibility of the gas-power system. Through the example analysis, it was found that the proposed method reduced the total operating cost of the system by 10.6%. [ABSTRACT FROM AUTHOR]

Coordinated fault recovery is essential for the resilience enhancement of integrated electric and heating systems (IEHS) following natural catastrophes as the linkage of the power distribution system (PDS) and district heating system becomes tighter. DHS reconfiguration is a viable method for service restoration because it could adjust the energy between energy sources and achieve uninterrupted energy supplies. In this paper, a collaborative service restoration model considering DHS reconfiguration is proposed to achieve better recovery after natural disasters. DHS reconfiguration could guarantee interrupted power supply in non-fault regions by shifting electric loads between power sources and accomplish optimal service restoration by adjusting the power output of combined heat and power units. Numerous case studies are undertaken to demonstrate the performance of coordinated reconfiguration on resilience enhancement and to confirm the efficacy of the proposed paradigm. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy, particularly wind power, and the integration of different energy systems have become two major trends in the development of energy systems. In this context, this paper proposes a robust interval optimization method for combined heat and power dispatch (CHPD) to address the challenges associated with wind power accommodation. To enhance the flexibility of a power system and support the integration of wind power, flexibility resources from a district heating system are introduced in the economic dispatch. To ensure the safety and reliability of the CHPD results, a robust interval optimization method is employed. By considering a range of possible wind power outputs, the robust interval optimization method provides a robust and reliable dispatch plan that can accommodate uncertainties and fluctuations in wind power generation. To verify the effectiveness of the proposed model and method, case studies were conducted on a 6-bus electrical power system connected with a 6-node district heating system. The results demonstrate that the proposed approach can effectively enhance the integration of wind power and improve the overall reliability and flexibility of the energy system. [ABSTRACT FROM AUTHOR]

The harmonic and resonant characteristics of a multi-inverter grid-connected system can negatively affect power quality when weak grid conditions are present. In this paper, firstly, harmonic currents are modeled for the inverter, the correctness of low-frequency harmonics and high-frequency harmonics are verified in closed loop, and the characteristics of harmonic currents are analyzed when the parameters are varied. Secondly, the resonant characteristics of the inverter with feed-forward link are analyzed, and a multi-inverter grid-connected equivalent model based on the triple-decomposition conductance is developed and analyzed in conjunction with the resonant modal analysis method. Then, a harmonic resonance impedance reshaping method is proposed to suppress the background harmonics using improved weighted average current control (WACC), suppress the system resonance based on the point of common coupling (PCC) paralleling virtual conductance method, and improve the stability margin of the system combined with impedance reshaping resonance suppression method. Finally, simulations and comparison of results with different suppression methods verify the superiority and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A combined heat and power virtual power plant (CHP-VPP) can effectively control the distributed resources in an electric–thermal coupling system and solve the problem of lack of flexibility caused by large-scale renewable energy grid connection. Similar to the optimal reconfiguration of distribution network topology by operating switches, the district heating system is also equipped with tie and sectionalizing valves to realize the optimal adjustment of district heating network (DHN) topology, which provides an economical and effective method for improving the power system's flexibility. Based on this, this paper proposes a CHP-VPP economic scheduling model considering reconfigurable DHN. Firstly, the energy flow model is introduced to reduce the computational complexity. Secondly, adaptive robust optimization solved by the column-and-constraint generation algorithm is used to settle the randomness of wind power to ensure that the results are feasible in all worst scenarios. Finally, the feasibility of the proposed model is illustrated by case studies based on an actual CHP-VPP. The results show that compared with the reference case, considering the reconfigurability of DHN in the CHP-VPP optimization scheduling process can reduce the cost by about 2.78%. [ABSTRACT FROM AUTHOR]

With the dramatic increase in the number of mobile users and wireless devices accessing the network, the performance of fifth generation (5G) wireless communication systems has been severely challenged. Reconfigurable intelligent surface (RIS) has received much attention as one of the promising technologies for the sixth generation (6G) due to its ease of deployment, low power consumption, and low price. RIS is an electromagnetic metamaterial that serves to reconfigure the wireless environment by adjusting the phase, amplitude, and frequency of the wireless signal. To maximize channel transmission efficiency and improve the reliability of communication systems, the acquisition of channel state information (CSI) is essential. Therefore, an effective channel estimation method guarantees the achievement of excellent RIS performance. This survey presents a comprehensive study of existing channel estimation methods for RIS. Firstly, channel estimation methods in high and low frequency bands are overviewed and compared. We focus on channel estimation in the high frequency band and analyze the system model. Then, the comprehensive description of the different channel estimation methods is given, with a focus on the application of deep learning. Finally, we conclude the paper and provide an outlook on the future development of RIS channel estimation. [ABSTRACT FROM AUTHOR]

In the task of text sentiment analysis, the main problem that we face is that the traditional word vectors represent lack of polysemy, the Recurrent Neural Network cannot be trained in parallel, and the classification accuracy is not high. We propose a sentiment classification model based on the proposed Sliced Bidirectional Gated Recurrent Unit (Sliced Bi-GRU), Multi-head Self-Attention mechanism, and Bidirectional Encoder Representations from Transformers embedding. First, the word vector representation obtained by the BERT pre-trained language model is used as the embedding layer of the neural network. Then the input sequence is sliced into subsequences of equal length. And the Bi-sequence Gated Recurrent Unit is applied to extract the subsequent feature information. The relationship between words is learned sequentially via the Multi-head Self-attention mechanism. Finally, the emotional tendency of the text is output by the Softmax function. Experiments show that the classification accuracy of this model on the Yelp 2015 dataset and the Amazon dataset is 74.37% and 62.57%, respectively. And the training speed of the model is better than most existing models, which verifies the effectiveness of the model. [ABSTRACT FROM AUTHOR]

Structural colors produced by light manipulating at subwavelength dimensions have been widely studied. In this work, a metasurface-based subtractive color filter (SCF) is demonstrated. The color display of the SCF is confirmed by finding the complementary color of colors filtered by SCF within the color wheel. In addition, two artificial neural network (ANN) models are utilized to accelerate the metasurface forward prediction, and the long short-term memory (LSTM) shows much better performance than traditional multilayer perceptron (MLP). Meanwhile, we train an inverse ANN model established with LSTM to recover the optimal geometric parameter combinations of the meta-atoms. With the variation of the geometric parameters of meta-atoms, versatile color displays of structural colors are realized. The metasurface we propose exhibits good performance of transmissive-type structural color in visible range. The work provides a method for high-efficiency geometric parameter prediction, and paves the way to nanostructure-based color design for display and anticounterfeiting applications. [ABSTRACT FROM AUTHOR]

Salicylic acid (SA) is a stress hormone synthesized in phenylalanine ammonia-lyase (PAL) and the branching acid pathway. SA has two interconvertible forms in plants: SAG (SA O-β-glucoside) and SA (free form). The molecular mechanism of conversion of SA to SAG had been reported previously. However, which genes regulate SAG to SA remained unknown. Here, we report a cytoplasmic β-glucosidase (β-Glu) which participates in the SA pathway and is involved in the brown hull pigmentation in rice grain. In the current study, an EMS-generated mutant brown hull 1 (bh1) displayed decreased contents of SA in hulls, a lower photosynthesis rate, and high-temperature sensitivity compared to the wild type (WT). A plaque-like phenotype (brown pigmentation) was present on the hulls of bh1, which causes a significant decrease in the seed setting rate. Genetic analysis revealed a mutation in LOC_Os01g67220, which encodes a cytoplasmic Os1βGlu4. The knock-out lines displayed the phenotype of brown pigmentation on hulls and decreased seed setting rate comparable with bh1. Overexpression and complementation lines of Os1βGlu4 restored the phenotype of hulls and normal seed setting rate comparable with WT. Subcellular localization revealed that the protein of Os1βGlu4 was localized in the cytoplasm. In contrast to WT, bh1 could not hydrolyze SAG into SA in vivo. Together, our results revealed the novel role of Os1βGlu4 in the accumulation of flavonoids in hulls by regulating the level of free SA in the cellular pool. [ABSTRACT FROM AUTHOR]

A three-phase three-wire voltage source converter (VSC) can produce third harmonics when it is operated under an unbalanced condition. It is essential to understand the mechanism of the production of this third harmonic and to assess its impact on power systems. Therefore, this paper presents an analytical model of the VSC under the unbalanced condition through mathematical derivations, and the final model is a coupled Thevenin circuit. The proposed model allows for direct computation of the non-characteristic third harmonics through harmonic power flow studies. The results show that VSC under unbalanced conditions emits both positive-sequence and negative-sequence third harmonics, and that the positive-sequence third harmonic is much larger than the negative-sequence third harmonic. It also shows that the unbalanced level and the size of the dc-link capacitor are critical to the level of non-characteristic third harmonics. The correctness of the proposed model and its application on noncharacteristic third harmonic evaluations have been verified using EMT simulations. [ABSTRACT FROM AUTHOR]

We reported the second- and third-order temporal interference of two non-degenerate pseudo-thermal sources in a nitrogen-vacancy center (NV - ). The relationship between the indistinguishability of source and path alternatives is analyzed at low temperature. In this article, we demonstrate the switching between three-mode bunching and frequency beating effect controlled by the time offset and the frequency difference to realize optical demultiplexer. Our experimental results suggest the advanced technique achieves channel spacing and speed of the demultiplexer of about 96% and 17 ns, respectively. The proposed demultiplexer model will have potential applications in quantum computing and communication.