bluuebunny/crossref_metadata_2025 huggingface dataset:
Optical properties of quasi-two-dimensional GaAs/AlGaAs nanosheets prepared by releasing epitaxial layer
Authors: Zhang Bowen , Hao Yu , Shi Chao , Pu Shuangshuang , Wang Xiaohua , Wang Dengkui , Fang Dan , Yan Hao , Li Jinhua , Fang Xuan
Published: January 2025

Quasi-two-dimensional nanosheets exhibit novel properties and promising applications in optoelectronic flexible devices. Research on non-layered III–V semiconductor nanosheets has been constrained by their covalent bonding connections. In this study, GaAs/AlGaAs heterojunction nanosheets were prepared by releasing an epitaxial layer, and their optical properties were investigated by adopting steady-state and transient absorption spectroscopy. The optical properties of the independent GaAs/AlGaAs heterojunction were investigated separately in order to exclude the effect of the substrate. This work provides a comprehensive understanding of the physics of III–V semiconductor quasi-two-dimensional nanosheets.
Recent advances in graphitic carbon nitride-based nanocomposites for energy storage and conversion applications
Authors: Tang Shuxian , Xing Yiwen , Wang Yan , Wei Gang
Published: January 2025

Graphitic carbon nitride (g-C3N4) has gained significant attention as a promising nonmetallic semiconductor photocatalyst due to its photochemical stability, favorable electronic properties, and efficient light absorption. Nevertheless, its practical applications are hindered by limitations such as low specific surface area, rapid recombination of photogenerated charge carriers, poor electrical conductivity, and restricted photo-response ranges. This review explores recent advancements in the synthesis, modification and application of g-C3N4 and its nanocomposites with a focus on addressing these challenges. Key strategies for enhancing g-C3N4 include various synthesis methods (solvothermal, microwave-assisted, sol–gel, and vapor deposition), doping, defect engineering, heterojunction formation, and surface modifications. Their potential in energy storage and conversion applications, including photocatalytic hydrogen production, carbon dioxide reduction, nitrogen fixation, and electrochemical energy storage are also highlighted. Overall, the review underscores the importance of structural and morphological modifications in improving the photoelectrochemical performance of g-C3N4-based nanocomposites, providing insights for future development and optimization.
A special two-working-electrode system: a summary of recent development in fabrication and application of interdigitated array electrodes
Authors: Zhang Tingsen , Jian Yingying , Deng Zhiyong , Wu Weiwei , Liu Fei
Published: January 2025

The utilization of two-working-electrode mode of interdigitated array (IDA) electrodes and other two-electrode systems has revolutionized electrochemical detection by enabling the simultaneous and independent detection of two species or reactions. In contrast to conventional two-potential electrodes, such as the rotating ring disk electrodes, IDAs demonstrate analogous yet vastly improved performance, characterized by remarkable collection efficiency, sensitivity, and signal amplification resulted from the ‘feedback’ effect. In recent decades, the research surrounding IDAs has garnered escalating interest due to their attractive attributes. This review centers its focus on the recent development on the fabrication of IDA electrodes as well as their applications leveraging the unique electrochemical and structural features. In fabrication, two critical breakthroughs are poised for realization: the achievement of reduced dimensions and the diversification of materials. Established fabrication methods for IDA electrodes encompass photolithography, inkjet printing, and direct laser writing, each affording distinct advantages in terms of size and precision. Photolithography enables the creation with finer structures and higher resolution compared to others. Inkjet printing or laser writing provides a simpler, more cost-effective, and straightforward patterning process, albeit with lower resolution. In terms of applications, IDAs have found utility in diverse fields. This review summarizes recent applications based on their fundamental working principles, encompassing redox cycling, resistance modulation, capacitance variations, and more. This specialized tool shows great promise for further development with enhanced properties. It is also important to note that, micron- or sub-micron-sized IDAs generally cannot be reused, as their small structures cannot be polished. Therefore, controlling the cost of IDA fabrication is crucial for promoting their broader application. Additionally, the distinctive electrochemical properties of ‘feedback’ effect is often underappreciated. The high sensitivity of IDA electrodes, arising from the ‘feedback’ signal amplification mechanism, holds significant potential for the detection of species with short lifetimes or low concentrations.
Multi-task interaction learning for accurate segmentation and classification of breast tumors in ultrasound images
Authors: Zheng Shenhai , Li Jianfei , Qiao Lihong , Gao Xi
Published: January 2025

Objective. In breast diagnostic imaging, the morphological variability of breast tumors and the inherent ambiguity of ultrasound images pose significant challenges. Moreover, multi-task computer-aided diagnosis systems in breast imaging may overlook inherent relationships between pixel-wise segmentation and categorical classification tasks. Approach. In this paper, we propose a multi-task learning network with deep inter-task interactions that exploits the inherently relations between two tasks. First, we fuse self-task attention and cross-task attention mechanisms to explore the two types of interaction information, location and semantic, between tasks. In addition, a feature aggregation block is developed based on the channel attention mechanism, which reduces the semantic differences between the decoder and the encoder. To exploit inter-task further, our network uses an circle training strategy to refine heterogeneous feature with the help of segmentation maps obtained from previous training. Main results. The experimental results show that our method achieved excellent performance on the BUSI and BUS-B datasets, with DSCs of 81.95% and 86.41% for segmentation tasks, and F1 scores of 82.13% and 69.01% for classification tasks, respectively. Significance. The proposed multi-task interaction learning not only enhances the performance of all tasks related to breast tumor segmentation and classification but also promotes research in multi-task learning, providing further insights for clinical applications.}
Proton minibeam (pMBRT) radiation therapy: experimental validation of Monte Carlo dose calculation in the RayStation TPS
Authors: Lin Yuting , Traneus Erik , Wang Aoxiang , Li Wangyao , Gao Hao
Published: January 2025

Background. Proton minibeam radiation therapy (pMBRT) is a spatially fractionated radiation therapy modality that uses a multi-slit collimator (MSC) to create submillimeter slit openings for spatial dose modulation. The pMBRT dose profile is characterized by highly heterogeneous dose in the plane perpendicular to the beam and rapidly changing depth dose profiles. Dose measurements are typically benchmarked against in-house Monte Carlo (MC) simulation tools. For preclinical and clinical translation, a treatment planning system (TPS) capable of accurately predicting pMBRT doses in tissue and accessible on a commercial platform is essential. This study focuses on the beam modeling and verification of pMBRT using the RayStation TPS, a critical step in advancing its clinical implementation. Methods. The pMBRT system was implemented in RayStation for the IBA Proteus®ONE single-room compact proton machine. The RayStation pMBRT model is an extension of the clinical beam model, allowing pMBRT dose calculations through the MSC using the existing clinical beam model. Adjustable MSC parameters include air gap, slit thickness, slit pitch, number of slits, slits direction and slit thickness. The pMBRT TPS was validated experimentally against measurements using six different collimators with various slit widths (0.4–1.4 mm) and center-to-center slit distances (2.8–4.0 mm). Each collimator comprised five non-divergent slits. Validation involved MatriXX measurements for average dose, Gafchromic film placed at varying depths to measure lateral dose profiles, and film placed along the beam axis to measure depth-dose curves in solid water phantoms. A single 150 MeV energy layer with a 0.5 cm spot spacing was used to create a uniform radiation map across the MSC field. Results. The comparison of average depth dose measurements with RayStation MC calculations showed a gamma passing rate better than 95% using 3 mm/3% criteria, except for the 0.4 mm slit width. After adjusting the slit width by 40–60 μm to account for machining uncertainties, the gamma passing rate exceeded 95% under the same criteria. For the peaks and valleys of the percentage depth doses, agreement between RayStation and film measurements was above 90% using 2 mm/5% criteria, except in the high linear energy transfer region. Lateral profile comparisons at depths of 2, 6, and 10 cm demonstrated over 90% agreement for all curves using 0.2 mm/5% criteria. Conclusions. The pMBRT beam model for the Proteus®ONE-based system has been successfully implemented in RayStation TPS, with its initial accuracy validated experimentally. Further measurements, including additional energies and Spread Out Bragg Peaks, are required to complete the clinical commissioning process.
First 2D electron density measurements using multi-delay coherence imaging spectroscopy in the MAST-U Super-X divertor
Authors: Lonigro N , Doyle R S , Allcock J S , Lipschultz B , Verhaegh K , Bowman C , Brida D , Harrison J , Myatra O , Silburn S , Theiler C , Wijkamp T A ,   MAST-U Team,   the EUROfusion Tokamak Exploitation Team
Published: January 2025

2D profiles of electron density and neutral temperature are inferred from multi-delay coherence imaging spectroscopy data of divertor plasmas using a non-linear inversion technique. The inference is based on imaging the spectral line-broadening of Balmer lines and can differentiate between the Doppler and Stark broadening components by measuring the fringe contrast at multiple interferometric delays simultaneously. The model has been applied to images generated from simulated density profiles to evaluate its performance. Typical mean absolute errors of 30% are achieved, which are consistent with Monte Carlo uncertainty propagation accounting for noise, uncertainties in the calibrations, and in the model inputs. The analysis has been tested on experimental data from the MAST-U Super-X divertor, where it infers typical electron densities of 2–3 1019 m−3 and neutral temperatures of 0–2 eV during beam-heated L-mode discharges. The results are shown to be in reasonable agreement with the other available diagnostics.
Sub-1 V/cm E-FISH-based picosecond electric field measurements in atmospheric pressure air
Authors: LaCombe Grayson , Wang Jianan , Frederickson Kraig , Simeni Simeni Marien
Published: January 2025

We report on the development of a highly sensitive electric field induced second harmonic generation diagnostic setup capable of measuring electric field strengths as low as 1

V

cm

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1

at the picosecond time scale under atmospheric pressure conditions. This unprecedented sensitivity is achieved through passive homodyne detection, which utilizes stray signals generated by an optical component in the beam path. Our detection limit of 0.3–0.5

V

cm

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1

represents an improvement of over 2–3 orders of magnitude compared to previous reports (100–1000

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cm

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) in the literature. Additionally, we demonstrate sensitivity to the polarity of the electric field. Experimental results are corroborated by simulations of the 400 ps time-resolved homodyne process, offering deeper insights into the enhanced detection capabilities and the system’s ability to resolve the field sign.
Piezoelectric energy harvesting: a review of energy sources, structures, and working mechanisms in high-frequency excitations and operations
Authors: Xiao Yu , Han Qinkai , Wu Nan
Published: January 2025

The advancement of information and energy technologies has spurred an increased demand for low-power and compact electronic devices with across various fields. Developing energy harvesting technologies to capture ambient and sustainable energy offers a promising solution to complement or replace conventional batteries. The piezoelectric technique provides a solution for energy harvesting from different energy sources, and high-frequency operation in piezoelectric energy harvesting offers several advantages. These include increased power output, as more charge is generated per unit of time, which increases the current. Additionally, better alignment with the natural resonance of piezoelectric elements enhances energy conversion efficiency. Considering the growing interest in efficient energy harvesting, a review of recent advancements in piezoelectric energy harvesting under high-frequency excitations and operations is presented in this paper. A brief introduction to the operating modes of piezoelectric energy harvester (PEH) is first introduced to provide a general understanding of energy conversion from the piezoelectric effect. PEHs under high-frequency operations from different energy sources are then reviewed and classified into three categories: wind, vehicle and train, and water flow. Next, novel ideas and structures to facilitate high-frequency operations for PEHs are summarized and discussed in detail. Subsequently, the working mechanisms for PEHs under high-frequency operations are described in detail and classified into three groups: high-speed rotation, frequency up-conversion, and friction-induced vibration mechanisms. Finally, applying advanced piezoelectric materials in novel structures and fostering application-oriented prototype testing are identified as trends for future development.
Development of a rotary piezoelectric platform with smooth displacement output based on tripod cooperation force adjustment mechanism
Authors: Deng Jie , Liu Yuxin , Lu Fei , Wang Weiyi , Liu Yingxiang
Published: January 2025

Inertial piezoelectric platforms have gained widespread attention for their high resolution, fast response, simple exciting scheme and structure. However, current inertial piezoelectric platforms face challenges in achieving smooth displacement output due to the inherent backward motion. To address this issue, a tripod cooperation force adjustment mechanism is proposed and a rotary piezoelectric platform is developed to achieve smooth output. The piezoelectric platform adopts three patch-type piezoelectric units to adjust the driving force in the operating cycle. The direction of the resultant force remains unchanged in the slip motion period as two units still move forward when one unit moves back, and the rollback displacement can be avoided. The structure of the rotary piezoelectric platform is designed by the assistance of theoretical and simulation analyses. A prototype is fabricated and its experiments are performed. Smooth displacement output is achieved based on the proposed tripod cooperation force adjustment mechanism, which could significantly suppress the backward displacement compared with the traditional force adjustment mechanism.
Novel nanosensors represented by CdS/ZnS quantum dots doped with manganese (II) Ions for detection of vancomycin
Authors: Shilova S V , Sagdeev D O , Mirgaleev G M , Romanova K A , Galyametdinov Yu G
Published: January 2025

This paper demonstrates potential for analytical nanosensoring offered by core–shell CdS/ZnS and CdS/ZnS quantum dots (QDs) doped with manganese (II) ions for rapid detection of a glycopeptide antibiotic vancomycin (VNC) in aqueous media by luminescence quenching. ‘core–shell’ quantum dots were synthesized by colloidal method and hydrophilized by mercaptopropionic acid (MPA). To reveal the mechanism for luminescence quenching of these nanosensors, we studied spectral characteristics of QDs and VNC and revealed a complex influence of VNC on the luminescence quenching of CdS/ZnS and Cd0.9Mn0.1S/ZnS nanoparticles. We performed quantum chemical calculations of the equilibrium geometry and IR spectra of the VNC-MPA system and the bond energies in the CdS/ZnS–MPA–VNC system. The luminescence quenching of CdS/ZnS QDs by vancomycin was shown to linearly depend on its concentration in the 35–690 μM range with the determination coefficient R2 = 0.988. The luminescence quenching of Cd0.9Mn0.1S/ZnS QDs was linearly sensitive to vancomycin in the narrower concentration range of 0–207 μM with the determination coefficient R2 = 0.999. The detection thresholds of vancomycin were found to be 56.2 μM and 1.9 μM by CdS/ZnS QDs and CdS/ZnS QDs doped with Mn (II) ions, respectively.
A multilayer snowflake resonator metamaterial for low-frequency broadband sound absorption
Authors: Liang Xiao , Shi Liang , Zhang Zhi , Tang Zhongyuan , Ye Yu
Published: January 2025

Low-frequency broadband sound-absorbing structures with smaller thicknesses are the focus of research in noise control. Based on the principle of Helmholtz resonant cavity and the internal spacer chamber division structure, a multilayer snowflake resonator metamaterial (MLSRCM) is proposed. The MLSRCM model is investigated using theoretical and simulation methods, and it is concluded that the MLSRCM has excellent sound absorption performance in the frequency range of 450–950 Hz with a thickness of only 28 mm. This mainly originated from the parallel connection of multi-units as well as the application of the weak resonance effect of coherent coupling and the full utilization of space. The broadband sound absorption mechanism in MLSRCM is theoretically investigated by analyzing the complex frequency plane. Subsequently, the sound absorption mechanism of the structure is further analyzed in terms of sound velocity and power dissipation density. The results show that the MLSRCM has excellent low-frequency broadband acoustic absorption performance, which provides a reference for the design of new acoustic-absorbing metamaterials with small thicknesses.
Active control of electromagnetically induced transparency based on vanadium dioxide microstructures
Authors: Wang Hui , Zhang Dong-Qin , Jin Zhong-Wei , Fang Bin , Pan Gui-Ming , Hong Zhi , Shu Fang-Zhou
Published: January 2025

Electromagnetically induced transparency (EIT) based on metasurfaces has made significant advancements in the past decade. The ability to actively tune EIT is desirable for practical applications, and this has been accomplished by integrating metallic structures with tunable materials. Here, we propose a dynamically tunable EIT using a metasurface composed of vanadium dioxide (VO2) microstructures without additional metallic structures. A single cut wire and a pair of U-Shape split ring microstructures are combined to design the unit cell of the VO2 metasurface, which functions as bright and dark modes, respectively. The destructive interference between these two modes causes an EIT-like resonance at the terahertz band for VO2 in its metallic phase. However, when VO2 transitions into its insulating phase, the EIT resonance gradually vanishes. Theoretical analyses based on the electric field distribution and coupled harmonic oscillator model indicate that the tunable EIT is due to changes in the attenuation rate of two modes. Furthermore, the phase transition of VO2 can generate tunable group delays. The active EIT utilizing VO2 microstructures could be applied in terahertz modulators and tunable slow light devices.
Medical image segmentation with hybrid neural networks
Authors: Li Chuangwei , Li Ling-Fang , Wang Xiaojun , Luo Ming-Xing
Published: January 2025

Recent advancements in CNN and Transformer-based models have significantly advanced medical image segmentation. CNN-based models are less effective at capturing global contexts than Transformer-based models and Transformers have structural disadvantages that limit their ability to capture detailed spatial information. In this paper, we introduce an Dual-Encoder Fusion Model that incorporates a novel Correlation Fusion Module (CFM) for medical image segmentation tasks. This model leverages the strengths of Convolutional Neural Networks (CNN) for local context modeling and Transformers for comprehending long-range dependencies in pixel interactions. Experimental results demonstrate a substantial improvement over existing models on the Synapse dataset, achieving enhancements of 2.28% and 3.47% on the dice metric for Aorta and Pancreas organs respectively. Additionally, our model attains the highest mean HD95 score of 9.05 on the Synapse dataset while utilizing fewer parameters. When evaluated on the MSD datasets, our model outperforms a fine-tuned nnUNet in three out of five tumor detection tasks and maintains competitive performance in three out of four organ boundary delineation tasks. Notably, on the MSD-Lung dataset, our model surpasses a fine-tuned nnUNet on the dice metric by 6.4%. These results underscore the effectiveness of the CFM module within the dual-encoder architecture.
Exploring soliton and soliton-type solutions to the modified Camassa-Holm and Schrödinger-Hirota equations: an analytical approach
Authors: Aziz Md Abdul , Iqbal Md Ashik , Akbar M Ali
Published: January 2025

In this work, we investigate the solitary wave solutions of two nonlinear evolution equations (NLEEs): the modified Camassa-Holm (MCH) equation and the Schrödinger-Hirota (SH) equation. Both are widely used, especially in fluid dynamics, nonlinear optics, and quantum mechanics. We analytically extract solitary wave solutions to the considered equations by applying the

G
′

/

G
′

+
G
+
A

-expansion method which enhances the understanding of wave dynamics in various fields of mathematical physics and engineering. The graphical representations of the obtained results of these two equations for certain values are shown in 3D, 2D, contour, and density plot diagrams, all of which are of the soliton types with one compacton, one anti-flat kink-shaped, one anti-bell-shaped, and one parabolic-shaped soliton. Moreover, we analyze the role of non-algebraic functions, specifically exponential and trigonometric functions, in characterizing the intricate waveforms and their stability properties. We systematically explore the applicability of the chosen expansion method, demonstrating its effectiveness in generating explicit solutions and examining the conditions under which these solitary wave phenomena arise. The novel findings contribute new analytical insights into these classical equations and pave the way for future research into the complex behaviors exhibited by nonlinear wave interactions.
A wide band circularly polarized antenna using meta surface for Wi-Fi applications
Authors: B Swapna Kumari , Sunder M Shyam
Published: January 2025

A circularly polarized, single-feed, low-profile patch antenna with enhanced gain and bandwidth for WI –FI applications is presented in this paper. The proposed antenna has a slot-loaded square patch (SLSP) is placed between reactive impedance structure (RIS)-based metasurface (MS) and the ground plane. A 6 × 6 circular RIS metasurface is used to improve the gain, impedance and axial ratio bandwidth. The antenna prototype’s overall dimensions are 60 mm × 60 mm × 3.6 mm.The measured impedance bandwidth (IBW) of the proposed antenna is 26% (4.98GHz–6.48 GHz) which covers the 5 GHz (5.150–5.850 GHz) and 6 GHz (5.950–7.125 GHz) frequency bands of wireless spectrum. The antenna exhibits right hand circular polarization with maximum measured gain of 6.5 dBic and the 3-dB ARBW is 5.23% (5.47GHz–5.77 GHz).
Investigating the kinetic effects on current gradient-driven instabilities of electron current layers via particle-in-cell simulations
Authors: Mishra Sushmita , Gaur Gurudatt , Patel Bhavesh G
Published: January 2025

Electron current layers, which form in various natural and laboratory plasmas, are susceptible to multiple instabilities, with tearing being a prominent instability driven by current gradients. Tearing is considered a potential mechanism for magnetic reconnection in collisionless regimes, where electron inertia acts as a non-ideal factor that causes magnetic field lines to break and reconnect. In contrast, another mode, known as the surface-preserving mode, also driven by current gradients, maintains the magnetic field topology. In this study, we investigate the kinetic effects on these modes in the presence of finite electron temperatures using two-dimensional particle-in-cell simulations. Our findings reveal that temperature significantly stabilizes the tearing mode, particularly at higher temperatures, due to an increased electron Larmor radius and the associated magnetic field diffusion. We also examine the interplay between the guide field and temperature. Additionally, we observe that growth rates for the surface-preserving mode, in contrast to the tearing mode, increase with temperature, likely due to enhanced electron flow velocities. Furthermore, we identify cases with mixed modes, where both tearing and surface-preserving modes coexist, exhibiting asymmetric structures characteristic of asymmetric magnetic reconnection. Finally, we outline potential future research directions that build upon our findings.
Improving lithium-ion battery state of health estimation with an integrated convolutional neural network, gated recurrent unit, and squeeze-and-excitation model
Authors: Chen Xueyang , Chen Mengyang , Fang Weiwei , Ye Jilei , Liu Lili , Wu Yuping
Published: January 2025

Estimating the State of Health (SOH) of lithium batteries is vital for the safe management of new energy systems. This study leverages voltage, current, and temperature data from the NASA battery dataset to extract health features. The relationship between these features and battery capacity is evaluated using mutual information analysis. An integrated Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), and Squeeze-and-Excitation (SE) model (CNN-GRU-SE) for estimating battery SOH is proposed. The CNN module identifies local features from the input data, the SE module emphasizes key features, and the GRU module captures temporal dependencies, effectively tracking the battery’s health trend over time. The estimation results indicate that the CNN-GRU-SE model reduces the Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Square Error (RMSE) by approximately 3% to 10% compared to the CNN, GRU, and CNN-GRU models. These results confirm the superior estimation capability of the integrated CNN-GRU-SE model. Furthermore, the study underscores the effective integration of the strengths of CNN, SE modules, and GRU, demonstrating its potential application in battery health management.
Measuring line-of-sight distances to haloes with astrometric lensing B-mode
Authors: Inoue Kaiki Taro
Published: January 2025

Relative astrometric shifts between multiply lensed images provide a valuable tool to investigate haloes in the intergalactic space. In strong lens systems in which a single lens plays the primary role in producing multiple images, the gravitational force exerted by line-of-sight (LOS) haloes can slightly change the relative positions of multiply lensed images produced by the dominant lens. In such cases, a LOS halo positioned sufficiently far from the dominant lens along the LOS can create a pattern in the scaled deflection angle that corresponds to the B-mode (magnetic or divergence-free mode). By measuring both the B-mode and E-mode (electric or rotation-free mode), we can determine the LOS distance ratios, as well as the `bare' convergence and shear perturbations in the absence of the dominant lens. However, scale variations in the distance ratio lead to mass-sheet transformations in the background lens plane, introducing some uncertainty in the distance ratio estimation. This uncertainty can be significantly reduced by measuring the time delays between the lensed images. Additionally, if we obtain the redshift values of both the dominant and perturbing haloes, along with the time delays between the multiply lensed images that are affected by the haloes, the B-mode can break the degeneracy related to mass-sheet transformations in both the foreground and background lens planes. Therefore, measuring the astrometric lensing B-mode has the potential to substantially decrease the uncertainty in determining the Hubble constant.
Tests of Solar X-ray Image Reconstruction: Study of X-ray Imaging Algorithms and Reconstruction Parameters
Authors: YU Wenhui , Su Yang , Li Zhentong , Chen Wei , Gan Weiqun
Published: January 2025

Abstract Imaging observations of solar X-ray bursts can reveal details of the energy release process and particle acceleration in flares. Most hard X-ray imagers make use of the modulation-based Fourier transform imaging method, an indirect imaging technique that requires algorithms to reconstruct and optimize images. During the last decade, a variety of algorithms have been developed and improved. However, it is difficult to quantitatively evaluate the image quality of different solutions without a true, reference image of observation. How to choose the values of imaging parameters for these algorithms to get the best performance is also an open question. In this study, we present a detailed test of the characteristics of these algorithms, imaging dynamic range and a crucial parameter for the CLEAN method, clean beam width factor (CBWF). We first used SDO/AIA EUV images to compute DEM maps and calculate thermal X-ray maps. Then these realistic sources and several types of simulated sources are used as the ground truth in the imaging simulations for both RHESSI and ASO-S/HXI. The different solutions are evaluated quantitatively by a number of means. The overall results suggest that EM, PIXON, and CLEAN are exceptional methods for sidelobe elimination, producing images with clear source details. Although MEM_GE, MEM_NJIT, VIS_WV and VIS_CS possess fast imaging processes and generate good images, they too possess associated imperfections unique to each method. The two forward fit algorithms, VF and FF perform differently, and VF appears to be more robust and useful. We also demonstrated the imaging capability of HXI and available HXI algorithms. Furthermore, the effect of CBWF on image quality was investigated, and optimal settings for both RHESSI and HXI were proposed.
Plug-and-play myoelectric control via a self-calibrating random forest common model
Authors: Jiang Xinyu , Ma Chenfei , Nazarpour Kianoush
Published: January 2025

Objective. Electromyographic (EMG) signals show large variabilities over time due to factors such as electrode shifting, user behavior variations, etc substantially degrading the performance of myoelectric control models in long-term use. Previously one-time model calibration was usually required each time before usage. However, the EMG characteristics could change even within a short period of time. Our objective is to develop a self-calibrating model, with an automatic and unsupervised self-calibration mechanism. Approach. We developed a computationally efficient random forest (RF) common model, which can (1) be pre-trained and easily adapt to a new user via one-shot calibration, and (2) keep calibrating itself once in a while by boosting the RF with new decision trees trained on pseudo-labels of testing samples in a data buffer. Main results. Our model has been validated in both offline and real-time, both open and closed-loop, both intra-day and long-term (up to 5 weeks) experiments. We tested this approach with data from 66 non-disabled participants. We also explored the effects of bidirectional user-model co-adaption in closed-loop experiments. We found that the self-calibrating model could gradually improve its performance in long-term use. With visual feedback, users will also adapt to the dynamic model meanwhile learn to perform hand gestures with significantly lower EMG amplitudes (less muscle effort). Significance. Our RF-approach provides a new alternative built on simple decision tree for myoelectric control, which is explainable, computationally efficient, and requires minimal data for model calibration. Source codes are avaiable at: https://github.com/MoveR-Digital-Health-and-Care-Hub/self-calibrating-rf.
Investigating the design characteristics and parameter laws of bird-like flapping-wing aerial vehicles from the perspective of scaling
Authors: Ma Dongfu , Song Bifeng , Cao Jianing , Wang Jiaxin , Xuan Jianlin , Liu Xia
Published: January 2025

Bird-like flapping-wing aerial vehicles (BFAVs) represent a significant advancement in the application of bird biology to aircraft design, with scaling analysis serving as an effective tool for identifying this design process. From the perspective of aviation designers, this paper systematically organizes the scaling laws of birds that are closely related to the design of BFAVs. An intriguing topic further explored is the comparison between birds and BFAVs from the standpoint of scaling, along with an examination of the differences in relevant design parameters. This analysis aims to enhance communication between biologists and engineers, ultimately fostering the development of improved bionic systems. By introducing the concept of periodic average angular velocity, both frequency and amplitude are uniformly considered, providing a clearer explanation of the design characteristics of BFAVs. Finally, a method for establishing the initial parameters based on the scaling laws of BFAVs is proposed, and its effectiveness is validated through design cases, offering a novel approach for the development of new prototypes.
Resilience of hierarchical actuators highlighted by a myosin-to-muscle mock-up
Authors: Perrier Raphaël , Linares Jean-Marc , Tadrist Loïc
Published: January 2025

Skeletal muscle is the main actuator of various families of vertebrates (mammals, fish, reptiles). It displays remarkable robustness to micro-damage, that supposedly originates both from its redundant hierarchical structure and its nervous command. A bioinspired mock-up was designed and manufactured mimicking sarcomeres (micro-scale) and its series and parallel structure from fibre to muscle. First, the mechanical performances namely the force–velocity curve of the intact muscle mock-up were measured and modelled. Then, mimicking micro-damage by making some myosin heads inoperative, the mechanical performances were again measured to determine the resilience of the actuator. The mock-up is shown to be resilient: in the event of 10% damage of the mock-up, the mechanical performance of the mock-up was around 80% of the intact one. In this multi degrees of freedom actuator with hierarchical structure, the resilience is shown to be almost linear with the damage level for uniformly distributed damage (both maximal force and velocity decrease). Differently when micro-damage are clustered on a fibre, this decreases the maximal force with little effect on velocity.
Environmental features related to the decadal variation of South China Sea tropical cyclogenesis in the context of summer monsoon
Authors: Cai Yuhao , Yang Song , Wu Huan , Chen Weizhen , Xu Juying
Published: January 2025

This study investigates the changes in environmental conditions related to the decadal variation of genesis frequency of tropical cyclones (TCGF) over the South China Sea (SCS) during the summer. Corresponding to the decadal increase in TCGF, the seasonal mean anomalies of the genesis potential and environmental fields over the SCS are not favorable for tropical cyclogenesis, indicating their limited role in the decadal variation of the SCS TCGF. It is found instead that the decadal change in tropical cyclogenesis over the SCS is more attributed to the local environmental fields associated with atmospheric intraseasonal oscillation (ISO). The decadal change in SCS TCGF is closely linked to the northward extension of ISO-related convection from the central SCS, which is contributed by the horizontal advection by background monsoon flow and the vertical advection by ISO-related vertical motions. Further analyses indicate that the anomalous upper-level cyclonic circulation over East Asia and the lower-level anticyclonic circulation over the western Pacific produce unfavorable seasonal mean environmental fields in the SCS, whereas the resultant strong summer mean SCS monsoon flow facilitates the northward extension of ISO-related convection. This study highlights the importance of ISO activity for projections of long-term change in the SCS TC activity.
Intensification of Hurricane Idalia by a river plume in the eastern Gulf of Mexico
Authors: Shi Jing , Hu Chuanmin , Cannizzaro Jennifer , Barnes Brian , Zhang Yingjun , Lembke Chad , Henaff Matthieu Le
Published: January 2025

Hurricane Idalia formed on 26 August 2023 and three days later rapidly intensified from a Category 1 to Category 4 strength storm in less than 24 h over the west Florida shelf. On August 30, it made landfall along Florida’s Big Bend area as a Category 3 hurricane. Strikingly, despite Idalia’s moderate intensity and favorable vortex structure, neither upper ocean thermal energy nor environmental vertical wind shear conditions were as favorable during its intensification from Category 2 to Category 4 as earlier in its path, raising the question of what external factors contributed to its extreme intensification during this phase. Using satellite data, underwater glider observations, and numerical model outputs, this study reveals that, in addition to the 2023 marine heatwave, an extensive riverine plume in the eastern Gulf of Mexico, extending from the Mississippi-Alabama-Florida shelf to the Straits of Florida, produced a ∼20 m thick low-salinity layer (∼34–34.5 psu) and a corresponding warm upper ocean (>29 °C, ∼25–30 m thick). This defined a 10–20 m thick strongly stratified barrier layer below the surface layer with buoyancy frequencies exceeding 10−3 s−1 that suppresses vertical mixing and became a critical factor contributing to Idalia’s rapid intensification under the relatively less than favorable thermal and wind field environments. Therefore, incorporating the river plume in future forecast models appears to be essential to improve the accuracy of intensity predictions, especially in the areas affected by the plume, where stratification plays an important role in the intensification dynamics.
Impact of metakaolin to partially replace granulated blast furnace slag on the performance of alkali-activated slag grouting materials and evaluation of grouting effectiveness
Authors: Han Bo , Cai Lingjian , Chi Fengxia , Zhan Wei
Published: January 2025

In recent years, alkali-activated slag materials have garnered widespread attention in the construction field due to their environmental friendliness and excellent mechanical strength. However, optimizing their composition to reduce autogenous shrinkage remains a pressing issue. This study aims to explore the effects of partially replacing granulated blast furnace slag with metakaolin on the performance of alkali-activated slag grouting materials and evaluate its grouting effectiveness. By setting different replacement levels of metakaolin for granulated blast furnace slag, the study systematically investigates the fluidity, autogenous shrinkage, and mechanical properties of alkali-activated slag grouting materials. The experimental results show that as the amount of metakaolin increases, the fluidity of the grouting material significantly decreases, while the autogenous shrinkage rate reduces; however, the mechanical properties exhibit a complex variation trend. Specifically, when the metakaolin content is at 10%, the comprehensive performance is optimal with excellent grouting effect. This finding provides new insights and methods for optimizing alkali-activated slag grouting materials.
Quantum-enhanced clock synchronization using prior statistical information
Authors: Gosalia Ronakraj K , Malaney Robert
Published: January 2025

Optical frequency combs (OFCs) are paving the way for an unprecedented level of precision in synchronizing optical clocks over free-space. However, the conventional intensity-based strategy for estimating the timing offset between two OFCs is sub-optimal, whereas a strategy based on temporal modes can achieve the optimal precision bound under ideal conditions. In practice, the performance of both strategies depends on prior information about the relative intensity of the two OFCs, and the timing centroid between the OFCs. Here, for the first time, we quantify the amount of information required about these two parameters to guarantee that the temporal mode strategy is superior. Using tools from quantum estimation theory and numerical simulations, we ascertain the significance of the timing centroid in quantum-enhanced clock synchronization. Most notably, when the prior information on the timing centroid is at anticipated levels, we find the reductions in the timing deviation achieved by the temporal mode strategy, relative to the intensity-based strategy, to be in the range 2–10. Our new insights can also be one-to-one mapped to the problem of super-resolution imaging of incoherent point sources.
Proof-of-work consensus by quantum sampling
Authors: Singh Deepesh , Muraleedharan Gopikrishnan , Fu Boxiang , Cheng Chen-Mou , Roussy Newton Nicolas , Rohde Peter P , Brennen Gavin K
Published: January 2025

Since its advent in 2011, boson sampling has been a preferred candidate for demonstrating quantum advantage because of its simplicity and near-term requirements compared to other quantum algorithms. We propose to use a variant, called coarse-grained boson-sampling (CGBS), as a quantum proof-of-work (PoW) scheme for blockchain consensus. The miners perform boson sampling using input states that depend on the current block information and commit their samples to the network. Afterwards, CGBS strategies are determined which can be used to both validate samples and reward successful miners. By combining rewards for miners committing honest samples together with penalties for miners committing dishonest samples, a Nash equilibrium is found that incentivises honest miners. We provide numerical evidence that these validation tests are hard to spoof classically without knowing the binning scheme ahead of time and show the robustness of our protocol to small partial distinguishability of photons. The scheme works for both Fock state boson sampling and Gaussian boson sampling and provides dramatic speedup and energy savings relative to computation by classical hardware.
Quadrature-PT symmetry: classical-to-quantum transition in noise fluctuations
Authors: Wang Wencong , Zhai Yanhua , Liu Dongmei , Jiang Xiaoshun , Vashahri Ghamsari Saeid , Wen Jianming
Published: January 2025

While gain-loss-coupled photonic platforms have achieved significant success in studying classical parity-time (PT) symmetry, they encounter challenges in demonstrating pure quantum effects due to incompatible operator transformations and Langevin noise. Here, we present compelling evidence that a non-Hermitian (NH) twin-beam system, undergoing phase-sensitive amplification and balanced loss, not only enables observing the usual eigenvalue-associated PT phase transition but also exhibits distinctive features absent in classical NH or traditional Hermitian quantum scenarios, encompassing quadrature PT symmetry, anomalous loss-induced quadrature squeezing, and classical-to-quantum (C2Q) transitions in noise fluctuations. Furthermore, our proposed bipartite open system promises optimal sensing for various quantum observable measurements, showcasing an improved signal-to-noise ratio and sensitivity, constrained by quantum Cramér–Rao bound or Fisher information. These findings deepen the comprehension of authentic quantum optical PT symmetry involving both gain and loss, addressing contentious issues and illuminating new facets of the subject.
Enhancing environmental monitoring of harmful algal blooms with ConvLSTM image prediction
Authors: Kim Sung Jae , Cho Yongbok
Published: January 2025

This study advances environmental monitoring by predicting the spatial and temporal distribution of Harmful Algal Blooms (HABs) in the Republic of Korea through a hybrid approach that combines geostatistical and deep learning methods. Using 3D universal kriging, the study interpolates missing HAB concentration values, transforming geospatial point data into spatially continuous grid images that serve as the foundation for predictive modeling. These interpolated images are then used as input for a ConvLSTM (Convolutional Long Short-Term Memory) network, which integrates convolutional layers to capture spatial patterns and LSTM units to model temporal dependencies. By leveraging this spatiotemporal modeling framework, the ConvLSTM network effectively predicts future HAB concentrations with improved accuracy. This innovative methodology highlights the utility of combining 3D universal kriging for spatial interpolation with image-based ConvLSTM prediction, offering valuable insights into HAB dynamics and supporting sustainable strategies for environmental management and public health.
Electrochemical conversion of methane measured by anode out gas monitoring over Ce–Co–Cu anode electrocatalysts
Authors: Sarruf Bernardo Jordão Moreira , Steinberger-Wilckens Robert , Valadão de Miranda Paulo Emílio
Published: January 2025

Solid oxide fuel cells (SOFCs) enable the highly efficient conversion of fuels to electricity, offering notable fuel flexibility. However, conventional nickel-based SOFC anode materials currently available on the market are unable to effectively utilise low-carbon fuels without succumbing to carbon deposition, which degrades the anode rapidly. This study introduces a nickel-free SOFC anode electrocatalyst capable of achieving impressive power densities exceeding 400 mW cm−2 at 850 °C when operating directly with pure methane. Comparative analysis of three cell types, each with varying amounts of ceria, cobalt, and copper in their anode compositions, was conducted. Gas chromatography was employed to monitor anode effluent gases under electrochemical conditions, complemented by electrochemical impedance assessments using hydrogen as the fuel to identify polarisation sources within these innovative anode configurations. The findings reveal that tracking chemical and electrochemical reactions in SOFCs provides insights into efficiency and fuel conversion mechanisms, wherein the anode material transforms fuel into useful products while generating electricity and heat. Notably, copper additions influence these behaviours, although Cobalt-rich catalysts exhibit superior performance in facilitating fuel conversion through combined electrochemical and thermochemical reactions. Distribution of relaxation times analysis highlights the necessity of optimising microstructure and mitigating gas diffusion polarisation effects, corroborating the validity of equivalent circuit models aligned with electrochemical impedance spectroscopy data.