bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pairing phase transition in the odd-A nuclei: identification and classification*
Authors: Wang 王 Yumeng 宇萌 , Gao 高 Yuhang 宇航 , Liu 刘 Lang 朗 
Published: August 2024

Abstract
Research on the pairing phase transition in the odd-A nucleus

is based on a sophisticated blend of the covariant density functional theory and the shell-model-like approach. It has been observed that variations in thermodynamic quantities at the critical temperature do not exclusively align with pairing phase transitions. The presence of an S-shaped heat capacity curve, often interpreted as an indicator of such transitions, does not offer a definitive confirmation. Additional factors, including the blocking effect, can modify the heat capacity curve and impede the transition process. The pairing phase transition in

, which occurs approximately from 0.7 to 1.0 MeV, is unequivocally characterized as a first-order transition. Furthermore, the analysis of the impact of varying strengths of pairing correlations on these transitions reveals a nonlinear relationship, thereby adding complexity to the transition dynamics.
EEG workload estimation and classification: a systematic review
Authors: Hassan Jahid , Reza Md. Shamim , Ahmed Syed Udoy , Anik Nazmul Haque , Khan Md. Obaydullah 
Published: August 2024

Abstract
Objective. Electroencephalography (EEG) has evolved into an indispensable instrument for estimating cognitive workload in various domains. ML and DL techniques have been increasingly employed to develop accurate workload estimation and classification models based on EEG data. The goal of this systematic review is to compile the body of research on EEG workload estimation and classification using ML and DL approaches. Methods. The PRISMA procedures were followed in conducting the review, searches were conducted through databases at SpringerLink, ACM Digital Library, IEEE Explore, PUBMED, and Science Direct from the beginning to the end of February 16, 2024. Studies were selected based on predefined inclusion criteria. Data were extracted to capture study design, participant demographics, EEG features, ML/DL algorithms, and reported performance metrics. Results. Out of the 125 items that emerged, 33 scientific papers were fully evaluated. The study designs, participant demographics, and EEG workload measurement and categorization techniques used in the investigations differed. SVM, CNN, and hybrid networks are examples of ML and DL approaches that were often used. Analyzing the accuracy scores achieved by different ML/DL models. Furthermore, a relationship was noted between sample frequency and model accuracy, with higher sample frequencies generally leading to improved performance. The percentage distribution of ML/DL methods revealed that SVMs, CNNs, and RNNs were the most commonly utilized techniques, reflecting their robustness in handling EEG data. Significance. The comprehensive review emphasizes how ML may be used to identify mental workload across a variety of disciplines using EEG data. Optimizing practical applications requires multimodal data integration, standardization efforts, and real-world validation studies. These systems will also be further improved by addressing ethical issues and investigating new EEG properties, which will improve human-computer interaction and performance assessment.
Epileptic network identification: insights from dynamic mode decomposition of sEEG data
Authors: Nieto Ramos Alejandro , Krishnan Balu , Alexopoulos Andreas V , Bingaman William , Najm Imad , Bulacio Juan C , Serletis Demitre 
Published: August 2024

Abstract

Objective. For medically-refractory epilepsy patients, stereoelectroencephalography (sEEG) is a surgical method using intracranial electrode recordings to identify brain networks participating in early seizure organization and propagation (i.e. the epileptogenic zone, EZ). If identified, surgical EZ treatment via resection, ablation or neuromodulation can lead to seizure-freedom. To date, quantification of sEEG data, including its visualization and interpretation, remains a clinical and computational challenge. Given elusiveness of physical laws or governing equations modelling complex brain dynamics, data science offers unique insight into identifying unknown patterns within high-dimensional sEEG data. We apply here an unsupervised data-driven algorithm, dynamic mode decomposition (DMD), to sEEG recordings from five focal epilepsy patients (three with temporal lobe, and two with cingulate epilepsy), who underwent subsequent resective or ablative surgery and became seizure free. Approach. DMD obtains a linear approximation of nonlinear data dynamics, generating coherent structures (‘modes′) defining important signal features, used to extract frequencies, growth rates and spatial structures. DMD was adapted to produce dynamic modal maps (DMMs) across frequency sub-bands, capturing onset and evolution of epileptiform dynamics in sEEG data. Additionally, we developed a static estimate of EZ-localized electrode contacts, termed the higher-frequency mode-based norm index (MNI). DMM and MNI maps for representative patient seizures were validated against clinical sEEG results and seizure-free outcomes following surgery. Main results. DMD was most informative at higher frequencies, i.e. gamma (including high-gamma) and beta range, successfully identifying EZ contacts. Combined interpretation of DMM/MNI plots best identified spatiotemporal evolution of mode-specific network changes, with strong concordance to sEEG results and outcomes across all five patients. The method identified network attenuation in other contacts not implicated in the EZ. Significance. This is the first application of DMD to sEEG data analysis, supporting integration of neuroengineering, mathematical and machine learning methods into traditional workflows for sEEG review and epilepsy surgical decision-making.
Disappearance of dimits shift in realistic fusion reactor plasmas with negative magnetic shear
Authors: Yang Dingkun , Li Shengming , Xiao Yong , Lin Zhihong 
Published: August 2024

Abstract
This study employs gyrokinetic simulations to investigate ion temperature gradient (ITG) turbulence in realistic fusion reactor plasmas featuring reversed magnetic shear. The weakly negative magnetic shear is observed to be more stable for the ITG instability than strongly positive shear in this equilibrium configuration, primarily stemming from the scarcity of mode rational surfaces induced by the weak negative shear. This superiority in suppression for the negative shear persists in nonlinear turbulence with zonal flow artificially eliminated, where the emergence of turbulence solitons is observed and found associated with locally dense mode rational surfaces. However, the difference in transport levels among different magnetic shears diminishes in the presence of self-consistently generated zonal flow, accompanied by the disappearance of turbulence solitons. The nonlinear generation of zonal flow is found to be significantly affected by the magnetic shear. The study reveals a remarkable phenomenon that the Dimits shift no longer exists for negative magnetic shear, which is attributed to the weakness of the zonal flow generation near the ITG marginal stability.
Two-phase flow simulation of the catalyst layer/microporous layer interfacial wettability in PEMFCs
Authors: Wang Mengli , Zhu Lijun , Sui Pang-Chieh 
Published: August 2024

Abstract
To address the microscale two-phase flow issues at the catalyst layer (CL)/microporous layer (MPL) interface in proton exchange membrane fuel cells (PEMFCs), the lattice Boltzmann method is used to simulate the liquid water transport at the CL/MPL interface with different wettability. By clarifying the CL/MPL interfacial volume saturation and surface saturation distribution, the effect of CL contact angle on liquid water transport is revealed. The results show that when the CL is hydrophilic, the CL/MPL interfacial water saturation increases as the CL contact angle increases. Oppositely, when the CL is hydrophobic, the CL/MPL interfacial water saturation decreases as the CL contact angle increases. Further, when both the MPL and CL contact angles are 130°, water drainage at the CL/MPL interface performs the best.
Multi-objective optimization model of energy storage participating in peak load regulation of power grid
Authors: Mao Lilin , Luo Luo , Leng Zhaojin , Li Qin , Wang Linan , Cui Yiqiong 
Published: August 2024

Abstract
There is an increasing amount of new energy power generation being applied in power systems. However, the peak shaving problem faced by the power grid is becoming more and more significant. Large-scale energy storage access to the power grid can assist the power system in peak shaving. Therefore, this paper establishes an energy storage peak shaving model considering carbon footprint cost and establishes a user-side carbon footprint cost model. On this basis, multi-objective optimization is carried out. A multi-objective optimization model of energy storage participating in power grid peak shaving considering carbon footprint is established. The optimization model aims at the optimal PS-VF (Peak Shaving and Valley Filling) effect and the optimal economy of the ESPS (Energy Storage Power Station). The net load variance is used as the evaluation index of the PS-VF effect of the ESPS. By normalizing the multi-objective function, the example analysis is carried out, and the results verify the effectiveness of the model.
Experimental investigation on a Fiber Carbon-nano Laminated heater to improve LiFePO4 battery performances under low-temperature conditions
Authors: Tang Chao , Yuan Peiyu , Cen Zhixiong , Yin Zhenghan , Yan Yang , Xie Zonghong 
Published: August 2024

Abstract
LiFePO4 batteries play a vital role in electric vehicles (EVs). However, LiFePO4 batteries are significantly affected by low temperatures. In this research, a lightweight, efficient, low-voltage, and safe Fiber Carbon-nano Laminated (FCL) heater for LiFePO4 batteries is designed, developed, and experimentally validated. Experiments are conducted to heat LiFePO4 batteries under -20°C and compared with traditional Positive Temperature Coefficient (PTC) heaters. The results demonstrate that the FCL heater exhibits stable heating performance with uniform temperature distribution within the heating area. Heating for 45 minutes can raise the temperature of a LiFePO4 battery module from -15°C to 0°C, consuming 128.2 Wꞏh, approximately 2.7% of the battery module’s capacity. Compared to traditional PTC heaters, the FCL heater shows significant advantages: a 65.6% reduction in supplied voltage, a 59% decrease in weight, a 21.4% increase in power, a 3.5% decrease in energy consumption, a 26.0% improvement in temperature rise efficiency, and a 195% increase in power-to-weight ratio.
Research on signal and energy forward transmission of wireless power transmission system Based on LCC-S compensation
Authors: Yang Yongjun , Xu Fei 
Published: August 2024

Abstract
To solve the problem of forward transmission of signal and energy in an LCC-S-compensated wireless power transmission system, a scheme for energy and signal sharing the same channel for transmission under constant power conditions was proposed, which controlled the working frequency of the inverter for forward signal transmission based on the method of electric energy frequency modulation. The principle of constant power transmission is to explore whether there are other frequency points to make the voltage gain the same as the load voltage gain of the system at the resonant frequency when the signal is a high level 1. The inverter working frequency is the resonant frequency when the signal is low level 0. The inverter resonates to meet the other frequencies of constant power transmission, and the signal characteristics are converted to the working frequency of the system to realize the transmission of signal and energy. In this paper, the circuit model of the LCC-S ICPT system is built and analyzed, the software MATLAB is used to simulate it, the frequency characteristics are successfully converted to the working frequency of the system under the condition of constant power transmission, and the feasibility of the scheme is verified theoretically.
Mechanism modeling and expert system design of radar cold plate cleaning process
Authors: Liu Liang , Qiu Zhi , Chai Yanhong , Li Yuan , Liu Lanbo 
Published: August 2024

Abstract
Regarding the problem of effective recommendation of parameter values for radar cold plate cleaning, firstly, a mechanism modeling is carried out based on the particle washing process in the cold plate flow channel. Then, a forward inference strategy is adopted to design a radar cold plate cleaning process expert system based on the mechanism modeling. The expert system consists of five main parts: knowledge base, database, inference machine, explanation part, and knowledge acquisition. Finally, a radar cold plate cleaning test was conducted to verify the effectiveness of the recommended parameters. The test results showed that the cleaning parameter values recommended by the expert system for the cold plate cleaning process designed in this paper can meet the cleanliness requirements of radar cold plate cleaning.
Weight evaluation of comprehensive evaluation of difficulty in mechanical structure design of toy products based on ANP
Authors: Guo Qiqi , Huang Huiyu , Shu Sheng 
Published: August 2024

Abstract
Human society is currently in the era of the knowledge economy, and quantitative measurement of the difficulty of product design provides a basis for enterprises to further implement rational resource allocation, which has important practical significance for enterprises.
Based on the actual situation of the enterprise, this study aims to gain a deep understanding of the development process of toy products and establish a comprehensive evaluation index system suitable for evaluating the difficulty coefficient of the mechanical structure design of toy products. The study determined the evaluation indicators that affect the difficulty of mechanical structure design in the product development process through investigation and analysis methods and used the network analysis method to determine the weights of relevant evaluation indicators. Finally, the design difficulty coefficient of toy products was obtained by weighting. ANP comprehensively considered various factors while considering the mutual influence between them, describing and calculating the relationship between each factor, and conducting a comprehensive ranking. Several examples were conveniently calculated by using Super Decisions software, and the results showed that the application of ANP to evaluate the difficulty of mechanical structure design for toy products is reasonable.
Performance testing of a novel angle comparator with inner and outer shafts
Authors: Xia Yangqiu , Tang Qiang , Li Mengyang , Chen Long , Li Qiang 
Published: August 2024

Abstract
The angle comparator is a key device for calibrating angle devices, and its performance seriously affects the accuracy of angle calibration. In order to achieve high-precision angle reproduction, a new type of inner and outer axis angle comparator was developed, its angle measurement performance was tested, and the diagonal position error was compensated. Firstly, the structure of an internal and external axis angle comparator based on dual drive of ultrasonic motor and torque motor is briefly introduced. Then, the external cross-calibration method for the full fillet position error of the angle comparator and the testing and evaluation method for motion resolution were studied. Finally, the angle measurement performance of the angle comparator was tested and compensated, and the measurement results were analyzed and verified. The experimental results show that the compensated internal and external axis angle comparator has an angular position error of 0.08”, a measurement uncertainty of 0.03” (k=2), and a motion resolution of 0.018”, indicating that the developed instrument has a stable high-precision calibration ability in the sub arc-second level.
Nanosecond laser processing of silicon carbide groove structure
Authors: Li Jian 
Published: August 2024

Abstract
Through orthogonal experiments, this work explores and improves the laser parameters that affect bottom surface roughness and groove depth in silicon carbide grooves produced by nanosecond pulse laser machining. According to the findings, a frequency of 20 kHz, scanning speed of 400 mm/s, laser power of 18 W, path interval of 0.02 mm, and depth of 411.139 μm may be achieved by creating a groove with a bottom surface roughness of 3.170 μm.
Improving the phosphating process for Ca-P coating on ZK21 biomedical magnesium alloy
Authors: Wang Ruochao , Liu Qing , Liu Hongtao 
Published: August 2024

Abstract
The optimization study of the phosphating process was conducted on the surface of ZK21 biomedical magnesium alloy using the chemical conversion technique to fabricate Ca-P coating. The findings reveal that the optimal concentrations of the three additives in the phosphating solution, Ca(CH3COO)2, C6H4O5NSNa, and Na2MoO4, are 12 g/L, 2 g/L, and 0.5 g/L, respectively. Under these specified conditions, the resulting Ca-P coating appears compact and uniform. An optimal quantity of Ca(CH3COO)2 can enhance the concentration of Ca2+ in the solution. C6H4O5NSNa accelerates the rate of membrane formation, whereas Na2MoO4 facilitates the creation of nucleation sites, consequently bolstering membrane formation even further. Analysis through EDS and XRD confirmed that the predominant compound in the Ca-P coating is CaPO3(OH)2·2H2O (DCPD).
Bioinspired deformation computational design method for muscle-driven soft robots using MPM
Authors: Yin Ying , Cheng Mo , Li Zhiwei , Guan Yisheng , Su Manjia 
Published: August 2024

Abstract
In order to adapt to complex and changing environments, animals have a wide variety of locomotor forms, which has inspired the investigation of their deformation and driving mechanisms. In this paper, we propose a computational design method for muscle-driven soft robots to satisfy desired deformations, aiming to mimic the deformation behavior of muscle-driven animals in nature. In this paper, we generate the ideal muscle-driven layout for the soft robot by inputting an initial shape and a desired shape, so that it can closely achieve the desired deformation. The material point method is utilized to simulate the soft medium so as to achieve the effect of coupling and coordinated deformation of arbitrary shapes. Our method efficiently searches for muscle layouts corresponding to various deformations and realizes the deformation behaviors of a variety of bio-inspired robots, including soft robots such as bionic snakes, frogs, and human faces. Experimental results show that for both the bionic snake and frog soft robots, the overlap of the geometric contour regions between the actual and simulated deformations is more than 90%, which validates the effectiveness of the method. In addition, the global muscle distributions of the bionic snake and human face soft robots during motion are generated and validated by effective simulation.
Observed trends in multiple breadbasket yield shocks
Authors: Chen Xuan , Anderson Weston , You Liangzhi , Pope Edward 
Published: August 2024

Abstract
Extreme climate events in breadbasket regions have become more frequent due to climate change, exposing crops to a greater frequency and intensity of abiotic stress. But by using observed crop yield statistics and an ensemble of statistical models, we demonstrate that over the last six decades the frequency of crop yield shocks in breadbasket regions has been decreasing due to both climate and non-climate factors. Here non-climate factors refer to interannual variability unrelated to abiotic stress, such as biotic stress and management decisions. We find that although the risk posed by extreme heat to crop yields has been increasing, this risk has been offset by changes to precipitation, extremely cold days, and average growing season temperature in many breadbaskets. As a result, total climate-related crop yield shocks have been decreasing for soybeans and wheat, while they have remained roughly constant for maize. Meanwhile, non-climate risks to crop yields have decreased in nearly every breadbasket region across crops. Because non-climate risks have decreased faster than climate risks, we find that the climate accounts for a greater proportion of crop yield shocks in the recent period (1991–2020) compared to an earlier period (1961–90). Our results indicate that extreme climate events are more important than ever to the relative stability of the food production system, even as the overall frequency of multiple breadbasket yield shocks decreases.
Physical and practical constraints on atmospheric methane removal technologies
Authors: Pennacchio Luisa , Mikkelsen Marie K , Krogsbøll Morten , van Herpen Maarten , Johnson Matthew S 
Published: August 2024

Abstract
Despite their apparent utility in mitigating climate change, technologies for removing methane from air are in early stages of development. Here we evaluate the limiting physical constraints, for three types of systems: two- and three-dimensional infrastructure and atmospheric oxidation enhancement, focusing on removing low (

x
CH4

<

1000 ppm) and ambient (

x
CH4

<

2 ppm) methane from air. With the space velocities and removal efficiencies of current three-dimensional technologies, volumes of 7–350 km3 are required to remove 1 Tg CH4 yr−1. Two-dimensional solutions are limited by the transport rate of methane to a surface. If every molecule of methane that collides with the surface is removed, an area of 1130 km2 is needed to remove 1 Tg CH4 yr−1 at ambient concentration. However, research shows that per-collision reaction probabilities are

<

10−8 requiring a surface area of 1010–1015 km2. Finally, we examine atmospheric oxidation enhancement, where 4.8 Tg yr−1 of Cl

⋅

or 8.8 Tg yr−1 of OH

⋅

is required to remove 1 Tg CH4 yr−1, with precursors such as H2O2 or O3. However, limitations arise concerning multiple environmental impacts. We conclude that the physical and practical constraints are considerable, and identify the main barriers that must be addressed.
The escape transition of a lattice star polymer grafted in a pore
Authors: Bradly C J , Janse van Rensburg E J 
Published: August 2024

Abstract
Polymers in confined spaces are compressed and have reduced conformational entropy, and will partially or fully escape from confinement if conditions are suitable. This is in particular the case for a polymer grafted in a pore. The escape of the polymer from the pore may be considered a partial translocation from the pore into bulk solution, and the resulting conformational readjustment of the polymer has characteristics of a thermodynamic phase transition. In this paper a lattice self-avoiding walk model of a star polymer grafted in a pore is examined numerically using the PERM algorithm. We show that the arms of the grafted lattice star escape one at a time as the length of the pore is reduced, consistent with earlier results in the literature. Critical points for the escape transitions are estimated for square and cubic lattice models and we also examine various properties of the model as it undergoes the escape transition.