bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study of transient arc properties near current zero in an experimental CO2 high-voltage circuit breaker
Authors: Engelbrecht Joseph T , Gortschakow Sergey , Methling Ralf , Pietrzak Pawel , Franck Christian M 
Published: February 2025

Abstract
CO2 has emerged as a leading candidate in the search for a more environmentally friendly alternative to SF6. In high-voltage circuit breakers, where the gas serves as both gaseous insulation and switching medium, commercially available solutions use CO2 either alone or as the primary component of a mixture. In order for breakers to provide the performance necessary to support growing energy demands, a thorough understanding of the transient arc properties of CO2 during the current interruption process is urgently needed. To support these efforts, an experimental puffer circuit breaker has been developed to study thermal interruption in CO2 with a high degree of control, under conditions otherwise comparable to a commercial breaker exposed to short-line fault-like current and voltage stresses. This test setup was used together with high-speed imaging and optical emission spectroscopy (OES) to measure the temporal evolution of a CO2 arc’s radial temperature profile in the stagnation region near the instant of current interruption, over a period ranging from −200 μs to 40 μs relative to current zero. A novel diagnostic technique, intensified video optical emission spectroscopy, has been applied for detailed analysis of plasma properties. This technique allows for evaluation of time-dependent temperature decay with microsecond resolution through current zero, which is not possible with OES methods. Results showed little temperature variation more than 50 μs before current zero, with changes in current mainly found to affect the arc cross-section. Fast temperature decay was limited to a period within 20 μs of current zero, when maximum temperatures dropped from 12000K to 7000 K, with a stable temperature near 6000K measurable up to 40 μs after current interruption. The results also revealed the influence of nozzle erosion on the arc temperature profile, showing that new nozzles provide stronger cooling, resulting in a higher temperature, more constricted arc.
A standalone and cost-effective MR-compatible computer numerical control machine for simultaneous, multi-parameter mapping
Authors: Oiye Ivan Etoku , Poojar Pavan , Qian Enlin , Vaughan John Thomas , Geethanath Sairam 
Published: February 2025

Abstract
Measuring parameters like magnetic field strength and temperature inside a magnet bore is of interest to characterize the system and use that information for downstream image quality improvement or to determine safety thresholds. Multiple commercial measurement systems are available to achieve this goal. However, these systems are often expensive, utilizing proprietary hardware and software, and making adjustments for specific applications is challenging, if not prohibitive. In this work, we design, build, and test a simple, MR compatible 3D movement robot with a sensor holder as a standalone system using a Raspberry Pi and a 16-channel ADC hat. This design costs less than $1200 and is assembled from widely available components with a working volume of 397x398x310 mm³. We demonstrate the 3D field mapping of a 47mT scanner and six-inch wide disc magnets as examples of the robot's use over multiple trials and geometries. We simultaneously mapped data from one magnetic flux density sensor and three temperature probes. We found the measurements highly repeatable, with the maximum value of the average coefficient of variation across space and time measurements from multiple experiments less than 3.5%. We characterized our robot’s spatial accuracy, acoustic noise, and vibrations and found them to be capable of 0.5mm spatial resolution, less than 75dB, and less than 1m/s2 during periods of probe movement.&#xD;
Bed sensor ballistocardiogram for non-invasive detection of atrial fibrillation: a comprehensive clinical study
Authors: Sandelin Jonas , Lahdenoja Olli , Elnaggar Ismail , Rekola Rami , Anzanpour Arman , Seifizarei Sepehr , Kaisti Matti , Koivisto Tero , Lehto Joonas , Nuotio Joel , Jaakkola Jussi , Relander Arto , Vasankari Tuija , Airaksinen Juhani , Kiviniemi Tuomas 
Published: February 2025

Abstract
Atrial fibrillation (AFib) is a prevalent cardiac arrhythmia associated&#xD;with significant morbidity and mortality. Early detection and continuous monitoring&#xD;of AFib are crucial for prevention of complications such as stroke. In this paper, we&#xD;explore the potential of using a ballistocardiogram (BCG) based bed-sensor to detect&#xD;AFib through a comprehensive clinical study consisting of night hospital recordings&#xD;for 116 patients split into 72 training subjects and 44 test subjects. The study uses&#xD;established methods such as autocorrelation in order to detect AFib from the BCG&#xD;signals. Spot and continuous Holter ECG were used as the reference methods to&#xD;detect AFib against which the BCG rhythm classifications were compared Our findings&#xD;suggest that this innovative approach holds promise for accurate and non-invasive&#xD;continuous monitoring of AFib, contributing to improved patient care and outcomes.&#xD;With full overnight recordings we were able to detect AFib with 94% accuracy with&#xD;the train set by using a rule-based method and achieving AUROC score of 97% for the&#xD;test set using a machine learning model trained with the training set.
Machine learning models for Si nanoparticle growth in nonthermal plasma
Authors: Raymond Matt , Elvati Paolo , Saldinger Jacob Charles , Lin Jonathan , Shi Xuetao , Violi Angela 
Published: February 2025

Abstract
Nanoparticles (NPs) formed in nonthermal plasmas (NTPs) can have unique properties and applications. However, modeling their growth in these environments presents significant challenges due to the non-equilibrium nature of NTPs, making them computationally expensive to describe. In this work, we address the challenges associated with accelerating the estimation of parameters needed for these models. Specifically, we explore how different machine learning models can be tailored to improve prediction outcomes. We apply these methods to reactive classical molecular dynamics data, which capture the processes associated with colliding silane fragments in NTPs. These reactions exemplify processes where qualitative trends are clear, but their quantification is challenging, hard to generalize, and requires time-consuming simulations. Our results demonstrate that good prediction performance can be achieved when appropriate loss functions are implemented and correct invariances are imposed. While the diversity of molecules used in the training set is critical for accurate prediction, our findings indicate that only a fraction (15-25%) of the energy and temperature sampling is required to achieve high levels of accuracy. This suggests a substantial reduction in computational effort is possible for similar systems.
An ISSA-TCN short-term urban power load forecasting model with error factor
Authors: Fan Chaodong , Li Gongrong , Xiao Leyi , Yi Lingzhi , Nie Shanghao 
Published: February 2025

Abstract
Under the general trend that all industries try to reduce energy consumption and carbon emissions, urban power load forecasting directly affects energy planning and power system management decisions. In this regard, this paper proposes an improved salp swarm algorithm (ISSA) optimized temporal convolutional network (TCN) load forecasting model with error factor. The model first introduces the SSA and improves it through adaptive leader scale adjustment, position update modification, and boundary adjustment strategy, aiming to improve the algorithm's pre-global search and post-local search ability; then, apply the improved algorithm to hyperparameters optimization for TCN, aiming to search for the optimal hyperparameters combination for different power load data, and the forecasting main model is constructed; Finally, to further enhance the accuracy and stability of power load forecasting, the paper considers the forecasting error of the main model and designs a specialized error auxiliary model. Test comparisons with different algorithms on the CEC2017 benchmark function were conducted to verify the effectiveness of the algorithm improvement. In addition, load forecasting experiments were conducted using data from three cities, and the forecast error values were lower than those of other forecasting models under three identical error metrics, showing good short-term load forecasting performance
Anharmonic corrections to the free energy and to the spectrum of collective modes in the 2d Wigner crystal
Authors: Kalinichenko Igor 
Published: February 2025

Abstract
In this paper we study the effect of anharmonicity on equilibrium properties of the&#xD;two-dimensional Wigner crystal. The leading-order perturbation theory is used restricted&#xD;to high- and zero-temperature limits. The correction to the harmonic free energy of a&#xD;crystal is found in both regimes. The correction to the Dulong-Petit law is found, which&#xD;appears to be positive. The shifts to the spectrum of the harmonic phonon frequencies&#xD;are calculated. In the high-temperature limit, it is shown that the anharmonicity softens&#xD;all the spectrum of phonon frequencies, and the shifts are rather small. In the quantum&#xD;limit, the anharmonicity softens only the lower transverse branch, whereas for the upper&#xD;longitudinal branch the corrections are multidirectional. The relative shifts even close to&#xD;quantum melting are less than 15%. The phonon lifetimes are also calculated for both&#xD;limits. We find Wigner crystal to be rather harmonic, at least in the limits considered&#xD;Our findings can be used for the experiments on equilibrium properties of Wigner crystals&#xD;as well as for the theoretical investigation of the phase diagram of interacting electrons.
Theoretical approach to study Li self-diffusivities dependence on composition in lithium niobate single crystals
Authors: Hboub Hamza , Zelmati Omar , Masaif Noureddine 
Published: February 2025

Abstract
This study proposes an Arrhenius laws formula for lithium self-diffusion in lithium niobate single crystals (LiNbO3, LN) as a function of nonstoichiometry x, with general formula, Li1-5xNb1+xV4xO3 based on the ferroelectric phase transition theory in lithium niobate. This approach demonstrates that the variation in Li self-diffusivities depends on factors such as mass, charge, defect structure, and, consequently, temperature. This theoretical investigation enables us to reproduce the measured data of Li diffusivities in LN single crystals of three different compositions with various ratios of Li/(Li+Nb) = 0.499, 0.494, 0.486 by a mixed vacancy model.&#xD;
Optimizing controlled degradation, bioactivity, and mechanical behaviour in sol-gel synthesized aluminium titanate biomaterials
Authors: B Shanmugapriya , Sathiyaseelan Shailajha , Muthulakshmi Sakthi 
Published: February 2025

Abstract
Abstract&#xD;	Orthopaedic applications require materials that balance mechanical strength, biocompatibility, and controlled degradation, particularly for bone regeneration and load-bearing purposes. This study investigates the effects of varying weight percentages of Al2O3 and TiO2 (25:75, 50:50, and 75:25) on the characteristics of Al2TiO5 biomaterials synthesized via the sol-gel method. Structural and chemical characterizations, including XRD and FTIR, confirmed the successful synthesis of phase-pure Al2TiO5, highlighting functional groups such as Al–O and Ti–O. Among the tested compositions, the 50:50 ratio exhibited the strongest antibacterial efficacy against Staphylococcus aureus and Escherichia coli, comparable to a commercial antibiotic, while also promoting hydroxyapatite (HAp) deposition in simulated body fluid (SBF). Additionally, cytotoxicity assessments using the L929 murine fibroblast cell line revealed that the 50:50 composition had the lowest toxicity. All formulations demonstrated controlled degradation, minimizing pH fluctuations and enhancing bioactivation and biocompatibility. Zeta potential analysis indicated that the 50:50 composition exhibited the most negative values over time, suggesting strong surface interactions with SBF and a favourable environment for HAp nucleation. Furthermore, the compressive strength of all formulations (71–74 MPa) was sufficient for load-bearing applications. These findings suggest that optimizing the 50:50 weight ratio enhances bioactivity, mechanical stability, and biocompatibility, making it a promising candidate for orthopedic and bone tissue engineering applications.
Quantitative assessment of the potential benefits of global afforestation on ecosystem productivity
Authors: Ren Jintong , Xiao Jianhua , Ma Jun , He Panxing 
Published: February 2025

Abstract
Accurately estimating the contribution of afforestation/deforestation to the ecosystem’s gross primary productivity (GPP) is necessary for developing future afforestation policy. However, there is currently a lack of reports on quantitative assessments of the potential consequences of afforestation or deforestation on GPP over the global. Here, we used a 30 m high-resolution forest raster map and a satellite-driven GPP product to assess GPP differences under various afforestation/deforestation scenarios using space rather than time. Our results showed that: (1) Globally, the probability of high-intensity afforestation and high-intensity deforestation was extremely low (4.64%). Under this hypothetical scenario, the potential GPP of afforestation can reach 734.13 g C m-2 year-1, significantly higher than in previous scenarios. Although the probability of concurrent low and medium afforestation and deforestation was up to 41.37%, the potential value of afforestation to promote GPP increase was only 219.56 g C m-2 year-1. (2) The potential of afforestation to boost GPP varies significantly across space and time. In general, the accumulation of GPP is facilitated by proximity to the equatorial forest type, such as evergreen broad-leaved forest. However, as latitudinal zonality increases, the fixed GPP potential of high-latitude coniferous forests decreases significantly. Summer (particularly June) has the highest potential for afforestation to enhance GPP by more than twice as much as other seasons, and this pattern holds globally. (3) Afforestation costs vary substantially depending on the forest type and cover. Afforestation in rainforest areas with a better water-heat mix often requires a higher GPP to obtain the desired effect. Low-density forests dominated by temperate or cold zones yield significantly lower GPP benefits than afforestation in tropical rainforests. The present study quantifies the potential impact of afforestation on GPP for the first time and provides guidelines for future afforestation planning in various regions.&#xD;
Recent Progress of Neuromorphic Sensory and Optoelectronic Systems
Authors: Nam San , Kang Donghyun , Jo Jeong-Wan , Kang Dong-Won , Park Sung Kyu , Kim Yong-Hoon 
Published: February 2025

Abstract
With the rise of the artificial intelligence (AI), neuromorphic sensory systems that emulate the five basic human sensations including tactility, audition, olfaction, gustation, and vision have attracted significant attention. In particular, research on integrating sensors with artificial synapses is being carried out extensively. These studies offer valuable opportunities for making another breakthrough in AI technology, including autonomous systems, real-time monitoring systems, human-machine interactions. In this review, we introduce promising reports of neuromorphic sensory systems. Specifically, the core sensing material, device architecture, fabrication process, and applications of the proposed systems are presented in detail. Finally, the unsolved challenges and the prospects of neuromorphic sensory systems are discussed.
Acoustofluidic pick-and-place operation for label-free spatial assembly of cellular spheroid
Authors: Yin Qiu , Chen Keke , Zhou Chenyang , Su Yimeng , Yu Xianglin , Feng Shiwei , Wang Xiaolin , Ma Zhichao , Zhang Wen-Ming 
Published: February 2025

Abstract
Cellular spheroids, closely resembling native tissue microenvironments, have emerged as pivotal constructs in tissue engineering due to their ability to naturally facilitate complex cell-cell and cell-matrix interactions. However, current methods for constructing spheroid assembloids with spatial arrangement or heterogeneous structures are limited, which has become a barrier for studying tissue engineering and in vitro disease modeling. Here, we demonstrate an acoustofluidic pick-and-place operation system capable of spatially assembling of spheroids into desired patterns in both 2D and 3D spaces. The underlying physical mechanism of the device are systematically studied to explain the interrelationship between trapping cell spheroids and acoustic streaming and acoustic radiation force (ARF) induced by acoustically activated microneedle. We exploited these mechanisms to successfully transfer cellular spheroids into hydrogel solutions, enabling them to be precisely patterned and fused into assemblies of predefined shapes. Besides, we demonstrate arranging MC3T3-E1 cellular spheroids into a ring shape to fabricate the osteogenic tissues. Besides, a co-culture model involving tumor cells (MCF-7) and normal human dermal fibroblasts (NHDFs) is constructed to validate our method's ability to reconstruct heterogeneous tumor model, revealing that that fibroblast spheroids promote tumor spheroid invasion. Our method holds significant potential in a range of applications including regenerative medicine, disease model construction and drug screening.
Laser-assisted Manufacturing for Sensors
Authors: han jing , Xin Di , Pang Jinbo , Zhao Lili , Sun Dehui , Zheng Yang , Liu Xiaoyan , Zhao Zhenhuan , Zhang Xiaoli , Sun Qijun , Liu Hong , Zhou Weijia 
Published: February 2025

Abstract
The laser-assisted manufacturing technology has significant advantages in meeting various demands such as complex structures, functional integration, customized devices, and cost-effectiveness, which allow it to be a highly attractive option for fabricating sensors. In this review, the latest advancements and strategies in intelligent sensor development through laser processing were surveyed and outlined following the interaction of laser and materials. Laser-assisted manufacturing technologies have been extensively applied in materials science and device processing. Firstly, laser technology can be utilized in a wide range of materials, encompassing carbon-based materials, metals, and metallic oxides. In the field of device scale processing, laser manufacturing is widely used in micro/nano structures, planar device construction, and stereoscopic electronic devices such as cutting, engraving, and lithography. Additionally, laser technology provides robust support for sensor applications, covering fields such as pressure sensing, temperature sensing, gas sensing and biosensors. Furthermore, laser considerably serves in real application areas such as multifunctional sensing systems, actuators, and robots. The widespread application of laser manufacturing technology in sensor platform fabrication offers effective solutions for realizing the miniaturization, multifunctionality, and integration of sensors.
The Impact of Vibration on the Deterioration of Suspended Discharge in Oil-paper Insulation
Authors: Yu Hua , Liu Hong , Wang Xuan , Chen Qingsong , Li Guodong 
Published: February 2025

Abstract
Partial discharge is considered one of the main reasons for insulation degradation. To investigate the effect of suspended discharge on oil-paper insulation degradation under mechanical vibration, a test platform for suspended electrode-paper insulation degradation was constructed. Experimental studies were conducted under static and mechanical vibration conditions. The results showed that mechanical vibration promotes the development of discharge, alters the electrode gap, enhances the electric field intensity ahead of the elec-trode tip, and accelerates the degradation of oil-paper insulation. During operation, ultra-high-voltage shunt reactors experience continuous vibrations, which can lead to loosening and detachment of components, forming suspended potentials in insulating oil, thereby causing partial discharges.
Heat impacts on school sports club activities in Japan under climate change and the effectiveness of countermeasures
Authors: Oyama Takahiro , Takakura Jun'ya , Hosokawa Yuri , Honda Yasushi , Fujii Minoru , Nakajima Kenichi , Hijioka Yasuaki 
Published: February 2025

Abstract
Millions of students in Japan participate in school sports club activities, where thousands of heat illness cases occur every year. With future climate change, there is concern about the increased health risks posed to students in sports club activities by the worsening heat environment. However, few studies have quantitatively assessed the heat illness risks associated with school sports activities and the effectiveness of countermeasures under future climate change scenarios. Here, we evaluated the impact of heat and effectiveness of countermeasures based on hourly wet-bulb globe temperature (WBGT) projections under multiple climate scenarios. For the 2060s to 2080s, even under a stringent greenhouse gas (GHG) emission control scenario (SSP1-1.9), strenuous exercise will be restricted for one to four months in five out of eight WBGT zones defined for Japan and for one to six months in six zones under the scenario with little control of GHG emissions (SSP5-8.5). In three of the four scenarios, unlike in the past, all physical activity should be stopped at least once a week in one or more zones. While common countermeasures like early morning exercise and reducing outdoor activity frequency effectively reduce heat illness risks, under the most pessimistic scenario (SSP5-8.5), strenuous exercise would still need to be restricted for one to four months in warmer zones, even with these measures. Common heat illness countermeasures remain necessary for sports club activities at present. However, further measures—such as replacing outdoor activities with indoor sessions—and behavioral changes—such as moving tournaments concentrated during summer vacation to cooler times of the year—will be inevitable as global warming progresses.
Effects of Virtual Reality Versus Narrative Case Study on Empathy and Ageist Attitudes in Prelicensure Nursing Students
Authors: Quay Catherine , Dickinson Jane K. , O’Connell Kathleen 
Published: February 2025

Abstract

AIM
This study examined the effects of a virtual reality (VR) experience on empathy and attitudes toward older adults in prelicensure nursing students.

BACKGROUND
With an aging global population and concerns about age bias in health care and its role in health disparities, nurse educators must develop educational strategies that improve empathy and decrease bias.

METHOD
A sample of 61 second-degree, prelicensure nursing students participated in a quasi-experimental, comparison group study. The intervention group participated in a VR experience; the comparison group completed a narrative case study.

RESULTS
A mixed analysis of variance showed that both groups significantly improved from pretest to posttest for both empathy and attitudes, and there were no differences between the groups.

CONCLUSION
The observed findings suggest that both the narrative case study and VR were effective at improving empathy and attitudes.