bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Sympathetic Inrush Identification Method Based on the Time-Frequency Energy
Authors: Peng Fang , Gao Houlei 
Published: December 2023

Abstract
Sympathetic inrush is a phenomenon caused by the energization of the neighboring unloaded transformer. It may cause current differential protection to operate in the wrong way. Due to the lack of a special and continuous identification method, this paper studies the inherent feature of the two transformers during sympathetic inrush. Then a substation-area current signal based on the feature is constructed and its characteristics are analyzed. The time-frequency energy of the current signal is extracted based on the synchrosqueezed wavelet transform (SWT) since the SWT can process the transient signals accurately. The extracted energy is taken as the basis of the identification criterion. The simulation results conducted by PSCAD/EMTDC software prove the accuracy and effectiveness of the proposed method.
Optimized Transfer Learning Based Short-term Electrical Load Interval Prediction
Authors: Bai Qinyi , Huang Dongbin , Xiao Ling 
Published: December 2023

Abstract
Electrical load forecasting is an essential foundation for power reliable and economical operation of the power grid. Most forecasting models regard the prediction results as deterministic variables, which ignores the randomness and volatility of the power load. At the same time, insufficient historical load data often lead to undertrained models, which affects the accuracy of capturing uncertain information. Therefore, we proposed an optimized transfer learning-based method for short-term load-interval prediction. A deep learning quantile regression model would be constructed by source domain data in the method, and the weights of the source model would be optimized to avoid negative transfer. Then, the target model is constructed by parameter transfer based on key layers and is tuned with hyperparameters by target domain data. From the experimental discussion, it is known that the model with an optimized transfer learning strategy can accurately quantify the fluctuation range of future power load.
Research on Networking of 10 kV Substation Management Information Area
Authors: Xiao Suchao , Wang Nan , Wang Shixin , Shen Xiangming 
Published: December 2023

Abstract
At present, the substation network management information area, as an essential part of the substation network communication, is an important transmission channel to realize the intelligent auxiliary control of the substation network. Establishing a stable and reliable substation management information area network has become an essential part of upgrading the substation network. Firstly, this paper designs a Gigabit-Capable PON, and an industrial Ethernet networking scheme, based on certain city data. Secondly, based on the availability of single-device operation, a calculation model algorithm for reliability analysis is innovatively proposed to realize the comparison of networking solutions. Thirdly, regarding the economy, the concept of unit incremental investment reliability index is applied to two groups of networking solutions comparison for the first time. Finally, a networking scheme and suggestions for the substation network management information area are proposed.
Topological Singularity Pair in Nonreciprocal Non-Hermitian Lossy-dielectric Gyromagnetic Metasurface
Authors: Jiang Yimin , Wong Wai Chun , Fung Kin Hung , Yu Siu Fung 
Published: December 2023

Abstract
The transmission properties of a nonreciprocal non-Hermitian metasurface composed of lossy dielectric and gyromagnetic materials are studied with closed-form analytical solutions. It is found that a pair of opposite topological singularities of isolation ratio exist in a two-dimensional (2D) parameter space, and their evolution with parameter adjustment is preliminarily studied. These results provide clues for the design of optical devices. Further study of the mechanism of this singular behavior may reveal the complex systematic effect of non-Hermiticity and non-reciprocity on optical performance.
A WSN clustering routing method based on an improved WOA-optimized K-means clustering algorithm
Authors: Jiang Zihao , Chen Renwen , Liu Hao , Zhang Junyi , Li Shanan 
Published: December 2023

Abstract
To address the problem of transmission energy consumption and premature node death in wireless sensor networks (WSN), a novel routing strategy by IWOA that optimizes the K-means (KM) is proposed. WOA is improved by using it to optimize the KM algorithm, and more evenly distributed and suitable cluster centers are selected as the initial cluster heads (CH). In the CH election process, a CH election function is established, and the optimal CH under the influence of multiple factors is obtained. The simulation results have verified the feasibility of the proposed scheme in this paper.
Collaborative Scheduling Algorithm for Dependent Tasks based on Multi-Agent RL in VEC Environment
Authors: Xu Pengfei , Ding Xu , Zheng Xiang , Zhang Bixun , Lyu Qingzhou , Liang Tao , Shi Lei 
Published: December 2023

Abstract
To address the problem of limited computing power of vehicles, Vehicle Edge Computing (VEC) allows vehicles to schedule tasks to edge nodes with sufficient resources. In this paper, we propose a multi-agent reinforcement learning (MARL) approach to solve the multi-task scheduling problem in a dynamic VEC environment. First, we model the cooperative scheduling problem of dependent tasks in the VEC environment, considering the task priority and edge node load balancing in the task scheduling process. We define the optimization objective as minimizing the task processing delay and find it is an NP-hard problem. Then, we design a distributed algorithm SCMA based on MARL. The algorithm enables vehicles to find the optimal scheduling strategy by cooperating and sharing resources with each other. Finally, we use SUMO to simulate the road network topology and generate vehicle traffic trajectories. We construct heterogeneous vehicular applications for simulation experiments using the DAG generator. Compared with existing algorithms, the simulation results validate the superiority of the SCMA algorithm.
A Fast Gap Detection Algorithm Based on Machine Vision
Authors: Li Pengxin , Gao Quanqin , Chen Yuepeng , Sun Haiyang , Cai Qingyu , Tang Xiaoan 
Published: December 2023

Abstract
In order to be able to quickly locate the position of the gap of an industrial device in the industrial inspection process, a fast gap detection algorithm based on machine vision is proposed by using the feature of a high gray level difference between the image gap and the background in machine vision. First, nonlinear equalization preprocessing is adopted, and then multiple one-dimensional functions are composed based on the sum of the gray values of the horizontal axis as well as the differentiation, and then the proximity position averaging operation is done after obtaining the positional information through the extreme value and the most value operation. The algorithm transforms the two-dimensional image into a combination of multiple one-dimensional functions with related features, and finally accurate position information is obtained by analysing and fusing the one-dimensional functions. Multiple discriminative bases are used for the same data source to ensure the accuracy of the results. Experiments show that the method proposed is faster and less error-prone, has higher accuracy and detection efficiency, and meets the needs of industrial real-time detection, compared with the traditional Hough transform algorithm and the LSD detection algorithm.
Research on 5G Network Slicing Algorithm Based on the Smart Grid
Authors: Teng Wanyi , Yang Xu 
Published: December 2023

Abstract
To address the problem of network-slicing resource allocation in the smart grid, this paper puts forward a hierarchical network-slicing resource scheduling strategy for the smart grid based on priority and network utility, which is a study of the 5G net slice resource allocation (the max algorithm of utility). It is divided into two layers, which are the user layer and the slice allocation layer. By adopting different resource allocation methods to better meet the service and the experience quality of power users in different slices, the simulation results playing the strategy are better than the other number of resource allocation schemes.
Sputtered vanadium carbon nitride (VCN) thin films: a potential electrode for supercapacitors
Authors: Prasath G Vijaya , Vivekanandan J , Selvamurugan M , Usha K S , Sakthivel P , Babu G Anandha , Ravi G 
Published: December 2023

Abstract
The preparation of efficient thin film-based electrode materials is a vital prerequisite for practical energy storage devices. Herein, we have prepared unique vanadium carbon nitride (VCN) thin films on FTO substrates by pulsed DC magnetron sputtering technique for competent supercapacitor electrodes. XRD analysis confirmed the crystalline nature of VCN thin films. SEM and AFM revealed a smooth morphology with an average grain size of 30 nm. Raman spectra showed two broad peaks around 1346 and 1589 cm−1, belonging to the D-band and G-band of VCN. The surface electronic states of VCN were investigated by XPS analysis, which confirmed the formation of pure VCN films without any impurities. The electrochemical performance of the thin film electrode was evaluated using cyclic voltammetry (CV), Galvanostatic charge–discharge (GCD), and Electrochemical impedance analysis (EIS). The electrochemical results showed the VCN thin films exhibited super capacitive behaviours. The maximum specific capacitance (Cs) value of 78.2 F g−1 was obtained from GCD studies. A variation in charge transfer resistance is detected from the EIS study, which arises due to the partial oxidation of the active nitride component. The VCN electrode showed good cycling stability, retaining 87% of its capacitance at a current density of 5 A g−1 even after 2000 cycles. The sputtered VCN films have been demonstrated as potential thin film electrodes for electrochemical supercapacitors for practical energy storage devices.
Observationally constrained mass balance box model analysis of aerosol mitigation potential using fan powered filters
Authors: Wang Shuo , Cohen Jason Blake , Wang Xinying , Chen Weina , Deng Weizhi , Tiwari Pravash , Yang Yuanjian , Lolli Simone 
Published: December 2023

Abstract
Indoor air pollution contributes significantly as a world-wide environmental issue, impacting health and livelihood. To quantify benefits of filtration on indoor air quality, it is essential to understand the relationships between the various factors impacting the concentrations of indoor air pollutants. This work uses a mass-conserving 2-box model, high-frequency observations of aerosol number concentration, and a home-made, low-cost, 3-layer non-woven fabric filter, powered by a standard ventilation fan to quantify the effectiveness aerosol reduction in multiple indoor environments. The data shows that aerosol loading is effectively reduced under both steady-state and extreme event conditions, although there are significant and important differences between simultaneous observations both indoor and outside. To obtain a proper accounting, the following must be considered: the usage or not of the fan filter, whether windows are opened or closed, the state of outdoor air is pollution, and the strength and duration of indoor emissions. The experiments are applied in residential indoor environments in four cities in eastern (Xuzhou), central (Zhoukou), and southern (Zhuhai and Shunde) China. Photographic evidence of the altered fan filter state under both conditions show that while usually dark/black aerosols dominate, there are conditions when yellow aerosols also dominate. The observations are based on multiple, independent, continuous low-cost sensors which have been calibrated against a GRIMM-180 over the number concentration range from 0.3 to 1.0 microns, and yield a removal rate due to the fan-filter of 46%, 80%, 81%, and 36% respectively across the four cities. A corresponding rate to return from an extreme event to steady-state, is computed outdoors and indoors respectively from: 14.−44. minutes, 6.6–21. minutes, 16.−33. minutes, and 24.−58. minutes. The most important factors contributing to the removal efficiency and decay gradient are observed as keeping windows closed and reducing leakiness, the apartment/classroom size, and the outdoor air pollution loading.
Computational phase transition signature in Gibbs sampling
Authors: Philathong Hariphan , Akshay Vishwanathan , Zacharov Igor , Biamonte Jacob 
Published: December 2023

Abstract
Gibbs sampling is fundamental to a wide range of computer algorithms. Such algorithms are set to be replaced by physics based processors—be it quantum or stochastic annealing devices—which embed problem instances and evolve a physical system into a low-energy ensemble to recover a probability distribution. At a critical constraint to variable ratio, satisfiability (SAT) problem instances exhibit a SAT-UNSAT transition (frustrated to frustration free). Algorithms require increasing computational resources from this critical point. This is a so called, algorithmic or computational phase transition and has extensively been studied. In this paper we consider the complexity in sampling and recovering ground states from resultant distributions of a physics based processor. In particular, we first consider the ideal Gibbs distributions at some fixed inverse temperature and observe that the success probability in sampling and recovering ground states decrease for instances starting at the critical density. Furthermore, simulating the Gibbs distribution, we employ Ising spin dynamics, which play a crucial role in understanding of non-equilibrium statistical physics, to find their steady states of 2-SAT Hamiltonians. We observe that beyond the critical density, the probability of sampling ground states decreases. Our results apply to several contemporary devices and provide a means to experimentally probe a signature of the computational phase transition.
Bark wings are related to the primary vascular system: the case of Piptadenia gonoacantha (Leguminosae)
Authors: Teixeira Felippe A , Gerolamo Caian S , Junior Amilcar W S , Pace Marcelo R 
Published: December 2023

Abstract
Bark wings are projections commonly interpreted as plant protective structures against herbivory. Their location in stems has been typically thought to be random, something that here we dispute, using Piptadenia gonoacantha as a case study. We collected stem samples from several specimens in different developmental stages from natural populations in the Brazilian Atlantic rainforest. These stems were studied in detail under light microscopy to determine the formation of bark wings and their possible correlation with other anatomical features. Stems of P. gonoacantha are deeply lobed during primary growth, with each lobe containing a large vascular bundle, alternating with smaller vascular bundles in the interlobes. On top of these lobes, prickles develop, being composed of epidermal tissue and the cortex beneath. Some of the eight lobes merge and a phellogen is installed on top of them, which starts to produce a large sheath of phellem, which will become the conspicuous bark wings of Piptadenia. The phellogen switches on and off, leaving marks resembling growth rings. The bark wings in Piptadenia have very specific positioning, always in the front of five to eight major vascular bundles, indicating that bark wings appear always in very precise locations.
Perioperative outcomes of bi-pigtail catheter drainage strategy versus conventional chest tube after uniportal video-assisted thoracic lung surgery
Authors: Song Liwei , Chen Xingshi , Zhu Li , Qian Gang , Xu Yanhui , Song Zuodong , Li Jiantao , Chen Tianxiang , Huang Jia , Luo Qingquan , Cheng Xinghua , Yang Yunhai 
Published: December 2023

Abstract

OBJECTIVES
Chest tube (CT) drainage is a main cause of postoperative pain in lung surgery. Here, we introduced a novel drainage strategy with bi-pigtail catheters (PCs) and conducted a randomized controlled trial to compare with conventional CT drainage after uniportal video-assisted thoracic surgery lung surgery.

METHODS
A single-centre, prospective, open-labelled, randomized controlled trial (ChiCTR2000035337) was conducted with a preplanned sample size of 396. The primary outcome was the numerical pain rating scale (NPRS) on the first postoperative day. Secondary outcomes included other indicators of postoperative pain, drainage volume, duration of drainage, postoperative hospital stay, incidence of postoperative complications, CT reinsertion and medical costs.

RESULTS
A total number of 396 patients were randomized between August 2020 and January 2021, 387 of whom were included in the final analysis. The baseline and clinical characteristics of the patients were well balanced between 2 groups. The NPRS on the first postoperative day was significantly lower in the PC group than in the CT group (2.40 ± 1.27 vs 3.02 ± 1.39, p &lt; 0.001), as well as the second/third-day NPRS, the incidence of sudden severe pain (9/192, 4.7% vs 34/195, 17.4%, P &lt; 0.001) and pain requiring intervention (19/192, 9.9% vs 46/195, 23.6%, P &lt; 0.001). In addition, the medical cost in the PC group was lower (US$7809 ± 1646 vs US$8205 ± 1815, P = 0.025). Univariable and multivariable analyses revealed that the drainage strategy was the only factor influencing the incidence of pain requiring intervention.

CONCLUSIONS
The drainage strategy with bi-PCs in patients undergoing uniportal video-assisted thoracic surgery lung surgery alleviates postoperative pain with adequate safety and efficacy.
Direct Seeding for Conifer Regeneration in the Pacific Northwest: A Past, Present, and Future of Operational Practices
Authors: Downer Rebecca , Manteuffel-Ross Tiffani , Tymon Lydia , Aghai Matthew 
Published: December 2023

AbstractUnited States Pacific Northwest (PNW) forests are important ecological, cultural, and recreational landscapes. Direct seeding to aid forest regeneration in the PNW region was developed to reduce reforestation costs and timelines. These practices were largely discontinued in the 1970s due to poor establishment resulting from issues of seed predation, a lack of targeting favorable site conditions, seed distribution issues, and improvements to nursery seedling production. A recent renewed interest in direct seeding research has resulted from the growing geographic extent of postdisturbance areas requiring reforestation. This interest is also supported by the increasing recognition of the logistical impossibility of satisfying reforestation demand via planted seedlings. This historical review highlights the timeline of direct seeding research and practice in the PNW. It describes the main obstacles to its widespread use and opportunities for improvement. These opportunities include upscaling seed collection efforts, increasing distribution precision of seeding methods, upgrading seed quality evaluations, and mitigating seed predation and desiccation.Study Implications: The availability of seedlings is increasingly limited due to the rising demand for reforestation as a result of more frequent and severe wildfires. Further research into direct seeding as an artificial regeneration strategy for trees is necessary to operationally increase reforestation abilities and thus supplement natural regeneration and seedling planting. This study summarizes findings from prior direct seeding studies in the Pacific Northwest region and identifies (1) improving seed collection efforts, (2) refining seed quality assessments, (3) standardizing seed dispersal methods, and (4) improving seedling establishment by targeting favorable site conditions and predation mitigation as key future research priorities.
Detection and Quantification of Extraterrestrial Platinum Group Element Alloy Micronuggets from Archean Impactite Deposits by Low-Voltage Scanning Electron Microscopy/Energy-Dispersive X-ray Spectrometry
Authors: Salge Tobias , Mohr-Westheide Tanja 
Published: December 2023

Abstract
Rare, heterogeneously composed platinum group element alloy micronuggets (PGNs) occur in primitive meteorites, micrometeorites, and terrestrial impactite deposits. To gain insight into the nature of these phases, we developed a workflow for the characterization of PGNs using modern scanning electron microscopy (SEM) and energy-dispersive X-ray spectrometry at a low accelerating voltage of 6 kV. Automated feature analysis—a combination of morphological image analysis and elemental analysis with stage control—allowed us to detect PGNs down to 200 nm over a relatively large analysis area of 53 mm2 with a conventional silicon drift detector (SDD). Hyperspectral imaging with a high-sensitivity, annular SDD can be performed at low beam current (∼100 pA) which improves the SEM image resolution and minimizes hydrocarbon contamination. The severe overlapping peaks of the platinum group element L and M line families at 2–3 keV and the Fe and Ni L line families at &lt;1 keV can be resolved by peak deconvolution. Quantitative elemental analysis can be performed at a spatial resolution of &lt;80 nm; however, the results are affected by background subtraction errors for the Fe L line family. Furthermore, the inaccuracy of the matrix correction coefficients may influence standards-based quantification with pure element reference samples.
False-Positive Human Immunodeficiency Virus Nucleic Acid Amplification Test After Chimeric Antigen Receptor T-Cell Therapy With Ciltacabtagene Autoleucel
Authors: Keri Vishakh C , Topulli Mary Vito , Deol Abhinav , Uberti Joseph , Salimnia Hossein , Chandrasekar Pranatharthi H 
Published: December 2023

Abstract
Chimeric antigen receptor (CAR) T-cell therapy has emerged as a novel therapeutic option for hematologic malignancies. Human immunodeficiency virus (HIV) nucleic acid amplification tests (NAATs) amplifying 5′ long terminal repeat and gag genes cross-react with lentiviral vector-based CAR T-cell products. Cross-reactivity between CAR T-cell products and HIV NAATs may lead to false-positive test results.