bluuebunny/crossref_metadata_2025_split huggingface dataset:
Method for analysing of wind power wave nature based on kernel density estimation
Authors: Luo Hongmei , Zhou Yi , Pei Lijie , Xu Hao , Fan Dongqi , Tang Yida , Gao Jianing , Liu Jiachen 
Published: March 2024

Abstract
It is beneficial for improving the accuracy of wind power output prediction by analysing and mastering the inherent laws of the fluctuation characteristics of wind power output, guiding the power grid dispatching department to reasonably arrange power generation plans, and improving the economic efficiency of system operation. In order to characterize the probability density distribution of wind power output fluctuation, two adaptive bandwidth kernel density estimation models are established by correcting the fixed bandwidth obtained from the empirical method and unbiased cross-validation method respectively, and then the two models are combined and optimized, and ultimately, the probability density distribution model of wind power output fluctuation based on Hybrid Adaptive Kernel Density Estimation (HAKDE) is established. A variety of probability density distribution models are used to fit the wind power output fluctuations at different spatial and temporal scales in a province in North China, and the example results show that the hybrid adaptive kernel density estimation model has the best fitting effect, thus verifying the effectiveness of the hybrid adaptive kernel density estimation model.
An improved resonant DC link inverter with a simple structure
Authors: Xia Wen , Jia Xiaodong , Song Jiaxiang 
Published: March 2024

Abstract
To further streamline the architecture of the resonant DC link inverter, this article shows an improved resonant DC link inverter with straightforward architecture. There is no oscillating capacitor on the main tubes. Part of the resonant current during resonance is detached from the main tubes. The soft-switching action of all the tubes of this topology can be effectuated by using a set of resonant cavities, and its topology is simple. It has main tubes for ZVS movement and auxiliary tubes for ZCS movement. Also, the circuit has a controllable zero voltage notch duration. The article will elaborate on the operating scheme of the circuit. Eventually, the simulation outcomes are given to validate the effectiveness of the circuit.
Research on simultaneous switch and multiple switch processing methods
Authors: Su Yinsheng , Ma Qian , Yao Haicheng , Shao Lei , Yao Shujun 
Published: March 2024

Abstract
In the simulation of complex power electronic equipment containing multiple power electronic switches, it is often encountered that the same switch occurs several times in one step, or there are multiple switch actions in one step, that is, multiple switches. When the switching event occurs between two moments, because the voltage value can only be updated at the end of the simulation step, there is a cumulative error in the current obtained by the integration. In traditional electromagnetic transient simulation, the interpolation algorithm and its deformation are commonly used to solve this problem. However, due to the complexity of the conventional interpolation algorithm, it will seriously affect the efficiency in large-scale power grid simulation, and can only be applied to offline simulation, which cannot meet the needs of real-time simulation. In this paper, a method is presented to deal with synchronous switches and multiple switches, which can reliably solve the problem of synchronous switches and multiple switches encountered in real-time simulation of complex power electronic systems.
Coordinated DC voltage control strategy for the receiving end hybrid LCC-VSC system
Authors: Zhou Yi , Luo Hongmei , Xu Hao , Xie Yan , Fan Dongqi , Li Zaihua , Tang Yida , Gao Jianing , Liu Jiachen 
Published: March 2024

Abstract
The receiving end hybrid line commutated converter (LCC) — voltage source converter (VSC) system has the obstacle that when an AC fault occurs at the sending LCC side, the DC voltage of the rectifier side will fall, resulting in the power transmission reduction of the whole system. Particularly, when the rectifier side DC voltage falls below the inverter side DC voltage, the power transmission is interrupted, posing a huge threat to the stability of the power grid at both the sending and receiving ends. To tackle these problems, a coordinated DC voltage control strategy for the receiving end is proposed. By controlling the DC voltage of the receiving VSC, the proposed method can improve the DC system power transmission capability when voltage drops at the sending side. The proposed control strategy is simple but practical, which is good for the stable and secure operation of both the sending and the receiving power system.
Error state prediction of capacitor voltage transformer based on TimesNet and gate control unit
Authors: Wang Shoukun , Song Zhen , Yang Lin , Dai Rui , Wang Weiguang , Zhang Wenting , Zhang Zhilong , Ge Chunmeng 
Published: March 2024

Abstract
The stability and reliability of the error state of capacitor voltage transformer (CVT) are poor, which affects the fairness of electricity trade settlement and the safe operation level of power grid. However, the CVT error data is superimposed by different periodic information such as daily period, monthly period and quarterly period, which makes the prediction of transformer error state challenging. In this paper, a CVT error state prediction method based on TimesNet and gate control unit (GRU) is proposed. The TimesNet network is employed to capture the intraperiod-variation and interperiod-variation characteristics of the ratio difference data of a-phase, b-phase and c-phase, and the feature data and GRU model are employed to predict the output. The simulation results demonstrate that the mean square error (MSE) and mean absolute error (MAE) of the proposed model are 0.0002 and 0.0101, respectively, indicating that this model has lower prediction error and higher prediction accuracy.
A fault location method for distribution network feeder terminal based on SABSO algorithm
Authors: Wang Pengfei , Ruan Xiaofei , She Lizhen 
Published: March 2024

Abstract
With the increasingly prominent problem of faults at the end of distribution network feeders, a fault area localization method based on simulated annealing Tianniu swarm optimization (SABSO) algorithm is proposed to address the shortcomings of traditional fault localization methods. This method achieves rapid and accurate location of fault areas by collecting and analyzing fault information at the end of the distribution network feeder. The experimental results show that this method has higher accuracy and can accurately locate the fault area at the end of the distribution network feeder, providing strong support for the safe and stable operation of the distribution network.
Optimized scheduling of energy-transport coupling systems considering uncertain traffic flow
Authors: Hou Yongkang , Xu Xu 
Published: March 2024

Abstract
To address energy and nature-related issues, the development of new energy vehicles has been rapid in recent years, gradually replacing traditional vehicles. This paper specifically focuses on the uncertainty of traffic flow for new energy vehicles within the transport system. We analyze the consequence of output from various equipment units in the energy system and their optimized scheduling. We construct an optimization scheduling model for integrating the electric-gas network and the transportation network, known as the energy-transport coupling system (ETCS). By incorporating the uncertainty of traffic flow and utilizing a data-driven approach to generate a set of uncertain traffic flow, we conduct a case study using an improved ETCS consisting of an IEEE-33 node distribution network, a 7-node natural gas network, and a 12-node transportation network to validate the scheduling method. The results demonstrate that the uncertainty of traffic flow does indeed affect the output of equipment units in the ETCS. Furthermore, through optimized scheduling, we can achieve positive interactions between different systems.
Construction of short-term electricity demand streaming forecasting model in demand-side dynamic response
Authors: Li Jie , Wu Yiming , He Yong , Wei Hang 
Published: March 2024

Abstract
In the context of demand-side dynamic response, the electricity supply-demand relationship undergoes constant changes, and short-term electricity load exhibits strong randomness and volatility, making load conditions challenging to predict. Hence, this paper proposes a short-term electricity demand streaming forecasting model that combines wavelet decomposition with Random Forest to enhance the accuracy of short-term electricity load forecasting. This model establishes a load feature system, utilizing a three-scale wavelet decomposition algorithm to break down the load sequence into several sub-sequences of different frequency bands. Subsequently, Random Forest load forecasting models are separately established for these sub-sequences. The final load prediction is obtained through reconstruction. This approach enables quasi-real-time short-term forecasting analysis of demand-side electricity demand.
Power system topological node tamper detection method based on fuzzy graph theory
Authors: Tan Huijuan , Guo Wenxin , Li Shiming , Zheng Wenjie , Li Qian 
Published: March 2024

Abstract
Power system involves a large number of nodes and lines, and the topology is very complex. In such a complex network, node tamper detection needs to consider a variety of combinations and connection modes, which increases the complexity of the problem. Therefore, a new method of topological node tamper detection based on fuzzy graph theory is proposed. The feature difference values of topological nodes are extracted according to the node tampering feature vector. Detection of topological node similarity based on fuzzy graph-neural network. Based on this, the cost function of topological node tampering is established to obtain the Bayesian estimate of the tampering coefficient of the topological node transmission channel, and the detection of topological node tampering is completed. The experimental results show that the application time of the research method is shorter, the detection of power node tampering behavior is more comprehensive, and the tampering success rate is higher.
Research on multiple calibration methods for measuring error of indicator value of withstand voltage tester
Authors: Liu Xiaoze , Sui Jiarui , Qin Yuewei , Han Bo , Guo Linlang 
Published: March 2024

Abstract
Voltage resistance testing often needs to be carried out under specific environmental conditions, such as high pressure and high temperature. These complex environments may interfere with the test equipment and calibration process, thus affecting the accuracy of calibration results. Therefore, it is necessary to ensure that the tester can adapt to various environmental conditions and make calibration adjustments accordingly. Therefore, a multi-calibration method based on the BP neural network is proposed to calibrate the error of the indicator value of the voltage tester. The power input and output characteristic function of the withstand voltage tester is established, and the output of each layer is described as the input of the BP neural network. Based on the adjustment results, multiple calibration steps for the measuring error of the voltage tester are designed. The experimental results show that the method can calibrate the measuring error of the voltage tester at different positions at the same time, and the application effect is good.
Monolithic HV-CMOS sensors for a beam monitoring system of therapeutic ion beams
Authors: Topko B. , Balzer M. , Dierlamm A. , Ehrler F. , Husemann U. , Koppenhöfer R. , Perić I. , Pittermann M. , Naumann J. 
Published: March 2024

Abstract
Nowadays, cancer treatment with ion beam is well established and studied. This method allows to deposit the maximum dose to the tumor and minimize the damage to healthy tissue, due to the Bragg peak of the ion energy deposition near the end of the particle range. During the treatment, it is possible to provide volumetric dose delivery by changing the particle energy (penetration depth) and adjusting the beam position via a magnetic system. For the beam monitoring system, the precise measurement of the beam direction, shape and fluence in real time becomes crucial to provide effective and safe dose delivery to the tumor. Additionally, the system should work for beam intensities up to 1010 s-1 for protons, be tolerant to 1 MeV neutron equivalent fluences up to 1015 cm-2 per year and be to tolerant to magnetic fields (for MR-guided ion beam).

The studies presented in this article are focused on the application of the HitPix sensor family with counting electronics and frame-based readout for such a beam monitoring system. The HitPix sensors are monolithic pixelated silicon sensors based on HV-CMOS technology and have been developed at the ASIC and Detector Lab (ADL, KIT). Recent measurements with ion beams and a multi-sensor readout as well as future developments are discussed.
Imaging performance of wide-field X-ray Transient Localization Experiment onboard microsatellite KOYOH
Authors: Sawano T. , Suzuki T. , Yonetoku D. , Arimoto M. , Yoshida T. , Mihara T. , Takahashi N. 
Published: March 2024

Abstract
We designed a flight model of the wide field X-ray imager on board the microsat
KOYOH, referred to as T-LEX, and investigated its imaging performance
through laboratory beam tests. T-LEX employs the coded mask method, wherein
the aperture pattern of the mask was selected and fabricated from 50,000 patterns
using a Monte Carlo approach. Utilizing the obtained mask along with a silicon
strip detector, we examined the angular response by varying the incident
angle with a stage during X-ray irradiation. The resulting angular response
exhibited deviations from the design values, yet it confirmed that the targeted
position accuracy of 15 arcminutes is maintained across a range from -20deg to
+20deg with the best fit calibrated model.
Metal wire embrittlement monitoring by the measurement of wire oscillation frequency
Authors: Arutunian S.G. , Harutyunyan G.S. , Lazarev L.M. , Margaryan A.V. , Manukyan N.M. , Lazareva E.G. , Mirzoyan G.V. , Gevorgyan R.S. , Chung M. , Korzhik M.V. 
Published: March 2024

Abstract
In the process of irradiation of materials by fluxes of heavy particles (protons, neutrons, alpha particles), damage to material structure is often observed. As a result of the accumulation of such damages, there is a subsequent change in the properties of materials, in particular, its embrittlement and hardening. Monitoring of the embrittlement process is important for nuclear reactor vessels exposed to high neutron fluxes. In this work, to observe the effect of heavy irradiation particles on the mechanical properties of metals, we propose to use vibrating wire resonators, in which the natural frequency of oscillations of the wire strongly depends on its tension. The change in the elastic characteristics of the wire alters the value of the natural frequency of wire oscillations. The natural oscillations are generated by a special circuit. Preliminary experiments to study the embrittlement effect of a stretched wire are performed by heating the wire with an electric current. In the case of short pulses, a significant increase in frequency is achieved, which is explained by the process of hardening of the material as a result of the thermal impact on the wire (rapid heating and cooling).
An insight into potential phosphate bioremediation and renewable energy from agricultural waste via integrated wastewater treatment systems in Indonesia
Authors: Asih Devi R , Handayani Windri , Ananda Alyssa Z , Yuniati Ratna , Hirota Ryuichi , Summerfield Tina C , Eaton-Rye Julian J 
Published: March 2024

Abstract
Indonesia is renowned as an agricultural powerhouse, ranking first globally in oil palm production. This prominence in agriculture leads to the consistent generation of agro-industrial waste, notably Palm Oil Mill Effluent (POME). Effectively addressing these waste concerns is important due to their adverse impacts on aquatic ecosystems and the nation’s health and economy. Anthropogenic wastewater with excessive phosphorus content can trigger eutrophication and toxic algal blooms, posing environmental risks and potentially precipitating a future clean water crisis. Thus, a comprehensive approach is necessary to restore the environment and biogeochemical cycles. Treatment efforts involving bioremediation agents aim to recycle organic and inorganic pollutants in the environment. Photosynthetic organisms like plants and microalgae serve as effective bioremediation agents, capable of absorbing excess phosphorus. They can utilize phosphate as an energy source to boost biomass. Integrating these bioremediation agents with bioengineering technology optimizes the treatment efficacy while simultaneously producing valuable biomass for products and bioenergy. This review article explores photosynthetic organisms’ multifunctional role as phosphorus bioremediation agents for wastewater treatment, minimizing environmental pollutant impacts, and providing biomass for fertilizers, polymers, bioplastics, and renewable energy. Furthermore, this study unveils opportunities for future technological advancements in this field.
Real-space multiple-scattering approach to the van der Waals interaction
Authors: Rehr J J , Kas J J 
Published: March 2024

Abstract
The van der Waals (vdW) interaction between non-overlapping systems arises from long-range correlations in electronic systems due to the attraction between their coupled density fluctuations. Here we present a treatment based on a generalized real-space multiple-scattering approach which is applicable to both spherical and non-spherical geometries. The method is tested for the vdW interactions between two isolated atoms.
A critical review on biomaterials using powder metallurgy method
Authors: Abraham Adarsh Mathew , Venkatesan S 
Published: March 2024

Abstract
Implants play a vital role in a person’s life because losing any body part to function less actively, which makes the sufferer uncomfortable. Implants should be both biocompatible and non-toxic to the body is essential to achieve its biocompatibility nature. To create orthopaedic, dental, and surgical implants, biomaterials were divided into three categories: metallic, polymeric, and ceramic. Materials based on polymers indicate their degree of adaptability in terms of sutures, medication delivery, etc. Ceramic materials are known for their high compressive strength and inert behaviour, which combine aesthetic qualities. Metallic biomaterials are enhanced by their high strength and resistance to fracture. One of the most promising techniques for improving a material’s mechanical qualities is powder metallurgy. Powder metallurgy involves blending of powders, compaction of blended powder, sintering and mechanical test. Samples with varying compact pressures, sintering temperatures, and sintering times were created using the powder metallurgy process. The aim of the research work is to get the concept of powder metallurgy, biomaterials commercially available for orthopaedic and dental applications, properties of biomaterial and methods to fabricate the material effectively.
High-resolution, open-source modeling of inland flooding impacts on the North Carolina bulk electric power grid
Authors: Prieto-Miranda Luis , Kern Jordan D 
Published: March 2024

Abstract
Although damages to local distribution systems from wind and fallen trees are typically responsible for the largest fraction of electricity outages during hurricanes, outages caused by flooding of electrical substations pose a unique risk. Electrical substations are a key component of electric power systems, and in some areas, the loss of a single substation can cause widespread power outages. Before repairing damaged substations, utilities must first allow floodwaters to recede, potentially leaving some customers without power for weeks following storms. As economic losses from flooding continue to increase in the U.S., there has been increasing attention paid to the potential impacts of flooding on power systems. Yet, this attention has mostly been limited to geospatial risk assessments that identify what assets are in the path of flooding. Here, we present the first major attempt to understand how flooding from hurricanes and other extreme precipitation events affects the dynamic behavior of power networks, including losses of demand and generation, and altered power flows through transmission lines. We use North Carolina, hit by major hurricanes in three of the past seven years, as a test case. Using open-source data of grid infrastructure, we develop a high-resolution direct current optimal power flow model that simulates electricity production and generators and power flows through a network consisting of 662 nodes and 790 lines. We then simulate grid operations during the historical (2018) storm Hurricane Florence. Time series of flooding depth at a discrete set of ‘high water’ mark points from the storm are used to spatially interpolate flooding depth across the footprint area of the storms on an hourly basis. Outages of substations and solar farms due to flooding are translated to location-specific losses of demand and solar power production throughout the network. We perform sensitivity analysis to explore grid impacts as a function of the height of sensitive equipment at substations. Results shed light on the potential for localized impacts from flooding to have wider impacts throughout the grid (including in areas not affected by flooding), with performance tracked in terms of transmission line flows/congestion, generation outputs, and customer outages.
Personality Disorder: A Contested and Evolving Construct
Authors: O'Loughlin Ailbhe 
Published: March 2024

Abstract
This chapter analyses the scientific, ethical, and legal debates surrounding the psychiatric construct of personality disorder. It sets the scene for the examination in subsequent chapters of attempts in England and Wales to address the legal and policy problems posed by ‘dangerous’ offenders and ‘difficult’ patients or prisoners. It shows that personality disorder should be regarded as a risk factor for offending rather than a cause, and that current risk assessment technologies cannot yet accurately identify which individuals in a high-risk group will go on to offend. As a result, policies of preventive detention may be expected to result in the over-use of detention. While there is a growing consensus that personality disorder is not necessarily untreatable, there is a continuing lack of robust evidence for the effectiveness of current treatments for antisocial personality disorder and psychopathy. This casts doubt on the idea that access to rehabilitative interventions will limit the use of preventive detention powers. While some jurisdictions have confined the use of mental health law powers to patients with treatable mental illnesses, the UK Government continues to resist calls to introduce stronger safeguards against the long-term detention of people who are unlikely to benefit from treatment. This approach is questionable in light of the principles governing mental health law developed by the European Court of Human Rights.