bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lattice and spin entropy changes in B2-type magnetocaloric Al–Mn–Ni alloy
Authors: Huang Shuo , Dastanpour Esmat , Ström Valter , Varga Lajos Károly , Eriksson Olle , Jin Hongyun , Vitos Levente 
Published: November 2024

Abstract
Understanding the electronic, lattice, and magnetic contributions to the magnetocaloric effect in magnetic materials can help to elucidate and optimize their performance. In this work, the structural and magnetocaloric properties of Al–Mn–Ni alloy are experimentally determined and theoretically analyzed based on ab initio calculations. The dominating B2 phase associated with the Mn-rich sublattice is found to be responsible for the observed magnetocaloric properties. The magnetic entropy change, refrigerant capacity, and adiabatic temperature change are evaluated. Through the analysis of the data, we find that for the B2 phase, changing from ferromagnetic to paramagnetic configurations results in a pronounced elastic hardening despite the volume expansion. The decrease in lattice entropy is significant and contributes negatively to the magnetic and electronic entropy changes. Our work emphasizes the critical role of the lattice sector in the magnetocaloric effect, and provides an in-depth understanding of the individual entropy terms in magnetic solid solutions.
The Fock-space landscape of many-body localisation
Authors: Roy Sthitadhi , Logan David E 
Published: November 2024

Abstract
This article reviews recent progress in understanding the physics of many-body localisation (MBL) in disordered and interacting quantum many-body systems, from the perspective of ergodicity breaking on the associated Fock space. This approach to MBL is underpinned by mapping the dynamics of the many-body system onto that of a fictitious single particle on the high-dimensional, correlated and disordered Fock-space graph; yet, as we elaborate, the problem is fundamentally different from that of conventional Anderson localisation on high-dimensional or hierarchical graphs. We discuss in detail the nature of eigenstate correlations on the Fock space, both static and dynamic, and in the ergodic and many-body localised phases as well as in the vicinity of the MBL transition. The latter in turn sheds light on the nature of the transition, and motivates a scaling theory for it in terms of Fock-space based quantities. We also illustrate how these quantities can be concretely connected to real-space observables. An overview is given of several analytical and numerical techniques which have proven important in developing a comprehensive picture. Finally, we comment on some open questions in the field of MBL where the Fock-space approach is likely to prove insightful.
Distinct spectral line shifts in the Raman lines’ Stokes and anti-Stokes components with temperature in the liquid crystalline system 4DBA
Authors: Thomas Anoop , Bhai Patel Chandan , K Singh Ranjan , Vikram Kunwar 
Published: November 2024

Abstract
An anomalous Raman phenomenon (ARP) refers to a scenario in which the Stokes and anti-Stokes frequencies of a Raman mode are different. Here we report that ARP introduces different line shifts in Stokes and anti-Stokes frequencies in 4-Decyloxy Benzoic acid with temperature across two thermally driven structural transitions: the smectic (S) to nematic (N) phase transition at 375 K and the nematic (N) to isotropic (I) transition at 390 K. Four Raman modes near 663, 773, 1128, and 1168 cm−1 shift towards higher frequencies (blueshift) in the Stokes frequency and towards lower frequencies (redshift) in the anti-Stokes frequency with rise in temperature near S to N phase transitions. However, in the isotropic liquid phase, both the Stokes and anti-Stokes components exhibit a redshift as temperature increases, without any noticeable distinct spectral lineshifts. Our studies bring out the importance of phonon band structure in ARP.
A dual-weight mechanism-based neural network for partial domain adaptation fault diagnosis of bearings under different working conditions
Authors: An Zenghui , Yan Yinglong , Jia Shi , Wang Houliang , Zheng Yihu , Yang Rui 
Published: November 2024

Abstract
The intelligent fault diagnosis of bearings often entails a distribution discrepancy between training data and real data, which significantly limits the generalization ability of fault diagnosis models. Traditional domain adaptation methods aim to achieve knowledge transfer from the source domain to the target domain. However, in reality, the incompleteness of the target domain dataset leads to the issue of missing classes in the target domain, rendering the assumption of identical label categories in traditional partial domain adaptation (PDA) methods difficult to implement. This study proposes a dual-weighted mechanism for fault diagnosis models in the context of PDA (PDA method-based dual-weight mechanism) to address the issue of weight bias in target domain labels due to category absence. This approach employs a sample-based weighting mechanism and a similarity-based weighting mechanism to assign weights to different label categories, referred to as the dual-weight mechanism based on similarity and sample number (WSS). This method can promote positive transfer while suppressing negative transfer, thereby resolving the issue of weight bias in the target domain label space. Experiments that use the WSS for fault transfer tasks under identical conditions, with multiple categories and multiple conditions employed for the same category, demonstrate the superior performance of the WSS.
Characteristics of road freezing-thawing environments in China oriented towards construction and maintenance
Authors: Li Shiyuan , Hu Xinyue , Cheng Mingqi , Wang Jianxing , Ni Peng , Ye Xuze 
Published: November 2024

Abstract
Road infrastructure suffers irreversible damage during service due to periodic or seasonal freeze-thaw (F-T) cycles, resulting in significant economic losses to the nation. However, systematic evaluation parameters for the entire road F-T environment are lacking, and there is insufficient understanding and short-term prediction of the underlying F-T environment changes and distribution. In this study, 13 F-T environmental parameters in three categories were summarized by combining meteorological parameters and multi-field evaluation parameters. Taking Shiquan River Town as an example, the statistical probability of road F-T environmental parameters was clarified by using the generalized extreme value (GEV) distribution. The study also clarified the spatiotemporal characteristics of road F-T environment across regions based on key F-T environmental parameters. The frequency of F-T events in China increases from south to north and from east to west, and F-T processes are influenced by regional altitude and latitude. Meanwhile, the temporal variation of the F-T environment in China shows significant seasonality. The F-T environment transitions from short-duration, high-frequency F-T cycles to longer-duration, low-frequency F-T cycles. The initial moisture condition of the road F-T environment in the northeastern regions increases, but the additional moisture during the F-T process decreases. This study provides critical insights into understanding the underlying mechanisms and short-term prediction of the road F-T environment changes, which can be used as a basis for the planning, construction, and maintenance of road infrastructure in China.
Impact analysis of fiber optic rings on partial discharge parameters
Authors: Sun Yuwei , Lv Anqiang , Xie Zhiyuan , Yinpeng Li , Kong Yan 
Published: November 2024

Abstract
Fiber optic ultrasonic sensors, which are highly resistant to electromagnetic interference, are expected to be implanted inside electrical equipment to achieve high-sensitivity partial discharge (PD) detection. However, the influence of the fiber optic rings on PD parameters remains unclear. In this paper, a three-dimensional finite element model of the needle plate discharge is established. The effect of the fiber ring on the ultrasonic characteristics of PD is systematically investigated. A parametric analysis is used to investigate the effect of the fiber ring’s diameter and height on the ultrasonic characteristics. The effect of fiber optic rings on PD characteristics is investigated through PD tests. The results indicate a time delay in the propagation of acoustic signals compared to electrical signals, typically at the microsecond level. As the diameter of the fiber ring increases, the maximum vibration velocity at the P-point initially increases and then tends to stabilize, but it always remains lower than the value observed without the fiber ring. Additionally, increasing the height of the fiber ring results in a decrease in the maximum vibration velocity at the P-point. The presence of the fiber ring does not affect the PD inception voltage, but it does influence the apparent discharge-phase spectra. This paper provides a theoretical and experimental basis for the application of fiber optic sensing technology in PD monitoring.
Correction of non-linearities in quadrature phase differential interferometry
Authors: Velasco Dandara , Cramail Caroline , Giraud Jérôme , Cross Benjamin , Lhermerout Romain 
Published: November 2024

Abstract
Quadrature phase differential interferometry is a technique of choice for measuring arbitrary large displacements with record resolution. The so-called Heydemann corrections are generally employed to take account of the unavoidable imperfections due to the optics or the electronics, and a linearisation of the signals is usually performed when the displacement to be determined is the superposition of a quasi-static component and a small harmonic component. Here we show that this standard analysis can lead to non-linearities of two types. The first type of non-linearities is due to optical and electronic imperfections that were not reported in the past and not included in the Heydemann corrections. These imperfections appear as amplitude difference and phase shift between each pair of intensity signals, and produce periodic non-linearities of nanometer amplitude when the intensity signals are combined to obtain contrats, i.e. quantities that are insensitive to intensity fluctuations of the light source. The second type of non-linearities is due to large amplitudes of harmonic oscillation, which become significant when the oscillations are typically larger than

20

nm

for a red-emitting laser source, and can lead to an underestimation of the measured amplitude of

∼

20
%

. In order to correct these non-linearities, new procedures of calibration and analysis are presented, implemented and successfully tested over a wide range of quasi-static velocities, frequencies and amplitudes of harmonic oscillation. The proposed corrections reduce non-linearities below the noise level, making them smaller than

100

pm

and

10

pm

for the quasi-static and harmonic displacement, respectively.
CLFNet: a multi-modal data fusion network for traffic sign extraction
Authors: Liu Rufei , Su Zhanwen , Zhang Yi , Li Ming 
Published: November 2024

Abstract
When using image data for signage extraction, poor visibility conditions such as insufficient light, rainy days, and low light intensity are encountered, leading to low accuracy and poor boundary segmentation in vision-based detection methods. To address this problem, we propose a cross-modal latent feature fusion network for signage detection, which obtains rich boundary information by combining images with light detection and ranging depth images, thus compensating for the pseudo-boundary phenomenon that may occur when using a single RGB image segmentation. First, HRNet is utilized as the backbone network to extract the boundary information of the point cloud depth map and RGB image by introducing the boundary extraction module; Second, the sensitivity to the boundary is enhanced by applying the feature aggregation module to deeply fuse the extracted boundary information with the image features; Finally, boundary Intersection over Union (IOU) is introduced as an evaluation index. The results show that the method performs more superiorly compared to the mainstream RGBD network, with an improvement of 5.5% and 6.1% in IOU and boundary IOU, and an accuracy of 98.3% and 96.2%, respectively, relative to the baseline network.
Shallow defects and optical properties of CsPbBr3 thin films through noble gas ion beam defect engineering
Authors: Fiedler Holger , Hardy Jake , Halpert Jonathan E , Davis Nathaniel J L K , Kennedy John 
Published: November 2024

Abstract
Ion implantation is widely utilised for the modification of inorganic semiconductors; however, the technique has not been extensively applied to lead halide perovskites. In this report, we demonstrate the modification of the optical properties of caesium lead bromide (CsPbBr3) thin films via noble gas ion implantation. We observed that the photoluminescence (PL) lifetimes of CsPbBr3 thin films can be doubled by low fluences (<1 × 1014 at·cm−2) of ion implantation with an acceleration voltage of 20 keV. We attribute this phenomenon to ion beam induced shallow minority charge carrier trapping induced by nuclear stopping, dominant by heavy noble gases (Ar, Xe). Simultaneously, the PL quantum yield (PLQY) is altered during noble gas ion implantation inversely correlates with the electronic stopping power of the implanted element, hence Ar implantation reduces the PLQY, while Ne even causes a PLQY enhancement. These results thus provide a guide to separate the effect of nuclear and electronic damage during ion implantation into halide perovskites.
Carbyne as a promising material for E-nose applications with machine learning
Authors: Kucherik Alexey , Kumar Ashok , Andrey Abramov , Vlad Samyshkin , Anton Osipov , Ilya Bordanov , Shchanikov Sergey , Kumar Mahesh 
Published: November 2024

Abstract
There has been a lot of study and advancement in the area of carbon allotropes in the last several decades, driven by the exceptional and diverse physical and chemical characteristics of carbon nanomaterials. For example, nanostructured forms such as carbon nanotubes (CNTs), graphene, and carbon quantum dots have the potential to revolutionize various industries (Roston 2010 The Carbon Age: How Life’s Core Element Has Become Civilization’s Greatest Threat; In and Noy 2014 Nanotechnology’s Wonder Material: Synthesis of Carbon Nanotubes; Peng et al 2014 Nanotechnol. Sci. Appl. 7 1–29). The global scientific community continues to research in the field of creating new materials, particularly low-dimensional carbon allotropes such as CNTs and carbyne. Carbyne is a one-dimensional carbon allotrope with a large surface area, chemical reactivity, and gas molecule adsorption potential that makes it extremely sensitive to gases and electronic nose (E-nose) applications due to its linear sp-hybridized atomic chain structure. The primary objective of this work is to increase the sensitivity, selectivity, and overall efficiency of E-nose systems using a synergistic combination of carbyne-based sensing components with cutting-edge machine learning (ML) techniques. The exceptional electronic properties of carbyne, such as its high electron mobility and adjustable bandgap, enable rapid and specific adsorption of various gas molecules. Additionally, its significant surface area-to-volume ratio enhances the detection of trace concentrations. Our suggested advanced hybrid system utilises support vector machines and convolutional neural networks as sophisticated ML approaches to analyse data provided by carbyne sensors. These algorithms enhance the precision and durability of gas detection by effectively recognising intricate patterns and correlations in the sensor data. Empirical evidence suggests that E-nose systems based on carbyne have superior performance in terms of reaction time, sensitivity, and specificity compared to conventional materials. This research emphasises the revolutionary potential of carbyne in the advancement of next-generation gas sensing systems, which has significant implications for applications in environmental monitoring, medical diagnostics, and industrial process control.
Comparative performance analysis of mixed metal oxide sensors for dual-sensing leveraging machine learning
Authors: Binowesley R , Savarimuthu Kirubaveni , Emimal M 
Published: November 2024

Abstract
This paper presents the synthesis of mixed metal oxide (BaTiO3: ZnO) (B: Z) sensors with various molar ratios using a low-temperature hydrothermal method for dual sensing applications (gas and acceleration). The sensor developed with an equal molar ratio of 1B:1Z, showcases superior performance compared to unmixed and alternative mixed metal oxide sensors. This equilibrium in ratios optimally enhances synergistic effects between elements B and Z, resulting in improved sensing properties. Furthermore, it contributes to structural stability, enhancing performance in gas and acceleration sensing. A decreased band gap of 2.82 eV and a rapid turn-on voltage of 0.18 V were achieved. The acceleration performance of 1B:1Z sensor exhibits a maximum voltage of 2.62 V at a 10 Hz resonant frequency and an output voltage of 2.52 V at 1 g acceleration, achieving an improved sensitivity of 3.889 V g−1. In addition, the proposed gas shows a notable sensor response of ∼63.45% (CO) and 58.29% (CH4) at 10 ppm with a quick response time of 1.19 s (CO) and 8.69 s (CH4) and recovery time of 2.09 s (CO) and 8.69 s (CH4). Challenges in selectivity are addressed using machine learning, employing various classification algorithms. Linear discriminant analysis achieves superior accuracy in differentiating between CO and CH4, reaching 96.6% for CO and 74.6% for CH4 at 10 ppm. Understanding these concentration-dependent trends can guide the optimal use of the sensors in different current applications.
Synthesis and magnetic properties of NiCo2O4 urchin-like nanofibers
Authors: Nashaat Ahmed M , Abu El-Fadl Abdulaziz , Nakamura Hiroyuki , Kassem Mohamed A 
Published: November 2024

Abstract
Single-phase NiCo2O4 (NCO) nanoparticles (NPs) with an average particle size of 12 (±3.5) nm were successfully synthesized as aggregates in urchin-like nanofibers via a hydrothermal route. Magnetization data measured as functions of temperature and magnetic field suggest a superparamagnetic-like behavior at room temperature, a ferrimagnetic transition around a Curie temperature T
C ∼ 200 K, and a spin blocking transition at a blocking temperature T
B ∼ 90 K, as observed at a field of 100 Oe. The spin blocking nature has been investigated by analyses of the field-dependence of T
B in the static magnetization and its frequency-dependence in the ac susceptibility data measured in zero-field cooling regime, both indicate a low-temperature spin glass-like state. Below T
B, the coercivity increases monotonically up to 1.7 kOe with decreasing temperature down to 5 K. Our results indicate that the magnetic behavior of NCO NPs, which is mainly determined by the cations’ ratio, oxidation states, and site-occupancy, can be controlled by a synthesis in appropriate particle size and morphology.
Optimal use of limited proton resources for liver cancer patients in combined proton–photon treatments
Authors: Marc Louise , Unkelbach Jan 
Published: November 2024

Abstract

Objective. Liver cancer patients may benefit from proton therapy through increase of the tumor control probability (TCP). However, proton therapy is a limited resource and may not be available for all patients. We consider combined proton–photon liver SBRT treatments (CPPT) where only some fractions are delivered with protons. It is investigated how limited proton fractions can be used best for individual patients and optimally allocated within a patient group. Approach. Photon and proton treatment plans were created for five liver cancer patients. In CPPT, limited proton fractions may be optimally exploited by increasing the fraction dose compared to the photon fraction dose. To determine a patient’s optimal proton and photon fraction doses, we maximize the target biologically effective dose (BED) while constraining the mean normal liver BED, which leads to an up- or downscaling of the proton and photon plan, respectively. The resulting CPPT balances the benefits of fractionation in the normal liver versus exploiting the superior proton dose distributions. After converting the target BED to TCP, the optimal number of proton fractions per patient is determined by maximizing the overall TCP of the patient group. Main results. For the individual patient, a CPPT treatment that delivers a higher fraction dose with protons than photons allows for dose escalation in the target compared to delivering the same proton and photon fraction dose. On the level of a patient group, CPPT may allow to distribute limited proton slots over several patients. Through an optimal use and allocation of proton fractions, CPPT may increase the average patient group TCP compared to a proton patient selection strategy where patients receive single-modality proton or photon treatments. Significance. Limited proton resources can be optimally exploited via CPPT by increasing the target dose in proton fractions and allocating available proton slots to patients with the highest TCP increase.
Impact of Bt direction on the detachment threshold during H-mode discharge on EAST with SOLPS-ITER modeling
Authors: Liu Daoyuan , Zhang Chen , Liu Jianbin , Sang Chaofeng , Wang Yilin , Zhang Yanjie , Zhao Xuele , Wang Liang , Wang Dezhen 
Published: November 2024

Abstract
Upper single-null H-mode detachment experiments on EAST were carried out with an ITER-like tungsten divertor, and it was found that the detachment threshold of the upper outer divertor was significantly lower under an unfavorable toroidal magnetic field (B
t) than a favorable B
t. In this work, SOLPS-ITER simulations are carried out to study the effects of B
t direction on the detachment threshold to explain the experimental observations. The simulation results are compared with the experiments, showing reasonable agreement with the diagnostics, and the simulation setups and parameters are thus determined. Based on the simulation data, two-point model formatting is applied to the flux tube where detachment occurs. A quantitative comparison highlights the critical roles of the upstream parallel heat flux and the downstream momentum and energy loss factors on the ion saturation current density at the target ( j
sat,t). Further analysis of the simulation results indicates that due to the influence of E×B drift on the convective heat flux, combined with the presence of heat transport associated with parallel current, the upstream heat flux is reduced under unfavorable B
t, while in the downstream region the divergence of the E×B drift flux acts as a particle source under unfavorable B
t and as a sink under favorable B
t, leading to increased momentum and energy losses under unfavorable B
t. These factors collectively cause a lower detachment threshold under unfavorable B
t.