bluuebunny/crossref_metadata_2025 huggingface dataset:
Tirasemtiv enhances submaximal muscle tension in an Acta1:p.Asp286Gly mouse model of nemaline myopathy
Authors: Galli Ricardo A. , Borsboom Tamara C. , Gineste Charlotte , Brocca Lorenza , Rossi Maira , Hwee Darren T. , Malik Fady I. , Bottinelli Roberto , Gondin Julien , Pellegrino Maria-Antonietta , de Winter Josine M. , Ottenheijm Coen A.C.
Published: February 2024

Nemaline myopathies are the most common form of congenital myopathies. Variants in ACTA1 (NEM3) comprise 15–25% of all nemaline myopathy cases. Patients harboring variants in ACTA1 present with a heterogeneous disease course characterized by stable or progressive muscle weakness and, in severe cases, respiratory failure and death. To date, no specific treatments are available. Since NEM3 is an actin-based thin filament disease, we tested the ability of tirasemtiv, a fast skeletal muscle troponin activator, to improve skeletal muscle function in a mouse model of NEM3, harboring the patient-based p.Asp286Gly variant in Acta1. Acute and long-term tirasemtiv treatment significantly increased muscle contractile capacity at submaximal stimulation frequencies in both fast-twitch extensor digitorum longus and gastrocnemius muscle, and intermediate-twitch diaphragm muscle in vitro and in vivo. Additionally, long-term tirasemtiv treatment in NEM3 mice resulted in a decreased respiratory rate with preserved minute volume, suggesting more efficient respiration. Altogether, our data support the therapeutic potential of fast skeletal muscle troponin activators in alleviating skeletal muscle weakness in a mouse model of NEM3 caused by the Acta1:p.Asp286Gly variant.
Design and feasibility analysis of magnetorheological flexible joint for upper limb rehabilitation
Authors: Li Ganglin , Yang Jiabin , Zhang Guang , Ouyang Qing , Hu Hongsheng
Published: February 2024

Traditional upper limb rehabilitation robots have several disadvantageous. For example, they can only conduct rehabilitation training along predetermined trajectories, their safety systems are unreliable, and they lack the ability to adjust or train the affected limb based on the expected torque of the human body. To overcome these limitations, this study proposes a flexible safety system for joint rehabilitation utilising magnetorheological (MR) fluid. MR damper inverters offer significant advantages, including high torque, rapid response, controllable flexibility, and safety assurance. The range of motion trajectories can be adjusted using a four-lever hinge mechanism. The necessary driving force is provided by the motor actuator, and the MR damper imparts flexibility and variable damping characteristics to the output torque. The system uses a force/position impedance safety-control method, and using an internal position closed-loop controller, the MR upper limb rehabilitation flexible joint guides the affected limb to a safe position. A simulation is performed to verify the accuracy of the system’s motion torque and position. Extensive research has been conducted on the safe rehabilitation outcomes of the upper limb rehabilitation system under three working conditions (step, incremental, and equation) involving the interaction moment of the affected limb. Simulation and experimental results demonstrate that the MR damper effectively controls the upper limb rehabilitation system to achieve the desired results, even when subjected to incremental and abrupt interaction forces from the patient. The tracking accuracy error remains within the range of 3%–7% for a certain period, confirming the safety and feasibility of the MR-based upper limb rehabilitation robot design.
Finslerian wormhole solution in the framework of modified gravity
Authors: Malligawad Manjunath , Narasimhamurthy S K , Nekouee Z , Mallikarjun Y Kumbar
Published: February 2024

This article investigates the properties of a wormhole model in a specific gravity theory, namely f(Ric, T) = Ric + 2λ
T. The wormhole solution is analyzed using an exponential shape function. The study examines various parameters, such as density, radial pressure, transverse pressure, equation-of-state parameters, and energy conditions, within the framework of deformed gravity. The research emphasizes the influence of the parameter λ on energy condition violations and the equilibrium state of the Finslerian wormhole solution. These effects are attributed to anisotropic and hydrostatic forces present in modified gravity. The study demonstrates that the gravity model effectively captures the characteristics of wormholes within the Finslerian space-time. Additionally, the identified features of the wormhole are utilized to visualize its structure by creating a three-dimensional representation of the embedded surface. In summary, this research contributes to understanding wormholes in modified gravity theories, highlighting the importance of the parameter λ in determining their behavior and properties.
A simple probabilistic neural network for machine understanding
Authors: Xie Rongrong , Marsili Matteo
Published: February 2024

We discuss the concept of probabilistic neural networks with a fixed internal representation being models for machine understanding. Here, ‘understanding’ is interpretted as the ability to map data to an already existing representation which encodes an a priori organisation of the feature space. We derive the internal representation by requiring that it satisfies the principles of maximal relevance and of maximal ignorance about how different features are combined. We show that, when hidden units are binary variables, these two principles identify a unique model—the hierarchical feature model—which is fully solvable and provides a natural interpretation in terms of features. We argue that learning machines with this architecture possess a number of interesting properties, such as the continuity of the representation with respect to changes in parameters and data, the possibility of controlling the level of compression and the ability to support functions that go beyond generalisation. We explore the behaviour of the model with extensive numerical experiments and argue that models in which the internal representation is fixed reproduce a learning modality which is qualitatively different from that of traditional models, such as restricted Boltzmann machines.
Effect of v-PP/r-PET composites filament on specific density, structural and mechanical properties
Authors: Pérez-Herbert C A , González-Hernández A , Morales-Cepeda A B , Hernández-Castillo Y , Barragán-Ramírez R , Bautista-García R , Aguilar-Rodríguez M D , Gamboa-Soto F
Published: February 2024

Polypropylene (PP) and its derivatives are widely used to produce molded plastics due to their lightweight and impact resistance. Polyethylene terephthalate (PET) is considered one of the essential engineering polymers for its applications, widely used to manufacture containers for liquids such as water, oil, etc. The compatibility of PP/PET increases the impermeability, thermic and mechanical properties. The present study shows the blend binary of recycling PET as refill into a v-PP matrix extruded in filament analyzing the specific density and XRD. The result XRD pattern exhibited the presence of miscibility of monoclinic α-form phase v-PP/r-PET peaks predominantly attributed to the crystallinity of baseline material. Likewise, crystallinity, and amorphous peaks are attributed to the semi-crystalline phase of r-PET with a triclinic structure. In the impact strength test, all specimens tested showed partial failure on the surface, majorly presenting cracks, and fractures.
Analysis of Mexican Amber and Natural Resins Using Fourier Transform Infrared Spectroscopy (FTIR) and Raman Spectroscopy
Authors: Vazquez-Bautista G , Zapata Torres M , Chalé Lara F
Published: February 2024

Amber is a semi-precious gemstone, it is a natural resin formed as a fossil and consists of labdanoid diterpenes. This study involves a compositional analysis of Mexican amber using FTIR Spectroscopy and Raman Spectroscopy, comparing it with resins mixed with sulphur, copal, and rosin, to determine the main spectral features of Mexican amber and identify differences from other fake amber resins. Samples of yellow, red, and green amber were utilised. The equipment used included an ATR FTIR spectrometer and a Raman spectrometer with a 785 nm laser source. In the FTIR analysis, the results reveal that the colour variations in Mexican amber do not reflect structural differences. The ester group is identified in amber through the C=O carbonyl bond at 1727 cm-1, confirmed by a band at 1243 cm-1 and a set of bands between 1200-1060 cm-1 corresponding to C-O-H and O-C-C bonds, respectively. The range between 1000-600 cm-1 is identified as the most crucial for distinguishing authentic amber and determining whether the resin is young or fossilised. In Raman, the main peaks to identify amber are at 1646 cm-1 and 1450 cm-1 with which the ratio of intensities was quantified to determine the maturity of the fossil resin.
Study of cerium adsorption in graphene oxide decorated with ZnO by X Ray Fluorescence
Authors: Hernández Castillo Yarazett , Nava Diguero Pedro , González Hernández Andrés , Caballero Briones Felipe
Published: February 2024

With the goal of recover strategic materials contained in spent electronic and electric devices; this work focuses on the recovery of Ce from Ce synthetic solutions, by using graphene oxides-based (GO) adsorbent materials. Graphene oxide is synthesized by the Hummers’ method and decorated with zinc oxide (ZnO-GO). After that, adsorption experiments at pH 2 and 6 were carried out using Ce(NO3)3 aqueous solutions with concentrations of 100-1000 mg/L. Compounds of GO and ZnO-GO with and without Ce were analysed by Raman where changes of GO structure were observed; by FTIR spectroscopy, after decoration, the reduction of COOH, C=O, C-OH and C-O groups were observed and after the adsorption the decrease of COOH and C-O groups as well as the presence of NO3 and CH2CH3 groups were detected. TEM micrographs show particles adsorbed in GO sheets, and XRF analysis helped to quantify cerium from solutions after adsorption. The ZnO-GO, obtained at pH 6, has higher Ce adsorption (3837.5 mgce/mgads) and highest percentage of Ce removal (43% of cerium); It concludes that ZnO improve the Ce adsorption, however, the adsorption mechanisms of Ce onto the graphene network are unknown, and Zn-Ce ion exchange was found depending on the pH.
First-principles simulations of magnetic properties of Co- and Ni-doped ZnSe
Authors: Jafarova Vusala N , Abdurahmanova Ulkar S
Published: February 2024

We purposed to analyze the theoretical ab initio study of ferromagnetism and to estimate Curie temperature of Co2+ and Ni2+ 3d transition metal (TM) ions doped Zn1-x
TM
x
Se compounds for 12.5 % and 6.25 % concentrations of impurity TM(Co, Ni) atoms. The calculations are carried out using the norm-conserving Fritz-Haber-Institute ionic pseudopotentials based on density functional theory within the local spin density approximation and Hubbard U (U(Znd)=4.5 eV; U(Sep)=3.8 eV) corrections. The analysis of the total and partial electron density of states shows the half-metallic ferromagnetic behavior with a half-metallic bandgap. The theoretically obtained total magnetic moments of TM(Co, Ni) doped Zn1-x
TM
x
Se systems are equal to 3 μB and 4 μB, correspondingly.
Deposition of CsFAPbI3 thin films by single source flash evaporation
Authors: Hernández M , Pacio M , Juárez H , Serrano L E , Pacio A
Published: February 2024

Formamidinium-cesium lead iodide (CsFAPbI3) is a promising perovskite material for photovoltaic applications with a suitable bandgap of 1.45 eV and excellent optoelectronic properties. In this work, CsFAPbI3 perovskite thin films were deposited by single-source flash evaporation on glass substrates using presynthesized crystalline powders as the source material in which the source challenges of simultaneously controlling the evaporation of organic and inorganic sources are avoided. The structural properties of the powders were evaluated by X-ray diffraction, thermal properties by TGA analysis and optical properties by UV-Vis absorption. We find that the formation of mixed phases is inevitable in flash evaporation of thin films. This undesirable phase could reduce the optical bandgap and the thermal stability which can affect the performance of the thin films. To obtain the cubic phase, a post-annealing process should be employed. We carried out structural, morphological, and optical characterizations to determine the phase purity in the films. These preliminary results suggest that flash evaporation deposition parameters can be optimized to understand the formamidinium evaporation and condensation dynamics for improve the properties of CsFAPbI3 perovskite thin films.
Obtaining and characterization of MAPbSnBr3 perovskite crystals trough AVC method
Authors: Pacio Castillo A. , Medina Velazquez D. Y. , Pacio Castillo M. , Reyes Miranda J. , Hernández M , Serrano De la Rosa L. E. , Antonio Hernández C. , Cortez Santiago A.
Published: February 2024

The obtaining tin-based perovskite from solution is challenging due to the rapid and uncontrollable crystallization of tin compared to lead-based perovskite. Another challenge is to reduce the use of lead to avoid poisoning. In this sense, Sn-based perovskite compounds such as CsSnBr3 have attracted great attention as an effective replacement, but current photovoltaic devices still problems of low efficiency and instability chemistry. The band gap of ASnX3 compounds is between 1.2 and 1.4 eV, being the ideal range for maximum theoretical efficiency in a solar cell. In contrast, APbX3 compounds have band gaps in the range of 1.45 to 1.6 eV. We synthesize MAPbSnBr3 perovskite crystals through the AVC method. The structural properties of the crystals were obtained by X-ray diffraction, Raman spectroscopy, these shown the presence of Sn and Pb in the crystals obtained, and the optical properties by UV-Vis absorption and photoluminescence spectroscopy obtaining the variation of the band gap in the perovskite.

The results obtained from the MAPbSnBr3 perovskite (such as the band gap, absorption spectrum and crystal lattice) meet the necessary requirements for its possible application in photovoltaic devices. It is shown that it is possible to obtain MAPbSnBr3 crystals with a lower amount of Pb and how the bandgap is affected by varying these elements, for their possible application in solar cells.
Study on the effect of pressure in humid air dehumidificationournal
Authors: Wang Xuefei , Wang Han
Published: February 2024

In this paper, there are problems such as large energy consumption and complex system in the field of condensation dehumidification. It is found that increasing pressure can strengthen the effect of condensation dehumidification, simplify the system and reduce energy consumption. So this paper simulates the condensation and dehumidification process of humid air in horizontal pipe under positive pressure. The results show that the dehumidification capacity increases by 25%∼30% when the pressure increases by 100kPa on average. The increase of pressure has little effect on the heat transfer coefficient, but the increase of humidity increases the heat transfer coefficient more obvious. When the humidity of wet air increases by 20%, the heat transfer coefficient increases by 18% ∼ 33%. The dehumidification capacity and heat transfer coefficient increase with the increase of pipe diameter and fluid flow rate.
Effects of different heating modes on room temperature and heat consumption of existing residential buildings in rural areas
Authors: Feng Shuaibin , Qi Yudong , Gao Guoxu
Published: February 2024

Affected by economic conditions, living habits and other factors, residents in rural areas have a high sense of self-regulation when heating. Rural residents often choose the corresponding heating mode according to the specific situation. This paper takes an existing building in the countryside of Zhangjiakou as the research object. The room temperature change and heat consumption under different heating modes are simulated and analyzed. The results show that the temperature of each room is higher than that of the natural room temperature under different heating modes. Even if the room is not heated during the day, the room temperature can be maintained at more than 10 °C. When the heating temperature is set to 18°C in the active state and 14°C in the sleeping state, the heat consumption can be reduced by up to 32.05% in each heating mode. The heat consumption of each mode is comparatively low, and the room temperature in each time period is similarly lower, when the heating temperature of all states is set to 14 °C.
Multi-scenario research on the low-carbon transition in energy-deficient cities-view from the power supply side
Authors: Zhu Zhifang , Wang Wenxiu , Lin Zihan , Dong Hong , Gao Yanna , Hu Liujun , Lu Juntong , Hao Weitao
Published: February 2024

Cities are the places where power supply demand is highly concentrated. How to ensure power supply security while realizing low-carbon transition is the key challenge faced by the construction of new power systems. In large cities with a shortage of local power generation resources, this problem is particularly prominent. The study takes Guangzhou city as a case study area, which has the typical characteristics of “serious energy shortage and extremely high-power load density” in China. This study explores the differences in power supply capacity, structure, carbon emissions, and power supply costs under the six different scenarios set up from the power supply side for future power supply structures. The optimal power supply modes have been matched for cities with different development characteristics and needs. The change in power supply structure and the realization path under the optimal power supply modes are discussed. The results show that the power supply capacity of Guangzhou is constantly improving under different scenarios, with the highest self-sufficiency rates of power production capacity and power production quantity reaching 80% and 50%, respectively, by 2030. Despite this, Guangzhou still does not have the basic conditions for building a new power supply system through the development of local high-proportion renewable energy only due to the limitation of resource endowment. The combination with increasing the ratio of renewable energy in outsourcing power is an inevitable choice for low-carbon transition for the city. This study provides a new idea on how to build a new power supply system for an energy shortage city. It can be used as a reference for safe power supply and low-carbon transition for the power supply sectors of other cities.
Microgrid energy management strategy using deep learning neural network
Authors: Li Jiageng , Wei Bin , Han Xiaoqing , Qiao Sen
Published: February 2024

Under the background of a large number of uncertain new energy connected to microgrids, traditional model driven methods could be hard to address the speed problem of microgrid optimization. Therefore, we come up with a data-model hybrid driven microgrid scheduling strategy. This strategy includes three stages: day-ahead dispatching, preparing for day-in dispatching and day-in dispatching. In the day-ahead dispatching stage, basing on the day-ahead forecast data of renewable energy, the mixed integer linear programming (MILP) is used to solve the day-ahead dispatching plan. In the preparing for intraday scheduling stage, a neural network is introduced as the day scheduling model, new energy power and load power regard as inputs to the neural network, controllable units in the microgrid as outputs to train the neural network. During the intraday scheduling phase, neural networks are used to optimize the scheduling of controllable units in microgrids based on ultra short term predictions and pre day predictions. Finally, the effectiveness of the raised method was verified through numerical analysis.
Study of hybrid energy storage system with energy management for electric vehicle applications
Authors: Shi Zhiqiang , Lu Renxiang
Published: February 2024

This paper conducts an in-depth study on the on-board energy storage system for electric vehicles. We analyze the advantages and disadvantages of domestic and foreign energy storage systems including battery, flywheel, superconductor and supercapacitor. We propose a hybrid energy storage system composed of battery and supercapacitor as the on-board power supply system. It adopts a two-phase staggered parallel bidirectional DC-DC converter as the main control circuit of the storage system. And we adopt the power outer loop and current inner loop control strategy. Then the rate limiter prevents the sudden change of battery power and realizes that the instantaneous power is provided by the supercapacitor individually. The purpose is to extend the battery life and achieve the purpose of reasonable and efficient utilization of energy. Finally, the simulation verification is carried out by Matlab/Simulink. And the results show that the energy management strategy is more efficient for both power and energy management, which meets the design expectation and achieves better experimental results.
Research on energy purchase combination strategies for multiple energy commercial buildings considering multistage market uncertainties
Authors: Xu Haowen , Tang Jun , Huang Qifeng , Zhuang Zhong , Duan Meimei , Sheng Ju
Published: February 2024

With the gradual development of the power markets, various types of uncertainty are gradually increasing. The overlapping effects of various uncertainties have a significant impact on the operational economy of multiple energy commercial buildings (MECB) relying on various energy sources. MECB can purchase electricity from multiple stages of the market, such as spot from medium to long term and the market electricity price risk varies at different stages. Therefore, this paper investigates the energy purchasing strategies of MECB in multistage markets, taking into account various uncertainties. Considering the actual operational characteristics of MECB, this paper proposes a MECB low-carbon economic optimization model and establishes an energy purchase strategy model for MECB under various risk scenarios based on random optimization theory. Research has found that in scenarios with higher risks, MECB will participate more conservatively in the market. By simultaneously participating in the medium to long-term market and spot market, MECB can effectively avoid the cost risks brought about by various uncertainties.
Long and short-term power supply and demand forecasting based on time series analysis under high proportion clean energy integration
Authors: Ma Luyu , Yang Jianhua , Peng Shuxi , Jiang Yanni
Published: February 2024

This paper focuses on the prediction of power supply and demand in the electric power system under a high proportion of clean energy integration using time series analysis. Firstly, the impact of clean energy integration on power supply and demand is analyzed, taking into account factors such as the volatility and seasonality of renewable energy sources. A case study is conducted in Region A, which comprises four areas in China, to forecast the power supply and demand in the electric power system. In terms of power demand, we employ two commonly used methods in time series analysis, namely SARIMAX and factor decomposition, to establish a comprehensive forecasting model. These methods are applied from both short-term and long-term perspectives to analyze the monthly maximum electricity demand of users, aiming to accurately predict power demand under a high proportion of clean energy integration. As for power supply, we utilize the least squares method to regressively fit the installed capacity of energy sources and analyze future trends. Through the predictions of both demand and supply, the stable operation of the power system is ensured.
Research on economic dispatching strategy of electric vehicles participating in frequency regulation ancillary service
Authors: Wu Zhouyang
Published: February 2024

Electric vehicles (EVs) are demand-side resources capable of rapid power adjustments. When clustered as aggregators in frequency regulation (FR) services, EVs have the advantages of low deployment cost and fast response speed. This passage studies description of uncertain scenarios when aggregators participate in FR services. With a focus on the optimization of charging and frequency reserve capacity for aggregators participating in FR, a conversion method from FR signal sequence to FR demand is proposed based on historical data of FR signals. The intent is to address the uncertainty of both system FR and load electricity consumption. This passage provides an uncertain characterization of FR demand, which performs as a key indicator of proposed economic dispatching strategy. The result shows how different levels of risk appetite affects the real-time responsiveness, thus mentoring the strategic decision of how much reserve capacity should be provided for FR.
Research on load curve fitting method based on K-means algorithm
Authors: Mi Ning , Qiao Ning , Zhang Chao , Zhang Jisheng , Yin Guolong
Published: February 2024

Some areas of China are affected by the fluctuation of new energy output and load, and the power supply as a whole presents an unbalanced phenomenon of abundant electricity supply but shortage of power supply. To understand the characteristics of the load electricity consumption curve more accurately, this paper proposes a method of fitting the load electricity consumption curve based on K-mea ns algorithm. First, analyze the characteristics of the load electricity consumption based on the industry subdivision, and build the load electricity consumption characteristic index system. Then, the k-mea ns cluster analysis is carried out based on the characteristics of the load power consumption curve of the subdivided industries to determine the number of clusters, and the curve fitting and deviation test are carried out for each cluster group. This paper carries out practical analysis and theoretical research based on the data of typical industry load power consumption curve in Ningxia.
Design of a high-precision current source system for tunable laser driving
Authors: Gui Peng , Zhao Chuang , Zhao Lei , Liu Wenyang , Chen Zitian , Mu Cheng , Zhang Yuhuan
Published: February 2024

Fiber Bragg Grating (FBG), which is an Optical Fiber Sensor with high sensitivity, light weight, and strong anti-interference ability, can realize the measurement of physical quantities, such as temperature and strain. The sensor network formed by FBG sensors is through wavelength division multiplexing, which greatly reduced the difficulty of sensor wiring. Therefore, FBG sensors are widely used in sensing fields such as aerospace, bridges and tunnels. As a wavelength-modulated Optical Fiber Sensor, FBG’s sensing accuracy depends not only on the performance of the laser, but also on the stability of the driving current. In this paper, a high-precision current source system for laser S7500 modulation drive is designed, with a resolution of output current is higher than 2uA. and the laser S7500 is continuously linearly scanned at 20pm intervals in the wavelength range of 1527nm to 1567nm. The wavelength accuracy of the output optical signal is better than 2pm. The test results prove that the system has the advantages of high modulation speed, good stability and high reliability, and can be applied to high-precision FBG sensor networks.
Multi-objective reactive power optimization for low voltage distribution networks based on improved marine predator algorithm
Authors: Qiu Jiyang , Lan Danyang , Zhang Yanli , Li Han
Published: February 2024

A large number of distributed photovoltaic generators are constructed in the 0.4 kV distribution network, which causes the distribution network’s power flow and voltage amplitude to change, and brings new challenges to the reactive voltage control. Firstly, a reactive power adjustment model is invented, and the objective of the optimization is to minimize the distribution network line losses and node voltage shifts. Secondly, the standard marine predator algorithm is improved by using Bernoulli mapping, nonlinear attenuation weight function, and elite replacement strategy, and the model is solved by the improved algorithm. The results of the example optimization of a 21-node low-voltage distribution network show that the presented reactive power adjustment method can control the voltage point within a reasonable range and reduce the line loss rate. The improved marine predator algorithm has better global optimality finding and faster convergence than traditional intelligent algorithms.
Hybrid attention-based improved temporal convolutional BiGRU approach for short-term load forecasting
Authors: Xie Yu , Zeng Pan , Chen Jiakun
Published: February 2024

Accurate load forecasting can ensure the safe and reliable operation of power systems, reduce generation costs, and improve economic efficiency. To improve the accuracy and performance of short-term load forecasting, this paper proposes a hybrid short-term load forecasting method composed of an improved temporal convolutional network (TCNPlus) with an attention mechanism and a bidirectional gated recurrent unit (BiGRU). Firstly, the collected pre-processed training data is reconstructed using a fixed-length sliding window. Secondly, using the self-attention mechanism (SA) in the improved TCN to further enhance the weight of key features, and introducing residual connections can allow the input to propagate forward faster and improve the representation ability and efficiency of error backpropagation of the network, to eliminate the impact of interference signals. Finally, BiGRU is used to learn the forward and backward dependencies of the load sequence in both directions and predict the true load value. Based on the real load data of a national power grid in South China, through experimental comparison of multiple models, the results show that this model still has higher short-term load forecasting accuracy with fewer input features.
Error prediction of a capacitor voltage transformer using dilated causal convolution and LSTM
Authors: Wang Shoukun , Dai Rui , Yang Lin , Song Zhen , Zhang Wenting , Wang Qinghao , Xiangli Ze , Ge Chunmeng
Published: February 2024

To timely and accurately complete the error prediction of capacitor voltage transformers, this paper proposes an error prediction algorithm for capacitor voltage transformers that combines dilated causal convolution and LSTM. The algorithm is divided into two parts: one part updates the state of the input sequence using LSTM, while the other part extracts features through dilated causal convolution, maintaining data causality about the original sequence. Finally, the outputs of these two parts are combined to make the obtained sequence feature information more accurate and enriched. Experiments show that the MSE between the error prediction results obtained by this method and the actual error samples of capacitor voltage transformers is only 0.0003, which can accurately and efficiently complete the error prediction of capacitor voltage transformers.
Electromagnetic interference compensation method of TMR current sensor
Authors: Chen Zhaohui , Chen Xu , Ding Xiaobing , Wei Liu , Tang Tao , Zhou Yu , Yu Weiguo
Published: February 2024

TMR current sensor has excellent characteristics such as high sensitivity, good temperature characteristics, and wide dynamic range, which can meet the new needs of smart grid development. However, the measured value of the output of the TMR current sensor changes with the change in the spatial magnetic field strength. External electromagnetic interference will bring large errors and DC bias to the measurement of the sensor, resulting in a narrowing of the measurement current range. Therefore, an electromagnetic interference compensation method for TMR current sensor is proposed. Two TMR chips are used to measure the synthetic magnetic field signal and the interference magnetic field signal, respectively. Then the output signals of the two TMR chips are compensated and reduced by the signal conditioning unit. The final output analog signal is the magnetic field intensity signal generated by the current of the line to be tested without interference. Finally, the effectiveness of the proposed method is verified by field tests.
Power quality interval grading evaluation method of AC/DC distribution network considering source-load weighting and voltage coupling
Authors: Wang Lianhui , Lin Yan , Xiang Yang , Zhang Yan , Lan Jinchen , Wang Jiang , Qin Liang
Published: February 2024

In the context of the ‘dual carbon’ goal, the integration of renewable energy sources has a significant impact on distribution systems, while the substantial integration of DC loads and photovoltaic power has led to a progressive transition of conventional distribution networks towards hybrid AC-DC distribution networks in the field of electrical engineering. However, this shift has brought about more formidable power quality challenges within the power industry. To address these emerging power quality issues, we propose a novel power quality interval grading evaluation method for AC/DC distribution networks considering source-load weighting and voltage coupling. Firstly, the voltage acquisition data is meticulously decoupled to disentangle the interdependencies. Secondly, the power quality evaluation system of the AC/DC distribution network is established. Considering the influence of different access source-load types on each node, the subjective weight is determined by source load weighted two-tuple linguistic analytic hierarchy process (AHP), the objective weight is determined by the entropy weight method, and the idea of using game equilibrium algorithm to obtain comprehensive weight to balance the error of single weight on evaluation result is put forward. Then, the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) of interval number improvement is used to classify and evaluate the power quality index to make up for the shortcomings of the single-point sampling method. Finally, a more accurate and comprehensive power quality evaluation result is obtained based on a practical example.
Transformer noise prediction method based on CEEMDAN-VMD-TCN
Authors: Liu Ping , Zhang Ying , Shi Jianbo , Guo Shinan
Published: February 2024

To solve the problem of weak precision of traditional prediction methods in transformer noise prediction, a novel prediction approach by CEEMDAN-VMD-TCN is presented in this paper. Firstly, the noise sequence is preliminarily disaggregated by Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN). Then, the fuzzy entropy value of each modal component is calculated. The genetic algorithm is adopted to find the optimum parameter group of Variational Mode Decomposition (VMD), with which the components with higher fuzzy entropy values are decomposed again by VMD. Finally, the decomposed components and related feature sequences are input into the Temporal Convolutional Network (TCN) for prediction. The prediction results are superimposed and reconstituted to yield the end results. The results show that the proposed method has greater prediction accuracies compared with other prediction ways.
A novel driver circuit of SiC MOSFET for suppressing crosstalk voltage in bridge circuit
Authors: Hao Jiade , Meng Runquan , Ren Yuhan , Li Ruishu
Published: February 2024

Due to the presence of crosstalk voltage in the circuit, SiC MOSFET devices can be damaged or misled. Suppressing crosstalk voltage makes it an important step for the circuit to function properly. This article first delves into the causes of crosstalk voltage generation. The main research object is synchronous Buck converters, and the reasons for the crosstalk voltage of SiC MOSFETs are analyzed. Afterwards, a novel drive circuit was designed to suppress crosstalk voltage, and the working principle of this drive circuit was analyzed. Finally, simulation was conducted using LTspice software to study and analyze the simulation results, proving the feasibility of this novel drive circuit for suppressing crosstalk voltage, and demonstrating the advantages and disadvantages of this novel drive circuit for suppressing crosstalk voltage.
Control strategy of bidirectional DC/DC converter under variable load state
Authors: Li Qiang , Liu Di , Chen Shen , Liu Zhu , Li Wenjing , Huang Lvchao , Fang Jinguo , Zhuang Yuqiang
Published: February 2024

To improve the stability of DC/DC converters under multiple load conditions, the control strategy of Buck-Boost bidirectional DC/DC converters under variable load conditions is studied in this paper, as well as the droop control strategy for parallel operation of two machines. Based on the topology and basic control strategy of the DC/DC converter, a load current feedforward compensation strategy to achieve ideal stability of output voltage during load switching is studied; then charging and discharging control switching strategy under external power supply is proposed, which achieves fast switching between charging and discharging by sampling battery current and load voltage; finally, a current sharing control method based on inductance current droop is proposed for the parallel operation of two machines, achieving the control effect of equal current sharing between the two modules. The effectiveness and feasibility of the control strategy were verified through prototype experiments.
Multifactor-based analysis of digital energy metering errors and online detection techniques
Authors: Hu Chen , Gu Yifan , Zhu Yongzheng , Zhu Houda , Qu Zemin , Feng Xin
Published: February 2024

In light of the lack of online detection techniques in digital energy metering systems and the ambiguity surrounding factors that contribute to metering errors, this study introduces a multifactor-based approach to comprehensively analyse and detect digital energy metering errors. Through a systematic exploration, the research not only identifies the factors that significantly influence metering errors within digital energy metering systems but also quantifies their individual impacts. A dedicated testing apparatus for digital energy metering systems is devised and the impact of error-inducing factors in the on-site testing is validated. The outcomes serve to validate the precision of theoretical analyses.
Analysis of Ice-shedding induced flashover accident on a transmission line in mountainous terrain
Authors: Ji Kunpeng , Liu Bin , Zhang Yuelong , Chen Jun , Li Yu , Li Xingyu , Lu Rui
Published: February 2024

Transmission lines are essential infrastructure for modern society. Large amplitude vibration of conductors due to ice shedding may cause electrical faults, resulting from insufficient clearance among different phases and phase conductors and ground wires. A flashover fault on a 500kV transmission line located in a mountainous area, which is caused by ice shedding, is analysed in this paper. The approximate reason and history of the flashover accident were restored by the nonlinear finite element method with the help of ANSYS software. The key physical parameters such as conductor ice thickness and amount of ice shedding at the moment of the accident were analysed. The study in this paper helps to gain a deeper understanding of the ice-shedding–induced disasters of transmission lines and provides important reference for the design of transmission structures.
Grid-supporting control strategy in Chongqing-Hubei Back-to-Back HVDC Project of China
Authors: Li Yanmei , Li Ming , Lu Qinghua , Li Tai , Zhao Zheng , Zheng Kuan
Published: February 2024

To resolve the instability problem of the current vector control strategy in the converter station of Shizhou when an N-2 fault occurs during the maintenance of Enshi power grid in Chongqing-Hubei Back-to-Back HVDC project (referred to as “Chongqing-Hubei project”), a new grid-support control strategy is proposed in this research. This strategy simulates the characteristics of the synchronous generator to generate its phase. By adjusting the phase and amplitude of the output voltage, it can flexibly adjust the output of active power and reactive power and realize the frequency and voltage support of the power grid. At the same time, it solves the problem of DC instability when the AC power grid is disturbed and ensures the stable operation of the system. PSCAD/EMTDC simulation test and application in Chongqing-Hubei engineering field verify the effectiveness of this strategy. The grid-supporting control strategy provides technical support for weak system access, inertia compensation and voltage support in the future new energy field.
Real-time signal processing and data acquisition for the Electric Field Detector (EFD-02) on the CSES-02 satellite
Authors: Ammendola R. , Badoni D. , De Santis C. , Rebustini G. , Alunno Camelia E. , Bertello I. , Cipollone P. , De Angelis F. , Diego P. , Fiorenza E. , Masciantonio G. , Nuccilli F. , Parmentier A. , Papini E. , Picozza P. , Piersanti M. , Russi A. , Sparvoli R. , Ubertini P. , Vertolli N.
Published: February 2024

The Electric Field Detector (EFD-02) on board the second China Seismo-Electromagnetic Satellite (CSES-02) will measure the electric field components at a Low Earth Orbit (LEO) over a wide frequency band (DC – 3.5 MHz) and with 1 μV/m sensitivity in the Low Frequency band. EFD-02 will measure the voltage differences between pairs of probes installed at the tips of four booms deployed from the satellite. In this article, we describe the Zynq System on Chip (SoC)-based digital hardware subsystem dedicated to signal processing, and the selected implementation strategy, which successfully complied to the specific requirements of the space mission. Furthermore, we present a comprehensive overview of the assessed instrument performance.
The impact of neutral beam parameters on current drive and neutron yield in DEMO-FNS tokamak
Authors: Dlougach E. , Veltri P.
Published: February 2024

DEMO-FNS (DEMO Fusion Neutron Source) will be a hybrid reactor designed to combine fusion
and fission technologies. In a hybrid reactor the power is mainly produced by a fission blanket
which is exposed to the neutron flux generated by confined fusion plasma used as a Fusion Neutron
Source (FNS). The steady-state operation of the FNS is easier to achieve as compared to pure
fusion reactors, allowing the FNS to be more compact. The DEMO-FNS will produce 40 MW of fusion
power. The neutral beam injectors (NBI) are designed to provide a steady state plasma heating,
rotation, fueling, current drive and neutron generation in DEMO-FNS. Four injector units will
deliver 30 MW power in deuterium with energy Eb
 = 500 keV. The NBI concept and main components
are inspired from ITER HNBI design implementing acceleration of negative ions with their
neutralization on gas.

The high density of injected power in DEMO-FNS leads to a very specific operation scenario with a
higher ratio of high-energy ions in the plasma with respect to conventional tokamaks, where the main
part of neutron flux will result from fusion between hot-tail ions and relatively cold
background. The current drive and neutron yield produced by the tangentially injected beam in a
steady-state operation are strongly affected by magnetic configuration and plasma kinetic
profiles. The fast ions deposition and performance in plasma are limited by the losses associated
with the neutral beam shape and aiming. The main channels of direct beam losses include
shine-through losses, as well as fast ion orbital losses. The detailed evaluation of NB parameters
and geometry effects is a necessary step of scenario optimization.

BTR code (Beam Transmission or, in earlier versions, Beam Transmission with
Reionization) is intended for injector beamlines study, and BTR detailed beam model can be also
applied to perform a detailed analysis of beam losses and performance in plasma. The analysis of
beam in plasma shows the ways towards higher values of beam driven current (NBCD) and neutral
yield; the beam-in-plasma behaviour can be tuned for a given tokamak configuration. The NB tracing
model workflow is implemented in the BTOR suite (Beam in TORoids). The results for DEMO-FNS
are compared with the NBI performance in ITER tokamak, as both machines are beam-driven and
implement a similar NBI concept.
Revisiting permafrost carbon feedback and economic impacts
Authors: Zhu Yang , Wang Kang , Jiao Wenxian , Xu Jinlong
Published: February 2024

Quantifying permafrost carbon feedback (PCF) is a critical step in conveying the significance of permafrost carbon emissions to decision-makers and stakeholders and achieving sustainable development goals. Simply assuming a rapid reduction in permafrost area may be an overaggressive approach. This study revisited PCF by incorporating relatively clear permafrost physics into the Dynamic Integrated model of Climate and the Economy. The results show that the total carbon released from permafrost regions in 2100 is 30.5 GtC, which is accompanied by an additional atmospheric warming of 0.038 °C, much lower than previous studies. This study provides a potential perspective to scrutinize the climate feedback and related economic impacts due to permafrost thawing. We may need to pay more attention to carbon processes during nongrowing seasons and sudden changes in permafrost.
Optical response properties and bipartite entanglement in a hybrid optomechanical system assisted by Kerr-nonlinearity and amplitude modulated drive field
Authors: Yadav Surabhi , Bhatt Vijay , Bhattacherjee Aranya B , Jha Pradip K
Published: February 2024

We theoretically investigate the optomechanical interaction between an optical field and a mechanical mode mediated by a Kerr nonlinear medium inside an optical cavity and simultaneously driven by an external amplitude-modulated pump field and a probe field. We show that switching between bistability and multistability is influenced by the rocking parameter and Kerr nonlinearity. Further, we study the quantum fluctuation dynamics of the system, which shows the quantum coherence and interference effects resulting in the transmission of the probe field from opacity to amplification. We also find that the rocking parameter, Kerr nonlinearity, and the optomechanical coupling influence the transmission spectrum. In addition, we also show that the rocking parameter significantly enhances the optomechanical coupling, which can be a new handle to control the entanglement between the optical and mechanical modes. The results show that such a hybrid optomechanical system has potential application in designing and optimizing all-optical switching and optical sensors.
Citizen participation during the 2014 protest in Burkina Faso: Aspiring to a ‘good state’
Authors: Desrosiers Marie-Eve , Hubert Nicolas
Published: February 2024

Analyses of the 2014 protest in Burkina Faso have predominantly focused on some of the movement’s major activists, to the neglect of ordinary citizens. Yet, while citizens’ participation in Burkina Faso in 2014 echoed to some extent the agendas of activists, it built on citizens’ own political subjectivities. Drawing on original interviews and Afrobarometer survey data, we show that Burkinabè citizens were motivated to protest by unmet expectations of the ‘good state’, as experienced in their daily existence in the sense of hardship and unequal treatment by the political system. These expectations and aspirations reflected citizens’ deeper political beliefs or political subjectivities, as already expressed in years prior to the 2014 political crisis. Overall, the article shows how looking at protest from the bottom-up can shift our understanding of political mobilization and its motives: citizen protest constitutes its own political phenomenon, in Burkina Faso and beyond, and should not be subsumed by analyses largely derived from speaking to major activists.