bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synergistic study of electromagnetic and mechanical properties of broadband star-shaped negative Poisson’s ratio wave-absorbing structures
Authors: Wang Yingming , Lei Zhenkun , Wang Xiaochen , Chen Zhaoliang , Lu Minghui , Bai Ruixiang , Yan Cheng 
Published: January 2025

Abstract
Multi-functional integrated sandwich composite structures have excellent wave-absorbing and energy-absorbing properties, and show great potential for application in a variety of fields, including civil, military, and aerospace. In this study, the optimal Latin hypercube sampling strategy is used to reveal the coupling mechanism between the electromagnetic and mechanical properties of three key design parameters (height, core tilt, and wall thickness) of the star-arrow negative Poisson’s ratio structure (SANPR) structure using absorbing and mechanical numerical modeling. The SANPR structure is based on an epoxy resin with a mixture of multiwall carbon nanotubes (CI) and multi-walled carbon nanotubes as an electromagnetic wave absorber. The results show that due to the combined effect of structural effect, dielectric loss, and magnetic loss, the optimum balance between wave absorption and mechanical properties is achieved in the space of specific design dimensional parameters when the height is 12.05 mm, the core inclination is 30.13° and the wall thickness is chosen to be 2 mm. The minimum reflection loss (RLmin) is −25.51 dB, the effective absorption bandwidth is 12.71 GHz (<−10 dB), the specific energy absorption is 33.39 J g−1, and the densification strain is 0.5. At the same time, the SANPR rotating configuration achieved a RLmin of −50.22 dB and a specific energy of 106.41 J g−1. This study can provide a reference for the design and development of new stealth devices.
Complex impedance measurement and saturation energy analysis of optical transition-edge sensors
Authors: Li Peizhan , Zhang Wen , Zhong Jiaqiang , Wang Zheng , Ma Qingxiao , Feng Zhifa , Miao Wei , Jin Junda , Ren Yuan , Li Jing , Shi Shengcai 
Published: January 2025

Abstract
Transition edge sensors (TESs) are highly sensitive thermal detectors that operate across a wide frequency range, from millimeter waves to gamma rays. For optical-single photon TES detectors, a high energy resolution and large saturation energy are required, primarily limited by factors such as heat capacitance and temperature sensitivity, α

I
. In this study, we evaluated TES devices of varying sizes by conducting complex impedance measurements using transfer function calibration, revealing that our titanium-based TES exhibits higher heat capacities compared to theoretical values. We obtained the measured and theoretical time constants, energy resolutions, and saturation energies for the different-sized TESs, notably constructing histograms from pulse area integral analysis. Our devices achieved an optimal energy resolution of 0.2 eV, with the largest TES demonstrating an energy resolution of 0.34 eV, a saturation energy of 35 eV and the ability to discriminate up to 20 photons at 438 nm. These results provide valuable insights for optimizing TES performance in precise photon detection.
Diverse spatiotemporal high harmonic generation
Authors: Li Xiaofei , Zhang Xiaomei , Zheng Xiaolong , Kong Fanqiu , Xing Jinlong , Liu Yuanyuan , Shen Baifei 
Published: January 2025

Abstract
A spatiotemporal optical vortex (STOV) has a transverse orbital angular momentum (TOAM) perpendicular to its direction of propagation. We propose the generation of intense spatiotemporal vortical high harmonics with tunable TOAM using two strong STOV beams that simultaneously interact with a solid thin foil from both sides. Theoretical predictions of harmonic order and topological charge were validated using particle-in-cell simulations. The results show that harmonics originate from the reflection and transmission of the two driving beams and that the ‘monochromaticity’ of the harmonics in the topological charge domain depends on the topological charges of the two driving beams.
Multi-parameter estimation of the state of two interfering photonic qubits
Authors: Maggio Luca , Triggiani Danilo , Facchi Paolo , Tamma Vincenzo 
Published: January 2025

Abstract
A two-photon interfering technique based on polarization-resolved measurements is presented for the simultaneous estimation with maximum quantum sensitivity of multiple parameters associated with the polarization state of two interfering photonic qubits. This estimation is achieved by exploiting a novel interferometric technique based on polarization-resolved two-photon interference. The experimental feasibility and accuracy of this technique is shown, even when a limited number of sampling measurements is employed. This work is relevant for the development of quantum technologies with photonic qubits and sheds light on the physics at the interface between multiphoton interference, boson sampling, multi-parameter quantum sensing, and quantum information processing.
ECA-FusionNet: a hybrid EEG-fNIRS signals network for MI classification
Authors: Qin Yuxin , Li Baojiang , Wang Wenlong , Shi Xingbin , Peng Cheng , Wang Xichao , Wang Haiyan 
Published: January 2025

Abstract

Objective. Among all BCI paradigms, motion imagery (MI) has gained favor among researchers because it allows users to control external devices by imagining movements rather than actually performing actions. This property holds important promise for clinical applications, especially in areas such as stroke rehabilitation. Electroencephalogram (EEG) signals and functional near-infrared spectroscopy (fNIRS) signals are two of the more popular neuroimaging techniques for obtaining MI signals from the brain. However, the performance of MI-based unimodal classification methods is low due to the limitations of EEG or fNIRS. Approach. In this paper, we propose a new multimodal fusion classification method capable of combining the potential complementary advantages of EEG and fNIRS. First, we propose a feature extraction network capable of extracting spatio-temporal features from EEG-based and fNIRS-based MI signals. Then, we successively fused the EEG and fNIRS at the feature-level and the decision-level to improve the adaptability and robustness of the model. Main results. We validate the performance of ECA-FusionNet on a publicly available EEG-fNIRS dataset. The results show that ECA-FusionNet outperforms unimodal classification methods, as well as existing fusion classification methods, in terms of classification accuracy for MI. Significance. ECA-FusionNet may provide a useful reference for the field of multimodal fusion classification.
Fast ion confinement in quasi-axisymmetric stellarator equilibria
Authors: Bonofiglo P.J. , Dudt D.W. , Swanson C.P.S. 
Published: January 2025

Abstract
This report presents an initial analysis of the fast ion confinement and losses within quasi-axisymmetric stellarator equilibria in consideration by Thea Energy. The equilibria have not yet been explicitly optimized for fast particle confinement and require validation. Modeling with the ASCOT5 code is used to directly examine the fast ion transport. The particle tracking simulations are purely (neo)classical in nature and simply contain the supplied equilibrium and collisions (pitch-angle, energy slowing, and velocity diffusion) from supplied thermal profiles. Uniform marker deposition is used to probe the general confinement properties of the equilibria while a realistic beam-born population is provided from the BEAMS3D code and an alpha particle population is calculated from a fusion source integrator. A first wall is included and defines the loss boundary. Analysis for NBI ions within Thea Energy’s conceptual Eos neutron source are presented along with alpha particles in an enlarged DT-plasma. The fast ions are assessed in regards to their confinement time, pitch, energy, and spatial coordinates. For each population, the impact of collisions and orbit drifts are discussed. It is found that NBI born ions in Eos are strongly confined until slowing-down, owing largely to the tangential injection geometry, while 22% of DT-born alpha energy is lost in the scaled device, indicating that any fusion pilot plant design optimization should include metrics for fast ion confinement.
Riverine microplastic discharge along the southern Black Sea coast of Türkiye
Authors: Terzi Yahya , Öztürk Rafet Çağrı , Eryaşar Ahmet Raif , Yandi İlhan , Şahin Ahmet , Yılmaz Fatih , Gedik Kenan , Gündoğdu Sedat 
Published: January 2025

Abstract
Rivers are critical pathways of microplastic (MP) pollution to marine environments, yet their contributions to the Black Sea remain understudied. This study evaluates the abundance and characteristics (polymer composition, shape, size, and color) of MPs discharged from 29 rivers flowing into the southern Black Sea. Using a plankton net with a 200 μm mesh size, samples were collected from river mouths, revealing an average MP abundance of 9.63 ± 1.27 MP m−3, ranging from 1.03 to 29.8 MP m−3. Eastern Black Sea rivers exhibited significantly higher MP levels (11.0 ± 1.57 MP m−3) compared to western rivers (5.15 ± 1.25 MP m−3). Annual MP discharge to the Black Sea was estimated at 1.49 × 1011 particles. Polyethylene terephthalate (PET, 59.3% ± 2.66%), polyethylene (PE, 20.8% ± 2.04%), and polypropylene (PP, 14.1% ± 2.36%) were the most common polymers, with PET and PE being significantly dominant. MP sizes ranged predominantly between 200–1000 μm, and fibers constituted the majority of shapes (64.1%), followed by fragments (28.3%). White (36.8% ± 1.93%) and transparent (30.9% ± 2.39%) MPs were the most prevalent colors. While no significant differences in MP characteristics were detected between basins (NMDS and ANOSIM), this study emphasizes rivers as major pathways for MP pollution in the Black Sea. These findings underscore the urgent need for targeted mitigation strategies to safeguard marine ecosystems and biodiversity.
Collagen silver-doped hydroxyapatite scaffolds reinforced with 3D printed frameworks for infection prevention and enhanced repair of load-bearing bone defects
Authors: Genoud Katelyn J , Sadowska Joanna M , Power Rachael N , Costard Lara S , Ryan Emily J , Matherson Austyn R , Gonzalez-Vazquez Arlyng G , Lemoine Mark , Eichholz Kian , Pitacco Pierluca , Chen Gang , Cavanagh Brenton , Garcia Orquidea , Murphy Ciara M , Curtin Caroline M , Kelly Daniel J , O’Brien Fergal J 
Published: January 2025

Abstract
Osteomyelitis, a severe bone infection, is an extremely challenging complication in the repair of traumatic bone defects. Furthermore, the use of long-term high-dose antibiotics in standard treatment increases the risks of antibiotic resistance. Herein, an antibiotic-free, collagen silver-doped hydroxyapatite (coll-AgHA) scaffold reinforced with a 3D printed polycaprolactone (PCL) framework was developed with enhanced mechanical properties to be used in the repair of load-bearing defects with antimicrobial properties as a preventative measure against osteomyelitis. The AgHA particles were fabricated in varying Ag doses and loaded within freeze-dried collagen scaffolds at two concentrations. The optimised Ag dose (1.5 mol% Ag) and AgHA concentration (200 wt%) within the collagen scaffold demonstrated in vitro osteogenic and antibacterial properties against S. aureus (S. aureus), the main causative pathogen of osteomyelitis. The addition of the PCL framework to the coll-AgHA scaffolds significantly enhanced the compressive modulus from 4 to 12 MPa while maintaining high porosity as well as both pro-osteogenic and antibacterial properties. The reinforced coll-AgHA scaffolds were implanted in vivo and demonstrated enhanced bone repair, significantly greater vessel formation, and calcified tissue in a load-bearing critical sized defect in rats. Taken together, these results confirm the capacity of this novel biomaterial scaffold as a preventative measure against infection in bone repair for use in load-bearing defects, without the use of antibiotics.
Integral imaging 3D display with enhanced depth range using slit mirror array and dual display systems
Authors: Kheibarihafshejani Sahar , Park Jae-Hyeung 
Published: January 2025

Abstract
This paper proposes a method to extend the depth range of integral imaging systems by representing three-dimensional (3D) images in both virtual-real and real–real forms. The approach combines two integral imaging systems using a transmission-type retroreflector and a beam splitter (BS). The transmission-type retroreflector relays the integrated images from one display to form a real full-color 3D aerial images while preserving the resolution at extended depths. The BS combines the second integral imaging system across various depth ranges, providing additional real or virtual 3D images. The proposed method enhances the applicability of integral imaging systems in mixed-reality environments without requiring complex equipment.
Kinetics of austenite formation during continuous heating in as-cast and as-annealed conditions in a low carbon steel
Authors: Oliver-Reynoso Antonio , Vázquez-Gómez Octavio , Reyes-Calderón Francisco , Vergara-Hernández Héctor J , Herrejón-Escutia Martín , Dávila-Pérez Miguel I , López-Martínez Edgar 
Published: January 2025

Abstract
Dilatometric analysis was used to study the effect of the initial microstructure on the kinetics of austenite formation during continuous heating in low–carbon steel. Two initial microstructures were analyzed: 1) as–cast condition, composed of columnar grains of Widmastätten ferrite and pearlite, and 2) as–annealed condition, formed of equiaxed grains of ferrite and pearlite. For both initial conditions, it was observed that austenite formation occurs in two stages: the first stage involves the decomposition of pearlite into austenite, and the second stage involves the transformation of ferrite into austenite. In the as–cast condition, a delay in austenite formation was observed, and a decrease in the transformation extent was associated with a higher transformation rate. The apparent activation energies for each stage of austenite formation were calculated using the Kissinger method, with the peak temperature at the point of maximum transformation rate as the criterion. The calculated energies were too high to be associated with a diffusive transformation mechanism, especially under as–annealed condition, so an analytical kinetic model was proposed to evaluate the behavior of the kinetic parameters. Additionally, the phases formed during intercritical annealing were analyzed to evidence the austenite formation and possible segregation of alloying elements. The analysis shows that elemental variations are negligible, so the difference lies mainly in the morphology of the initial condition.
Deep learning for single-site solar irradiance forecasting using multi-station data*
Authors: Guatibonza Daniel , Narvaez Gabriel , Giraldo Luis Felipe 
Published: January 2025

Abstract
This study examines the integration of data from multiple stations for solar irradiance forecasting at a single site using advanced deep learning models, such as long-term memory (LSTM), deep modular attention (DeepMap), and graph convolutional networks (GC-LSTM). The research addresses an important gap: the statistical evaluation of the contribution of neighboring data to improving forecast accuracy in solar PV applications. Using a large dataset from 12 Colombian locations, representing diverse climatic conditions, we rigorously evaluate the ability of these models to take advantage of spatio-temporal information. The results reveal slight improvements in short-term forecasting, but these improvements are statistically insignificant, as validated by chi-square tests. The results highlight the need for more advanced methods to effectively exploit spatial data, which will guide the future development of solar irradiance prediction models.
Rapid vehicle electrification reduces carbon benefits but increases resource savings in circular automobile transitions
Authors: He Ziyan , Sun Xin , Nakajima Kenichi , Murakami Shinsuke , Hijioka Yasuaki , Fujii Minoru , Sun Lu 
Published: January 2025

Abstract
The automobile sector faces major challenges in reducing greenhouse gas (GHG) emissions, with the shift to electric mobility raising concerns about resource sustainability. Although circular economy (CE) strategies are suggested as complementary solutions, their long-term effectiveness is questioned due to rapid vehicle electrification. This study examines whether evolving energy scenarios affect the effectiveness and priority of CE strategies in Japan’s and China’s automobile sectors. Under moderate vehicle electrification scenario, CE strategies could reduce cumulative resource extraction by 2.4 Gt in Japan and 49 Gt in China, with GHG reductions of 0.28 Gt and 6.1 Gt, respectively, by 2050. Under more aggressive electric vehicle scenarios, resource savings rise to 3.1 Gt (Japan) and 52 Gt (China), although GHG reductions decrease to 0.21–0.25 Gt in Japan and 5.2–5.6 Gt in China, depending on the energy mix. Over 50% of remaining GHG emissions in Japan and China will be tied to vehicle manufacturing, especially lithium-ion battery (LIB) production. Reducing vehicle ownership remains the most impactful strategy, with vehicle downsizing and enhanced material recycling offering notable benefits, especially in China. Policy measures such as shared mobility services, subsidies for durable and fuel-efficient vehicles, and advanced LIB recycling systems are critical to addressing resource demands and environmental impacts. While the GHG mitigation potential of CE strategies may decrease as grids decarbonize, their role in conserving critical resources remains indispensable. These findings highlight the need for holistic, life-cycle approaches that integrate CE strategies with decarbonization policies to achieve net-zero goals. Lessons from Japan’s and China’s experiences provide actionable insights for other regions, emphasizing the enduring relevance of CE strategies in reducing resource consumption and mitigating environmental impacts in a rapidly electrifying automobile industry.
Emergent Voluntary Action for Gifted Children, 1963–1969
Authors: Crane Jennifer 
Published: January 2025

Abstract
This chapter explores how interest in the gifted child first emerged in Britain, building on the ecosystems and cultural understandings traced in Chapter One. Interest came first from disparate local experiments and then, more strongly, from the passionate campaigning of the National Association for Gifted Children. The chapter discusses early and localised educational experiments explicitly focused on the ‘gifted’ for the first time in Britain, notably the Brentwood Experiment in Essex, which started in 1963. It also reflects on the life of Margaret Branch and her work in establishing the National Association in 1966, showing how Branch drove broadsheet interest around her new organisation, and framed ideas of giftedness around equality. Finally, the chapter explores how members of the House of Lords became significant policy advocates for the National Association in the late 1960s. This chapter then shows that, in the 1960s, the gifted child was presented as a vulnerable individual, struggling in education and family life and in need of assistance. By the 1970s and 1980s, as subsequent chapters show, the gifted child was more consistently represented as a powerful elite of the future—able to solve a range of economic and diplomatic issues.
Revisiting Visual Criteria of the Ideal Neck in the Young Caucasian Female
Authors: Halani Sameer H , Chang Victor , Lee Michael R 
Published: January 2025

Abstract

Background
The aesthetically ideal neck was first described by Ellenbogen and colleagues in 1980. Since then, the visual and aesthetic goals of patients have evolved as new surgical techniques have been described.

Objectives
The aim of this study was to provide current objective data regarding the aesthetically ideal neck in a young Caucasian female and evaluate Ellenbogen's original criteria for a youthful neck in this specific population.

Methods
A survey was created and deployed using the Amazon MTurk platform. Respondents rated a panel of digitally altered female necks from most to least attractive.

Results
These results concur with Ellenbogen's findings and suggest new criteria for defining the ideal neck: (1) defined anterior two-thirds of the mandible; (2) presence of a subhyoid depression; (3) subtle thyroid cartilage bulge; (4) partial sternocleidomastoid muscle definition; (5) cervicomental angle of 100°.

Conclusions
Although the visual criteria proposed by Ellenbogen mostly hold true, surgeons should focus on communicating with patients to determine their specific anatomic surgical goals and implementing the appropriate operative intervention.

Level of Evidence: 4 (Diagnostic)
mmGEBLUP: an advanced genomic prediction scheme for genetic improvement of complex traits in crops through integrative analysis of major genes, polygenes, and genotype–environment interactions
Authors: Zhang Qi-Xin , Zhu Tianneng , Lin Feng , Fang Dunhuang , Chen Xuejun , Lou Xiangyang , Tong Zhijun , Xiao Bingguang , Xu Hai-Ming 
Published: January 2025

Abstract
Current genomic prediction (GP) models often fall short of fully capturing the genetic architecture of complex traits and providing practical breeding guidance, particularly under varying environments. Here, we propose the mmGEBLUP, an advanced GP scheme designed to tackle the current limitations in fully exploiting the genetic architecture of complex traits and to predict individual breeding value (BV) with multi-environment trial data. Our approach considers four genetic structural indicators to capture the genetic architectures stepwise across four models: the Genomic Best Linear Unbiased Prediction (GBLUP) model considers only main polygenic effects; the GEBLUP model includes both main and genotype-by-environment (GE) interaction polygenic effects; and the mmGBLUP and mmGEBLUP models further incorporate main and GE interaction effects of major genes. Through systematic simulations and applications to nine traits, three in rice and six in tobacco, we show stepwise increases in prediction accuracy from GBLUP to mmGEBLUP, providing evidence on the scale of heritability and polygenicity of traits. In practical terms, we predict four components of BV: major additive, minor additive, major interaction, and minor interaction. Interestingly, we discover that for traits like natural leaf number in tobacco, the major additive BVs for the top 20 individuals are substantially equal; it is the minor additive BV that causes the difference in the total BV. The relative size of major/minor additive BVs suggests performing either marker-assisted selection or genomic selection or both. Overall, mmGEBLUP is an advanced prediction scheme that enhances the understanding of genetic architectures and facilitate the genetic improvement of complex traits in crops under diverse environments.