mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Single-phase-to-ground Fault Detection with Distributed Parameters Analysis in Non-direct Grounded Systems

The fast and accurate detection of the single-phaseto-ground fault is of great significance for the reliability and safety of the power supply.In this paper,novel algorithms for distribution network protection were proposed with distributed parameters analysis in non-direct grounded systems.At first,novel generating mechanisms of zero-sequence voltage and residual current were proposed.Then the compositions of residue parameters,including residual current and residual admittances,were decomposed in detail.After that,an improved algorithm for a fault resistance calculation of a single phase-to-earth fault was also proposed,and the algorithm is much more convenient as it only needs to measure the variation of the zero-sequence voltage and does not need the prerequisites of the faulty feeder selection.Furthermore,the fault feeder can also be selected by an improved calculation algorithm of zero-sequence admittance of the faulty feeder,which cannot be affected by the asymmetry of the network.Theoretical analysis and the MATALB/Simulink simulation results demonstrate the effectiveness of the proposed algorithms.
Two-port Equivalent Circuit Model for UHVDC Converter Valves

UHVDC converter valves during operation may experience overvoltage,which come from the AC or DC systems to which they are connected.Therefore,building an equivalent circuit model (ECM) for the converter valve to analyze the interlayer transient voltage distribution characteristics has important engineering significance for safe and reasonable voltage equalization methods and improving the stability of the DC system.This paper proposes a two-port equivalent circuit model for ±1100 kV converter valve based on the structure of the valve and parameter extraction methods presented.In terms of lumped parameters,integrated ECMs for valve layers are built through impedance-frequency characteristic analysis;in terms of parasitic capacitance parameters,port equivalent parasitic capacitance parameters are obtained by terminal capacitance method and iterative equivalence methods proposed in this paper.By combining integrated ECMs of valve layers and port equivalent parasitic capacitances,the two-port ECM is obtained.Simulations are carried out to test the effectiveness of the twoport ECM.Using the ECM,the voltage transmission characteristics and their influencing factors are analyzed,depending on which corresponding voltage equalization method is proposed in this paper,and the effect of this method is verified through simulation.
Reliability Assessment of a Cyber Physical Microgrid System in Island Mode

As cyber physical systems,microgrids (MGs),with distributed generations and energy management systems,can improve the reliability of power supply for customers in MGs.To quantify the reliability of isolated MGs,a cyber-physical assessment model is proposed.In this model,the circuit breakers and distributed energy resources are treated as the coupling elements between the cyber system and physical system,where the circuit breakers are uniquely modelled by using the Markov process theory based on the indirect interdependencies between cyber physical elements.For the cyber system,the reliability model of communication networks is formulated based on the link connectivity evaluation method.For the physical system,a system state generating method is presented to account for the optimal operation strategy,which considers the influence of the optimization strategy on the failure consequence analysis.With the proposed cyber and physical reliability models,the sequential Monte Carlo (SMC) simulation method is adopted to assess the reliability of islanded MGs.Simulations are carried out on a test system,and results verify the feasibility and effectiveness of proposed assessment method.Furthermore,one application of the proposed method is on the parameter setting of the cyber system,in terms of enhancing MGs reliability.
Scenario-based Planning of Active Distribution Systems Under Uncertainties of Renewable Generation and Electricity Demand

The rising penetration of intermittent renewable distributed generation leads to uncertainties in the planning of electric distribution networks.Fully considering the uncertainties pertinent to wind power generation,photovoltaic power generation and load demand,this paper proposes a scenariobased model for the planning of active distribution systems.The solution obtains the optimal capacities and locations of wind and photovoltaic based distributed generators in the distribution system,whilst minimizing the active and reactive power losses as well as voltage deviation.A scenario matrix is generated using the heuristic moment matching technique that captures the stochastic moments and correlation among historical wind and photovoltaic power,and electricity demand.The scenario matrix is then incorporated to propose a stochastic planning model that considers a multi-objective index for minimizing power losses and voltage deviation.Finally,the effectiveness of the proposed planning model is confirmed using case-studies in 53-bus and IEEE 123-bus distribution systems.
Artificial Intelligence Based Smart Energy Community Management:A Reinforcement Learning Approach

This paper presents a smart energy community management approach which is capable of implementing P2P trading and managing household energy storage systems.A smart residential community concept is proposed consisting of domestic users and a local energy pool,in which users are free to trade with the local energy pool and enjoy cheap renewable energy while avoiding the installation of new energy generation equipment.The local energy pool could harvest surplus energy from users and renewable resources,at the same time it sells energy at a higher price than Feed-in-Tariff (FIT) but lower than the retail price.In order to encourage the participation in local energy trading,the electricity price of the energy pool is determined by a real-time demand/supply ratio.Under this pricing mechanism,retail price,users and renewable energy could all affect the electricity price which leads to higher consumers’ profits and more optimized utilization of renewable energy.The proposed energy trading process was modeled as a Markov Decision Process (MDP) and a reinforcement learning algorithm was adopted to find the optimal decision in the MDP because of its excellent performance in on-going and model-free tasks.In addition,the fuzzy inference system makes it possible to use Qlearning in continuous state-space problems (Fuzzy Q-learning) considering the infinite possibilities in the energy trading process.To evaluate the performance of the proposed demand side management system,a numerical analysis is conducted in a community comparing the electricity costs before and after using the proposed energy management system.
From Independence to Interconnection-A Review of AI Technology Applied in Energy Systems

The development of diversified energy structures,distributed energy scheduling models and active participation ability of users,leads to a rapid movement toward energy system in which different energy carriers and systems interact together in a synergistic way.This energy development will face many challenges with the requirements of big data processing capability,professional skill,distributed collaboration and realtime monitoring for the energy system that demands an intelligent and flexible tool to realize the smart energy.Artificial intelligence (AI) technology has become a focus because of its better performance.This paper proposed a classification method that incorporates the intelligence of an independent energy unit (IEU) and the intelligence among interconnected energy units (IEUS) to review the development of AI technology in energy systems.The dominant structures of IEU can be considered from three aspects including perception,decision and implementation to study the optimal strategy for AI methods utilized in IEU.And considering the interaction relationship of IEUS,the AI applied for it can be described by the coordinated relationship and adversarial relationship problems to achieve consensus.By discussing the AI technologies and the potentials of AI in the energy system,some suggestions are presented to improve intelligent technologies for sustainable energy systems in the future.
Development of non-shrinkable ceramic composites for use in high-power microwave tubes

Al_2O_3–CaO–SiC-based ceramic composites with four different compositions were sintered at 1700°C for 3 h in an air furnace. The phase analysis, microstructural characterization, and elemental composition determination of the developed composites were performed by X-ray diffraction(XRD), field-emission scanning electron microscopy(FESEM), and energy-dispersive X-ray(EDAX) analysis, respectively. The shrinkage, thermal properties, and electrical resistivity of the composites were also studied. The experimental results showed the effects of adding silicon carbide and calcia to alumina on the thermal, electrical, and shrinkage properties of the resultant composites. Among the four investigated ceramic composites, the one composed of 99wt% alumina, 0.5wt% CaO, and 0.5wt% SiC exhibited the best characteristics for use as a potting material in a dispenser cathode of a microwave tube. The material exhibited slight expansion instead of shrinkage during drying or firing. Other properties of the composite powder, such as its thermal properties and electrical resistivity, were comparable to those of a commercial alumina powder.
Malicious Synchrophasor Detection Based on Highly Imbalanced Historical Operational Data

By maliciously manipulating the synchrophasors produced by phasor measurement units in power systems,cyber attackers can mislead the control center into taking wrong actions.From the viewpoint of machine learning,normal and malicious synchrophasors may exhibit different spatial distribution characteristics when mapped into a latent space.Hence,a malicious synchrophasor detector can be acquired by training a classification model with instances derived from historical operational synchrophasor data.However,malicious synchrophasors occur infrequently in practice.It is likely to incur a great deal of effort and may even introduce inevitable experience errors when extracting and labeling a sufficient number of malicious synchrophasors from historical operational data for training.For most existing detectors,if they are directly trained with highly imbalanced datasets,their performances may severely deteriorate.In this paper,a novel type of malicious synchrophasor detector is developed based on a combinatorial use of data rebalancing,Bagging-based ensemble learning,and the widely recognized eXtreme Gradient Boosting (XGBoost) classifier.Experiments show that although fewer malicious instances are provided,the proposed detector is still capable of detecting malicious synchrophasors.
Effects of freeze-thaw cycle and dry-wet alternation on slope stability

The typical loess on high slopes along the BaoLan High-speed Rail, China, was selected as the research object. The influence of the freeze-thaw cycle and dry-wet alternation on the shear-strength parameters of the unsaturated loess was investigated by laboratory experimental methods. Moreover, the temperature field, seepage field, and stability of slopes with different gradients were simulated under the effect of the freeze-thaw cycle and dry-wet alternation by using the geotechnical analysis software Geo-Studio. The research results showed (1) when the freeze-thaw cycle was repeated on the slope, with the frozen depth increasing, the melted depth did the same; besides, the closed loop of isotherms formed on the slope; (2) under the action of dry-wet circulation, the negative pore-water pressure and volumetric water content showed an upward tendency. However, owing to the different slope gradients, rainfall infiltration was not the same. As time went by, the differences of the negative pore-water pressure and volumetric water content between the slopes of different gradients continued to increase; (3) with the freeze-thaw cycle and dry-wet alternation increasing, the slope-safety factor decreased. Especially in the early period, the slope-safety factor changed remarkably. For slopes undergoing freeze-thaw action, the slope-safety factor was negatively correlated with the gradient. However, with regard to slopes undergoing dry-wet alternation, the result became more complex because the slope-safety factor was related to both seepage strength and slope grade. Accordingly, further research is needed to study the effect of seepage strength and slope grade on the stability of loess slopes.
Improving effect on forming quality and accuracy using a polyurethane board positioning/resetting the discrete steel pad in multi-point forming

To improve the quality of multi-point die forming, a new approach using discrete steel pads was proposed. The formability of three different multi-point die forming processes was analyzed through numerical simulation and experiments. Numerical simulation and experimental results showed that the use of discrete steel pads in the multi-point forming process can substantially improve the stress–strain state on the plate and suppress dimple, straight-edge, and wrinkle defects. This analysis verified that the use of discrete steel pads in a multi- point forming process can effectively improve the quality and accuracy with which sheet metal is formed.
Analysis of vegetation changes and dominant factors on the Qinghai-Tibet Plateau, China

This research was undertaken to clarify the characteristics of vegetation change and its main influencing factors on the Qinghai-Tibet Plateau. Using the greenness rate of change (GRC) and correlation factors, we analyzed the trend of vegetation change and its dominant factors from 2000 to 2015. The results indicate that the vegetation tended to improve from 2000 to 2015 on the Qinghai-Tibet Plateau, with the improved area accounting for 39.93% of the total; and the degraded area accounting for 19.32%. The areas of degraded vegetation are mainly concentrated in the low-relief and intermediate-relief mountains of the high-altitude and extremely high-altitude areas on the Qinghai-Tibet Plateau, as the vegetation characteristics are impacted by the terrain. Temperature and precipitation have obvious response mechanisms to vegetation growth, but the effects of precipitation and temperature on vegetation degradation are not significant over a short time frame. Overgrazing and population growth are the dominant factors of vegetation degradation on the Qinghai-Tibet Plateau.
Segmented tubular synthesis of monodispersed microsized copper oxalate

Monodispersed microsized copper oxalate particles were prepared in a segmented continuous flow tube reactor, and the effect of the main parameters such as organic additive agent, initial copper ions concentration, residence time, and segmented media on the final products were investigated experimentally. The obtained copper oxalate microsized particles were disc-like in the presence of citrate ligand, which was the shape inducer for the precipitated copper oxalate. Thermodynamic equilibrium diagrams of the Cu(II)–oxalate–H_2O, Cu(II)–oxalate–citrate–H_2O, and Cu(II)–oxalate–EDTA–H_2O solution systems were drawn to estimate the possible copper species under the experimental conditions and to explain the formation mechanisms of copper oxalate particles in the segmented fluidic reactor. Both theoretical and experimental results indicated that the presence of chelating reagents such as citrate and EDTA had distinct effect on the evolution of particle shape. Air and kerosene were tested as media for the fluidic flow segmentation, and the latter was verified to better promote the growth of copper oxalate particles. The present study provides an easy method to prepare monodispersed copper oxalate microsized particles in a continuous scaling-up way, which can be utilized to prepare the precursor material for conductive inks.
Development of Optimal Maintenance Policies for Offshore Wind Turbine Gearboxes Based on the Non-homogeneous Continuous-Time Markov Process

Gearbox in offshore wind turbines is a component with the highest failure rates during operation. Analysis of gearbox repair policy that includes economic considerations is important for the effective operation of offshore wind farms. From their initial perfect working states, gearboxes degrade with time, which leads to decreased working efficiency. Thus, offshore wind turbine gearboxes can be considered to be multi-state systems with the various levels of productivity for different working states. To efficiently compute the time-dependent distribution of this multi-state system and analyze its reliability, application of the nonhomogeneous continuous-time Markov process(NHCTMP) is appropriate for this type of object. To determine the relationship between operation time and maintenance cost, many factors must be taken into account, including maintenance processes and vessel requirements. Finally, an optimal repair policy can be formulated based on this relationship.
Review of Condition-Based Maintenance Strategies for Offshore Wind Energy

The existing maintenance strategies of offshore wind energy are reviewed including the specific aspects of condition-based maintenance, focusing on three primary phases, namely, condition monitoring, fault diagnosis and prognosis, and maintenance optimization. Relevant academic research and industrial applications are identified and summarized. The state of art, capabilities, and constraints of condition-based maintenance are analyzed. The presented research demonstrates that the intelligent-based approach has become a promising solution for condition recognition, and an integrated data platform for offshore wind farms is significant to optimize the maintenance activities.
关节镜下滑膜全切除术治疗肘关节类风湿关节炎的研究进展

类风湿关节炎( rheumatoid arthritis,RA)是一种以慢性、侵蚀性多关节炎为主要表现的自身免疫病,我国RA患病率约为0.42%。对于药物治疗效果不佳的难治性RA,关节镜下滑膜全切术( arthroscopic synovectomy,AS)是挽救关节功能的重要治疗手段。本文对AS的手术指征、手术方式、疗效、并发症等进行文献总结,旨在为临床实践和研究提供帮助。
白细胞介素-6及其信号通路在中枢神经系统感染中的作用研究进展

白细胞介素-6(IL-6)是一种由184个氨基酸组成,分子质量为26 ku的糖蛋白,可以由单核细胞、淋巴细胞、巨噬细胞、成纤维细胞、内皮细胞、角化细胞及某些肿瘤细胞合成。活化的单核细胞是产生IL-6的主要来源,在机体发生炎性反应时,单核细胞和巨噬细胞最早活化并产生 IL-6。
Performance of S-CO_2 Brayton Cycle and Organic Rankine Cycle (ORC) Combined System Considering the Diurnal Distribution of Solar Radiation

This paper researches the performance of a novel supercritical carbon dioxide (S-CO_2) Brayton cycle and organic Rankine cycle (ORC) combined system with a theoretical solar radiation diurnal distribution. The new system supplies all solar energy to a S-CO_2 Brayton cycle heater, where heat releasing from the S-CO_2 cooler is stored in the thermal storage system which is supplied to the ORC. Therefore, solar energy is kept at a high temperature, while at the same time the thermal storage system temperature is low. This paper builds a simple solar radiation diurnal distribution model. The maximum continuous working time, mass of thermal storage material, and parameter variations of the two cycles are simulated with the solar radiation diurnal distribution model. 10 organic fluids and 5 representative thermal storage materials are compared in this paper, with the mass and volume of these materials being shown. The longer the continuous working time is, the lower the system thermal efficiency is. The maximum continuous working time can reach 19.1 hours if the system provides a constant power output. At the same time, the system efficiency can be kept above 38% for most fluids.
Design and Analysis of S-CO_2 Cycle and Radial Turbine for SOFC Vehicle Waste-Heat Recovery

Solid oxide fuel cell (SOFC) vehicles are considered to have broad prospects for development, and the high operating temperature of SOFC results in great potential for waste-heat recovery. Many concepts for utilizing waste heat of SOFC have been suggested and studied, and most of them directly couple an SOFC to a gas turbine, which require the SOFC to operate at an elevated pressure and make the system less flexible and thus harder to operate. In recent years, with the development of turbine and heat exchanger technology, the supercritical carbon dioxide (S-CO_2) power cycle has raised widespread attractions for the waste recovery. This study explores the potential of S-CO_2 Brayton cycle to realize waste-heat recovery for an SOFC vehicle. The SOFC can operate at atmospheric pressure, and the hybrid system is easier to operate than the directly coupled systems. In this paper, a simple recuperated S-CO_2 Brayton cycle is proposed and the key component, radial inflow turbine is designed and focused. The flow state of the designed turbine is analyzed in detail based on computational fluid dynamics (CFD) numerical simulation. Five cases with different impeller tip clearances are numerically simulated to study its influence on the turbine performance. In addition, off-design performance analysis of the radial inflow turbine is conducted considering the temperature fluctuation of SOFC in practical applications.
伴皮脂腺分化的腺样囊性癌和鳞癌构成的食管碰撞瘤1例并文献复习

目的探讨伴皮脂腺分化的腺样囊性癌和鳞癌构成的食管碰撞瘤的临床病理学特征、诊断及鉴别诊断。方法回顾性分析1例伴皮脂腺分化的腺样囊性癌和鳞癌构成的发生在食管的碰撞瘤,分析其临床表现、组织病理学特征和免疫表型,并复习相关文献。结果胃镜下见距门齿34 ~ 37 cm处食管见一隆起型灰黄色肿物,组织学表现为双原发肿瘤,糜烂区为中分化鳞癌,浸润黏膜下层,周围可见鳞状上皮不典型增生;隆起型灰黄色肿物主要由3种不同组织构型区域融合构成。免疫表型:未分化基底样细胞CK8/18、CAM5.2、p63、p40、GATA-3、S-100均(+),CK5/6、CK7均灶(+),AR、GCDFP-15、SMA均(-);腺样囊性癌样区域:腺上皮CK8/18、CAM5.2、CK7均(+),基底细胞p63、p40、CK5/6、S-100、CD117均(+),SMA、AR、GCDFP-15、GATA-3均(-);皮脂腺分化区域:CK5/6、p40、GATA-3、EMA均(+),SMA灶(+);AR、GCDFP-15、vimentin、CD117、CD15均(-);鳞癌区域:p40、p63、CK5/6均(+) 。随访56个月,患者无复发及转移。结论伴皮脂腺分化的腺样囊性癌和鳞癌构成的食管碰撞瘤临床罕见,需与基底细胞样鳞癌、黏液表皮样癌、腺鳞癌及MuiR-Torre综合征鉴别。
孤立性部分实性肺结节28例影像学与临床病理分析

目的探讨孤立性部分实性肺结节不同病理学类型与临床及影像学特征的相关性。方法将28例孤立性部分实性肺结节分为良性组、浸润前病变组、微浸润腺癌组和浸润性腺癌组;分析上述不同病理类型部分实性肺结节在临床资料及CT影像学特征间的差异。结果28例患者中良性病变3例、浸润前病变5例、微浸润腺癌12例、浸润性腺癌8例。不同病理类型的临床特征、组间差异,均无统计学意义(P均>0.05) 。不同病理类型中肺结节大小、外形、空泡征、支气管充气征、分叶或毛刺、实性成分大小及比例,在4组间差异有统计学意义(P均<0.05) 。进一步两两比较:浸润性腺癌结节大小、外形、空泡征、支气管充气征、分叶或毛刺、实性成分大小及比例与其它组别相比,差异有统计学意义(P均<0.05);微浸润腺癌结节大小、空泡征、分叶或毛刺与良性、浸润前病变组相比,差异有统计学意义(P均<0.05) 。以实性成分长径5 mm及占结节比例0.25为界,其中长径>5 mm且构成比>0.25的浸润性腺癌明显高于其它组,差异有统计学意义(P均<0.05) 。结论孤立性部分实性肺结节病理以微浸润及浸润性腺癌恶性病变为主。影像学特征与病理学存在一定相关性;结节越大、外形不规则,伴空泡征、支气管充气征、分叶或毛刺,多提示浸润性或微浸润腺癌;以实性成分长径5 mm及占结节比例0.25为界,其中长径>5 mm且构成比>0.25有助于浸润性腺癌诊断,为临床提供指导。