bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recovery Patterns of Low-frequency Fatigue in Elite Youth Soccer
Players after Official Matches
Authors: Tito Sandro , Maia Filipe , Correia Marco , Ribeiro João 
Published: October 2024

AbstractThis study aimed to analyze the associations between recovery of low-frequency
fatigue, jump height, and perceptual responses following official soccer
matches. Forty-two male youth elite soccer players (age: 17.13±0.70 years;
height: 179.17±5.94 cm; weight: 69.74±4.91 kg) participated in this study.
Low-frequency fatigue, countermovement jump, perceived fatigue, muscle soreness,
and perceived recovery were assessed at − 2 h, +30 min, +24 h and +48 h relative
to the match. Linear mixed models analysis showed that low-frequency fatigue was
reduced at the match-end (ES=− 0.679 [95% CI =− 1.01; − 0.34]; p<0.001) but
returned to baseline after 24 h (ES=0.149 [95% CI = − 0.26; 0.56]; p=1.00).
Perceptual responses were impaired for up to 48 hours following the match
(ES=− 0.868–1.174; p<0.001). Countermovement jump did not differ between any
time point (ES=− 0.204–0.216; p>0.05). Additionally, the within-subject
correlation analysis showed that low-frequency fatigue pre- to post-match
changes presented moderate to large associations with perceived fatigue
(rm[57]=− 0.43; p<0.001), muscle soreness (rm[57]=− 0.52; p<0.001), and
perceived recovery (rm[57]=0.38; p=0.003). The assessment of low-frequency
fatigue could serve as an additional objective measurement for monitoring
post-match fatigue, as findings suggest that young elite soccer players
experience transient reductions following match-play, which are strongly
correlated with subjective markers of recovery.
From fiscal-military state to laissez-faire science: liberal government and the nineteenth-century market of scientific activity
Authors: Gillin Edward 
Published: October 2024

AbstractIn nineteenth-century Britain, the role of the state in the cultivation of scientific activity was controversial. After the conclusion of the Napoleonic Wars in 1815, successive governments rolled back the apparatus of the ‘fiscal-military state’, characterized by high taxation and government spending. What followed was a moment of self-avowedlylaissez-faire, liberal governance in which contemporaries placed great emphasis on the value of minimal government intervention in market activity. This not only concerned the nation’s social and economic life, but its scientific culture. Leading political and scientific figures frequently promoted science as something best advanced if left to individuals. Yet by the 1900s, the British state was increasingly engaged in financing and organizing large-scale scientific research. The twentieth century would see governments around the world expand their scientific and technological investment, epitomized by the American concept of ‘Big Science’. This article analyses the relationship between the British government and scientific activity during the nineteenth century and argues that, far from a simple matter of minimal intervention, the state was always highly active in the market of science.
One-dimension periodic potentials in Schrödinger equation solved by the finite difference method
Authors: Li Lingfeng , Hu Jinniu , Zhang Ying 
Published: October 2024

Abstract
The one-dimensional Kronig–Penney (KP) potential in the Schrödinger equation, a standard periodic potential in quantum mechanics textbooks known for generating band structures, is solved by using the finite difference method (FDM) with periodic boundary conditions. This method significantly improves the eigenvalue's accuracy compared to existing approaches such as the filter method. The effects of the width and height of the KP potential on the eigenvalues and wave functions are then analyzed. As the potential height increases, the variation of eigenvalues with the wave vector slows down. Additionally, for higher-order band structures, the magnitude of the eigenvalue significantly decreases with increasing potential width. Finally, the Dirac comb potential, a periodic δ potential, is examined using the present framework. This potential corresponds to the KP potential's width and height approaching zero and infinity, respectively. The numerical results obtained by the FDM for the Dirac comb potential are also perfectly consistent with the analytical solution.
Data-driven AI for the automated classification of the isothermal heat-treated thermal barrier coatings using pulsed infrared thermography
Authors: Kunji Purayil Sruthi Krishna , Balasubramaniam Krishnan 
Published: October 2024

Abstract
Development of reliable age prediction models are crucial in monitoring the formation of oxide layer and degradation of TBC at regular intervals. This study proposes an automated classification of isothermal heat-treated TBC samples using temperature data, which helps in predicting the TBC life and monitoring the TBC degradation. TBC-coated samples are isothermal heat-treated at 1000 °C, and the initial growth of thermally grown oxide is monitored using a non-destructive thermal imaging technique. The proposed study integrates data-driven AI (DAI) models and feature extraction techniques to interpret complex thermal patterns measured from the TBC coating surface. The performance of the proposed classification framework is tested using deep learning and classical machine learning models with different types and window sizes of input data. Input data used for validation are raw experiment data, logarithmic of experiment data, polynomial fit data, and thermal signal reconstruction fit coefficients. The maximum classification performance is obtained with gated recurrent unit with accuracy and F1-score of 89.2% and 89.0%, respectively with raw temperature data as input of window 300. The study demonstrates that the proposed DAI approach effectively predicts the age of thermal barrier coatings under isothermal heat-treatment conditions by correlating the thermal response with coating degradation.
Exploring magnetic disorder in inverted core-shell nanoparticles: the role of surface anisotropy and core/shell coupling
Authors: Ccahuana Dámaso , De Biasi Emilio 
Published: October 2024

Abstract
In this work, we have studied the effect of internal coupling in magnetic nanoparticles with inverted core-shell structure (antiferromagnet-ferrimagnet) and also magnetic surface anisotropy, performing Monte Carlo simulations based on a micromagnetic model applied in the limit of lattice size equal to the crystalline unit cell. In the treatment, different internal regions of the particle were labeled in order to analyze the magnetic order and the degree of coupling between them. The results obtained are in agreement with experimental observations in CoO/CoFe2O4 and ZnO/CoFe2O systems, which we have taken as reference. It is observed that the surface anisotropy decreases the coercive field and the blocking temperature of the system. However, the core/shell coupling improves these properties and magnetically hardens the system. Our study shows that a significant magnetic stress is generated in the system, leading to magnetic disorder in the spins of the particle interface. On the other hand, in cases of high surface anisotropy, within a range of interfacial exchange values, a clear magnetic disorder is observed in the shell, which leads to anomalous behavior because the magnetization reversal process is no longer coherent.
Self-supply of hydrogen peroxide by a bimetal-based nanocatalytic platform to enhance chemodynamic therapy for tumor treatment
Authors: Yan Tingxuan , Su Jiahao , Yan Tingyuan , Bian Jinlei , Ali Ahmed R , Yuan Wei , Wei Linping , Wang Yu , Gao Mengting , Ding Qiang , Bi Lei , Wang Shuangshou , Han Xinya 
Published: October 2024

Abstract
The tumor microenvironment (TME) is characterized by low pH, hypoxia, and overexpression of glutathione (GSH). Owing to the complexity of tumor pathogenesis and the heterogeneity of the TME, achieving satisfactory efficacy with a single treatment method is difficult, which significantly impedes tumor treatment. In this study, composite nanoparticles of calcium-copper/alginate-hyaluronic acid (HA) (CaO2-CuO2@SA/HA NC) with pH and GSH responsiveness were prepared for the first time through a one-step synthesis using HA as a targeting ligand. Nanoparticles loaded with H2O2 can enhance the chemodynamic therapy effects. Simultaneously, Cu2+ can generate oxygen in the TME and alleviate hypoxia in tumor tissue. Cu2+ and H2O2 undergo the Fenton reaction to produce cytotoxic hydroxyl radicals and Ca2+ ions, which enhance the localization and clearance of nanoparticles in tumor cells. Additionally, HA and sodium alginate (SA) were utilized to improve the targeting and biocompatibility of the nanoparticles. Fourier transform infrared, x-ray diffraction, dynamic light scattering, SEM, transmission electron microscope, and other analytical methods were used to investigate their physical and chemical properties. The results indicate that the CaO2-CuO2@SA/HA NC prepared using a one-step method had a particle size of 220 nm, a narrow particle size distribution, and a uniform morphology. The hydrogen peroxide self-supplied nanodrug delivery system exhibited excellent pH-responsive release performance and glutathione-responsive •OH release ability while also reducing the level of reactive oxide species quenching. In vitro cell experiments, no obvious side effects on normal tissues were observed; however, the inhibition rate of malignant tumors HepG2 and DU145 exceeded 50%. The preparation of CaO2-CuO2@SA/HA NC nanoparticles, which can achieve both chemokinetic therapy and ion interference therapy, has demonstrated significant potential for clinical applications in cancer therapy.
A new concept of structural smart fabric activated by shape memory alloys
Authors: Mariotti Luca , Patriarca L , Rossoni Marco , Parenti Paolo , Martulli Luca Michele 
Published: October 2024

Abstract
This work presents the development, prototyping and validation of a new concept of structure called structural smart fabric (SSF). An SSF is a chainmail fabric composed by interconnected elements, called cells, which can be stiffened by reactive elements, such as those made by shape memory alloy (SMA). Exploiting the shape memory functionality, SSFs are capable of sensing and reacting to external stimuli. Based on this concept, in this study we propose an SSF that integrates SMA wires into a 3D-printed chainmail structure. The shape memory effect of these wires is used as an actuating mechanism that, at high temperature, tightens the adjacent cells together and provides increased structural stiffness. In this study, finite element simulations were initially conducted to enhance the comprehension of the SSF’s mechanical behaviour. The influence of the initial cell spacing on the SSF stiffness and the wire stress profiles was evaluated during bending loading, as well as the evolution of contact pressure profiles between adjacent cells. This numerical approach enabled to tune the design of the SSF prototypes which were successively manufactured using selective laser sintering additive manufacturing technology with PA12. After the integration with the SMA wires, the SSF prototypes were tested under a 3-point bending configuration at different temperatures. The results revealed a remarkable increase in structural stiffness at elevated temperatures compared to ambient conditions. This study set the basis for a deeper understanding of SSF’s unique capabilities and potential applications in fields where adaptive and responsive structures are required.
On determining London penetration depth from magnetic susceptibility measurements: Reply to Comment on ‘Superconductivity of amorphous and crystalline Re–Lu films’ (Teknowijoyo and Gulian 2024 Supercond. Sci. Technol. 37 035005)
Authors: Teknowijoyo Serafim , Gulian Armen 
Published: October 2024

Abstract
Recently, in Teknowijoyo and Gulian (2024 Supercond. Sci. Technol.
37 035005) we introduced a new, rhenium–lutetium superconducting series (highest

T

c

≈
7

K). In light of some other Re-based materials, our films are also a candidate to the time-reversal symmetry breaking family of superconductors. Both polycrystalline and amorphous materials in thin-film form have been reported, together with their basic properties, which include the estimates of the coherence length and London penetration length. In our original treatment, both of these quantities were deduced to be rather small (

ξ
(
0
)
,

λ
L

(
0
)
∼
5

nm) and the so-called Ginzburg–Landau parameter κ is about 0.9. The author of Comment brings in arguments in favor of the statement that the new material has

κ
∼
250

. We find that the discrepancy comes from the two-solution nature of the equation for

λ
L

(
0
)

. We agree with the Comment’s author that the London penetration depth in our films is more likely in the order of 1 µm, which makes Re–Lu a high-κ superconductor. Future research in both thin films and single crystals may shed more light in the accurate determination of the characteristic lengths of this material.
In-phase collective unconventional photon blockade and its stability in an asymmetrical cavity containing N bosonic atoms
Authors: Luo 罗 Ying 颖 , Zhang 张 Xinqin 新琴 , Xiao 肖 Yi 祎 , Xu 许 Jingping 静平 , Li 李 Haozhen 浩珍 , Yang 羊 Yaping 亚平 , Xia 夏 Xiuwen 秀文 
Published: October 2024

Abstract
We present work on a cavity-driven QED system combining an asymmetrical Fabry–Perot cavity and N two-level atoms (TLAs) and show the convenience of simplifying from distinguishable atoms to undistinguishable bosons when the atoms are prepared in the same initial state. Such simplification is valid even when the atoms are not prepared in the in-phase condition, since any partial in-phase initial state will evolve into the ground state through a relaxation process. Thus, we get a reduced group of differential equations by introducing the Dicke states, and the under-zero Lyapunov exponents verify its stability. We also work out the collective unconventional photon blockade (UCPB) and get two kinds of giant nonreciprocal UCPBs (NUCPBs) in the weak-driving approximation. Results show that we can employ N noninteracting bosonic atoms to generate a collective UCPB instead of a monoatomic UCPB as the UCPB conditions do not vary with the number of atoms. Furthermore, the forward giant NUCPB only occurring for N larger than a certain number as well as the backward giant NUCPB are controllable by the cavity asymmetry and by the number of atoms. Our findings suggest a prospective approach to the generation of quantum nonreciprocity by N identical atoms.
Implementation of spectral methods on Ising machines: toward flow simulations on quantum annealers
Authors: Takagi Kenichiro , Moriya Naoki , Aoki Shiori , Endo Katsuhiro , Muramatsu Mayu , Fukagata Koji 
Published: October 2024

Abstract
We investigate the possibility and current limitations of flow computations using quantum annealers by solving a fundamental flow problem on Ising machines. As a fundamental problem, we consider the one-dimensional advection–diffusion equation. We formulate it in a form suited to Ising machines (i.e. both classical and quantum annealers), perform extensive numerical tests on a classical annealer, and finally test it on an actual quantum annealer. To make it possible to process with an Ising machine, the problem is formulated as a minimization problem of the residual of the governing equation discretized using either the spectral method or the finite difference method. The resulting system equation is then converted to the quadratic unconstrained binary optimization (QUBO) form through the quantization of variables. It is found in numerical tests using a classical annealer that the spectral method requiring a smaller number of variables has a particular merit over the finite difference method because the accuracy deteriorates with the increase of the number of variables. We also found that the computational error varies depending on the condition number of the coefficient matrix. In addition, we extended it to a two-dimensional problem and confirmed its fundamental applicability. From the numerical test using a quantum annealer, however, it turns out that the computation using a quantum annealer is still challenging due largely to the structural difference from the classical annealer, which leaves a number of issues toward its practical use.
A quantification of the electron return effect using Monte Carlo simulations and experimental measurements for the MRI-linac
Authors: Tortorelli Francesco , Borrazzo Cristian , Masi Marica , Rago Maria , El Gawhary Randa , Properzi Claudio , Marchesano Domenico , Grimaldi Gianmarco , Bianciardi Federico , Annessi Ivan , Di Palma Annamaria , Valentino Maria , Verna Laura , Chiarello Giuseppina , Wolfango Plastino , Gentile Piercarlo 
Published: October 2024

Abstract
The integration of magnetic resonance (MR) imaging and linear accelerators into hybrid treatment systems has made MR-guided radiation therapy a clinical reality. This work aims to evaluate the influence of the Electron Return Effect (ERE) on the dose distributions. This study was conducted using MRIdian (ViewRay, Cleveland, Ohio) system. Monte-Carlo simulations (MCs) and experimental measurements with EBT3 Gafchromic films were performed to investigate the dose distribution in a slab water phantom with and without a 2-cm air gap. Plus, MCs took into account different field sizes and a lung gap. A gamma analysis compared calculated versus measured dose distributions. The MCs have shown an increase of the ERE with the radiation field size both in Percent Depth Dose (PDD) and crossline direction. As concerns to the PDD direction, the smallest field for which there was a significant dose accumulation was 4.15 × 4.15 cm2 both for air-gap (13.5%) and lung-gap (3.3%). The largest field for which there was a significant dose accumulation was 24.07 × 24.07 cm2 both for air-gap (39.7%) and lung-gap (4.9%). Instead for the crossline direction, the smallest field for which there was a significant dose accumulation was 2.49 × 2.49 cm2 both for air-gap (8.6% ) and lung-gap (0.5%). The largest field for which there was a significant dose accumulation was 24.07 × 24.07 cm2 both for air-gap (46.2%) and lung-gap (4.2%). PDD and crossline profiles showed good agreement with a gamma-passing rate higher than 91.15% for 2%/2 mm. The ERE can be adequately calculated by MC dose calculation platform available in the MRIdian Treatment Planning System. The MCs show an increase of the ERE directly proportional with the radiation field size. Good agreement was observed between the experimental measurements and calculated dose distributions.
General solutions of the Maxwell’s equations for a mechano-driven media system (MEs-f-MDMS)
Authors: Wang Zhong Lin 
Published: October 2024

Abstract
For engineering electromagnetism, media/objects have shapes and sizes and may move with accelerations along complex trajectories in reference to the observers in the Laboratory frame. To describe the electromagnetic behavior of a system that is made of multiple moving objects, we have developed the Maxwell’s equations for a mechano-driven media system (MEs-f-MDMS) under low-speed approximation (v << c) [Advances in Physics: X, 9 (2024) 2354767]. Through extensive studies, the MEs-f-MDMS are required for describing the electrodynamics inside a moving object, while the classical Maxwell’s equations are to describe the electrodynamics in the region that is at stationary with respect to the Laboratory frame. The full solutions of the two regions satisfy the boundary conditions. The accelerated movement of a medium is a source for generating electromagnetic wave at its vicinity, but this component was missed in classical Maxwell’s equations. In this paper, we present the strategies for solving the MEs-f-MDMS for a generate case with considering the dispersion of the medium and the related constitutive relations both in time and frequency spaces. The theory is rather general and will serve as general guidance for numerical calculations toward practical applications.
Improving DC power supply performance: insights into Cuk and modified Cuk converters' stability and power factor
Authors: Patel Pushpak B , Vyas Sanjay R 
Published: October 2024

Abstract
The conversion of alternating current (AC) to direct current (DC) is pivotal for modern electrical systems, significantly influencing power delivery efficiency and stability. As the reliance on DC-powered electronic devices grows, optimizing AC-DC converters becomes increasingly important. Various converter topologies, including buck, boost, buck-boost, Cuk, and SEPIC configurations, exhibit unique characteristics that affect their efficiency and impact on the power grid. This study examines the performance of Cuk and modified Cuk converters, utilizing PSIM software to simulate these converters for a 1.4 kW power supply. The simulations reveal that both the Cuk and modified Cuk converters achieve reduced ripple in voltage and current outputs, addressing a significant concern for DC power supplies. Additionally, the modified Cuk converter demonstrates a marked reduction in the total harmonic distortion (THD) of the source current. This study explored the interaction between converter topologies and varying load conditions, emphasizing their impact on power factor—a measure of electrical power consumption. A higher power factor indicates improved efficiency and reduced reactive power, benefiting both the electrical system and the grid. The research further investigates how load variations affect power factor and converter performance, providing insights into designing converters that enhance system reliability and efficiency. By validating the simulation results with experimental data, it has been established that the modified Cuk converter topology offers superior performance and stability. This advancement supports the development of converters that optimize power factor and energy consumption, which are crucial for advancing electrical infrastructure. By bridging the gap between simulation and real-world performance, this work aims to provide valuable insights that can inform future enhancements in domestic EV charging infrastructure, ultimately contributing to the broader adoption of electric vehicles.
Non-conventional feature-based LSTM model for prediction of bearing performance degradation
Authors: G Geetha , C Shanthini , P Geethanjali 
Published: October 2024

Abstract
Mechanical bearings are critical in electrical machines, such as motors and generators. They provide support and facilitate the movement of rotating components in these machines. They are essential to the operation of electrical machinery cause they provide support, reduce friction, ensure proper alignment, and improve overall reliability and efficiency. The appropriate selection, installation, and maintenance of these bearings allow the longevity of such machines. The maintenance and the extent of usage determine the usefulness of the bearings. In predictive maintenance and condition monitoring, accurately predicting the level of bearing degradation holds significant importance for strategizing maintenance tasks, reducing downtime, and avoiding unforeseen breakdowns. This study centers on predicting the level of bearing degradation through the application of neural networks, focusing mainly on non-conventional features, rather than the usual features like kurtosis, and skewness. The dataset utilized is sourced from NASA and includes diverse time series signals that provide insights into the entire lifespan of the bearing. In this investigation, advanced machine learning techniques, long-short term memory (LSTM) in particular, are employed to harness the intricate patterns within the bearing dataset, aiming to improve the accuracy of the predictions.