bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-field coupling challenges the stability test of silicon solar cells
Authors: Wang Na , Deng Qi , Gu Xuehui , Xu Xiaohua , Zhou Su , Yang Chen , Liu Jiakai , Meng Fanying , Zhang Liping , Liu Zhengxin , Yu Jian , Liu Wenzhu
Published: January 2025

UV-induced degradation is an important factor affecting the stability of silicon heterojunction (SHJ) solar cells. Many works investigated the root cause of this degradation previously, but its coupling with other external stress, such as temperature, has rarely been reported. Here, we examine the decrease in SHJ solar cells induced by UV irradiation at different temperatures (−30 and 80 °C) using ultraviolet lamps at 200 W/m2 for 300 h. The results showed that the UV-induced degradation is more severe at low temperature (−30 °C), leading to a significant power decrease (13.5% on average) compared with the power attenuation of the solar cell at 80 °C (1.59% on average). At a low temperature (−30 °C), the VOC and FF evidently decrease much faster. Light soaking can repair the damage to some extent, but the power conversion efficiency cannot restore to the initial value. A 3D microscope confirmed this is because the silver metal electrodes are permanently degraded. These findings challenge the standard International Electrotechnical Commission (IEC) stability test for solar cells, in other words, we have to take into account multi-field coupling to evaluate the long-term reliability of solar cells in real environments.
Aerodynamic characteristics study on multiple propellers in distributed electric propulsion configurations
Authors: Gao Zeming , Zheng Siyuan , Zhang Sheng , Wang Han , Shao Xueming , Zeng Lifang
Published: January 2025

Distributed electric propulsion is widely recognized as a disruptive technology in aviation, and the aerodynamic characteristics of a multi-propeller are critical to the design of such configurations. A reformulated vortex particle method is adopted to provide an in-depth analysis of the aerodynamic characteristics between the multiple propellers operating in close proximity. According to the symmetrical distribution features of the particle field, the entire flowfield is divided into a noninterference region and an interference region. The results show that the aerodynamic performance of the middle propeller fluctuates more than the other two adjacent propellers in the hover state, and the flowfield in the noninterference zone exhibits time-independent characteristics. As the advance ratio increases, the performance fluctuations decrease, the radial contraction of the tip vortex is gradually attenuated, and the initial vortex strength decreases. For the interference zone in hover, the aerodynamic load of each blade drops as the propellers approach the interference region and the wake geometry shows asymmetry. The slipstream deformation of the multi-propeller is more pronounced in hover. The downwash from the previous propeller is responsible for the sequential decrease in thrust coefficient for multi-propeller systems operating at different sideslip angles, and the middle propeller experiences the greatest thrust fluctuation.
Water drop on thin viscous oil layers: From stick-slip spreading to dewetting
Authors: Kumar Shubham , Sahu Piyush , Bharatsingh Surjit , Salwan Gaurav , Mampallil Dileep
Published: January 2025

The impact of water droplets on thin layers of immiscible viscous liquids, such as oil films, is commonly encountered across contexts ranging from kitchen activities to industrial processes. In this study, we experimentally investigate the short-term and long-term behavior of water drops spreading on silicone-oil-coated surfaces. We report that the drop edge exhibits stick-slip dynamics on highly viscous oil layer, characterized by intermittent stops during the initial spreading. The stick-slip behavior diminishes with increasing spreading energy from impacts. The stick-slip spreading is also absent when the drop (ethanol) density is lower than that of the oil. During this smooth spreading and the early time of the stick-slip spreading, the base radius vs time (t) follows the well-known t1/2 scaling corresponding to the inertial-capillary regime. Contrary to the expected rupturing of the oil layer upon the water drop impact, we note that the initial spreading is mostly peripheral without noticeably displacing the oil layer. In the long-term dynamics, regardless of whether spreading occurs upon soft contact or impact, the water drop eventually spreads onto the substrate by dewetting the oil layer. The growth of the dewetting hole beneath the drop follows a dynamics t2/3, characteristic of the dewetting of thin oil layers. During the slow spreading of the water drop on the substrate, the precursor oil film forms a tiny oil droplet under the water drop. Our findings provide new insights into the dynamics of water–oil interactions, with implications for both practical applications and fundamental research.
Time-dependent nonlinear fluid oscillations in the gap between two side-by-side ships during transfer
Authors: Song Zhiwei , Lou Xiaofan , Jin Yan , Liu Hao
Published: January 2025

Time-dependent nonlinear fluid oscillations in the gap between two side-by-side ships during transfer process are investigated numerically based on a two-dimensional fully nonlinear potential flow solver in the time domain. The focus is on understanding the nonlinear dynamic evolution of fluid oscillations within the gap under different incident wave parameters and varying operation windows. Amplitude dynamics, phase dynamics (via Hilbert transform), and time-varying wavelet energy spectra reveal that the fluid oscillations are significantly influenced by incident wave frequency, amplitude, and operation window. The nonlinear evolutions are fundamentally governed by the relative phase between excitation and response. The significance of transfer process, especially within the resonant frequency band, is highlighted for the ship-to-ship operations. Additionally, the combined effects of free-surface nonlinearity and operation window on the relative phase, resonant frequency, and response amplitudes are examined. Two typical nonlinear behaviors of hysteresis and jump are observed in the transient fluid oscillations during the transfer process. The physical insights gained from this study provide a deeper understanding of the nonlinear transient fluid resonance involved in the ship-to-ship transfer process, offering valuable knowledge for the practical side-by-side transfer operations, and contributing new perspectives on the gap resonance problem.
Effect of dynamic coupling in an inferior olive neuron model and synchronization
Authors: Tchuisseuh M. R. , Ghomsi P. Guemkam , Chamgoué A. C. , Kakmeni F. M. Moukam
Published: January 2025

In this paper, we use the idea of dynamic coupling to describe the effect of drugs or chemical substances on the electrophysiological properties of the inferior olive neuron (ION). Therefore, a six-dimensional dynamically coupled Kazantsev master–slave configuration of the ION is obtained. In this configuration, the master and slave subsystems have an indirect interaction, and they are not connected through common signals; instead, the slave subsystem receives a coupling signal, which is dynamically generated by a second order linear system. This type of coupling is called dynamic coupling and enables us to take into consideration the state of the medium through which the master and slave are interconnected. The dynamical behavior of the new model is analyzed analytically using limit cycle prediction and numerically via the two-dimensional bifurcation diagrams with respect to two essential bifurcation parameters of the model. Taking the nonlinear function parameter a and two parameters from the coupling subsystem, the adaptive coupling parameter γ2 and the master–slave coupling strength b, as essential bifurcation parameters, the results show that a change of one of these parameters gives rise to complex dynamics such as periodic oscillations, period doubling scenarios, and chaotic states characterized by spike-bursting. Assuming two coupled neurons with parameter mismatch, it is observed that an increase in the external coupling strength ɛ1 favors their synchronization. Furthermore, the analog circuit of the complete new model confirms the burst analysis and the existence of chaos in the model.
Aging in a weighted ensemble of excitable and self-oscillatory neurons: The role of pairwise and higher-order interactions
Authors: Sharma Amit , Rakshit Biswambhar , Aihara Kazuyuki
Published: January 2025

We investigate the aging transition in networks of excitable and self-oscillatory units as the fraction of inherently excitable units increases. Two network topologies are considered: a scale-free network with weighted pairwise interactions and a two-dimensional simplicial complex with weighted scale-free pairwise and triadic interactions. Without triadic interactions, the aging transition from collective oscillations to oscillation death (inhomogeneous stationary states) can occur either suddenly or through an intermediate state of partial oscillation. However, when triadic interactions are present, the network becomes less resilient, and the transition occurs without partial oscillation at any coupling strength. Furthermore, we observe the presence of inhomogeneous steady states within the complete oscillation death regime, regardless of the network interaction models.
Flow-induced vibrations of staggered circular cylinders
Authors: Wang Yuqi , Xu Fuyou , Zhang Zhanbiao
Published: January 2025

The flow-induced vibrations (FIVs) of staggered two-degree-of-freedom cylinders with a constant streamwise offset (L/D = 2, L is the streamwise spacing between the cylinders of diameter D) and varying cross-stream offset (0 ≤ S/D ≤ 5, S is the cross-stream spacing) were numerically simulated. The effects of S/D on the in-line and cross-flow vibrations, flow fields, distributions of the surface pressures, and the energy properties were comprehensively investigated to study the characteristics of the FIVs. The upstream cylinder primarily experiences vortex-induced vibrations (VIVs), while distinct FIVs of the downstream cylinder occur when S/D ranges from 0 to 3, and the flow characteristics vary with the reduced velocity (Vr) and S/D. When Vr = 3, vortex pairs along with reverse-flow reattachment are observed within the gap zone at small S/D. The pressures on the downstream cylinder become asymmetric due to the vortex strong interactions. When Vr = 7 and 11, a merging vortex emerges and moves closer to the rear surface of the downstream cylinder with increasing S/D, which increases negative pressure on the lower part of the downstream cylinder, further influencing the promoting effect of the merging vortex on structural vibrations. Moreover, when S/D ≥ 3, the effects of the upstream cylinder on the downstream cylinder diminish. Both cylinders exhibit identical vibrations and wake patterns, and the mean power distribution on the downstream cylinder becomes symmetrical with a magnitude similar to that of the upstream cylinder, which can be considered as two independent cylinders undergoing VIVs.
Research on the promotion of ultrasonic vibration on the development of coal pore fractures and permeability
Authors: Huang Qiming , Yu Bo , Wang Gang , Yan Guoqiang , Liu Shimin , Li Mingyang , Liu Hongzhan , Yan Yuting , Wang Xu
Published: January 2025

Coal seam water injection can effectively reduce the amount of dust suspended in the working face during coal mining. However, the permeability of the coal seam gradually deteriorates with the increasing depth of mining. Ultrasound excitation can improve the water injection conditions of coal seams. To explore the mechanism of ultrasound excitation in improving the water permeability of the coal seam, the evolution of the coal mass fracture after ultrasound excitation was investigated through low-temperature nitrogen adsorption experiments and microscopic observation. Additionally, the changes in the pore volume and specific surface area of the coal mass were quantitatively analyzed. The changes in the effective permeability of water-bearing coal samples stimulated by ultrasonic waves were also investigated through seepage experiments. The research results indicated that ultrasound excitation produced pores in the size scale range of 2–10 nm and concentrated the distribution of the mesopores, thereby increasing the pore volume and the specific surface area of the coal mass. The confining pressure gradually closed the fractures and decreased the permeability of the coal body. Injection pressure can improve the effect of ultrasound excitation on fracturing. There is a critical value for ultrasound excitation, below which more small pores will be produced, and above which small pores will be rapidly converted into large pores, increasing the permeability of the coal body.
Electronegative effect in layered double-perovskite La1.9Ba0.1CuSnO6 adjusted by non-magnetic Zn doping
Authors: Yang Liping , Shi Lei , Zhang Jinhui , Tong Ruixue
Published: January 2025

The La1.9Ba0.1Cu1−yZnySnO6 (0 ≤ y ≤ 0.25) (LBCZSO) ceramics were synthesized by the solid-state reaction, and the effect of non-magnetic Zn2+ ion doping on the crystal structure and electrical and magnetic properties is systematically investigated. It is found that all the samples are layered double perovskite with a space group P21/m. The resistivity ρ(T) shows a semiconductor behavior, which follows Mott's 3D variable-range hopping mode. The magnetizations M(T) and the isothermal M-H loops reveal the coexistence of ferromagnetic (FM) and antiferromagnetic (AFM) interactions in the 2D CuO2 layer. With increasing Zn doping at Cu sites, the resistivity ρ(T) increases, the FM transition temperature TC decreases, the FM/AFM interactions weaken/enhance, and the ground state of the system changes from FM to AFM one. It is suggested that cationic electronegativity plays an important role in understanding the transport and magnetic properties of the non-magnetic Zn-doped La1.9Ba0.1CuSnO6, besides the cationic radius. Since the smaller electronegativity of Cu2+ ions compared to that of Sn4+ ions, the CuO6 octahedral distortion with the in-plane compressive strain and out-plane tensile strain is induced by the lattice mismatch between CuO2 and SnO2 layers, forming C-type AF structure with the spin-canted weak FM in 2D CuO2 plane. Since the different cationic electronegativities of Zn2+ and Cu2+ ions, non-magnetic Zn doping leads to the charge transfer between Zn and Cu ions, resulting in the electronic redistribution (transformation) along the ordered Cu–O–Zn chains and non-magnetic Cu+ ions in LBCZSO, which further speeds up the decrease of TC, lead to the abnormal change in the hopping energy W and Curie temperature Θ. Besides, it is confirmed that there is a spin-glass state transition at around 26 K in the non-magnetic Zn doping La1.9Ba0.1CuSnO6 compound.
Simultaneous measurement of multi-physics parameters in laminar flames based on background-oriented schlieren
Authors: Wu Jun , Liu Yuting , Zhang Zhen , Guo Runxia , Liu Guihang , Xing Zhiwei
Published: January 2025

The aerospace sector is experiencing an escalating need for the accurate measurement of high-temperature, high-speed flow field parameters. Conventional contact-based measurement methods are fraught with substantial limitations in terms of dynamic response and measurement precision, frequently leading to disruption of the flow field. In contrast, non-optical measurement techniques generally fall short in providing the capability for concurrent multi-parameter analysis. This study introduces a novel approach for concurrent measurement of multiple physical parameters in laminar flames utilizing the background-oriented schlieren technique. A sophisticated algorithm has been crafted to precisely determine light deflection angles in the context of near-field testing conditions through a detailed examination of the light transmission model. Following this, the axisymmetric refractive index field is meticulously reconstructed with the aid of Abel inversion techniques. Utilizing the Gladstone–Dale relationship, the spatial density distribution of the flow is quantified. Culminating this process, the temperature and velocity fields are inferred by applying the Navier–Stokes equations in conjunction with the ideal gas law, thereby offering a comprehensive analysis of the high-temperature, high-speed flow field parameters within the aerospace sector. The proposed method's viability and precision are confirmed through comparative experiments that utilized high-accuracy thermocouples and Pitot tubes for validation. The findings underscore that this method successfully delivers accurate and synchronized mapping of the density, velocity, and temperature distributions within laminar flames, thereby offering a robust experimental technique for the characterization of high-speed laminar flow fields.
Tissue-resident NK cells do their own glandscaping
Authors: Myers Jacob A. , Reilly Shanelle P. , Brossay Laurent
Published: January 2025

In this issue of JEM, Sparano et al. (https://doi.org/10.1084/jem.20240930) present compelling evidence that salivary gland trNK cells originate from cNK cells and are developmentally distinct from ILC1 cells. Mechanistically, they demonstrate that continuous autocrine TGF-β signaling drives salivary gland tissue residency and works in synergy with IL-15 to enhance Hobit-dependent cytotoxicity.
Comparative analysis of modified Johnson–Cook model and artificial neural network for flow stress prediction in BN-reinforced AZ80 magnesium composite
Authors: Elajjani Ayoub , Feng Shaochuan , Sun Chaoyang
Published: January 2025

Boron nitride (BN), renowned for its exceptional optoelectrical properties, mechanical robustness, and thermal stability, has emerged as a promising two-dimensional material. Reinforcing AZ80 magnesium alloy with BN can significantly enhance its mechanical properties. To investigate and predict this enhancement during hot deformation, we introduce two independent modeling approaches a modified Johnson–Cook constitutive model and an artificial neural network (ANN). These models aim to capture both linear and nonlinear deformation characteristics. Hot compression tests conducted across various temperatures and strain rates provided a comprehensive dataset for model validation. The MJCC model, accounting for strain rate and temperature effects, achieved a correlation coefficient R of 0.96 and an average absolute relative error (AARE) of 6.28%. In contrast, the ANN, trained on experimental data, improved the correlation coefficient to R of 0.99 and reduced the AARE to below 1.5%, significantly enhancing predictive accuracy. These results indicate that while the modified J–C model provides reliable predictions under moderate conditions, the ANN more effectively captures complex behaviors under extreme deformation conditions. By comparing these modeling approaches, our study offers valuable insights for accurately predicting the rheological behavior of BN-reinforced AZ80 magnesium composite, aiding process optimization in industrial applications.
Anomalous and large topological Hall effects in β-Mn chiral compound Co6.5Ru1.5Zn8Mn4: electron electron interaction facilitated quantum interference effect
Authors: Ahmed Afsar , Bhattacharya Arnab , Das I
Published: January 2025

β-Mn-type chiral cubic Co
x
Zn
y
Mn
z
(x + y + z = 20) alloys present a intriguing platform for exploring topological magnetic orderings with promising spintronic potential. This study examines the magnetotransport properties of Co6.5Ru1.5Zn8Mn4, a skyrmion-hosting β-Mn-type chiral compound. The longitudinal resistivity (ρ

xx
) exhibits field-insensitive low-temperature minima due to quantum interference effects, driven by

T

1

/

2

-dependent electron–electron interactions. We observe a substantial intrinsic anomalous Hall conductivity, unaffected by quantum interference. Additionally, a pronounced topological Hall effect is observed at the metastable skyrmionic state, persisting up to

T
C

and achieving notable magnitudes for stoichiometric compounds. These results position the Co
x
Zn
y
Mn
z
family favourably to leverage the rich pallete of emergent magnetotransport properties for spintronic applications.
Dynamical analysis of a tri-stable piezoelectric energy harvester with stops driven by narrow-band random noise
Authors: Zhao Zhen , Jin Yanfei , Zhang Tingting
Published: January 2025

The tri-stable vibrational energy harvester (VEH) is commonly designed to achieve the large-orbit motion, but it is always trapped in one potential well and performs an intra-well motion under weak vibration excitations. To solve this problem, a tri-stable piezoelectric VEH with stops is proposed in this paper. The analytic expressions of the first-order and second-order moments for system response are derived based on the multiple scale method. It is found that the harvesting frequency bandwidth of the tri-stable VEH becomes wider under an optimal impact distance. Compared with the tri-stable VEH without stops, the consideration of stops can help the system achieve the multiple high-energy solutions. The choice of high-stiffness stops at high frequencies can enhance the harvesting efficiency of the tri-stable VEH with stops. Moreover, the experimental results and analysis also are presented to verify the obtained theoretical results. It is found that the energy harvesting efficiency can be increased to 140% of the unrestricted state at the optimal impact distance. Compared with the tri-stable VEH with rubber and stiff springs, the one with silica gel stops has a higher output voltage.
A CNN-BiLSTM short-term wind power forecasting model incorporating adaptive boosting
Authors: Cai Jingkao , Wang Yang , Chen Zongchuan , Gao Yulun , Tang Guangyu
Published: January 2025

Aiming at the wind power signal with the characteristics of intermittency, nonlinearity, volatility, non-stationarity and uncertainty, this paper establishes a wind power prediction model based on the combination of variational modal decomposition (VMD), convolutional neural network (CNN), bi-directional long and short-term memory network (BILSTM) and adaptive boosting mechanism (AdaBoost). In terms of data processing, the core parameters of VMD such as decomposition modulus number and penalty factor affect the data decomposition ability, thus the core parameters of VMD are optimized using the multi-strategy mutation sand cat swarm optimization (SSCSO). The global search ability and convergence speed of SSCSO algorithm are enhanced by integrating cubic mapping, spiral search strategy and sparrow alert mechanism, etc., and are applied to optimize the core parameters of VMD, so as to effectively improve the data decomposition performance of VMD; in terms of the prediction model, for the existence of a single deep neural network model with slow arithmetic speed, artificial parameter tuning, etc., which affects the overall prediction accuracy of the model, thus CNN-BiLSTM combination prediction model with the introduction of AdaBoost is adopted. The CNN-BiLSTM is repeatedly trained as a weak predictor and outputs the prediction results, and the weights are calculated and the errors are corrected according to the prediction error values of each weak predictor. Finally, the strong predictor is obtained by combining several groups of weak predictors after several rounds of training, and the output predicted values are superimposed to obtain the final predicted values, which further improves the overall prediction accuracy of the model, and the strong predictor composed of the CNN-BiLSTM model trained in several rounds is able to process the data more adaptively, and improves the operation speed to a certain extent under the premise of guaranteeing the prediction accuracy. The experimental results show that the root mean square error (RMSE), mean absolute error (MAE) The experimental results show that the RMSE, MAE, correlation coefficient and running time of the proposed model are better than those of SSCSO-VMD-CNN-BiLSTM, SSCSO-VMD-CNN-LSTM and SSCSO-VMD-CNN-GRU, VMD-CNN-BiLSTM-Adaboost, SABO-VMD-CNN-BiLSTM-Adaboost, DBO-VMD-CNN-BiLSTM-Adaboost and WOA-VMD-CNN-BiLSTM-Adaboost prediction models. Therefore, the combined model proposed in this paper has better prediction accuracy and running speed.
Topology optimization design of the ‘Beam Shaping Assembly’ of an AB-BNCT facility—application to the case of glioblastoma treatment
Authors: Chabod Sébastien , Santos Daniel , Sauzet Nadine
Published: January 2025

Objective. This study aims to determine the optimal structure of the Beam Shaping Assembly (BSA) for an accelerator-based boron neutron capture therapy (BNCT) facility. The aim is to maximize the possible depth of treatment for glioblastoma while ensuring that a treatment time constraint is not exceeded. Approach. To achieve this goal, we utilize a new optimization procedure known as topology optimization. This technique can accurately identify the most optimal structure of a nuclear device, in this case a BSA, to be identified among 9 × 101206 possible structures for the example given in this study. The exploration of such a vast space of configurations is inaccessible to any other method available to date. Main results. The topology optimization generated Air-AlF3–LiF–LiFPE BSA has an original structure that differs significantly from the structures previously tested by the BNCT community. This structure, which combines a ring collimator and a filter cone to mimic the effect of multi-field treatment, generates unprecedented treatment depths, with a treatable depth TD = 10.01 cm and an advantage depth AD = 12.48 cm (for 15 ppm of Boron-10 in blood, with a 3.5 tumor-to-blood Boron-10 concentration ratio), or TD = 10.30 cm and AD = 12.69 cm (for 18 ppm of Boron-10). These depths are much greater than any other design proposed to date by the community. The structure also verifies the latest proposed radiation protection constraints, which set limit values on its out-of-field leakages. Significance. The findings of this study indicate that topology optimization procedures are highly beneficial for the design of BSAs. In particular, the use of ring collimators could significantly improve the quality of BNCT treatments of brain tumors.
Dual-modality flow phantom for ultrasound and optical flow measurements
Authors: Kallweit Chris M , Chee Adrian J Y , Yiu Billy Y S , Peterson Sean D , Yu Alfred C H
Published: January 2025

As ultrasound-compatible flow phantoms are devised for performance testing and calibration, there is a practical need to obtain independent flow measurements for validation using a gold-standard technique such as particle image velocimetry (PIV). In this paper, we present the design of a new dual-modality flow phantom that allows ultrasound and PIV measurements to be simultaneously performed. Our phantom’s tissue mimicking material is based on a novel hydrogel formula that uses propylene glycol to lower the freezing temperature of an ultrasound-compatible poly(vinyl) alcohol cryogel and, in turn, maintain the solution’s optical transparency after thermocycling. The hydrogel’s optical attenuation {1.56 dB cm−1 with 95% confidence interval (CI) of [1.512 1.608]}, refractive index {1.337, CI: [1.340 1.333]}, acoustic attenuation {0.038 dB/(cm × MHz
b
), CI: [0.0368 0.0403]; frequency dependent factor of 1.321, CI: [1.296 1.346]}, and speed of sound {1523.6 m s−1, CI: [1523.8 1523.4]} were found to be suitable for PIV and ultrasound flow measurements. As an application demonstration, a bimodal flow phantom with spiral lumen was fabricated and used in simultaneous flow measurements with PIV and ultrasound color flow imaging (CFI). Velocity fields and profiles were compared between the two modalities under a constant flow rate (2.5 ml s−1). CFI was found to overestimate flow speed compared to the PIV measurements, with a 14%, 10%, and 6% difference between PIV and ultrasound for the 60°, 45°, and 30° angles measured. These results demonstrate the new phantom’s feasibility in enabling performance validation of ultrasound flow mapping tools.
Gadolinium oxide nanoparticles as a multimodal contrast enhancement agent for pre-clinical proton imaging
Authors: Würl Matthias , Liubchenko Grigory , Hu Guyue , Schnürle Katrin , Meyer Sebastian , Bortfeldt Jonathan , Landry Guillaume , Käsmann Lukas , Lauber Kirsten , Granja Carlos , Oancea Cristina , Verroi Enrico , Tommassino Francesco , Parodi Katia
Published: January 2025

Orthotopic tumor models in pre-clinical translational research are becoming increasingly popular, raising the demands on accurate tumor localization prior to irradiation. This task remains challenging both in x-ray and proton computed tomography (xCT and pCT, respectively), due to the limited contrast of tumor tissue compared to the surrounding tissue. We investigate the feasibility of gadolinium oxide nanoparticles as a multimodal contrast enhancement agent for both imaging modalities. We performed proton radiographies at the experimental room of the Trento Proton Therapy Center using a MiniPIX-Timepix detector and dispersions of gadolinium oxide nanoparticles in sunflower oil with mass fractions up to 8wt%. To determine the minimum nanoparticle concentration required for the detectability of small structures, pCT images of a cylindrical water phantom with cavities of varying gadolinium oxide concentration were simulated using a dedicated FLUKA Monte Carlo framework. These findings are complemented by simulating pCT at dose levels from 80 mGy to 320 mGy of artificially modified murine xCT data, mimicking different levels of gadolinium oxide accumulation inside a fictitious tumor volume. To compare the results obtained for proton imaging to x-ray imaging, cone-beam CT images of a cylindrical PMMA phantom with cavities of dispersions of oil and gadolinium oxide nanoparticles with mass fractions up to 8wt% were acquired at a commercial pre-clinical irradiation setup. For proton radiography, considerable contrast enhancement was found for a mass fraction of 4wt%. Slightly lower values were found for the simulated pCT images at imaging doses below 200 mGy. In contrast, full detectability of small gadolinium oxide loaded structures in xCT at comparable imaging dose is already achieved for 0.5wt%. Achieving such concentrations required for pCT imaging inside a tumor volume in in-vivo experiments may be challenging, yet it might be feasible using different targeting and/or injection strategies.
An unsupervised automatic texture classification method for ultrasound images of thyroid nodules
Authors: Lu Chenzhuo , Fu Zhuang , Fei Jian , Xie Rongli , Lu Chenyue
Published: January 2025

Objective. Ultrasound is the predominant modality in medical practice for evaluating thyroid nodules. Currently, diagnosis is typically based on textural information. This study aims to develop an automated texture classification approach to aid physicians in interpreting ultrasound images of thyroid nodules. However, there is currently a scarcity of pixel-level labeled datasets for the texture classes of thyroid nodules. The labeling of such datasets relies on professional and experienced doctors, requiring a significant amount of manpower. Therefore, the objective of this study is to develop an unsupervised method for classifying nodule textures. Approach. Firstly, we develop a spatial mapping network to transform the one-dimensional pixel value space into a high-dimensional space to extract comprehensive feature information. Subsequently, we outline the principles of feature selection that are suitable for clustering. Then we propose a pixel-level clustering algorithm with a region growth pattern, and a distance evaluation method for texture sets among different nodules is established. Main results. Our algorithm achieves a pixel-level classification accuracy of 0.931 for the cystic and solid region, 0.870 for the hypoechoic region, 0.959 for the isoechoic region, and 0.961 for the hyperechoic region. The efficacy of our algorithm and its concordance with human observation have been demonstrated. Furthermore, we conduct calculations and visualize the distribution of different textures in benign and malignant nodules. Significance. This method can be used for the automatic generation of pixel-level labels of thyroid nodule texture, aiding in the construction of texture datasets, and offering image analysis information for medical professionals.
3D printable piezoelectric composites manufactured via scalable and sustainable solvent-free multi-extrusion process
Authors: Kompelli Gopi , Dauksevicius Rolanas , Kleiva Arunas , Turczyn Roman , Krukiewicz Katarzyna
Published: January 2025

The study presents the development of 3D printable lead-free particulate piezocomposites by implementing a solvent-free multi-extrusion process (MEP) to address the scalability limitations and safety concerns of solvent-based processing commonly used with highly resilient fluoropolymer polyvinylidene fluoride (PVDF) and its copolymers (e.g. with hexafluoropropylene (HFP)). Composite filaments of PVDF-HFP with ferroelectric barium titanate (BTO) particles at 20, 40 and 60 wt% were manufactured for fused filament fabrication (FFF) by applying the melt-based process consisting of effectively composed multiple extrusion and granulation cycles. The results from TGA, DSC, FTIR, XRD, EDS-SEM and tensile tests indicate that physical and mechanical properties of the re-extruded and printed PVDF-HFP are largely preserved. The process ensures homogeneous BTO dispersion within the consistently printable piezocomposites, which demonstrate satisfactory levels of piezoresponse and flexibility together with filler-reinforcing and high-field poling capabilities. The FFF-printed piezocomposites tested at higher strain rates (up to 0.17 s−1) exhibit 30%–40% increase in tensile strength at the expense of reduced ductility. Brief thermal poling at 80 °C and 20 kV mm−1 is observed to improve coefficient d
33 through more effective BTO polarization compared to room-temperature poling (up to 7.3 pC/N is measured for the 40/60 wt% PVDF-HFP/BTO). Thermal poling also enhances piezoresponse stability by minimizing depolarization (d
33 decay) regardless of poling duration. Increase in BTO content results in stronger dependence of piezoresponse on poling field, temperature and duration, as well as weaker dependence of ductility characteristics on the strain rate. The MEP approach is environmentally and economically sustainable manufacturing method that is accessible to a wide FFF user community. It is also scalable to high-throughput production of functional composites based on thermally resistant materials to enable 3D printing of customizable piezoelectric sensing devices.
Efficient digital quadratic unconstrained binary optimization solvers for SAT problems
Authors: Fong Robert Simon , Song Yanming , Yosifov Alexander
Published: January 2025

Boolean satisfiability (SAT) is a propositional logic problem of determining whether an assignment of variables satisfies a Boolean formula. Many combinatorial optimization problems can be formulated in Boolean SAT logic—either as k-SAT decision problems or Max k-SAT optimization problems, with conflict-driven clause learning (CDCL) solvers being the most prominent. Despite their ability to handle large instances, CDCL-based solvers have fundamental scalability limitations. In light of this, we propose recently-developed quadratic unconstrained binary optimization (QUBO) solvers as an alternative platform for 3-SAT problems. To utilize them, we implement a 2-step [3-SAT]-[Max 2-SAT]-[QUBO] conversion procedure and present a novel approach using linear systems and Diophantine equation to calculate the number of both satisfied and violated clauses of the original 3-SAT instance from the transformed Max 2-SAT formulation. We then demonstrate, through numerical simulations on several benchmark instances, that digital QUBO solvers can achieve state-of-the-art accuracy on 78-variable 3-SAT benchmark problems. Our work facilitates the broader use of quantum annealers on noisy intermediate-scale quantum devices, as well as their quantum-inspired digital counterparts, for solving 3-SAT problems.
Superconductivity in Weyl semimetals with time reversal symmetry
Authors: Bai Xuesong , LiMing W , Zhou Tao
Published: January 2025

This theoretical study delves into the superconducting traits of Weyl semimetals that possess time reversal symmetry, utilizing the Bogoliubov–de Gennes equations. Our meticulous self-consistent calculations have unveiled a dual superconducting gap at the surface. We have also contrasted these findings with the superconducting characteristics of models that exhibit broken time-reversal symmetry. Our analysis indicates that Weyl semimetals with unimpaired time-reversal symmetry not only sustain a complete energy gap but also display modified Fermi arc surface states, which are notably distinct from those in models with compromised time-reversal symmetry. This work bridges the gap between theoretical expectations and experimental observations, advancing our understanding of the superconducting properties of Weyl semimetals.
System of fractal-fractional differential equations and Bernstein wavelets: a comprehensive study of environmental, epidemiological, and financial applications
Authors: Rayal Ashish
Published: January 2025

The fractal-fractional derivatives uniquely incorporate memory effects, heterogeneity, and fractal geometry, making them essential for studying dynamic systems compared to integer-order derivatives which cannot capture such intricate dynamics. So, this study aims to analyze the dynamical behaviour of the model of systems of differential equations under Caputo fractal-fractional derivative by designing a numerical framework based on the fractional order Bernstein wavelets. The Caputo fractal-fractional derivative under the power law kernel has been employed to obtain more accurate performances of the considered model as compared to fractional and integer order. A key novelty of this work lies in the implementation of fractional order Bernstein wavelets with collocation grids, which transform the complex differential equations into simpler algebraic equations, ensuring computational efficiency. The validity of the mentioned scheme is demonstrated by examining some famous problems, such as pond pollution problem, SIR epidemic modelling of infectious disease, a model of HIV interactions with CD4+T cells, and a financial model, showcasing its broad applicability across applied science, finance and engineering. For compactness, an error analysis using residual function is performed for fractal-fractional order. The graphs of the solution in integer, fractional and fractal-fractional order show that the achieved solutions are very close to the actual result of the examples and the error progressively decreases as the number of wavelets basis increases. In the case α = β = 1, the obtained approximated wavelet solutions for the suggested model are in good harmony with the exact solutions, the fourth-order Runge-Kutta (RK4) method and existing schemes provided in the literature. This investigation demonstrates that the mentioned scheme is very effective and straightforward for solving such kinds of fractal-fractional models.
Analysis of 1D NMR spectra with 2D image processing techniques
Authors: Meshkian M , Schmid N , Henrici A , Bruderer S
Published: January 2025

Rapid advances in NMR spectroscopy instrumentation demand powerful analysis techniques to be implemented to cope with the development. These include extracting patterns from the data acquired, such as images and 1D spectra. Furthermore, deep learning models have shown to be very powerful in extracting patterns from such data. However, current analysis techniques include several manual steps to label the data, which are usually time-consuming and crucially dependent on expert knowledge. Therefore, this paper aims to demonstrate the applicability of neural networks for extracting different spectral structures and specially, investigating an analysis approach, inherited from 2D image processing, to determine its usefulness in feature extraction from 1D spectroscopy data. The approach utilizes bounding-box algorithms, same as in image recognition, to recognize patterns in 1D spectra.
Simulating fish autonomous swimming behaviours using deep reinforcement learning based on Kolmogorov–Arnold Networks
Authors: Li Tao , Zhang Chunze , Zhang Guibin , Zhou Qin , Hou Ji , Diao Wei , Meng Wanwan , Zhang Xujin
Published: January 2025

The study of fish swimming behaviours and locomotion mechanisms holds significant scientific and engineering value. With the rapid advancements in artificial intelligence, a new method combining deep reinforcement learning (DRL) with computational fluid dynamics has emerged and been applied to simulate the fish’s adaptive swimming behaviour, where the complex fish behaviour is decoupled to focus on the fish’s response to the hydrodynamic field, and the simulation is driven by reward-based objectives to model the fish’s swimming behaviour. However, the scale of this cross-disciplinary method is directly affected by the efficiency of the DRL model. To promote it to more general application scenarios, there is a pressing need for further research on more efficient and economical network architectures to address the challenge of approximating state-value function in high-dimensional, dynamic, and uncertain environments. Building upon a previously proposed computational platform for the simulation of fish autonomous swimming behaviour, we integrated Kolmogorov–Arnold Networks(KANs) and tested their performance in point-to-point swimming and Kármán gait swimming environments. Experimental results demonstrated that, compared to long short-term memory Networks(LSTMs) and multilayer perceptron networks(MLPs), the introduction of KANs significantly enhanced the perception and decision-making abilities of the intelligent fish in complex fluid environments. With a smaller network scale, in the point-to-point swimming case, KANs effectively approximated the state-value function, achieving average reward improvements of up to 88.0% and 94.1% over MLPs and LSTMs networks, respectively, and increased by 766.7% and 105.6% in the Kármán gait swimming case. Under comparable network sizes, the intelligent fish with KANs exhibited faster learning capabilities and more stable swimming performance in complex fluid settings.
Decellularized cartilage tissue bioink formulation for osteochondral graft development
Authors: Golebiowska Aleksandra A , Tan Mingyang , Ma Anson WK , Nukavarapu Syam P
Published: January 2025

Articular cartilage and osteochondral defect repair and regeneration presents significant challenges to the field of tissue engineering (TE). TE and regenerative medicine strategies utilizing natural and synthetic-based engineered scaffolds have shown potential for repair, however, they face limitations in replicating the intricate native microenvironment and structure to achieve optimal regenerative capacity and functional recovery. Herein, we report the development of a cartilage extracellular matrix (ECM) as a printable biomaterial for tissue regeneration. The biomaterial was prepared through decellularization and solubilization of articular cartilage. The effects of two different viscosity modifiers, xanthan gum and Laponite®, and the introduction of a secondary photo-crosslinkable component on the rheological behavior and stability were studied. dcECM-Laponite® bioink formulations demonstrated storage modulus (G′) ranging from 750 to 4000 Pa, which is three orders of magnitude higher than that of the dcECM-XG bioink formulations. The rheological evaluation of the bioinks demonstrated the tunability of the bioinks in terms of their viscosity and degree of shear thinning, allowing the formulations to be readily extruded during 3D printing. Also, a spreadable ink composition was identified to form a uniform cartilage layer post-printing. The choice of viscosity modifier along with UV cross-linking warrants shape fidelity of the structure post-printing, as well as improvements in the storage and loss moduli. The modified ECM-based bioink also significantly improved the stability and allowed for prolonged and sustained release of loaded growth factors through the addition of Laponite®. The ECM-based bioink supported human bone-marrow derived stromal cell and chondrocyte viability and increased chondrogenic differentiation in vitro. By forming decellularized cartilage ECM biomaterials in a printable and stable bioink form, we develop a ‘Cartilage Ink’ that can support cartilaginous tissue formation by closely resembling the native cartilage ECM in structure and function.
Structural, electronic, mechanical, optical and magnetic properties of RhNbZ (Z = Li, Si, As) Half-Heusler compounds: a first-principles study
Authors: Bejo Adem Beriso , Shura Megersa Wodajo , Tadele Kumneger , Afrassa Mesfin Asfaw , Maremi Fekadu Tolessa
Published: January 2025

Structural, mechanical, electronic, optical and magnetic properties of the cubic RhNbZ (Z = Li, Si, As) half-Heusler compounds is reported using density functional theory (DFT) as implemented in quantum espresso simulation package. Structurally, the compounds are most stable when they are in type I atomic arrangement. Studies of mechanical properties indicate that all the three compounds are ductile in nature and mechanically stable. Calculations of electronic band structure and density of states (DOS) affirm that RhNbSi is a semi-conductor with an indirect band gap of 0.662 eV and 1.0095 eV from generalized gradient approximation (GGA) and GGA+U approaches respectively, where U is Hubbard parameter, RhNbLi has metallic property under both GGA and GGA+U approaches whereas RhNbAs has metallic nature under GGA prediction but it has half-metallic property under GGA+U approach, a property which is essential for spintronic applications. Optical parameters such as dielectric function, reflectivity, refractive index, extinction coefficient, absorption coefficient, optical conductivity and electron energy loss were estimated in the photon energy range of 0–40 eV. Results from these properties calculations reveal that both absorption coefficient and optical conductivity have maximum values whereas electron energy loss has minimum value in the lower energy ranges which show that the materials under our study can be considered as potential candidates for optoelectronic applications. From magnetic property calculations, RhNbSi is predicted to be nonmagnetic material but RhNbLi and RhNbAs have magnetic nature.
Laser treated super hydrophobic glass for solar PV self cleaning application: a SWOT-TWOS-based analysis
Authors: Rai Rahool , Ishak Mahadzir , Kumarasamy Sudhakar , Bin Mohd Halil Aiman , Quazi M M
Published: January 2025

With the increasing demand for sustainable energy solutions, laser surface modification has emerged as a promising technique to enhance the functional properties of materials, particularly in optimizing glass surfaces for solar applications that require hydrophobicity and environmental resilience to improve photovoltaic performance and durability. Consequently, a SWOT-TWOS analysis is conducted to identify the strengths, weaknesses, opportunities, and threats of integrating these technologies. This analysis assesses the advantages, such as improved light diffusion and reduced glare, along with the disadvantages, including decreased transparency and potential glass damage. Additionally, there are opportunities for technological and sustainable advancements, as well as threats such as quality control issues. The SWOT analysis for Laser Treated Super Hydrophobic Glass in solar PV self-cleaning applications revealed a distribution of 42% technical, 26% environmental, and 21% economic factors, with 11% of factors spanning all three domains. Notably, the two elements are complex and interdependent across multiple domains, underscoring the intricate influences affecting the viability of this technology. By identifying these characteristics, the study aims to provide a comprehensive understanding of laser texturing potential and limitations, as well as recommendations for future research and practical applications.