bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-distance three-dimensional object detection in rainy conditions from multi-sensory measurements using a new machine learning model
Authors: Deng Mingxing , Bai Zian , Qi Qinghua , Xu Xiaowei , Li Z
Published: February 2025

To address the challenges of feature extraction and low detection accuracy for long-range three-dimensional (3D) objects in rainy environments, this paper proposes an improved probabilistic and geometric depth (PGD) machine learning-based detection method using multi-sensory measurements. In this new method, the deformable convolutions replace the regular convolutions in the PGD network to enhance the feature layer adaptability to the target shapes. A receptive field enlarging network is also designed to improve the detection performance for distant objects. Furthermore, an optimized multi-level feature pyramid is developed to improve the detection accuracy across varying scales. Lastly, a decision-level fusion aggregates the PGD detection head and the branch network detection head using a deep fusion module to produce the 3D object information and recognize different targets in a long distance. The proposed method is validated using the KITTI, nuScenes public datasets, and real-world testing datasets, where the camera and millimeter-wave radar are used to collect these datasets. The analysis results indicate 4%, 5.4%, and 12% increase in detection accuracy over the original PGD algorithm across these three datasets, demonstrating superior feasibility and accuracy of the proposed method for long-range object detection.
An efficient multi-scale feature enhancement network for industrial surface defect detection
Authors: Chen Jiusheng , Zha Haoxiang , Zhang Xiaoyu , Guo Runxia , Wu Jun
Published: February 2025

Surface defect detection in industrial manufacturing ensures product quality and prevents malfunctions. To address issues such as multi-scale damage, low contrast, and small defects on the surfaces of industrial components, we propose an efficient multi-scale feature enhancement network for improving the detection performance of industrial surface defects. First, a multi-scale extraction module is proposed to extract defect features at multiple levels to ensure sufficient semantic information for multi-scale damage and enhance the feature extraction ability of defects with different scales. Dual-orientation attention is then introduced into the detection network to establish a connection between spatial and channel dimensional information, which enables the network to focus on defect regions and filter out background noise. This alleviates the problems of low contrast and small defects. The experimental results confirm that the proposed network demonstrates superior detection performance compared to other detection algorithms across five surface defect datasets. Additionally, the parameters are reduced by 7.9%, the floating-point operations decrease by 6.7%, and the model size is reduced by 5.2%. These improvements collectively provide an efficient solution for industrial surface defect detection.
Dual photoacoustic/ultrasound technologies for preclinical research: current status and future trends
Authors: Pérez-Liva Mailyn , Alonso de Leciñana María , Gutiérrez-Fernández María , Camacho Jorge , Fernández Cruza Jorge , Rodriguez-Pardo Jorge , García Ivan , Laso Fernando , Herraiz Joaquin L , Elvira Luis
Published: February 2025

Photoacoustic imaging (PAI), by integrating optical and ultrasound modalities, combines high spatial resolution with deep tissue penetration, making it a transformative tool in biomedical research. This review presents a comprehensive analysis of the current status of dual photoacoustic/ultrasound (PA/US) imaging technologies, emphasising their applications in preclinical research. It details advancements in light excitation strategies, including tomographic and microscopic modalities, innovations in pulsed laser and alternative light sources, and ultrasound instrumentation. The review further explores preclinical methodologies, encompassing dedicated instrumentation, signal processing, and data analysis techniques essential for PA/US systems. Key applications discussed include the visualisation of blood vessels, micro-circulation, and tissue perfusion; diagnosis and monitoring of inflammation; evaluation of infections, atherosclerosis, burn injuries, healing, and scar formation; assessment of liver and renal diseases; monitoring of epilepsy and neurodegenerative conditions; studies on brain disorders and preeclampsia; cell therapy monitoring; and tumour detection, staging, and recurrence monitoring. Challenges related to imaging depth, resolution, cost, and the translation of contrast agents to clinical practice are analysed, alongside advancements in high-speed acquisition, artificial intelligence-driven reconstruction, and innovative light-delivery methods. While clinical translation remains complex, this review underscores the crucial role of preclinical studies in unravelling fundamental biomedical questions and assessing novel imaging strategies. Ultimately, this review delves into the future trends of dual PA/US imaging, highlighting its potential to bridge preclinical discoveries with clinical applications and drive advances in diagnostics, therapeutic monitoring, and personalised medicine.
Recent advances in GaN-based power devices and integration
Authors: Xiong Yixin , Sadek Mansura , Chu Rongming
Published: February 2025

Gallium nitride (GaN) has gained traction in replacing silicon for power electronics applications, due to its high breakdown field, high mobility 2D electron gas, and effective n/p-type doping. This paper reviews three important topics of GaN power devices. One is the voltage-blocking structures needed to operate at high voltage while minimizing conduction loss and switching loss. Another one is the structure used to achieve normally-off operation, which is often required for power electronics. The third topic is the monolithic integration of gate drivers and power switches to achieve the ultimate switching speed at a low cost.
Infill structure analysis of FDM-printed PLA wood glass fiber composite for commercial product applications
Authors: N Pragadish , M Bakkiyaraj , P Rajakrishnamoorthy , R Ganapathy Srinivasan , M Selvam , A Thamarai Selvan
Published: February 2025

In this study, the mechanical properties of triangular and honeycomb infill structures with varying percentages (20%, 40%, and 60%) of 3D printed polylactic acid (PLA) wood-glass fiber for bi-directional reinforcement are explored. The objective is to assess these structures under different loading conditions and select the most suitable configuration for practical applications. Flexural strength, hardness, impact, tensile strength and scanning electron microscope analysis of fracture morphology were conducted on a range of mechanical tests. In addition, thermal conductivity, V-notch rail shear strength and wear resistance tests were performed. Structural integrity, resilience, material durability, heat transfer, adhesive properties, and fracture behavior are tested, and a complete analysis of performance is performed. Form the results, honeycomb structures with 60% infill demonstrated a high strength-to-weight ratio, offering potential for lightweight structural components across various sectors. Their lightweight yet robust nature enhances overall performance. Meanwhile, triangular structures with 40% infill showcased competitive mechanical properties and efficient load distribution, making them suitable for lightweight sporting equipment, furniture, protective gear, and safety equipment. At higher infill percentages, both honeycomb and triangle infill patterns are found to provide increased wear resistance to density ratios for automotive components (gears, brake pads), aerospace parts (landing gear, engine components), industrial machinery (bearings, pulleys), and consumer electronics (wearable devices, protective casings) where wear resistance and durability under friction are critical.
Research on the microwave heating and de-icing performance of various composite coatings
Authors: Huang Qinqin , Yang Zhengqing , Liu Ning , Zhang Dongdong , Jiang Guangwen , Zhang Hailong , Zhu Haiyang , Liu Xiangyan
Published: February 2025

Microwave heating and de-icing is an efficient, eco-friendly choice for wind turbine blade de-icing methods, where microwave energy is converted into heat through absorbing coatings. Thus, the heating characteristics of absorbing coatings under microwave irradiation are of paramount importance. In this paper, 15 types of polyurethane composite coatings containing different absorbing fillers were prepared, and their heating performance under 2.45 GHz microwave irradiation was investigated. The effects of filler type, filler content and irradiation distance on heating rate were systematically evaluated, and the de-icing performance of various ice layer thicknesses was analyzed. Results revealed that ferroferric oxide/polyurethane coatings with an identical filler content exhibited the fastest heating rate, followed by graphite/polyurethane and silicon carbide/polyurethane. The heating characteristics of the coatings were positively correlated with filler content and negatively correlated with irradiation distance. As ice thickness increased, so did the time for ice shedding and melting. Composite coatings demonstrated superior de-icing performance compared with control specimens, creating a central melting region that gradually expanded to melt the entire ice layer.
Some properties of hyperbolic Yamabe solitons
Authors: Blaga Adara M , Ozgur Cihan
Published: February 2025

We define the hyperbolic Yamabe flow and obtain some properties of its stationary solutions, namely, of hyperbolic Yamabe solitons. We consider immersed submanifolds as hyperbolic Yamabe solitons and prove that, under certain assumptions, a hyperbolic Yamabe soliton hypersurface is a pseudosymmetric or a metallic shaped hypersurface. We characterize the hyperbolic Yamabe soliton factor manifolds of a multiply twisted, multiply warped, doubly warped, and warped product manifold and provide a classification for a complete gradient hyperbolic Yamabe soliton factor manifold. We also determine the conditions for the factor manifolds to be hyperbolic Yamabe solitons if the manifold is a hyperbolic Yamabe soliton and illustrate this result for a physical model of the universe, namely, for the Robertson--Walker spacetime.
Thermal conductivity of surface phonon polaritons in SiC elliptical nanofibers
Authors: Huang Congliang , Du Changkang , Wang Xiaodong
Published: February 2025

Surface phonon polaritons (SPhPs) in polar dielectric are considered to be a class of potential efficient heat carriers for heat dissipation in micro electric devices, due to their high contribution to the thermal conductivity. In this work, the contribution of SPhPs to the thermal conductivity of a fiber with a general elliptical cross-section area was studied. The effects of cross-sectional size and shape of the SiC elliptical nanofibers were investigated. A method for analytically solving the dispersion relation of SPhPs in elliptical fibers was firstly presented, based on which the contribution of SPhPs to the thermal conductivity was further analyzed. It was found that the SPhP-contributed thermal conductance of a SiC nanofiber with an equivalent diameter of 19.4 nm is about 51.2 pW·K−1, which is comparable to that contributed by phonons. Importantly, this value is also comparable to that reported for nanofilms. For eccentrics being smaller than 0.6, the effect of the eccentricity can be neglected, and there is a power-function relationship between the thermal conductivity and the equivalent diameter, i. e.

λ
~

d

−
α

,

α
=
1.222

. When the eccentricity becomes larger than 0.6, the thermal conductivity increases rapidly because the geometry approaches the one of a film. This study shows a great potential of utilizing SPhPs in nanofibers as effective carriers for heat dissipation.
Stability analysis and Hopf bifurcation in a delayed nonlinear tumor-macrophage model
Authors: Li Jianping , Xu Guoming , Liu Nan , Wang Danni , Yang Hongli
Published: February 2025

Macrophages have a dual effect on tumor cells. This paper investigates a delayed nonlinear model describing the interactions between tumor cells (T), classically activated macrophages (M1), and alternatively activated macrophages (M2). The existence and non-negativity of the solutions are established, and the stability of equilibrium points is analyzed. It is found that as the time delay increases, the stability of the coexisting equilibrium point may switch through a Hopf bifurcation. Then, the multiple time scales method (MTS) is employed to derive the normal form of the Hopf bifurcation. Numerical simulations validate our theoretical analysis. Additionally, controlling the parameter (the ratio of activation rates by tumor cells M2/M1 macrophages) can also trigger a Hopf bifurcation. The emergence of stable limit cycles implies the long-term coexistence of tumor cells and macrophages, as well as the long term recurrence of tumors. Sensitivity analysis further confirmed the importance of macrophages in tumor treatment. These results may provide clues for combating cancer.
Bounded synchronization of fractional-order chaotic systems with external disturbance based on dissipative decomposition
Authors: Li Ruihong , Liu Jiayi , Huang Dongmei
Published: February 2025

Compared with the classical synchronization phenomena, practical synchronization considers the factors of the real environment and has a wider range of applications. For fractional- order disturbed systems, a practical synchronization type, bounded synchronization, is discussed for the first time. The proposed synchronization model does not require the error system to converge completely to the origin but allows convergence to a bounded region around the origin. Employing the dissipative decomposition of vector field, a simple and novel synchronization scheme is presented for a class of fractional-order chaotic systems with external disturbance. The Mittag-Leffler input stability of the error system can be guaranteed by means of fractional-order stability theory. Two fractional-order chaotic systems with periodic and noise disturbances, respectively, are taken as examples to demonstrate the feasibility of the proposed method. Numerical results indicate that regardless of the disturbance, the error system is eventually kept within the boundary and the boundary values are related to the controller strength. Furthermore, the effect of controller parameters on the error boundary is also analyzed, and the results help to select the control parameters according to the actual needs in the application.
Influence of magnesium doping on carbon dots for enhancing photocurrent generation in photodetectors
Authors: Gopi Pavithra , Ponnusamy Kathirvel
Published: February 2025

In recent years, carbon dots (CDs) doped with metals have garnered significant attention. Metal doping introduces free electrons, thereby increasing the carrier concentration within the CDs and altering their intrinsic properties. This study explores the influence of magnesium (Mg) doping on CDs (MCDs) to enhance photocurrent generation in photodetectors (PDs). CDs and MCDs are synthesised using a microwave method. Comparative analysis of the structural and optical properties of MCDs and CDs reveals the impact of Mg doping on the surface of CDs. Characterization techniques demonstrate that Mg doping enhances conjugation within the CDs, leading to improved charge transfer by reducing bandgap and improving the density of states. Photocurrent measurements are conducted under visible, long UV, and short UV illumination. The results indicate an increase in photocurrent, particularly under 365 nm illumination, rising from 3.86 × 10−6 A to 2.98 × 10−5 A, suggesting a positive correlation between Mg concentration and enhanced photocurrent.
Laser cladding of inconel 718 coating on stainless steel surface
Authors: Du Fengming , Zhang Yuhong , Mi Zetian , Shen Yan , Wang Jingsi , Wang Jinlong , Yang Yuxing , Liu Yu
Published: February 2025

An Inconel 718 coating was applied to the surface of 316L stainless steel to enhance its wear resistance. The coating’s phase composition, element distribution, microstructure, hardness, and wear resistance were analyzed. The results revealed that the Inconel 718 coating comprised the γ∼(Fe, Ni) solid solution, Ni3Nb, (Nb0.03Ti0.97)Ni3, and MCX (M = Cr, Nb, Mo). The coating achieved a maximum hardness of 640.2 HV0.2, which is more than three times that of the substrate. The main wear mechanisms of the coating are adhesive and abrasive wear, with a wear rate of 2.97 × 10−5 mm3 · N−1 · min−1. In the coating bonding zone, relatively coarse cellular and columnar crystals grew perpendicular to the planar crystals. The central region was predominantly composed of dendritic crystals, while a small amount of equiaxed crystals formed in the upper region. This work can provide guidance for surface strengthening of stainless steel.
Coaxial transition with very large diameter ratio of inner conductor using equal amplitude in-phase feeding
Authors: Qin Feng , Zhu Yuping , Geng Hui , Feng Jinghao , Wu Qiuyi
Published: February 2025

This paper presents a novel design for a broadband coaxial transition featuring a large inner conductor radius ratio. To establish the equivalence between a two-port matching network and the even mode of a symmetrical power splitting network, an equivalent circuit model of an ideal Tee junction is proposed. Subsequently, a highly integrated impedance transition model is developed by employing a double splitting strategy. Subsequently, a highly integrated impedance transition model is developed by employing a double splitting strategy. By adopting a symmetrical, in-phase, and equal-amplitude feeding strategy, the challenges associated with impedance matching and spurious mode suppression are effectively addressed. Furthermore, a symmetrical and equal amplitude in phase feeding strategy are introduced to the great challenges of impedance matching and spurious suppression can be overcome. In addition, the design complexity is alleviated by using the equivalence between the wrapped waveguide and a coaxial to reduce the numerical burden. A typical design example with the radius ratio of the inner conductor up to 1:25 is designed and fabricated. The simulated and measured results have proven the feasibility of the proposed method. It can be applied to broadband rotary joints that demand large hollow space through the center.
An analytic approximate solution for nonlinear drift-diffusion equation
Authors: Shweta S , Khurana Karizma , Kumar Rajesh
Published: February 2025

The drift-diffusion equation is a fundamental model used for modeling phenomena in physics, finance, biology, and engineering. Its applications span particle dynamics, molecular diffusion, asset pricing, population dynamics, and noise control systems. The wide range of its applications motivated us to address the non-linear problem semi-analytically via two advanced schemes: the Accelerated Homotopy Perturbation Elzaki Transformation Method (AHPETM) and the Optimized Decomposition Method (ODM). AHPETM combines the accelerated homotopy perturbation method with the Elzaki transform, while ODM employs linear approximations and Adomian polynomials. Through diverse test cases in 1-, 2- and 3-dimensions, we demonstrate AHPETM’s superior accuracy, computational efficiency, and capability to provide closed-form solutions as compared to the ODM and the well-established semi-analytical schemes, i.e., variational iteration as well as Temimi and Ansari methods. Furthermore, rigorous convergence analysis and derivation of worst-case error bounds validate the reliability of the proposed methods, establishing AHPETM as a robust and versatile tool for tackling complex nonlinear systems
A generalization of cell survival models via fractional approach
Authors: Şen Mürsel , Çalık Abdullah Engin , Senturk Ibrahim , Şirin Hüseyin
Published: February 2025

This study investigates the relationship between radiation dose and the number of surviving cells as a result of radiation treatment by revisiting and extending linear, quadratic, and linear-quadratic cell survival models using fractional calculus. The generalized version of these models, called as fractional cell survival model, offers a deeper insight into the mechanisms underlying cell survival. This model shows a good harmony with the experimental findings, and it is also generalized the standard models when the fractional derivative orders are equal to 1. This new approach not only makes cell survival predictions more accurate, but also gives us a better understanding of how radiation affects cells and how they respond.
Federated learning-based defect localization on metal surfaces using ensembled pretrained deep neural networks with feature fusion
Authors: Kansal Isha , Popli Renu , Khanna Divya , Sharma Vikas , Sharma Ashutosh , Kumar Rajeev , Khullar Vikas
Published: February 2025

This work proposes an effective approach towards effective classification of metallic surface defects by using feature extraction, feature reduction, deep neural networks and federated learning. The process starts with using the GC10-DET dataset which consists of 3,570 grayscale images of ten different types of defects on steel sheet namely punching, weld line, and oil spot among others. Firstly, the images are preprocessed and normalized where the dimensions of the images are resized to a certain size and also the images may be augmented to have similar format. The feature extraction is done by five Efficients models—B0 to B4, and this results in extracting 7,296 features for each image. Linear Discriminant Analysis (LDA) is then used, which projects feature space into nine significant features to enhance its readiness for classification. Classification is being performed through Deep Neural Network (DNN), Long Short Term Memory (LSTM), and Bi-directional LSTM (Bi-LSTM). Among these, EfficientNetB2 combined with LDA demonstrates superior performance, achieving a validation accuracy of 88.7446%, precision of 90.4545%, and recall of 86.1472%. Federated learning is employed to preserve data privacy while enabling collaborative model training across four clients, representing different data holders. The system shows impressive performance in both Independent and Identically Distributed (IID) and Non-IID data scenarios, with clients achieving up to 100% accuracy, precision, and recall under IID conditions, and rapid convergence to near-perfect accuracy under Non-IID conditions. These results highlight the methodology’s effectiveness in real-world industrial applications, where high accuracy and data privacy are paramount.
Probability density functions covering stretched exponential and stretched Cauchy distributions
Authors: Duan Lingjie , Duan Junsheng
Published: February 2025

A class of probability density functions with three parameters in terms of Mittag-Leffler functions is presented. The proposed distributions include stretched exponential and stretched Cauchy distributions as special cases, and stretched exponential distributions cover Gaussian and Laplace distributions. Heavy-tailed distributions are clarified as a subclass of the proposed distribution. For heavy-tailed distributions, a variance does not exist, nor does even a mean. Instead of the variance and kurtosis defined for stretched exponential distributions, a class of light-tailed distributions, we present two characteristic numbers, fractional order moment and centrality, applicable for heavy-tailed distributions to describe degree of variation of the corresponding random variable. The fractional order moment is defined as an absolute central moment of fractional power while the centrality is prescribed as the product of the full width at the half maximum and the peak value of the probability density function. Numerical simulations show the effectiveness of the proposed perspective and methods.
Fusion magnet quench risk increase with irradiation damage
Authors: John Jacob Maxwell , Gilbert Mark R , Hardie Chris D.
Published: February 2025

Superconducting material enables fusion reactor magnet concepts to operate with current densities that would melt materials with non-zero resistance. The application of superconducting material is considered essential for net-positive power machines. Catastrophic damage can occur when superconductivity is lost and the current generates heat. This scenario is called a quench. Stabilizer material carries the magnet current (typically copper) during a quench and is the focus of this work.Irradiation-induced defects store energy in the Cu crystalline lattice. The presence of defects reduces thermal conductivity (thermally insulating the superconductor), electrical conductivity (increasing temperature ramp rate during a quench), and specific heat capacity (increasing thermodynamic instability). The release of stored energy in the magnet materials, in combination with the magnet material property changes, has the potential to cause extreme off-normal events in superconducting magnets that worsen with fluence.Stored energy can be released causing local heating and increasing the risk of a quench. For example, following irradiation at 4.6K and a fluence of 0.45*10^18 n/cm^2, an energy release of 0.023 J/g was measured from Cu when increased in temperature from 10K to 18K, which would have been enough energy to create the same temperature increase spontaneously.Extrapolations of experimental data are used to estimate when spontaneous heating can occur due to the release of energy stored in irradiation-induced defects. Critical fluence values are estimated between 1.74*10^18 n/cm^2 and 2.85*10^19 n/cm^2 for neutron irradiation of Cu at a temperature of 20K.In-situ cryogenic calorimetry experiments, operated at high-temperature-ramp rates on irradiated magnet materials, could offer certainty for fusion magnet system designers. Periodic annealing of defects through controlled temperature cycling will be essential in fusion power plants to manage the increasing risk of quench as the superconducting magnets accumulate dose. The ideal frequency and dynamics of these maintenance temperature cycles will be established with further experimental examination. 
Numerical simulation of the heat release process of a novel aluminum-silicon phase change energy storage device
Authors: Dong Yuming , Fan Yi , Shi Zhengrong
Published: February 2025

High-temperature thermal energy storage technologies are important for addressing the energy supply-demand imbalance. For better using the aluminum-silicon PCM, a novel shell-tube heat storage and exchange device has been designed. In this paper, numerical simulations were conducted on the heat release process of the proposed device. We regard the inlet velocity and tube arrangement as influential parameters in the heat release process and analyze the performance of the device. The results show that increasing the inlet velocity effectively reduced the solidification time of the PCM within the device but also decreased the device’s utilization rate. Initially, the thermal release power was positively correlated with the velocity, but it later showed a negative correlation trend. Studies have indicated that the arrangement of PCM within a device has a significant impact on its performance, hence two PCM configurations have been proposed: triple-row and five-row arrangements. Compared to the triple-row arrangement, the five-row configuration exhibits a more complex airflow pattern, characterized by a wavy configuration at the inlet and an extended flow path. The utilization rate for the triple-row arrangement is 75.3%, while for the five-row arrangement, it is 78.6%, representing an improvement of 3.3%. The five-row arrangement significantly enhances the system’s utilization rate and heat transfer performance. These findings contribute significantly to the understanding of TES and can inform the direction of future advancements in this field.
Analysis of the impact of different inflow conditions on the wake and aerodynamic noise of wind turbines
Authors: Yang Hua , Liu Liguo , Wang Xiaofeng , Zhang Keming , Zhang Yigong , Chen Jian , Qin Jin , Ma Ran
Published: February 2025

This paper studies the aerodynamic performance and noise characteristics of a 6 MW horizontal axis wind turbine based on CFD fluid simulation and acoustic analogy method. The influence of different flow velocities on wind turbine wake and aerodynamic noise are compared. The result shows that: The main load source of the wind turbine is the shaft flow; the airflow through the engine room and the tower, the blade, and the tower will make the airflow speed through the wind turbine change, and form a large range of low-speed area in the rear of the wind wheel; the maximum axial velocity loss of wind turbine wakes at different sections under different flow speeds is located at the hub; the wake behind the wind turbine under high turbulence intensity obtains significantly higher energy than the low turbulence intensity during development; under different inflow velocity, the higher inflow velocity increases the aerodynamic noise, which is mainly affected by the tip vortex; under low turbulent intensity, different turbulence intensity has less influence on the wind turbine aerodynamic performance and aerodynamic noise.
Thermal analysis of novel polar thermal energy generating equipment
Authors: Cao Zhizheng , Ge Yunzheng , Liu Weimin , Chen Fengyun
Published: February 2025

To address the power supply needs of small scientific expedition equipment in the Arctic region, a 100W polar thermal energy generating equipment is proposed. This equipment harnesses the temperature difference between the cold polar air (averaging −34°C) and the seawater under the ice layer (averaging 0.12±0.18°C) to generate electricity. This paper provides a detailed explanation of the thermal cycle principles and the selection of working fluids, along with a thermal analysis of the equipment. The analysis reveals that the thermal efficiency of the system and the output work per unit of working fluid flow initially increase and then decrease as the turbine inlet pressure rises, with the inflection point occurring near the saturation pressure of the working fluid. The circulating thermal efficiency and output work per kilogram of working fluid flow are unaffected by the turbine inlet temperature but decrease significantly with rising condensing temperature. Under the same working conditions, R134a outperforms R227ea and R1234yf.
Mechanical mechanism of stress wave dissociation of flake graphite under micro-jet impact
Authors: Dong Xing , Jiang Yun , Guo Chenhao , Qu Fang , Chen Jifeng
Published: February 2025

Using a cavitating water jet to dissociate non-metallic minerals is a new method for processing non-metallic minerals. In this paper, to investigate the mechanical principles underlying the dissociation of flake graphite via micro-jet impacts generated by a cavitation water jet, the process of dissociating flake graphite by the cavitation water jet is analyzed using the water hammer principle and stress wave theory. It has been found that upon impacting on the flake graphite, the micro-jet produces hydraulic shock on its surface, initiates the propagation of stress waves within the flake graphite, and causes reflections and transmissions of stress waves at the interface between the flake graphite and water. Moreover, the stress direction of the reflected wave is opposite to that of the incident wave, which causes tensile stress inside the flake graphite; it is found that when the water hammer pressure exceeds the compressive strength of flake graphite and the tensile stress reaches the dynamic crack strength of the flake graphite, the dissociation of the flake graphite will be achieved. The reflection of the stress wave causes the flake graphite to undergo layer cracks, corner cracks, and core cracks. Under the combined action of these three cracking types, the flake graphite’s stress wave reflection dissociation is achieved. This research outcome further solidifies the mechanical foundation underlying the dissociation of flake graphite via a cavitation water jet.
SOH estimation of lithium-ion battery under complex operating conditions based on BP neural network
Authors: Xu Zuming , Li Yikai
Published: February 2025

The precise state of health (SOH) estimation and monitoring of lithium-ion batteries are extremely important for future BMS (intelligent battery management system). However, there is a lack of SOH estimation methods for complex on-board conditions in the existing research results. This research suggests a battery SOH estimate technique based on the battery’s CCCV (constant voltage and constant current) charging curve and BP neural network in order to solve this issue. Firstly, multiple health indicators are extracted and screened by analyzing the correlation between battery CCCV charging curve characteristics and battery SOH. Then, the lithium-ion battery data under complex operating conditions are corrected by the empirical capacity model, and the SOH estimation model of lithium-ion battery is constructed by using the BP neural network. In conclusion, this study trains and validates the model using battery aging experimental data from NASA (National Aeronautics and Space Administration). The results demonstrate that the model’s error is less than 5%, confirming the model’s efficacy.
Machine learning for real-time processing of ATLAS liquid argon calorimeter signals with FPGAs
Authors: Voigt Johann Christoph ,   the ATLAS Liquid Argon Calorimeter group
Published: February 2025

To deal with the higher pileup after the high-luminosity upgrade of the LHC, the ATLAS
liquid argon calorimeter readout electronics will be replaced. 556 Intel Agilex-7 FPGAs will be
installed as part of the off-detector electronics, enabling a more sophisticated digital energy
reconstruction. Instead of using a linear optimal filter like the current readout, we evaluated
the use of recurrent and convolutional neural networks. These artificial neural networks are
trained on signal-enriched simulated detector pulses for a set of representative cells. The
network size is limited to approximately 500 multiply-accumulate operations per detector
cell. They show improvements in energy reconstruction especially for the case of overlapping
signal pulses, as they will appear more often under high-luminosity conditions. An FPGA prototype
firmware has been developed for both RNNs and CNNs, that supports processing the required number
of 384 detector cells on one FPGA. This uses a low-level VHDL approach to minimize the resource
usage. The ANN architecture is fixed at compile time, but the weights are configurable per
cell. The compilation results show that such a neural network based readout is feasible with the
available hardware. This is possible through the use of time multiplexing, i.e. by running the
FPGA at a multiple of the 40 MHz input data frequency.
Decline of antarctic circumpolar current due to polar ocean freshening
Authors: Sohail Taimoor , Gayen Bishakhdatta , Klocker Andreas
Published: February 2025

The Antarctic Circumpolar Current is the world’s strongest ocean current and plays a disproportionate role in the climate system due to its role as a conduit for major ocean basins. This current system is linked to the ocean’s vertical overturning circulation, and is thus pivotal to the uptake of heat and CO2 in the ocean. The strength of the Antarctic Circumpolar Current has varied substantially across warm and cold climates in Earth’s past, but the exact dynamical drivers of this change remain elusive. This is in part because ocean models have historically been unable to adequately resolve the small-scale processes that control current strength. Here, we assess a global ocean model simulation which resolves such processes to diagnose the impact of changing thermal, haline and wind conditions on the strength of the Antarctic Circumpolar Current. Our results show that, by 2050, the strength of the Antarctic Circumpolar Current declines by~20% for a high-emissions scenario. This decline is driven by meltwater from ice shelves around Antarctica, which is exported to lower latitudes via the Antarctic Intermediate Water. This process weakens the zonal density stratification historically supported by surface temperature gradients, resulting in a slowdown of sub-surface zonal currents. Such a decline in transport, if realised, would have major implications on the global ocean circulation.
The topography of Taiwan Island mitigates the damage of tropical cyclone disasters in southeastern China
Authors: Wu Jingwen , Zhang Yinchi , Zhu Laiyin , Yang Ruyuan , Su Tonghua , Wang Lan , Gao Lu
Published: February 2025

The intensity, structure, and path of tropical cyclones (TCs) are altered when they cross Taiwan Island, and this directly affects the severity of disasters in the southeastern coastal region of China, especially Fujian Province. Therefore, the extent of mitigating effect of Taiwan Island on Fujian Province-bound TCs requires investigation. Here, we classified 71 Fujian Province-bound TCs from 1984 to 2023 into two categories based on their track: Taiwan Island-crossing TCs (TCTs) and non-TCTs (nTCTs). We discovered that the duration of nTCTs was longer than TCTs, and nTCTs landing positions are more inclined to the southern Fujian Province with greater intensity as compared with TCTs. Due to the obstruction of Taiwan Island, the intensity of nTCTs with Fujian landfall was greater than that of TCTs cases. The disaster losses caused by nTCTs were significantly greater than those caused by TCTs. The number of victims, including deaths and missing people, as well as collapsed buildings, caused by nTCTs were three and two times greater than that caused by TCTs, respectively. Whether it is TCT or nTCT, the landing track and specific location determine the severity of the disaster. The damage caused by TCTs with southern tracks was more serious than that caused by TCTs with other tracks. The south -tracks caused more severe damage than north-tracks in the nTCTs category.
A micro-lung chip with macrophages for targeted anti-fibrotic therapy
Authors: Xia Jingjing , Dong Ruming , Fang Yongcong , Guo Jiabin , Xiong Zhuo , Zhang Ting , Sun Wei
Published: February 2025

Idiopathic pulmonary fibrosis (IPF) is a lethal lung disease of unknown etiology. Macrophages are implicated in the fibrotic process, but exhibit remarkable plasticity in the activated immune environment in vivo, presenting significant challenges as therapeutic targets. To explore the influence of macrophages on IPF and develop macrophage-targeted therapies, we engineered a micro-lung chip with a lung epithelium–interstitium tissue unit to establish a controlled immune environment containing only macrophages. We discovered that macrophages exacerbated inflammation and fibrosis by comparing microchips treated with bleomycin (BLM) in the presence and absence of macrophages. Based on the duration of BLM treatment, we established pathological models corresponding to inflammation and fibrosis stages. Transcriptome analysis revealed that activation of the PI3K-AKT signalling pathway facilitates the transition from inflammation to fibrosis. However, LY294002, a PI3K inhibitor, not only suppressed fibrosis and decreased the accumulation of M2 macrophages but also intensified the severity of inflammation. These findings suggest that macrophages play a pivotal role in the potential development at the tissue level. The micro-lung chip co-cultured with macrophages holds significant potential for exploring the pathological progression of IPF and elucidating the mechanisms of anti-fibrotic drugs.
Micro-milling cutting conditions influence on part geometrical accuracy, surface quality and tool wear in Ti-Grade-5 alloy
Authors: R Rajamani , S P Leo Kumar
Published: February 2025

This work focuses on analyzing the consequences of micro-milling process variables on part geometrical accuracy, area surface finish (Sa) and tool wear. Ti-Grade-5 (Ti-6Al-4V) was selected as the work material due to its established applications in biomedical micro parts and its potential for performance improvement. A tungsten carbide flat end two flute micro-milling cutter with a diameter of 500 μm was chosen as the cutting tool. A feed rate (fz) range of 0.2–0.3 μm tooth−1 was selected for the work material, taking into account the size effect. Other variables included a depth of cut (ac) ranging from 75 to 150 μm and cutting speed (vc) ranging from 23.55 to 70.65 m min−1. Taguchi L9 Orthogonal array-based micro-milling experiments were conducted using a unique micro-cutting tool. The response variables measured included tool wear, geometrical accuracy, and Sa values.The results indicate that operating at lower ranges of vc (23.55 m min−1), fz (0.2 μm tooth−1), and ac (75 μm) yields a geometrical accuracy of 33.334 μm, an Sa value of 0.185 μm, and minimal tool wear of 11 μm. It was observed that under these lower operating conditions, there is an increased time interval for material removal and reduced contact between the workpiece and the tool. In conclusion, optimizing cutting conditions based on the size effect will enhance part geometrical accuracy, surface finish, and tool performance during the micro-part generation process in Ti Grade-5 alloy.
Characterization, cytotoxicity and cell proliferation of two Hydroxyapatite products from Lates calcarifer fish bones via thermal calcination
Authors: Le Ho Khanh Hy , Dao Viet Ha , Pham Xuan Ky , Nguyen Phuong Anh , Phan Bao Vy , Doan Thi Thiet , Tran Xuan Vinh
Published: February 2025

This study investigates the sustainable extraction of nano-Hydroxyapatite (nano-HAp) from Lates calcarifer fish bones, a by-product of the seafood industry, through thermal calcination. Nano-HAp was synthesized at two temperatures (650 °C and 700 °C), resulting in rod-like (42 nm) and spherical (98 nm) particles, respectively. Both samples were identified as B-carbonated HAp, with Ca/P molar ratios of 1.842 for HAp 650-4 h and 1.856 for HAp 700-4 h, confirming the presence of B-type HAp, which has higher Ca/P ratios than the standard HAp found in bones and teeth (1.67). Cytotoxicity tests showed that both samples exceeded the ISO 10993-5:2009 standard, with L929 cell viability above 70% at concentrations up to 2 mg mL−1. Notably, the study emphasizes that the size and morphology of nano-HAp play a critical role in its biological activity. Larger spherical particles (HAp 700-4 h) enhanced the proliferation of human bone marrow-derived mesenchymal stem cells (hBMSCs) more effectively than smaller rod-like particles (HAp 650-4 h), suggesting their greater potential for tissue engineering and bone regeneration applications. This work demonstrates the promising biocompatibility of fish bone-derived nano-HAp and its potential for sustainable biomedical applications.
Symmetry/asymmetry within a cylindrical lattice model of nuclear structure predicts cosmic abundance/scarcity
Authors: Walsh Ray
Published: February 2025

Protons and neutrons are the smallest forms of matter with measurable size, and each nucleon has a mix of three up (+2/3) and down (−1/3) quarks. Quarks are treated as point-like particles within polygon-based geometries in order to model the structures of stable nuclides through 36Ar. The model derives ab initio from the proton’s radius (r = 0.8414 fm), the hadron’s prolate spheroid shape (from the transition to the nucleon’s first excited state (the ∆(1232) resonance), and the separation distance between bound nucleons (≈0.8 fm, from the Argonne v18 NN potential). The spatial extent of the prolate spheroid nucleon is assumed to arise from its three quarks, which implies a qualitatively linear quark sequence. Spin–spin forces repel the two like-flavored quarks to opposite ends of the prolate nucleon leaving the unlike quark in the middle. It then follows that the quark-to-quark distance within the nucleon corresponds to the nucleon’s radius. Nucleons link by quark-to-quark interactions to form proton-neutron short-range correlated pairs (pn SRCs), separated by a distance assumed equivalent to the proton’s radius. Alternating nucleons thus produce regularly alternating up/down point-like quark sequences. We contemplate various structures for each stable nuclide through

Ar

18

36

and include the one whose calculated rotational radius (derived from the radius formula of a regular polygon) best correlates with its IAEA-accepted charge radius (r(31) = .98, p<.001). Nucleon alternation inherently makes pn SRC pairs, and produces the observed equal numbers of protons and neutrons (Z = N) found within isotopes

He
,

2

4

C
,

6

12

N
,

7

14

O
,

8

16

Ne
,

10

20

Mg
,

12

24

Si
,

14

28

and

S

16

32

, which together comprise 99.5% of nonhydrogen baryonic matter. Bilateral structural symmetry emerges as a sensitive and specific predictor of cosmic abundance. Opposing deuteron-deuteron’ alternating quark charge sequences produce alternating and unequal electromagnetic fields shown capable of modelling the close-range attraction and far-range repulsion of the fusion potential curve and Coulomb potential energy barrier.
Evapotranspiration, land cover, and climatic factors in southeastern Mexico and Central America
Authors: Mendoza-Aguilar Brenda Yutziny , Carbajal Noel , Pineda-Martínez Luis Felipe , León-Cruz José Francisco
Published: February 2025

Evapotranspiration is a vital component of the hydrological cycle, returning approximately 65% of precipitated water to the atmosphere, influenced by soil characteristics and vegetation cover. Understanding its spatial and temporal distribution is essential for grasping climatic phenomena, cloud formation, and the impacts of various land uses. This study analyzed the spatiotemporal variation of evapotranspiration (ET) and its relationships with precipitation (P), temperature (T), and the Enhanced Vegetation Index (EVI) in southeastern Mexico and northern Central America over 20 years (2002–2021). Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor were used to analyze ET and EVI, complemented by gridded climate data for P and T. The study considered subregions characterized by distinct vegetation types, including tropical evergreen forests, tropical dry forests, pine-oak forests, and grasslands. The results indicate that the T trend is a significant driver of increasing ET in the region. Although the P variation did not show a significant trend, decreases in precipitation were negatively correlated with both EVI and ET. A subregional analysis revealed that tropical evergreen forests exhibited the highest ET values, peaking in February and July. Mixed oak-pine forests reached their maximum ET from May to September, while tropical dry forests showed clear seasonality, with peaks from June to September and minima from December to April. This seasonality is closely linked to the annual plant growth cycle and interannual and seasonal precipitation patterns. These results highlight the complex interactions between climatic factors and evapotranspiration across different vegetation types.