bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-time multi-risk assessment of large scale power system with high-penetration renewable energy
Authors: Zhang Tingxiang , Xu Ying , Yi Zhongkai , Xu Jianing , Cai Xinlei , Wang Naixiao 
Published: June 2024

Abstract
To accurately assess the impact of real-time uncertainty of high penetration renewable energy sources on the real-time operation of large-scale power systems, this study proposes an innovative method for real-time multi-risk assessment in power systems. Firstly, by utilizing an improved spectral clustering algorithm and mixture density network to analyze historical operational data, effective clustering of different renewable energy generation curves and accurate fitting of prediction errors were achieved. Next, random sampling was performed from the probability density curves of prediction errors to obtain real-time renewable energy outputs. At the same time, a non-sequential Monte Carlo method was used to incorporate interruptions for each component into the scenario simulation. Subsequently, a state assessment was conducted for each sampled scenario by minimizing load shedding and energy curtailment. On this basis, risk indices that comprehensively consider the real-time flexibility of the system and power supply-demand imbalances were established. Finally, validation in a test system verified the accuracy and speed of the proposed multi-risk assessment method.
Research on system/regional dispatch center-based hierarchical zonal load dispatch model
Authors: Yang Zhuo , Zhao Shilin , Lu Wenbing 
Published: June 2024

Abstract
The development of new power systems and the expanding scale of demand-side load resources represented by electric vehicles have brought new challenges to the stable and economic operation of power systems, and the current load aggregation regulation model is no longer adapted to the current environment. Based on this, this paper proposes a hierarchical zonal load aggregation regulation model, in which the system layer and the regional layer cooperate to regulate the resources, and finally verifies the feasibility and economy of the model by example analysis.
Simulation of breakdown voltage associated with phase-to-phase air gap for ultra high voltage transmission lines under switching impulse voltage
Authors: Su Yu , Ding Yujian , Yao Xiuyuan , Fu Yufei 
Published: June 2024

Abstract
Knowledge of the breakdown voltage of air gaps when subjected to positive switching impulse voltage is fundamental to the design of insulation coordination for power transmission systems. However, the length of phase-to-phase air gaps in ultra-high voltage power transmission lines has reached more than 30 m. It is very difficult, costly, and impossible to conduct full-scale test experiments to obtain the breakdown voltage of these gaps. Here, the numerical simulation method based on the self-consistent leader inception and propagation model was first used to simulate the air gap discharge process at four different scales and to obtain the gap breakdown voltage. The simulated data was compared with the measured data to verify the validity of the model. Then, the numerical simulation method was used to simulate the discharge process of phase-to-phase air gap for ultra-high voltage transmission lines with 30.3 m in length. The current and the development trajectory of the leader tip were obtained for the discharge process. More importantly, the breakdown voltage, which could not be obtained by full-scale testing, was obtained by simulation.
Multi-level anomaly detection of lithium battery energy storage system
Authors: Zhu Yong , Liu Mingyi , Hao Xiaowei , Liu Shunfu , Kong Jinliang , Yang Jieli , Li Peng , Wang Jianxing 
Published: June 2024

Abstract
The energy storage technology route represented by lithium battery energy storage strongly supports China’s energy structure transformation. The widespread use of lithium batteries also poses a significant safety risk that is often overlooked. Energy storage system security is facing severe challenges. It is very beneficial for the safety of energy storage systems to predict the potential faults of lithium batteries before they are used and find anomaly batteries in time. This paper proposes a three-stage anomaly detection method based on statistics and density concepts to provide real-time potential fault prediction of lithium battery energy storage systems. Considering both efficiency and accuracy, this method can detect anomaly samples from shallow to deep. Finally, the battery condition of a large energy storage plant was studied, and 11 anomaly batteries were detected. The proposed method is significant for safely operating large energy storage power stations.
The aging pattern of lithium-ion batteries based on experiments at different temperatures
Authors: Cui Yugang , Wang Xiao , Zou Shibo , Wang Qian , Kang Jianqiang 
Published: June 2024

Abstract
In this paper, we take an 18650-type LiFePO4 battery as the research object to investigate the aging mechanism of Li-ion batteries at different temperatures. The aging tests are conducted at 25°C, 35°C and 45°C. The results show that elevating the operating temperature can improve the cycle life of Li-ion batteries. The aging mechanism was analyzed by incremental capacity and electrochemical impedance spectrum analysis. The following conclusions were obtained: the aging mechanism of lithium-ion batteries mainly includes loss of lithium inventory, loss of active material, and conductivity loss, among which loss of lithium inventory and loss of active material are the main causes of Li-ion battery aging, and the contribution of conductivity loss is the smallest. Further analysis of the causes of battery aging by disassembling and testing the aging electrode sheet SEM and TEM shows that the aging of Li-ion battery is manifested by the rupture of graphite particles, the generation of SEI layer and lithium dendrite, and increasing the temperature can ease the rupture of graphite particles and the generation of lithium dendrite, thus improving the cycle life of the battery.
Research on anomaly detection in oil chromatography based on convolutional neural network and grey relational analysis algorithm
Authors: Li Yongqin , Fu Yifeng , Han Fei , Zhao Zehaohan 
Published: June 2024

Abstract
The power transformer is a crucial voltage conversion node and a core device in substations. Currently, dissolved gas analysis (DGA) in oil is a practical and validated method for assessing the operational status of transformers. In this study, addressing issues such as insufficient data mining from single dissolved gas measurements, we employed a combination of Convolutional Neural Network and Grey Relational Analysis algorithm to enhance the reliability of identifying abnormal dissolved gas data in transformer oil. This approach improves the sensitivity and accuracy of transformer fault detection. The study includes data processing and result analysis, indicating that the proposed algorithm effectively identifies abnormal dissolved gas data in transformer oil.
Analysis of frequency stability of power grid considering variable speed constant frequency wind motor with local low rotational inertia
Authors: Jia Qi , Liu Wansong , Wang Mingkai , Zhang Xiaoming , Cao WenBin , Liu Kai 
Published: June 2024

Abstract
A significant quantity of renewable energy equipment, including photovoltaics and wind turbines, will be connected to the grid instead of traditional synchronous generator sets. However, the significant percentage of renewable energy sources that have been integrated into the power grid will lead to the frequency safety problem of the power system. The decrease in system inertia can adversely affect the stability of the power system’s frequency. Therefore, the influence of the local low moment of inertia on the frequency stability of the power grid is analyzed from the static and dynamic perspectives, and the method of participating in the primary frequency modulation after the wind turbine is connected to the grid is studied by taking the variable speed constant frequency wind turbine as an example.
Study on product structure of 8 GW converter transformer for 800 kV flexible HVDC
Authors: Wang Mingsheng , Chai Dongxin , Liang Shuqi , Wang Haorui 
Published: June 2024

Abstract
Based on the design scheme of ±800 kV 8 GW flexible DC converter transformer, given the large magnetic leakage loss caused by a large number of voltage regulating leads, this paper proposes an improvement measure to add a compensating copper plate to the core plate at the side of the voltage regulating leads. It calculates the structural parts with the help of magnetic field analysis software MagNet. The analysis shows that the compensation copper plate can reduce the loss of structural parts and control the local overheating caused by magnetic leakage.
Research on current harmonic suppression of permanent magnet synchronous motor using smith predictive controller
Authors: Kan Kun 
Published: June 2024

Abstract
Due to the dead time added to the operation of the motor inverter, the generated current harmonics are introduced into the synchronous motor, increasing the harmonic content of the motor. The higher harmonic content is the 5th, 7th, 11th, and 13th current harmonics, which can cause motor torque ripple [1]. To suppress the current harmonics that cause torque ripple, a control method of using a PI controller and a quasi-proportional resonant controller in parallel is considered to suppress current harmonics. However, the introduction of a proportional resonant controller can cause greater overshoots in the current response, and external environmental influences can also generate current disturbances. Therefore, a method based on Smith prediction-PID and quasi-proportional resonance controller cascade control structure is proposed to suppress current harmonics and current overshoot in response to this problem. Finally, the effectiveness of this method was verified through simulation experiments, thereby improving the stability of synchronous motor operation.
Beyond comparison: Brillouin microscopy and AFM-based indentation reveal divergent insights into the mechanical profile of the murine retina
Authors: Gutmann Marcus , Salvador Jana Bachir , Müller Paul , Kim Kyoohyun , Schicht Martin , Aif Serhii , Paulsen Friedrich , Meinel Lorenz , Guck Jochen , Möllmert Stephanie 
Published: June 2024

Abstract
Mechanical tissue properties increasingly serve as pivotal phenotypic characteristics that are subject to change during development or pathological progression. The quantification of such material properties often relies on physical contact between a load-applying probe and an exposed sample surface. For most tissues, meeting these requirements entails an invasive preparation, which poses the risk of yielding mechanical properties that do not portray the physiological state of a tissue within a functioning organism. Brillouin microscopy has emerged as a non-invasive, optical technique that enables the assessment of mechanical cell and tissue properties with high spatio-temporal resolution. In optically transparent specimens, it does not require animal sacrifice, tissue dissection or sectioning. However, the extent to which results obtained from Brillouin microscopy allow to infer conclusions about potential results obtained with a contact-based technique, and vice versa, is unclear. Sources for discrepancies include the varying characteristic temporal and spatial scales, the directionality of measurement, environmental factors, and mechanical moduli probed. In this work, we addressed those aspects by quantifying the mechanical properties of acutely dissected murine retinae using Brillouin microscopy and atomic force microscopy (AFM)-based indentation measurements. Our results show a distinct mechanical profile of the retinal layers with respect to the Brillouin frequency shift, the Brillouin linewidth and the apparent Young’s modulus. Contrary to previous reports, our findings do not support a simple correlative relationship between Brillouin frequency shift and apparent Young’s modulus. Additionally, the divergent sensitivities of Brillouin microscopy and AFM-indentation measurements to structural features, as visualized by transmission electron microscopy, to cross-linking or changes post mortem underscore the dangers of assuming interchangeability between the two methods. In conclusion, our study advocates for viewing Brillouin microscopy and AFM-based indentation measurements as complementary tools, discouraging direct comparisons a priori and suggesting their combined use for a more comprehensive understanding of tissue mechanical properties.
Precontractual Justice
Authors: Dagan Hanoch , Dorfman Avihay 
Published: June 2024

Abstract
This chapter argues that the maxim of reciprocal respect for self-determination and substantive equality is key to liberal contract law because it justifies the enforcement of contracts and prescribes a mandatory floor for contractual justice. In modern contract law, this floor deviates from the traditional laissez-faire mode of regulating the parties’ bargaining process, which only prohibits one party’s active interference with the other’s free will. Discarding the contractual vision of interpersonal independence by carefully following relational justice, however, does not create unacceptable interpersonal subordination, as champions of the ancien régime would want us to believe. This chapter analyzes in these terms the affirmative interpersonal obligations that typify many of contract’s invalidating factors. Thus, it celebrates the expansion of the law of fraud beyond the traditional categories of misrepresentation and concealment to include affirmative disclosure duties, showing how the same conceptual expansion also underlies doctrines as diverse as unilateral mistake, duress in cases of wrongful threats that do not violate others’ rights, anti-price-gouging laws, and admiralty rules of salvage. Likewise, it explains why a concern with relational justice offers the most charitable explanation of the unconscionability doctrine and some of its modern regulatory cognates.
Physical activity, fitness, and cardiac autonomic function among adults born postterm
Authors: Oksanen Päivi , Tikanmäki Marjaana , Tulppo Mikko P , Niemelä Maisa , Korpelainen Raija , Kajantie Eero 
Published: June 2024

Abstract
Recent studies have suggested that adverse outcomes of postterm birth (≥42 completed weeks of gestation), including increased cardiometabolic risk factors, impaired glucose metabolism, and obesity, may extend into adulthood. We studied interconnected determinants of cardiovascular health, including physical activity (PA; based on accelerometry for 2 weeks), muscular strength (measured by handgrip strength), cardiorespiratory fitness (CRF; measured by 4-min step test), and cardiac autonomic function (heart rate [HR] recovery, HR variability, and baroreflex sensitivity) among 46-year-old adults from the Northern Finland Birth Cohort born postterm (n = 805) and at term (n = 2645). Adults born postterm undertook vigorous PA 2.0 min day−1 (95% CI, 0.4-3.7) less than term-born adults when adjusted for sex, age, and maternal- and pregnancy-related covariates in multiple linear regression. Postterm birth was associated with reduced CRF, based on a higher peak HR (2.1 bpm; 95% CI, 0.9-3.4) and slower HR recovery 30 s after the step test (−0.7 bpm; 95% CI, −1.3 to −0.1). Postterm birth was associated with less PA of vigorous intensity and CRF and slower HR recovery in middle age. Our findings reinforce previous suggestions that postterm birth should be included as a perinatal risk factor for adult cardiometabolic disease.
Triple challenges—small sample size in both exposure and control groups to scan rare maternal outcomes in a signal identification approach: a simulation study
Authors: Thai Thuy N , Winterstein Almut G , Suarez Elizabeth A , He Jiwei , Zhao Yueqin , Zhang Di , Stojanovic Danijela , Liedtka Jane , Anderson Abby , Hernández-Muñoz José J , Munoz Monica , Liu Wei , Dashevsky Inna , Messenger-Jones Elizabeth , Siranosian Elizabeth , Maro Judith C 
Published: June 2024

Abstract
There is a dearth of safety data on maternal outcomes after perinatal medication exposure. Data-mining for unexpected adverse event occurrence in existing datasets is a potentially useful approach. One method, the Poisson tree-based scan statistic (TBSS), assumes that the expected outcome counts, based on incidence of outcomes in the control group, are estimated without error. This assumption may be difficult to satisfy with a small control group. Our simulation study evaluated the effect of imprecise incidence proportions from the control group on TBSS’ ability to identify maternal outcomes in pregnancy research. We simulated base case analyses with “true” expected incidence proportions and compared these with imprecise incidence proportions derived from sparse control samples. We varied parameters that have an impact on type I error and statistical power (exposure group size, outcome’s incidence proportion, and effect size). We found that imprecise incidence proportions generated by a small control group resulted in inaccurate alerting, inflation of type I error, and removal of very rare outcomes for TBSS analysis due to “zero” background counts. Ideally, the control size should be at least several times larger than the exposure size to limit the number of false positive alerts and retain statistical power for true alerts.
This article is part of a Special Collection on Pharmacoepidemiology.
Effect of pharmacist care on clinical outcomes and therapy optimization in perioperative settings: A systematic review
Authors: Naseralallah Lina , Koraysh Somaya , Alasmar May , Aboujabal Bodoor 
Published: June 2024

Abstract

Purpose
Integration of pharmacists into the perioperative practice has the potential to improve patients’ clinical outcomes. The aim of this systematic review is to systematically investigate the evidence on the roles of pharmacists in perioperative settings and the effects of pharmacist interventions on clinical outcomes and therapy optimization.

Methods
A protocol-led (CRD42023460812) systematic review was conducted using search of PubMed, Embase, CINAHL and Google Scholar databases. Studies that investigated the roles and impact of pharmacist-led interventions in the perioperative settings on clinical outcomes were included. Data were extracted and quality assessed independently by two reviewers using the DEPICT-2 (Descriptive Elements of Pharmacist Intervention Characterization Tool) and the Crowe Critical Appraisal Tool (CCAT), respectively. Studies were grouped according to the clinical area into 5 sections: (1) pain control and opioid consumption; (2) venous thromboembolism (VTE); (3) surgery-related gastrointestinal complications; (4) postoperative medication management; and (5) total parenteral nutritional.

Results
Nineteen studies involving a total of 7,168 patients were included; most studies were conducted in gastrointestinal (n = 7) and orthopedics (n = 6) surgical units. Most included studies (n = 14) employed a multicomponent intervention including pharmaceutical care, education, guideline development, drug information services, and recommendations formulation. The processes of developing the implemented interventions and their structures were seldom reported. Positive impacts of pharmacist intervention on clinical outcomes included significant improvement in pain control and reductions in the incidence of VTE, surgery-related stress ulcer, nausea, and vomiting. There is inconsistency in the findings related to medication management (ie, achieving desired therapeutic ranges) and management of chronic conditions (hypertension and type 2 diabetes).

Conclusion
Whilst there is some evidence of positive impacts of pharmacist intervention on clinical outcomes and optimizing drug therapy, this evidence is generally of low quality and insufficient volume. While this review suggests that pharmacists have essential roles in improving the care of patients undergoing surgery, more research with rigorous designs is required.
Hierarchical multimodal self-attention-based graph neural network for DTI prediction
Authors: Bian Jilong , Lu Hao , Dong Guanghui , Wang Guohua 
Published: June 2024

Abstract
Drug–target interactions (DTIs) are a key part of drug development process and their accurate and efficient prediction can significantly boost development efficiency and reduce development time. Recent years have witnessed the rapid advancement of deep learning, resulting in an abundance of deep learning-based models for DTI prediction. However, most of these models used a single representation of drugs and proteins, making it difficult to comprehensively represent their characteristics. Multimodal data fusion can effectively compensate for the limitations of single-modal data. However, existing multimodal models for DTI prediction do not take into account both intra- and inter-modal interactions simultaneously, resulting in limited presentation capabilities of fused features and a reduction in DTI prediction accuracy. A hierarchical multimodal self-attention-based graph neural network for DTI prediction, called HMSA-DTI, is proposed to address multimodal feature fusion. Our proposed HMSA-DTI takes drug SMILES, drug molecular graphs, protein sequences and protein 2-mer sequences as inputs, and utilizes a hierarchical multimodal self-attention mechanism to achieve deep fusion of multimodal features of drugs and proteins, enabling the capture of intra- and inter-modal interactions between drugs and proteins. It is demonstrated that our proposed HMSA-DTI has significant advantages over other baseline methods on multiple evaluation metrics across five benchmark datasets.
NR4A1-mediated regulation of lipid droplets in progesterone synthesis in goat luteal cells
Authors: Yu Hao , Li Xiaotong , Zhao Jie , Wang Wei , Wei Quanwei , Mao Dagan 
Published: June 2024

AbstractNuclear receptor NR4A1 is a key factor in glycolipid metabolism and steroidogenesis, while lipid droplets serve as crucial dynamic organelles for lipid metabolism in luteal cells. To investigate the effects of NR4A1 on lipid droplet metabolism and progesterone (P4) synthesis in goat corpus luteum in vitro, luteal cells from the middle-cyclic corpus luteum were isolated and treated with Cytosporone B (CSNB, an agonist) or siRNA of NR4A1. Results showed that both low (1 μM) and high (50 μM) concentrations of CSNB promoted lipid droplet accumulation, while NR4A1 knockdown reduced lipid droplet content. CSNB increased while siNR4A1 decreased total cholesterol content; however, CSNB and siNR4A1 did not change triglyceride content. CSNB increased the expression of perilipins at mRNA and protein levels, also increased LDLR, SCARB1, SREBFs, and HMGCR mRNA abundance. Treatment with siNR4A1 revealed opposite results of CSNB, except for HMCGR and SREBF2. For steroidogenesis, 1 μM CSNB increased, but 50 μM CSNB inhibited P4 synthesis, NR4A1 knockdown also reduced the P4 level. Further analysis demonstrated that 1 μM CSNB increased the protein levels of StAR, HSD3B, and P-HSL, while 50 μM CSNB decreased StAR, HSD3B, and CYP11A1 protein levels. Moreover, 50 μM CSNB impaired active mitochondria, reduced the BCL2, and increased DRP1, Caspase 3, and cleaved-Caspase 3 protein levels. siNR4A1 consistently downregulated the P-HSL/HSL ratio and the steroidogenic protein levels. In conclusion, NR4A1-mediated lipid droplets are involved in the regulation of progesterone synthesis in goat luteal cells.