bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptive anomaly detection disruption prediction starting from first discharge on tokamak
Authors: Ai X.K. , Zheng W. , Zhang M. , Ding Y.H. , Chen D.L. , Chen Z.Y. , Guo B.H. , Shen C.S. , Wang N.C. , Yang Z.J. , Chen Z.P. , Pan Y. , Shen B. , Xiao B.J. ,   J-TEXT team
Published: January 2025

Abstract
Plasma disruption presents a significant challenge in tokamak fusion, especially in large-size devices like ITER, where it causes severe damage. While current data-driven machine learning methods perform well in disruption prediction, they require extensive discharge data for model training. However, future tokamaks will begin operations without any prior data, making it difficult to train data-driven disruption predictors and select appropriate hyperparameters during the early operation period. In this period disruption prediction also aims to support safe exploration of operation range and accumulate necessary data to develop advanced prediction models. Thus, predictors must adapt to evolving plasma states during this exploration phase. To address these challenges, this study further develops the enhanced convolutional autoencoder anomaly detection (E-CAAD) predictor and proposes a cross-tokamak adaptive transfer method based on E-CAAD. By training the E-CAAD model on data from existing devices, the predictor can effectively distinguish between disruption precursor and non-disruption samples in new device, enabling disruption prediction from the first shot on the new device. Additionally, adaptive learning from scratch and alarm threshold adaptive adjustment strategies are proposed to enable model automatically adapt to changes in the discharge scenario. The adaptive learning strategy enables the predictor to fully use scarce data during the early operation of the new device while rapidly adapting to changes in the discharge scenario. The threshold adaptive adjustment strategy addresses the challenge of selecting alarm thresholds on new devices where the validation set is lacking, ensuring that the alarm thresholds adapt to changes in the discharge scenario. Finally, the experiment transferring the model from J-TEXT to EAST exhibit that this method enables disruption prediction from the first shot on EAST, allowing the predictor to adapt to changes in the discharge scenario and maintain high prediction performance.
Research on end-to-end process model based on process mining for cross-disciplinary domains in power grid industry
Authors: Chen Zhen , Liao Rongzhou , Wu Xiaoquan 
Published: January 2025

Abstract
Conventional end-to-end process models are developed from an end-to-end perspective, which are affected by the inconsistency of massive data in cross-disciplinary domains and fails to meet the model implementation requirements. Therefore, the topic of end-to-end process modeling based on process mining for cross-disciplinary domains in power grid industry is studied. Grid cross-disciplinary domain parameter identifiers are generated to define the key attributes and characteristics of end-to-end processes in the power grid industry. We optimize the goal of closeness of end-to-end process links across professional domains based on process mining, assigning goal weights in terms of the average time delay of process links, the delivery error or abnormal rate, and the number of interactions between processes in different professional domains. The value constraints of the end-to-end process in the power grid industry cross-disciplinary domain are established. The constraints of the end-to-end process, such as security, grid reliability, economy, social responsibility, are taken into account to satisfy the needs of cross-disciplinary domains. Comparative experiments are used to verify that the model has better performance and can be applied in real life.
Comprehensive analysis of electrical faults in shore power systems and research on performance improvement strategies
Authors: Wu Peisen , Xiao Kangcong , Zhang Bo , Zhang Ying 
Published: January 2025

Abstract
The use of shore power by docked ships is an important energy substitute for environmental protection measures, and an efficient and stable shore power system is the cornerstone of achieving green transformation in ports. This study delves into various electrical faults encountered by shore power systems in practical applications, including short circuits, overloads, high and low voltages, and power quality issues. Targeted fault diagnosis techniques and improvement strategies are proposed. The effectiveness of the improvement measures proposed in this paper has been verified through field investigations and simulation experiments, providing a useful reference for eliminating electrical safety hazards in shore power systems.
Overall architecture design of power IoT transmission scenario based on cloud-edge-end collaboration
Authors: Li Hua , Wu Zhengrong , Liu Yunhua , Luo Jialin , Yang Kangping 
Published: January 2025

Abstract
The general architecture of the conventional power IoT transmission scenario mainly uses MPCAuth (mutual proof of consent authentication) mutual authentication protocol for identity authentication, which is vulnerable to the impact of remote deployment expansion, resulting in poor comprehensive performance indicators. Therefore, a general architecture of the power IoT transmission scenario based on cloud-side collaboration is proposed. That is, the cloud-side collaborative classification is used to process the data of the power Internet of Things, optimize the overall architecture response mode of the power Internet of Things transmission scenario, and thus complete the overall architecture design of the power Internet of Things transmission scenario. The experimental results show that the overall architecture of the power IoT transmission scenario designed has good performance indicators, reliability, and certain application value, and has made certain contributions to promoting the development of power informatization and ensuring the quality of power supply and distribution.
Research on fault identification method of high-voltage circuit breaker based on wavelet packet dispersion entropy feature extraction
Authors: Yan Xuefeng , Chen Shengcang , Jin Siming , Liu Hongxu , Ma Shouxiao 
Published: January 2025

Abstract
A high-voltage circuit breaker fault identification approach based on wavelet packet dispersion entropy feature extraction is suggested in order to address the issue of low accuracy of high-voltage circuit breaker fault diagnosis and identification under complicated operation states. Wavelet packet transform (WPT) is used first to break down the vibration signal. The feature matrix is then constructed by calculating the dispersion entropy of each subband. Lastly, the classification algorithm models of support vector machine (SVM), extreme learning machine (ELM), and particle swarm optimized extreme learning machine (PSO-ELM) are compared with the fault diagnosis model of particle swarm optimized support vector machine (PSO-SVM) to diagnose and classify each operating condition state of the circuit breaker. The PSO-SVM fault recognition model’s test set fault diagnostic accuracy is 95.83%, which is noticeably higher than that of the other three models, as demonstrated by the findings, confirming the method’s efficacy.
Investigation of GIS post-arc current test device and post-arc recovery behavior
Authors: Chen Yuexian , He Ruobing , Yuan Linkun , Xu Zhixian , Chen Ke , Li Jinglai 
Published: January 2025

Abstract
GIS is crucial in high-voltage power systems, necessitating high standards of reliability and ease of maintenance. The circuit breaker, as the system’s core component, is vital for the safe operation of both GIS and the broader power grid. During the interruption of high current, plasma exists in the circuit breaker’s contact gap, and its movement, influenced by transient recovery voltage (TRV), leads to post-arc current. Accurately measuring this post-arc current is essential for assessing the circuit breaker’s performance. This paper presents a self-developed testing device that evaluates post-arc current under harmonic influences, exploring how varying short-circuit current frequencies and zero-front current slopes affect the characteristics of the post-arc current in a 126 kV pressurized gas circuit breaker.
An ultra low-power galloping monitoring sensor based on acceleration measuring unit
Authors: Gao Kai , Lu Bo , Xiao Rong , Yao Zhoufei , Zhang Kaili , Wang Mengge 
Published: January 2025

Abstract
The galloping of transmission lines is a phenomenon that transmission lines vibrate and wobble due to the influence of weather, power load, wire distortion and other factors in the process of power transmission. This phenomenon will lead to the tripping of the transmission line, and the damage to tower crossarms, jumpers, and insulators, which will pose a great threat to line operation. In order to detect this phenomenon as early as possible, an ultra low-power sensor based on the acceleration measuring unit (AMU) is designed to monitor the conductor galloping phenomenon on the transmission line. The sensor uses AMU to monitor the original motion parameters of the wire acceleration and angular velocity, and can identify the wave frequency and amplitude accurately by the improved wave characteristic parameter analysis algorithm. At the same time, the galloping monitoring sensor has a low power consumption design, which can detect the galloping phenomenon of the transmission line more safely and stably.
A fault diagnosis method for partial discharge in distribution switchgear based on global Feature-enhanced residual shrinkage network
Authors: Zhuang Qingtao , Zhang Juan , Lin Jianhua , Liu Wanwei 
Published: January 2025

Abstract
Partial Discharge (PD) is a vital indicator of insulation performance and degradation in distribution switchgear. Efficiently and accurately identifying PD fault types is crucial for rectifying equipment anomalies and ensuring the power grid’s reliability. However, current PD diagnosis methods fall short in denoising capabilities and global feature extraction, hindering their effectiveness amidst complex and noisy PD signals. This study introduces the Global Feature-Enhanced Residual Shrinkage Network (GFRSNet) to overcome these challenges. By integrating a non-local module and Residual Attention Denoising modules (RADM), GFRSNet not only captures extensive global feature information but also effectively eliminates noise features from PD signals. This integration enhances the model’s capability to provide more precise and reliable fault diagnosis. Experimental results on our on-site PD dataset show that the GFRSNet attains an accuracy of 94.06%, surpassing many other excellent methods. This indicates that our method has high application value in diagnosing PD fault types.
Controls on coastal saline groundwater across North America
Authors: Kretschmer Daniel V , Michael Holly A , Moosdorf Nils , Essink Gualbert H P Oude , Bierkens Marc F P , Wagener Thorsten , Reinecke Robert 
Published: January 2025

Abstract
Groundwater is crucial to sustaining coastal freshwater needs. About 32 million people in the coastal USA rely on groundwater as their primary water source. With rapidly growing coastal communities and increasing demands for fresh groundwater, understanding controls of continental-scale coastal groundwater salinity is critical. To investigate what hydrogeological factors (e.g. topography, hydraulic conductivity) control coastal saline groundwater at continental scales, we have simulated variable-density groundwater flow across North America with the newly developed Global Gradient-based Groundwater Model with variable Densities (G3M-D). The simulation results suggest that under a steady climate and pre-development conditions (i.e. steady 30-year mean groundwater recharge, no withdrawals nor sea level rise) saline groundwater is present in 18.6% of North America’s coastal zone, defined as up to 100 km inland and up to 100 m above mean sea level. We find that the coastal zone is particularly vulnerable to containing saline groundwater at low hydraulic gradients (<10−4) and large hydraulic conductivities (>10−2 m d−1). To analyze model parameter sensitivities, i.e. which parameters control the resulting distribution of saline groundwater, we utilize the inherent spatial model variability. We find that hydraulic gradient, topographic gradient, hydraulic conductivity, and aquifer depth are important controls in different places. However, no factor controls coastal groundwater salinization alone, suggesting that parameter interactions are important. Using G3M-D based on G3M, a model that previous work found to be strongly controlled by topography, we find no controlling influence of recharge variability on the saline groundwater distribution in North America. Despite a likely overestimation of saline interface movement, the model required 492 000 years to reach a near-steady state, indicating that the saline groundwater distribution in North America has likely been evolving since before the end of the last ice age, approximately 20 000 years ago.
Transport analysis of the EHL-2 spherical torus in a high-ion-temperature scenario
Authors: WANG 王 Xueyun 雪韵 , LIU 刘 Wenjun 文军 , YANG 杨 Danke 丹可 , YANG 杨 Guang 光 , TAN 谭 Muzhi 沐芝 , JIANG 姜 Xinchen 欣辰 , XIE 谢 Huasheng 华生 , SHI 石 Yuejiang 跃江 , ZHAO 赵 Hanyue 寒月 , WANG 王 Yumin 嵎民 , LIANG 梁 Yunfeng 云峰 , DONG 董 Jiaqi 家齐 , WU 吴 Bin 斌 , LIU 刘 Chengyue 成岳 , Team the EHL-2 
Published: January 2025

Abstract
EHL-2 is an ENN second-generation device aimed at studying proton-boron (p-11B) fusion reactions in a spherical torus. The design parameters are T
i0 ~ 30 keV, T
i/T
e > 2,

, I
p ~ 3 MA, B
t ~ 3 T, and

~ 0.5 s. High ion temperature is one of the standard operation scenarios of EHL-2, aiming to reduce bremsstrahlung radiation while enhancing plasma parameters by elevating the ion to electron temperature ratio. In order to achieve high ion temperature, neutral beam injection is considered the primary heating method during the flat-top phase. The neutral beam system for EHL-2 comprises 3–5 beams with energy/power ranging from 60 keV/4 MW, 80–100 keV/10 MW, to 200 keV/3 MW. This work conducts predictive analysis on core transport during the flat-top phase of EHL-2’s high-ion-temperature scenario utilizing ASTRA. The study delineates the potential operating range of core temperature and other parameters given the designed heating capacity. Specifically, the study presents predictive simulations based on CDBM, GLF23, Bohm–gyro–Bohm, and IFSPPPL transport models, evaluating the steady-state power balance, energy confinement time, and impact of various parameters such as plasma density and NBI power on core ion temperature. The simulations demonstrate that the design parameters of the EHL-2 high-T
i scenario, although sensitive to varying transport models, are hopefully attainable as long as adequate ion heating and controlled ion transport levels are ensured.
Conceptual framework to integrate food waste research and food systems research
Authors: Rolker Heike B , Cardenas Laura , Reynolds Christian , Takahashi Taro 
Published: January 2025

Abstract
It is estimated that a quarter to one-third of food intended for humans does not fulfil its original purpose. Yet, and despite its universally acknowledged importance for sustainability, mechanisms behind food waste generation are often studied unconnectedly from other challenges surrounding food systems. Here, we examine how concepts, assumptions and frameworks adopted in the food waste literature and the food systems literature overlap, contradict and complement one another. We discuss the current evidence on why and how food waste occurs and discuss modifications required for a conceptual framework to improve the integration between the two groups of studies. The resulting framework makes an explicit distinction between context-specific direct causes and context-independent indirect drivers of food waste, with practice theory interlinking them by portraying human behaviour and associated agency that translate the latter into the former. Central to our conceptualisation is an enhanced recognition that the ultimate cause of food waste is almost always natural decay, which cannot be prevented but can be managed through a systems approach with clear definitions of temporal boundaries.
Effectiveness of different colors of aerial fruit-baited traps for trapping Cerambycidae and Cetoniidae beetles (Insecta: Coleoptera) in the Amazon rainforest
Authors: Puker Anderson , Ferreira Evangelista Luiz Filipe , Brandão Mattos Diego , Mattos Brandão Carlos Eduardo , Ferreira Evangelista João Pedro , Correa César Murilo de Albuquerque , da Silva Pedro Giovâni , Salomão Renato Portela , Monné Marcela Laura 
Published: January 2025

Abstract
Colored traps can attract or repel insect species, and effects vary among biological groups. Cerambycidae and Cetoniidae are diverse Coleoptera families of ecological and economic importance in forest and agroecosystems. Here, we assessed the effectiveness of different colors of aerial fruit-baited traps in capturing Cerambycidae and Cetoniidae beetles in the Amazon rainforest. We evaluated 4 trap colors: blue, yellow, red, and transparent (control). We sampled Cerambycidae and Cetoniidae beetles from February 2022 to January 2024 in 5 Amazon forests. We collected a total of 1588 individuals and 18 species of Cerambycidae, and 345 individuals and 11 species of Cetoniidae. Species richness and composition of Cerambycidae and Cetoniidae beetles did not differ across the different trap colors. Blue traps exhibited lower abundance of Cerambycidae than did other trap colors. Transparent traps captured more common species (Shannon diversity) than red traps. Moreover, transparent traps harbored more dominant species (Simpson diversity) of Cerambycidae compared to other trap colors. A combination of factors involving the insect with its innate or learned ability to perceive different colors and the characteristics of local vegetation can influence insect preference for certain colors. Our findings provide evidence of the high efficiency of transparent traps for sampling the diversity of Cerambycidae and Cetoniidae beetles in the Amazon rainforest.
Effects of US state paid family leave policies on perinatal and postpartum health: A quasi-experimental analysis
Authors: Wells Whitney M , White Justin S , Collin Daniel F , Wang Guangyi , Modrek Sepideh , Hamad Rita 
Published: January 2025

Abstract
The US is the only high-income country without a national paid family leave (PFL) policy, although several states have implemented policies recently. This study evaluated whether PFL policies in six states improved maternal and infant health. We used difference-in-differences, a quasi-experimental approach, to estimate the impact of state-level policy implementation. We leveraged recently developed methods designed to account for staggered policy implementation and treatment effect heterogeneity. Data were drawn from the Pregnancy Risk Assessment Monitoring System 2004-2021 waves. Primary outcomes included breastfeeding, maternal postpartum depressive symptoms, and attendance at a postpartum check-up; secondary outcomes included birth outcomes. Multivariable regressions were adjusted for possible confounders. PFL policies led to increased breastfeeding duration (0.53 weeks; 95% CI: 0.06 to 0.99) and decreased depressive symptoms (-0.93 percentage points; 95% CI: -1.84 to -0.01). Policies were also associated with worsening of some birth outcomes, possibly reflecting selection in utero, data limitations, or true negative effects. Estimates were largely robust to alternative specifications, with subgroup differences by race/ethnicity and income. This study adds important evidence on the health effects of state-level PFL policies at a critical point when many states are considering or enacting policies, and during ongoing conversations about national PFL policy implementation.
Ancient reticulation, incomplete lineage sorting and the evolution of the pyrenoid at the dawn of hornwort diversification
Authors: Peñaloza-Bojacá Gabriel , Maciel-Silva Adaíses , Cargill D Christine , Bell David , Sessa Emily B , Li Fay-Wei , Burleigh J Gordon , McDaniel Stuart F , Davis E Christine , Endara Lorena , Allen N Salazar , Schafran Peter , Chantanaorrapint Sahut , Duckett Jeffrey G , Pressel Silvia , Solís-Lemus Claudia , Renzaglia Karen S , Villarreal A. Juan Carlos 
Published: January 2025

Abstract

Background and Aims
Resolving the phylogeny of hornworts is critical in understanding the evolution of key morphological characters that are unique to the group, including the pyrenoid. Extensive phylogenomic analyses have revealed unexpected complexities in the placement of Leiosporoceros, the previously identified sister taxon to other hornworts. We explore the role of incomplete lineage sorting (ILS) and ancient reticulation in resolving interrelationships and comprehending the diversification and evolutionary processes within hornworts.

Methods
Using the GoFlag probe set, we sequenced 405 exons representing 234 nuclear genes, sampling 79 hornwort specimens, including representatives of all hornwort genera. We inferred the species phylogeny from gene tree analyses using concatenated and coalescence approaches, assessed ancient reticulation, ILS, and estimated the timing of divergences based on fossil calibrations.

Key Results
Extreme levels of gene tree incongruence challenge the sister relationship of Leiosporoceros to other hornworts. This phylogenetic discordance is due to incomplete lineage sorting and ancient reticulation, the latter revealed using a network approach to identify evidence of gene flow among hornwort lineages. Hornworts diversification began in the Carboniferous with widespread family-level divergences during the mid-Cretaceous and Paleogene.

Conclusions
Incomplete lineage sorting and ancient reticulation are identified as important in hornwort evolution. Patterns of hornwort diversification parallel those in other plants groups (e.g., liverworts, mosses, ferns, and gymnosperms). Two scenarios on pyrenoid evolution are plausible based on the variable position of the pyrenoid-free Leiosporoceros. Pyrenoids were retained from a green algal ancestor and are plesiomorphic, or they evolved in response to the substantial drop in atmospheric CO2 levels during the Carboniferous as has been hypothesized in other photosynthetic organisms. Both hypotheses require losses and gains during hornwort speciation.
Unpalatable birds are black: a re-analysis of Hugh Cott’s data on bird palatability
Authors: Delhey Kaspar , Valcu Mihai , Kempenaers Bart 
Published: January 2025

Abstract
Many animals are aposematic, signalling their unprofitability via sounds, smells, or conspicuous colours. Although some birds are toxic, it remains unclear whether aposematism is broadly distributed in birds. Here, we re-analyse historical data compiled by Hugh Cott on bird palatability as assessed by humans and hornets. We use phylogenetic analyses to link palatability to plumage coloration and other covariates. Our analyses reveal that bird palatability has a moderate phylogenetic signal and that species with low palatability are more black. We also show that low palatability is associated with an animal-based diet and, paradoxically, with safer nests. However, accounting for the effects of these covariates in the model does not change the effects of colour. These results support Cott’s original hypothesis that birds can signal distastefulness through their colours. The convergence on black coloration might constitute a case of Müllerian mimicry. We hypothesize that black is a suitable aposematic colour because melanization is often associated with needs for detoxification. Our results suggest that aposematism in birds might be more widespread than assumed, but they need to be corroborated using other relevant predators of birds.