bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tracing embodied CO2 emissions and drivers in China’s financial industry under inter-provincial trade
Authors: Xiao Donghua , Guo Wenhui , Liu Xincong , Zheng Yi , Gong Hao , Wang Chuan 
Published: November 2024

AbstractWith the establishment of “Dual Carbon” targets and industrial restructuring in China, the transition from the secondary industry to the tertiary industry has facilitated the rapid development of the financial sector. However, the significant CO2 emissions embodied within inter-provincial trade result in carbon leakage, posing challenges in assigning equitable carbon reduction responsibilities to the financial sectors across the 31 provinces of China. This study establishes a framework for evaluating CO2 emissions of financial sectors through 134 samples of 60 listed financial enterprises in the 31 provinces, tracking the embodied CO2 emissions within inter-provincial trade by using a multiregional input–output approach. The results reveal that the total CO2 emissions of the financial sector in China surged from 4.591 to 12.423 Tg CO2-eq between 2012 and 2020. The regions with the highest annual net CO2 emissions are Anhui (0.244 Tg), Zhejiang (0.242 Tg), and Henan (0.211 Tg). The key factors influencing net CO2 emissions are in the following order of importance: net CO2 density, per capita added value of service industry, the proportion of finances in service industries, and population size. Based on the findings, this study provides policy implications: reducing net carbon intensity, enacting tailored carbon tax policies based on embodied CO2 emissions, and fostering interdepartmental collaboration to address the impact of carbon leakage.
Root morphology, nitrogen metabolism and amino acid metabolism in soybean under low phosphorus stress
Authors: Liu Meiling , Zhao Mingzhe , Yang Guang , Sun Mingze , Yang Ahui , Sun Chang , Zhao Hongyu , Ao Xue 
Published: November 2024

AbstractPhosphorus deficiency is a major influence on growth and development of soybean. Therefore, improving phosphorus utilization efficiency in soybean is a research priority for the soybean community. In this experiment, Liaodou 13 (high phosphorus utilization: HPE) and Tiefeng 3 (low phosphorus utilization: LPE) were used as test varieties. We investigated changes in root morphology, amino acid content, and content of key substances of the nitrogen metabolic pathway with normal phosphorus (0.5 mM) and low phosphorus (0.005 mM) treatments. The results showed that the root length, root surface area and number of lateral roots of HPE roots were higher than those of LPE roots under normal and low phosphorus conditions. The contents of different types of amino acids showed different trends in two varieties. The HPE showed small change in the content of total hydrolyzed amino acids under the low phosphorus condition when compared to the normal phosphorus treatment by a 6.67% decrease, on the contrary LPE showed a drastic decrease by 20.36%. However, HPE exhibited similar decreasing trends in the contents of hydrolyzed and free aspartic acid with the low phosphorus treatment. Moreover, the contents of free histidine and valine in LPE were significantly increased by 657.84% and 149.29% respectively, in contrast to significant decreases in HPE. In aspects of major nutrient elements, the contents of phosphorus, total nitrogen and ammonia nitrogen in both HPE and LPE varieties decreased to dramatic levels. However, the nitrate nitrogen content significantly increased 78.51% for HPE and 65.12% for LPE. Compare to the normal condition, the GOGAT activity in HPE decreased by 5.18% but increased by 33.10% in LPE. Compare to the normal condition, the GS activity in HPE increased by 7.26% but decreased by 21.72% in LPE under phosphorus deficiency. In summary, the phosphorus-efficient soybean variety HPE exhibited superior tolerance to low phosphorus deficiency through advantageous root morphology, phosphorus uptake and transfer capability, and balanced amino acid metabolism and nitrogen metabolism pathways.
A photometric and spectroscopic study of eight semi-detached eclipsing binaries
Authors: Lei Yajuan , Zhou Guiping , Wang Liang , Li Guangwei , Li Kai , Yi Tuan 
Published: November 2024

Context. Semi-detached eclipsing binaries offer an exceptional opportunity to validate the evolutionary models of interacting binaries. This entails determining the absolute parameters and evaluating the evolutionary status of the binary components through simultaneous analysis of both light and radial velocity curves. The Transiting Exoplanet Survey Satellite (TESS) provides high-precision light curves, while the Large Sky Area Multi-Object Fibre Spectroscopic Telescope Medium-Resolution spectroscopic Survey (LAMOST MRS) offers multi-epoch observations. The combination of these data enhances the accuracy of deriving precise parameters for binary systems.
Aims. The aim of this study is to estimate the absolute parameters of semi-detached binary components, offer potential explanations for their evolutionary status, and investigate long-term variations in orbital periods to explore their underlying causes.
Methods. By cross-matching the eclipsing binary catalogue from TESS with that from LAMOST MRS, semi-detached eclipsing binaries with radial velocities spanning more than 0.3 phases were authenticated. The absolute parameters for these systems were determined by simultaneous modelling of light curves and radial velocities using the Wilson-Devinney programme. Additionally, the secular orbital variations were further analysed using O–C curves.
Results. Eight semi-detached eclipsing binaries have been identified. Among them, seven contain primary stars situated within the main-sequence band, while their secondaries are all in evolved stages. This suggests that these systems likely originated as detached binaries and have undergone a reversal of the mass ratio. However, TIC 428257299 is an exception where the primary is Roche lobe-filling, and its secondary has experienced mass loss events. Additionally, TIC 8677671 and TIC 318217844 demonstrate secular cyclical variations in orbital periods. Specifically, for TIC 8677671, the cyclical change could result from magnetic activity or a third body that is likely to be compact, with a mass of at least 2.97 M⊙.
Ultrasound of Postoperative Ankle Instability: How to Manage with Arthroscopic Reparation or Anatomical Reconstruction of Lateral Ankle Ligaments
Authors: Dallaudière Benjamin , Dalmau-Pastor Miki , Pesquer Lionel , Boudahmane Sofiane , Cordier Guillaume 
Published: November 2024

AbstractSurgical repair or reconstruction of lateral ankle ligaments is indicated in patients with persistent ankle instability, with arthroscopic/endoscopic treatment becoming more frequent. Although presurgical imaging of the ankle is always standard procedure, more is needed to understand the evolution of the repaired ligament or the tendinous graft to help improve length of postoperative time and functional results. This review describes the normal ultrasound aspects and possible complications of repaired/reconstructed ankle ligaments after an all-inside endoscopic repair/reconstruction of the anterior talofibular ligament and the calcaneofibular ligament.
1.2.5. German traditions
Authors: Henzel Katrin 
Published: November 2024

In German-speaking countries, scientific, poetological as well as political criteria have shaped literary archives, especially during the nineteenth century – with impact on their selection of manuscripts regarding authors, epochs and genres to the present day. The historical-critical edition and the genetic edition as one of its subtypes can be seen as a product of these circumstances and will be considered in this chapter to point out the varying role of literary drafts on the perception and reception of literary works. This must also include a critical examination of the German editorial tradition that – although a gradual change is emerging – still predominantly concentrates on canonical works.
Genomic surveillance for tackling emerging plant diseases, with special reference to wheat blast
Authors: Islam Tofazzal 
Published: November 2024

Abstract
Plant diseases are responsible for 20–40% of global crop yield losses, posing a significant threat to food security in the face of an ever-growing population. Genomic surveillance emerges as a powerful tool for diagnosing, early warning, and mitigating emerging plant diseases. This approach provides molecular insights into plant-pathogen interactions, essential for developing durable management strategies. Various omics techniques, including metagenomics, are employed in genomic surveillance to systematically monitor and analyze pathogen genomes. These analyses enable early detection of emerging threats, characterization of pathogen populations, tracking of pathogen movement, and accurate prediction of disease outbreaks. Genomic data serve as the foundation for point-of-care disease management using genome-specific primers and CRISPR technology. Despite its significant advantages, genomic surveillance faces challenges such as data analysis complexity, protocol standardization, ethical considerations, and technology accessibility. Key strategies to address these challenges include open data sharing, open science, and international collaboration. Recent advancements in sequencing technologies, bioinformatics tools, and collaborative networks offer promising solutions to these challenges, enhancing the potential of genomic surveillance in plant pathology. This comprehensive review updates the current progress and future prospects of genomic surveillance in disease detection and sustainable plant health management. It critically discusses the challenges of large-scale application and explores mitigation strategies through open data sharing, open science, and international collaboration.
Thermal pressure on ultrarelativistic bubbles from a semiclassical formalism
Authors: Long Andrew J. , Turner Jessica 
Published: November 2024

AbstractWe study a planar bubble wall that is traveling at an ultrarelativistic speed through a thermal plasma. This situation may arise during a first-order electroweak phase transition in the early universe. As particles cross the wall, it is assumed that their mass grows frommatomb, and they are decelerated causing them to emit massless radiation (mc= 0). We are interested in the momentum transfer to the wall, the thermal pressure felt by the wall, and the resultant terminal velocity of the wall. We employ the semiclassical current radiation (SCR) formalism to perform these calculations. An incident-charged particle is treated as a point-like classical electromagnetic current, and the spectrum of quantum electromagnetic radiation (photons) is derived by calculating appropriate matrix elements. To understand how the spectrum depends on the thickness of the wall, we explore simplified models for the current corresponding to an abrupt and a gradual deceleration. For the model of abrupt deceleration, we find that the SCR formalism can reproduce thePtherm∝γ0wscaling found in earlier work by assuming that the emission is soft, but if the emission is not soft the SCR formalism can be used to obtainPtherm∝γ2winstead. For the model of gradual deceleration, we find that the wall thicknessLwenters to cutoff the otherwise log-flat radiation spectrum above a momentum of ∼γ2w/Lw, and we discuss the connections with classical electromagnetic bremsstrahlung.
Axion signals from neutron star populations
Authors: Bhura U. , Battye R.A. , McDonald J.I. , Srinivasan S. 
Published: November 2024

Abstract
Neutron stars provide a powerful probe of axion dark matter, especially in higher
frequency ranges where there remain fewer laboratory constraints. Populations of neutron stars
near the Galactic Centre have been proposed as a means to place strong constraints on axion dark
matter. One downside of this approach is that there are very few direct observations of neutron
stars in this region, introducing uncertainties in the total number of neutron stars in this
“invisible” population at the Galactic Centre, whose size must be inferred through birth rate
modelling. We suggest this number could also be reduced due to stellar dynamics carrying stars
away from the Galactic Centre via large kick velocities at birth. We attempt to circumvent the
uncertainty on the Galactic Centre population size by modelling the axion signal from better
understood populations outside the Galactic Centre using PsrPopPy which is normalised
against pulsar observations. We consider lower-frequency, wider-angle searches for this signal via
a range of instruments including MeerKAT and SKA-low but find that the sensitivity is not
competitive with existing constraints. Finally, returning to the Galactic Centre, we compare
populations to single objects as targets for axion detection. Using the latest modelling of
axion-photon conversion in the Galactic Centre magnetar, we conclude that within astrophysical
uncertainties, the Galactic Centre population and the magnetar could give comparable sensitivities
to axion dark matter, suggesting one should continue to search for both signals in
future surveys.
Non-uniform electron density estimation based on electromagnetic wave attenuation in plasma
Authors: Wang 王 Zhaoying 召迎 , Guo 郭 Lixin 立新 , Fu 付 Maixia 麦霞 , Guo 郭 Shaoshuai 韶帅 , Li 李 Yinsheng 寅生 
Published: November 2024

Abstract
The surface of a high-speed vehicle reentering the atmosphere is surrounded by plasma sheath. Due to the influence of the inhomogeneous flow field around the vehicle, understanding the electromagnetic properties of the plasma sheath can be challenging. Obtaining the electron density of the plasma sheath is crucial for understanding and achieving plasma stealth of vehicles. In this work, the relationship between electromagnetic wave attenuation and electron density is deduced theoretically. The attenuation distribution along the propagation path is found to be proportional to the integral of the plasma electron density. This result is used to predict the electron density profile. Furthermore, the average electron density is obtained using a back-propagation neural network algorithm. Finally, the spatial distribution of the electron density can be determined from the average electron density and the normalized derivative of attenuation with respect to the propagation depth. Compared to traditional probe measurement methods, the proposed approach not only improves efficiency but also preserves the integrity of the plasma environment.
Unique Existence of Solution for A Fifth-order Fractional-type Fuzzy Difference Equation
Authors: Teng Xu , Wang Changyou , Li Lian 
Published: November 2024

Abstract
Based on the fuzzy numbers’ g-division, a fifth-order fractional-type fuzzy difference equation is a focus of research in this article. Firstly, by means of the fuzzy set theory, the fuzzy difference equation is converted into a homogamous constant difference equation with parameters, where the parameter values range from 0 to 1. Secondly, the unique existence of solutions to ordinary differential equations was obtained through iterative methods, inequality techniques, and mathematical induction. Finally, the unique existence of a solution to the fuzzy difference equations was proved.
Development of Rapid Evaluation and Analysis Cloud System for Bearing Capacity of Highway Bridges
Authors: Song Jianyong , Wang Zhicheng , Zhao An 
Published: November 2024

Abstract
In order to address and optimize the issues in the current assessment of bridge bearing capacity, such as the heavy workload associated with processing bridge data, the tedious modeling process, the inability to automatically calculate sub-item correction coefficients, and the lack of automatic report output and key data analysis functions, this paper has developed a cloud-based rapid calculation and analysis system for highway bridge bearing capacity. Firstly, the system is capable of quickly establishing finite element models and conducting detailed finite element calculations and analyses. Subsequently, based on field test data, it automatically calculates checking coefficients for each item and compares and analyzes the bridge’s bearing capacity. Utilizing a cloud network platform enables more convenient and rapid creation of bridge tasks and projects, key data statistical analysis, automatic report output, among other functions. Examples demonstrate that the system achieves data fusion, statistics, result verification which shifts highway bridge bearing capacity evaluation towards networking and automation while enhancing efficiency and quality in carrying capacity evaluation work.
A Semi-supervised Protein Complex Identification Algorithm Based on Sparseness Constraint
Authors: Liu Guangming , Dang Fengqing , Wang Bin , Peng Yonghong , Wang Xiaofan , Tan Li 
Published: November 2024

Abstract
Recognising protein complexes in protein interaction networks is crucial, but poses a major challenge due to the frequency of noisy interactions. These networks typically involve numerous protein complexes, with each protein generally only participating in a few complexes. Current recognition models often ignore this aspect. To address this problem, we present a semi-supervised protein complex identification algorithm that extends non-negative matrix factorization (NMF) with sparsity constraints. In contrast to conventional approaches that apply a global sparsity constraint to the entire matrix, our method imposes individual sparsity constraints on protein membership indicator vectors. This targeted strategy controls the algorithm more effectively. Our experimental results with yeast and human protein interaction networks show that our algorithm achieves higher accuracy in identifying protein complexes than leading contemporary methods.
Modeling and Optimization Algorithm for Rotational Irrigation Group Based on Connectivity Weighted Index
Authors: Li Wei , Deng Hongtao , Lin ping , Ding lianjun , Cao bing 
Published: November 2024

Abstract
Manual calculations for rotational irrigation groups are inefficient, and a single objective cannot provide farmers with diverse options. Based on considering both engineering standards and practical needs, this study designs a connectivity index and proposes a new model with the optimization objectives of balanced flow and minimum connectivity. To address infeasible solutions and constraint issues, A hybrid genetic algorithm based on variable neighborhoods is adopted to enhance the search capability of the classical non-dominated sorting genetic algorithm. The effectiveness and universality of the model and algorithm are verified through multiple real-world cases. The research shows that the proposed multi-objective model is more practical than a single-objective model, and farmers can be provided with diverse Pareto solutions by adjusting the weight index ω. The variable neighborhood search algorithm enhances the search capability within the radius threshold, improves population diversity, and analyzes the radius threshold and branch pipe flow parameters to explore factors that affect algorithm performance and indicators.
Multi-Objective Reliable Optimization Dispatch of High-proportion Power System Based on Improved Particle Swarm Algorithm
Authors: Huang Linyun , Zhang Yong , Su Yujie , Bae Youngchul 
Published: November 2024

Abstract
Energy storage technology is pivotal for managing high-proportion power system consumption and maintaining real-time power balance. The optimal configuration of energy storage is influenced by factors such as capacity, wind power loads, and output power. This paper utilizes dynamic programming to evaluate the operational efficiency of conventional units and wind turbines within the power system, followed by the application of an enhanced particle swarm optimization algorithm to tackle optimization challenges. A BP neural network is employed to predict the impact of different units on the power balance of the micro-grid, aiming to achieve maximum comprehensive benefits and minimize investment costs. A reliability model is proposed to balance power storage and load release, thereby improving system stability and reliability. Simulation results demonstrate that dynamic programming combined with enhanced particle swarm optimization can reduce the operating costs of the micro-grid, highlighting the practical advantages of power system energy storage technology.
Adaptive Prediction and Error Correction of Outlet Moisture Content in Rotary Drying Using Multivariate Linear Regression and Transfer Function Models
Authors: Gao Yulei , Qi Jun Xing Yu , Wu Yongxin , Yang Yaojing , Zhou Xiaolong , Han Jinjiang 
Published: November 2024

Abstract
To achieve adaptive prediction and error correction of tobacco moisture content after rotary drying in cigarette production, hierarchical cluster analysis was employed to prune the drying parameters of cut tobacco. Leveraging the data characteristics observed during the drying process, we constructed a multivariate linear regression model and a transfer function model based on principal component analysis. For seamless implementation in a computer program, both forecasting models were discretized. The prediction error was corrected online using the moving average method and the second-order exponential smoothing method to enhance the models’ adaptive capability and prediction accuracy. Results from the production environment indicate that while the multivariate linear regression model can generally capture the overall trend of data changes, it falls short in accurately predicting local and real-time moisture variations. In contrast, the transfer function model, enhanced with second-order exponential smoothing, improved the root mean square error (RMSE) and the coefficient of determination (R2) to 0.052 and 0.779, respectively. This adaptive approach effectively accommodates the dynamic characteristics of the rotary drying process, captures random fluctuations in moisture, and delivers precise moisture predictions.
Simulation and Field Measurement of Wind-Induced Vibration Response Characteristics of the Lightning Rod
Authors: Guo Wei , Ma Wenchang , Hu Mengqin , Meng Jiazheng , Liu Yanliang , Shang Yanjun , Liu Bo , Xu Jianxin , He Bo 
Published: November 2024

Abstract
Studying the wind-induced vibration model and response characteristics of lightning rods is crucial for achieving their rational design and wind stability. To address the current shortcomings in considering on-site wind load characteristics and the lack of differentiated considerations in the design phase of lightning rods, it is essential to establish an effective simulation model that accurately reproduces the wind induced vibration response of lightning rods and extracts key parameters for analysis. In this study, a 330kV independent lightning rod in Ningxia province, China, was identified as the subject of analysis. Building upon the structural vibration model, the response of the lightning rod to wind induced vibrations was calculated, and the simulation results were systematically validated through on-site measurements. The results indicate that the simulation model developed in this study can effectively replicate the vibration process of the lightning rod under wind load, providing comprehensive mechanical data. The research findings contribute to a deeper understanding of the wind induced characteristics of on-site lightning rods, facilitating the simulation analysis of lightning rod wind induced responses. Furthermore, the vibration law and characteristic parameters of the lightning rod structure hold great significance for the differentiated design and structural health monitoring of independent lightning rods.