bluuebunny/crossref_metadata_2025 huggingface dataset:
A lightweight hybrid model-based condition monitoring method for grinding wheels using acoustic emission signals
Authors: Xu Fan , Wu Jianwei , Hong Duo , Zhao Feng , Wu Junhui , Yan Jianguo , Hu Weifei
Published: November 2024

Various data-driven methods based on acoustic emission (AE) signals have been proposed to monitor and accurately identify the wear stages of the grinding wheel. However, extracting effectively generalized and discriminative features from AE signals remains a challenging task. This paper proposes a new lightweight hybrid deep learning model that combines enhanced convolution with enhanced vision transformer (ViT) to effectively address the above challenges. Specifically, the key contributions of this paper are three-fold: (1) A two-stage signal preprocessing mechanism based on variational mode decomposition and continuous wavelet transform is proposed to improve the signal-to-noise ratio and feature representation of the AE signals. (2) To prevent model overfitting, a new regularization strategy based on stabilizing sparse convolutional weights and a weight penalty mechanism is designed. This approach improves the hybrid mode’s capacity to extract generalized features. (3) To concentrate on capturing multi-scale discriminative features between different wear conditions, a parameter-efficient residual convolution module based on the dropout depthwise convolution is designed, which is utilized to reconstruct the encoder of the ViT. In particular, to improve the training efficiency of the model, a lightweight mechanism using a stage-stride decreasing strategy is used to compress the spatial dimensions of the feature maps in the attention mechanism. The ablation experiment demonstrates the rationality of the proposed model structure. Comparative experiments show that the proposed method achieves a diagnostic accuracy of 99.6% on the test set and outperforms other state-of-the-art deep learning methods.
Comparing attendance versus exam performance for topics within first year physics courses
Authors: Gladys M J , Dastoor P C
Published: November 2024

This paper revisits the relationship between lecture attendance and final exam performance of students attending first year Advanced Physics classes at The University of Newcastle. The results compare attendance to non-attendance for topics within the Advanced Physics courses and indicate that, on average, students attending lectures always score higher than students not attending with variations on the size of this effect depending on topic such that the gap is generally larger for topics not covered in secondary school. This correlation may indicate the importance for students to attend classes covering new material.
FLIP: a novel method for patient-specific dose quantification in circulating blood in large vessels during proton or photon external beam radiotherapy treatments
Authors: García-Cardosa Marina , Meiriño Rosa , Calvo Felipe A , Antolín Elena , Aguilar Borja , Vidorreta Marta , Cuevas Roberto , Barbés Benigno , Huesa-Berral Carlos , Azcona Juan Diego , Burguete Javier
Published: November 2024

Purpose. To provide a novel and personalized method (FLIP, FLow and Irradiation Personalized) using patient-specific circulating blood flows and individualized time-dependent irradiation distributions, to quantify the dose delivered to blood in large vessels during proton or photon external beam radiotherapy. Methods. Patient-specific data were obtained from ten cancer patients undergoing radiotherapy, including the blood velocity field in large vessels and the temporal irradiation scheme using photons or protons. The large vessels and the corresponding blood flow velocities are obtained from phase-contrast MRI sequences. The blood dose is obtained discretizing the fluid into individual blood particles (BPs). A Lagrangian approach was applied to simulate the BPs trajectories along the vascular velocity field flowlines. Beam delivery dynamics was obtained from beam delivery machine measurements. The whole IS is split into a sequence of successive IEs, each one with its constant dose rate, as well as its corresponding initial and final time. Calculating the dose rate and knowing the spatiotemporal distribution of BPs, the dose is computed by accumulating the energy received by each BP as the time-dependent irradiation beams take place during the treatment. Results. Blood dose volume histograms from proton therapy and photon radiotherapy patients were assessed. The irradiation times distribution is obtained for BPs in both modalities. Two dosimetric parameters are presented: (i) D
3%, representing the minimum dose received by the 3% of BPs receiving the highest doses, and (ii) V
0.5 Gy, denoting the blood volume percentage that has received at least 0.5 Gy. Conclusion. A novel methodology is proposed for quantifying the circulating blood dose along large vessels. This methodology involves the use of patient-specific vasculature, blood flow velocity field, and dose delivery dynamics recovered from the irradiation machine. Relevant parameters that affect the dose received, as the distance between large vessels and CTV, are identified.
Transport properties of high Mach number hypersonic air plasmas
Authors: Petrova Tzvetelina B , Petrov George M , Peñano Joseph R
Published: November 2024

The collisional and transport properties of hypersonic plasmas have been simulated by an air plasma chemistry model, which includes collisions with electrons, ions and neutral species, elastic scattering, vibrational relaxation and a transport model. Species and thermal fluxes at the surface of the vehicle have been investigated as a function of post-shock gas temperature and species sticking coefficient for a fixed altitude of 50 km. At temperatures below about 5000 K, the leading species are vibrationally excited nitrogen molecules, while at higher temperatures the atomic oxygen and nitrogen dominate. Large fluxes of oxygen atoms have been observed in the simulations, on the order of 1020 cm
−

2 s
−

1, which may lead to high rates of surface oxidation. Another subject of this study is temperature equilibration. For electrons, equilibration takes tens of microseconds, while the vibrational temperature equilibration time vary widely; from a few microseconds to hundreds of microseconds, depending on the gas temperature. Finally, the adiabatic parameter γ was calculated for post-shock gas temperatures 5000 K and 10 000 K and total gas density

1.2
×

10

17

c

m

−
3

. For post-shock gas temperature 5000 K, only a slight reduction of γ from the ideal gas value of γ = 1.4 is observed, while for 10 000 K it drops to γ ≅ 1.26, which has a considerable impact on plasma properties. It was further established that the vibrational kinetics plays a leading role. While a single excited vibrational level of the N2 molecule captures the salient properties of the plasma, a detailed vibration kinetics is required for high-fidelity simulations.
A computational approach to optimize the linearity in dual-gate InAlGaN/AlN/GaN HEMTs
Authors: Awasthi Shivansh , Hsu Heng-Tung , Tsao Yi-Fan , Chiu Ping-Hsun , Gupta Ankur
Published: November 2024

This paper investigates the effect of the proposed dual gate structures in enhancing the linearity of InAlGaN/AlN/GaN high-electron-mobility transistors (HEMTs) using TCAD analysis. Through the comprehensive analysis of the dual gate structure with the additional gate placed between the gate–source (DG-GS) and gate–drain (DG-GD) regions, the impact on the linearity performance has been compared with that of a standard single gate (SG) structure. The dual gate configuration exhibits a flatter and broader transconductance (g
m) profile than the SG configuration. The reduction in the third-order intermodulation levels is confirmed with the polynomial fitting method. The f
T/f
max of the DG-GS case is simulated to be 52/102 GHz, which shows that such configuration does not deteriorate the RF performance. Comprehensive simulations are carried out to study the device physics and assess the mechanism behind the linearity improvement. The large signal model has been developed to examine the large signal RF performance as well as linearity performance metrics. An improvement of 9.6 dB in the carrier-to-intermodulation (C/I) ratio and that of 2.4 degrees in the amplitude-to-phase modulation at 6 dB backoff from P
sat have been observed as compared to the SG configuration. Such characteristics have evidenced that the optimized dual-gate configuration with the second gate placed between the source and gate can effectively improve the linearity performance of the InAlGaN/AlN/GaN HEMT configurations.
Effects of simplicial centrality on robustness of higher-order multiplex world trade networks
Authors: Ren Zhuoming , Wang Wan , Weng Tongfeng , Du Wenli
Published: November 2024

World trade networks are exhaustively described by pairwise interactions, and overlook higher-order structure from the outcome of collective interactions at the level of groups of nodes like multilateral trade agreements. To address this limitation, we collect multiplex world trade networks, including the bilateral regional trade agreement network, which represents pairwise interactions; the multilateral regional trade agreement network, which naturally represents a higher-order network structure; and the import and export trade network, which represents pairwise interactions and additional complexities. The analysis of simplicial centrality, including degree, closeness, and subgraph at 0, 1, and 2-simplex levels, reveals that intra-level correlations are high, while inter-levels may exhibit significant disparities. Nodes with low centrality at higher-order levels could influence network robustness due to the diversity of interactions and higher-order dependencies. Simplicial centrality on robustness of multiplex world trade networks under random and targeted attacks reveals that the complex connectivity of higher-order levels renders them more vulnerable post-attack. An optimization strategy of the rebalancing of network centrality is proposed to enhance the robustness, and the simulation shows risks posed to central nodes are minimized and opportunities for peripheral nodes to partake in global trade are broadened.
Continuous-variable electromechanical quantum thermal transistors
Authors: Nie Wenjie , Xu Junxi , Zhan Huiya , Chen Aixi , Lan Yueheng
Published: November 2024

We present a scheme to realize quantum thermal transistor effects in a continuous-variable electromechanical system including two microwave cavities and one mechanical oscillator. The thermal noise fluxes between the quantum system and its baths are evaluated by quantum master equation. It is shown that the thermal noise flux at one microwave cavity as an emitter can be dissipated into the other as a collector by combining the heating Stokes and cooling anti-Stokes processes. The indirect energy transfers between the two microwave modes can be significantly amplified by small energy changes at the mechanical oscillator as the base. The extremely high amplification depends sensitively on the detunings of the two microwave modes, which provides a new tool for precision measurements. This study opens the door for constructing quantum thermal transistors using various continuous-variable systems and is well accessible based on current experimental techniques.
Entanglement polygon inequalities for a class of mixed states
Authors: Shi 石 Xian 现
Published: November 2024

The study on the entanglement polygon inequality of multipartite systems has attracted much attention. However, most of the results are on pure states. Here we consider the property for a class of mixed states, which are the reduced density matrices of generalized W-class states in multipartite higher dimensional systems. First we show the class of mixed states satisfies the entanglement polygon inequalities in terms of Tsallis-q entanglement, then we propose a class of tighter inequalities for mixed states in terms of Tsallis-q entanglement. At last, we get an inequality for the mixed states, which can be regarded as a relation for bipartite entanglement.
Database of ternary amorphous alloys based on machine learning
Authors: Gong 巩 Xuhe 旭菏 , Li 李 Ran 然 , Xiao 肖 Ruijuan 睿娟 , Zhang 张 Tao 涛 , Li 李 Hong 泓
Published: November 2024

The unique long-range disordered atomic arrangement inherent in amorphous materials endows them with a range of superior properties, rendering them highly promising for applications in catalysis, medicine, and battery technology, among other fields. Since not all materials can be synthesized into an amorphous structure, the composition design of amorphous materials holds significant importance. Machine learning offers a valuable alternative to traditional “trial-and-error” methods by predicting properties through experimental data, thus providing efficient guidance in material design. In this study, we develop a machine learning workflow to predict the critical casting diameter, glass transition temperature, and Young’s modulus for 45 ternary reported amorphous alloy systems. The predicted results have been organized into a database, enabling direct retrieval of predicted values based on compositional information. Furthermore, the applications of high glass forming ability region screening for specified system, multi-property target system screening and high glass forming ability region search through iteration are also demonstrated. By utilizing machine learning predictions, researchers can effectively narrow the experimental scope and expedite the exploration of compositions.
Pressure-induced structural transitions and metallization in ZrSe2
Authors: Gao 高 Yiping 一平 , Liu 刘 Chenchen 晨晨 , Tian 田 Can 灿 , Zhu 朱 Chengcheng 程程 , Huang 黄 Xiaoli 晓丽 , Cui 崔 Tian 田
Published: November 2024

High-pressure studies of two-dimensional materials have revealed numerous novel properties and physical mechanisms behind them. As a typical material of transition metal dichalcogenides (TMDs), ZrSe2 exhibits high carrier mobility, rich electronic states regulated by doping, and high potential in applications at ambient pressure. However, the properties of ZrSe2 under pressure are still not clear, especially for the structural and electrical properties. Here, we report the investigation of ZrSe2 under pressure up to 66.5 GPa by in-situ x-ray diffraction, Raman, electrical transport measurements, and first-principles calculations. Two structural phase transitions occur in ZrSe2 at 8.3 GPa and 31.5 GPa, from P-3m1 symmetry to P21/m symmetry, and finally transformed into a non-layer I4/mmm symmetry structure. Pressure-induced metallic transition is observed at around 19.4 GPa in phase II which aligns well with the results of the calculation. Our work will help to improve the understanding of the evolution of the structure and electrical transport properties of two-dimensional materials.
Improving performance of screening MM/PBSA in protein–ligand interactions via machine learning
Authors: Chen 陈 Yuan-Qiang 远强 , Xu 徐 Yao 耀 , Ma 马 Yu-Qiang 余强 , Ding 丁 Hong-Ming 泓铭
Published: November 2024

Accurately estimating protein–ligand binding free energy is crucial for drug design and biophysics, yet remains a challenging task. In this study, we applied the screening molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) method in combination with various machine learning techniques to compute the binding free energies of protein–ligand interactions. Our results demonstrate that machine learning outperforms direct screening MM/PBSA calculations in predicting protein–ligand binding free energies. Notably, the random forest (RF) method exhibited the best predictive performance, with a Pearson correlation coefficient (r
p) of 0.702 and a mean absolute error (MAE) of 1.379 kcal/mol. Furthermore, we analyzed feature importance rankings in the gradient boosting (GB), adaptive boosting (AdaBoost), and RF methods, and found that feature selection significantly impacted predictive performance. In particular, molecular weight (MW) and van der Waals (VDW) energies played a decisive role in the prediction. Overall, this study highlights the potential of combining machine learning methods with screening MM/PBSA for accurately predicting binding free energies in biosystems.
Estimating cognitive workload using a commercial in-ear EEG headset
Authors: Tremmel Christoph , Krusienski Dean J , schraefel mc
Published: November 2024

Objective. This study investigated the potential of estimating various mental workload levels during two different tasks using a commercial in-ear electroencephalography (EEG) system, the IDUN ‘Guardian’. Approach. Participants performed versions of two classical workload tasks: an n-back task and a mental arithmetic task. Both in-ear and conventional EEG data were simultaneously collected during these tasks. In an effort to facilitate a more comprehensive comparison, the complexity of the tasks was intentionally increased beyond typical levels. Special emphasis was also placed on understanding the significance of γ band activity in workload estimations. Therefore, each signal was analyzed across low frequency (1–35 Hz) and high frequency (1–100 Hz) ranges. Additionally, surrogate in-ear EEG measures, derived from the conventional EEG recordings, were extracted and examined. Main results. Workload estimation using in-ear EEG yielded statistically significant performance levels, surpassing chance levels with 44.1% for four classes and 68.4% for two classes in the n-back task and was better than a naive predictor for the mental arithmetic task. Conventional EEG exhibited significantly higher performance compared to in-ear EEG, achieving 80.3% and 92.9% accuracy for the respective tasks, along with lower error rates than the naive predictor. The developed surrogate measures achieved improved results, reaching accuracies of 57.5% and 85.5%, thus providing insights for enhancing future in-ear systems. Notably, most high frequency range signals outperformed their low frequency counterparts in terms of accuracy validating that high frequency γ band features can improve workload estimation. Significance. The application of EEG-based Brain–Computer Interfaces beyond laboratory settings is often hindered by practical limitations. In-ear EEG systems offer a promising solution to this problem, potentially enabling everyday use. This study evaluates the performance of a commercial in-ear headset and provides guidelines for increased effectiveness.
Multi-body dynamic assessment of vessel-floater accessibility for floating wind
Authors: Moreno Carlos Pérez , Lange Johannes , Snedker Thor , Bayati Ilmas
Published: November 2024

The floating wind industry faces several challenges in the road map to full maturity of commercial-scale floating projects. Accessing the floating offshore wind turbines poses larger risks due to the added degrees of freedom of the platform, with respect to bottom-fixed technology. When a vessel approaches, the platform’s motion leads to the introduction of multi-body dynamic effects. This work deals with the modeling of the vessel-platform dynamics for the VolturnUS-S 15MW platform and IEA15MW Reference Wind Turbine and a generic Crew Transfer Vessel (CTV) by means of performing a fully coupled assessment. The hydrodynamic properties are computed by solving the multi-body radiation-difraction problem. The inertial and hydrodynamic properties are included in an OrcaFlex model to perform a time-domain analysis under several sea states. A P-controller represents the helmsman pushing the vessel against the access point. The contact forces are modeled using a linear fender system to represent slip-and-stick events during the CTV’s push-on maneuver. The resulting relative motions are analyzed, and industry-typical limits are considered to quantify accessibility levels. The results show that peak wave period and wave heading play a major role in the accessibility scores.
Offshore wind project installations: an advanced approach for weather risk assessments
Authors: de la Torre-Castro L. , Behm L. , Kaczenski J. , Wiggert M.
Published: November 2024

This paper presents the development of a sequence-based simulation tool for the weather risk assessment of offshore work processes. The approach developed at the Fraunhofer Institute for Wind Energy Systems is the Advanced Weather Time Series Scheduling (Ad-WATSS) method. For statistical significance, this method combines hindcast weather time series of many years with the weather restrictions associated with offshore activities. The method is incorporated into the software tool COAST, where a project plan schedule is simulated by placing activities according to their operational limits, constraints and relationships, and minimum-required time for each operation. A scenario of an offshore wind installation project in the North Sea is used as reference test case for a weather risk assessment using the developed tool and ERA5 weather data. The assessment is then compared with the weather window statistics approach, based on the same weather data sets. The results from both approaches are analysed and compared on a project and task level detail. The results from the sequence-based simulations show that the method is able to capture the long-term variability and extreme events in weather conditions, making it a reliable tool for the simplification of the weather data-based planning, validation, and assessment of offshore projects.
Increasing revenues of offshore wind farms with co-located energy storage systems
Authors: Juhlin R , Eren E , Kloster E , Hoen MHJ‘t , Hörler M , Kharabe S , Buhagiar D
Published: November 2024

Co-located onshore and offshore energy storage systems exhibit the potential of diversifying and increasing revenue streams of offshore wind farms. However, these systems should be designed and sized considering the power generation profile, the route to market of these assets, i.e. power trading strategy, and dynamics of the various segments of the power market. In this study, the feasibility of deploying subsea hydro-pneumatic storage systems was investigated. It was seen that if a 50MW capacity system with a storage duration of 4 hours is deployed in an offshore wind farm of 1000MW capacity, the wind farm can potentially participate in the day-ahead and ancillary services markets more confidently from a risk perspective. The relatively higher volatility in these markets presents an opportunity to improve economics of these offshore wind projects as long as costs can be kept under control.
Transnational experience exchange between countries towards speeding up EU renewable transition: example of Norway-Croatia
Authors: Lučin Ivana , Čarija Zoran , Teja Kandukuri Surya , Schlanbusch Rune
Published: November 2024

The RePowerEU plan aims to increase wind energy capacity to 480 GW by 2030, with 300 GW coming from offshore wind farms, to achieve climate neutrality by 2050. Due to Croatia’s substantial dependence on nautical and coastal tourism, along with significant concerns regarding negative environmental impacts, the installation of offshore wind farms has not been previously considered. However, due to increased demand for renewables, the offshore energy potential resurfaced. The recent Action Plan for the Uptake of Offshore Renewable Energy Sources in Croatia (May 2023) estimated offshore wind potential at 25 GW and identified more than 29 000 km2 of area available for offshore renewables. Norway, with its extensive experience in offshore engineering and pioneering developments in offshore wind, is a suitable partner in joint innovation and a resource for tried and tested best practices. In this collaborative research, a review of relevant documents, research articles, and interviews with industry experts from both from Croatia and Norway was conducted to obtain a broader perspective of the implications of offshore development in Croatia. As an outcome of this preliminary research, the paper outlines the required evaluations in the Croatian context, in terms of the social, environmental, legislative, and technical aspects that are to be considered for large-scale integration of wind energy into the Croatian grid. It also identifies the necessary grid improvements to achieve a reliable and sustainable grid of the future.
Application of simplifying jacobian matrix and introducing iterative threshold to improve newton-raphson method in three-phase power flow calculation
Authors: Cui Jiadong , Wang Jiahui , Li Tengxiao , Zhao Ying , Pan Jianwei , Hua Yongzhu
Published: November 2024

With the expansion of the scale and complexity of the power system, traditional three-phase power flow calculation methods are facing dual challenges of computational efficiency and accuracy. Power flow calculation is a mathematical method for analyzing the power flow of an electrical system. And the Newton-Raphson (NR) method is an effective algorithm for solving nonlinear problems. However, updating the Jacobian matrix in the NR method can take a lot of time. Based on the asymmetry in three-phase power systems and the time-consuming nature of the NR method, an enhanced version of the NR method is proposed in this paper that improves the efficiency of power flow calculations by simplifying the Jacobian matrix and optimizing the iteration speed. Furthermore, in order to minimize the number of iterations in the NR method, it is proposed to use the PO method to determine the ideal iteration threshold.
Parameters determination of the photovoltaic cell model
Authors: Zhao Yiman , Liu Ping
Published: November 2024

The dual diode model of photovoltaic cells has high accuracy, but there are seven parameters to be sought. To improve the accuracy of photovoltaic cell models and facilitate parameters determination, a method for determining the parameters of a dual diode photovoltaic cell model is proposed based on the three state point data provided by photovoltaic cell manufacturers under standard testing conditions, using the maximum power point derivative method. By using the Simulink software, the photovoltaic cell model was simulated, and we can obtain that the maximum relative error of voltage of the model was 0.8139%, and the maximum relative error of power was 1.0537%, with significantly higher accuracy than the Rs
model and the Rp
model.
Load forecasting based on multi-core learning Support Vector Machine (SVM)
Authors: Si Junchen , Wang Yuanyuan , Guan Yongchang , Sun Yongjian , Zhang Shuangle , Zhang Zhishuai
Published: November 2024

The development of smart grids requires enhanced data integration, robust risk assessment, and dynamic response optimization. In this paper, a multi-core learning Support Vector Machine (SVM) model is presented to improve the accuracy and efficiency of load and photovoltaic output forecasting. The model leverages kernel function optimization and parallel computing frameworks to handle large-scale data efficiently. Additionally, a comprehensive risk assessment system is developed to quantify risks such as overvoltage, undervoltage, line overload, and load loss in distribution networks. An adaptive genetic algorithm-based risk control model is also proposed, optimized in two stages—day-ahead and intra-day—to achieve minimal comprehensive risk through real-time adjustments in distributed power output and electric vehicle charging strategies. Furthermore, an integrated virtual synchronous control online verification method for source-network-load-storage is introduced, enhancing system response speed and control accuracy. These innovations collectively provide a solid theoretical foundation and technical support for the efficient and safe operation of smart grids, addressing the increasing demands of modern energy systems.
Research on energy interactive operation optimization strategy of multi-energy network with integrated energy based on cooperative game
Authors: Wu Simin , Dou Zhenlan , Du Yang , Zhang Chunyan , Chen Hongtao , Guo Lingyu , Yang Zhongguang , Yu Hui
Published: November 2024

Integrated energy includes multi-energy networks such as electricity, gas, cold, and heat. Horizontal multi-energy coordination and vertical source network storage load interaction can effectively support large-scale new energy consumption. In this paper, a multi-energy flow model of the integrated energy multi-energy network is constructed, an optimization model of energy sharing and mutual benefit of the multi-energy network is established based on Nash negotiation, and then the model is solved to obtain the optimal distribution scheme of cooperation benefits. Finally, a numerical example is given to verify the proposed energy sharing and mutual benefit method. The results show that the total power generation cost of each park is reduced by 27%, and the profit distribution of each park is more reasonable.
Automated production of nerve repair constructs containing endothelial cell tube-like structures
Authors: Smith Poppy O , Huang Guanbingxue , Devries Kate , Nazhat Showan N , Phillips James B
Published: November 2024

Engineered neural tissue (EngNT) is a stabilised aligned cellular hydrogel that offers a potential alternative to the nerve autograft for the treatment of severe peripheral nerve injury. This work aimed to automate the production of EngNT, to improve the feasibility of scalable manufacture for clinical translation. Endothelial cells were used as the cellular component of the EngNT, with the formation of endothelial cell tube-like structures mimicking the polarised vascular structures formed early on in the natural regenerative process. Gel aspiration-ejection for the production of EngNT was automated by integrating a syringe pump with a robotic positioning system, using software coded in Python to control both devices. Having established the production method and tested mechanical properties, the EngNT containing human umbilical vein endothelial cells (EngNT-HUVEC) was characterised in terms of viability and alignment, compatibility with neurite outgrowth from rat dorsal root ganglion neurons and formation of endothelial cell networks in vitro. EngNT-HUVEC manufactured using the automated system contained viable and aligned endothelial cells, which developed into a network of multinucleated endothelial cell tube-like structures inside the constructs and an outer layer of endothelialisation. The EngNT-HUVEC constructs were made in various sizes within minutes. Constructs provided support and guidance to regenerating neurites in vitro. This work automated the formation of EngNT, facilitating high throughput manufacture at scale. The formation of endothelial cell tube-like structures within stabilised hydrogels provides an engineered tissue with potential for use in nerve repair.
Corrigendum: A study on the effects of hybrid (SIC- PSSA) nano sized reinforcement on mechanical and tribological behaviour of Al alloy-based metal matrix composite produced by ultrasonic assisted stir casting (2024 Mater. Res. Express 11 075010)
Authors: Tenali Nagaraju , Ganesan G , Ravindra Babu P
Published: November 2024

This study focuses on the effects of hybrid reinforcement consisting of nanosized particles of Palm Sprout Shell Ash (PSSA) and silicon carbide (SiC) on the mechanical and tribological properties of the Al-Cu-Mg alloy. Hybrid reinforced composites with different weight percentages of SiC and PSSA (0:0, 0:4, 1:3, 2:2, and 4:0 wt%) were prepared using the ultrasonic-assisted bottom-poured stir casting technique. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) were used to characterize the hybrid composite made of Al-Cu-Mg alloy. The optical and SEM microstructural analyses demonstrated an even distribution of SiC and PSSA nanosize reinforcements within the matrix. The EDS analysis revealed SiC and PSSA reinforcement particles in the composite. The mechanical properties (tensile, flexural, and impact strength) and wear properties (wear rate and coefficient of friction) of the composites and alloys were evaluated according to the ASTM standards. The hybrid reinforced composites outperformed the base alloy. Among all composites, the 2:2 wt% SIC and PSSA hybrid-reinforced composites exhibited a significant enhancement in both tensile and flexural strength, with a 22.64% and 27.64% increase in strength, respectively. However, the inclusion of these reinforcements led to a reduction in the ductility and impact strength of the Al-Cu-Mg alloy composite. The 0:4 wt% SiC- and PSSA-reinforced composites experienced the largest reductions in ductility and impact strength, with decreases of 47.67% and 4.38%, respectively. For the 2:2 wt% SiC and PSSA composites, these reductions were 23.64% and 3.19%, respectively. The SEM analysis of the fractured surfaces of the composites tested for mechanical properties revealed evidence of both ductile and brittle fracture mechanisms in the tensile, flexural, and impact tests. The wear behaviour of the prepared samples was evaluated, and all composites exhibited superior performance compared with the base alloy, demonstrating adhesive and abrasive wear mechanisms and varying friction coefficients. Among all the composites, the 2:2 wt% SiC- and PSSA-reinforced composites exhibited high wear resistance and a lower coefficient of friction than the other fabricated composites.
Investigation of laser sintering process parameters for anode foils in aluminium electrolytic capacitors considering temperature distribution
Authors: Zhang Qianqian , Cao Li
Published: November 2024

The anode foil is a critical component of aluminium electrolytic capacitors, with its performance directly impacting the overall quality of the capacitors. Currently, sintered anode foil with excellent bending resistance and high specific capacitance is considered an ideal material for capacitor manufacturing; however, research on its optimal sintering parameters remains insufficient. In this study, a three-dimensional temperature field model is developed within the Comsol Multiphysics (6.0) environment, accounting for the temperature dependence of aluminium. By varying laser power and scanning speed, the temperature distribution along the laser scanning trajectory is determined, facilitating the identification of optimal process parameters for laser sintering anode foils in electrolytic capacitors. Subsequent laser sintering experiments validate the accuracy of these parameters. The findings indicate that the peak temperature of the molten pool rises with increased laser power and decreased scanning speed. The optimal process parameters for laser sintering anode foils in electrolytic capacitors are a powder layer thickness of 50 μm, a laser power of 140 W, and a scanning speed of 0.05 m s−1. The specific capacitance of laser-sintered anode foil, formed at voltages of 375 V and 520 V, ranges from 0.847 to 1.157 μF cm−2 and 0.717 to 0.935 μF cm−2, respectively, when the particle size is between 3 and 4 μm. A specific capacitance of 0.733 μF cm−2 can be achieved, which meets the performance requirements for aluminium electrolytic capacitors.
Annealing temperature-dependent microstructure, mechanical, and tribological properties of intercritically heat-treated dual-phase steel
Authors: Çiftçi Yusuf Sefa , Aygün Zeynep , Gecü Rıdvan
Published: November 2024

This study investigates the role of intercritical annealing temperature on microstructural characteristics, mechanical performance, and wear resistance of DP1000 steel. As-received DP1000 steel samples in cold-rolled conditions were subjected to intercritical annealing between 730 and 880 °C with an interval of 30 °C, followed by water quenching. After heat treatment, the specimens were characterized by x-ray diffraction (XRD), scanning electron microscopy (SEM), mechanical tests consisting of hardness, impact, and tensile tests, and dry sliding wear tests. The findings revealed that equiaxed ferrite grains replaced elongated ones, and the martensite ratio increased from 21% up to 64% with increasing annealing temperature. Due to the formation of equiaxed grains, the impact strength was at least doubled for each specimen by heat treatment, reaching a peak value (9.55 J cm−2) at 760 °C. The hardness (311 HB) and tensile strength (1007 MPa) of the as-received sample were higher than that of the annealed steels up to 820 °C. The mechanical strength of the samples improved at 850 and 880 °C by approximately 10%, and accordingly, the lowest wear rate was obtained at the specimen annealed at 850 °C. The increase in temperature up to 880 °C caused a decrease in wear resistance due to excessive brittleness.
The effect of cryogenic treatment on a high Co bearing DIN 1.2888 steel used as die in hot forging process
Authors: Kiraz Caner , Birol Burak , Sağın Ahmet
Published: November 2024

Die steels used in metal forming processes require resilience in harsh conditions. Therefore, it becomes crucial to convert retained austenite into martensite and uniformly distribute fine carbide phases in these steels. Cobalt is known for its ability to enhance carbide formation in tool steels. In the present work, DIN 1.2888, a hot work tool steel characterized by high cobalt content, was subjected to the conventional HT and CT processes at −100, −140, and −180 °C for 6 h, then double-tempered. The properties of samples were investigated by XRD, SEM-EDS, and Microhardness analyses. The wear mechanism was investigated by a pin-on-disc wear testing device and the impact toughness of the samples was examined both at room temperature and the working temperature of the dies (350 °C). It was observed that decrease of the cryogenic treatment temperature resulted with a slight change on the hardness values of the samples from 507 HV to 529 HV, while impact toughness increased from 12.35 J to 23.44 J at 350 °C. Also, the wear rates of the samples exhibited a ∼50% decrease. It can be deduced that cryogenic treatment had positive effect on the properties of steel, depending on the retained austenite decrement and homogenous fine carbide density increment with the decreasing cryogenic treatment temperature.
Photocatalytic synthesis of chromeno[4,3-b]chromenes, serving as potential drugs in oral cavity and dentistry mediated by TiO2/Ag2WO4
Authors: Ma Ning , Liu Hongwei , Zhang Chunyan , Lv Pengfei , Zhang Juan
Published: November 2024

This research focused on a newly developed heterojunction nanocomposite, TiO2/Ag2WO4, which combines titanium dioxide (TiO2) and silver tungstate(VI) (TiO2/Ag2WO4) to enhance the photocatalytic performance. The TiO2/Ag2WO4 photocatalyst was characterized using FT-IR, XRD, DRS, PL, SEM, EDS, and XPS. TiO2/Ag2WO4 proved to be an effective nanophotocatalyst for synthesizing chromeno[4,3-b]chromene derivatives, which exhibit potential antibacterial and antifungal properties relevant to oral health issues like dental caries and periodontal disease. TiO2 can absorb light to generate electrons and holes when exposed to direct light; however, combining it with Ag2WO4 enhances its photocatalytic activity. The study also examined the effects of various factors such as the amount of photocatalyst, reaction time, temperature, solvent choice, and the reusability of the nanocomposite. The best reaction condition involves 1 mmol of dimedone, benzaldehyde, and 4-hydroxycoumarin in the presence of 15 mg TiO2/Ag2WO4 in 3 ml ethanol under irradiation of a green laser at room temperature for 60 min. Findings of this investigation show that TiO2/Ag2WO4 heterojunction is one of the best among the similar introduced counterparts in photocatalytic synthesis of chromeno[4,3-b]chromene derivatives.
On the degree of uniformity measure for probability distributions
Authors: Rajaram R , Ritchey N , Castellani B
Published: November 2024

A key challenge in studying probability distributions is quantifying the inherent inequality within them. Certain parts of the distribution have higher probabilities than others, and our goal is to measure this inequality using the concept of mathematical diversity, a novel approach to examining inequality. We introduce a new measure m

D
(P), called the degree of uniformity measure on a given probability space that generalizes the idea of the slope of secant of the slope of diversity curve. This measure generalizes the idea of degree of uniformity of a contiguous part (P = {k
1, k
2} in the discrete case or P = (a, b) in the continuous case) in a probability space related to a random variable X, to an arbitrary measurable part P. We also demonstrate the truly scale free and self-contained nature of the concept of degree of uniformity by relating the measure of two parts P
1 and P
2 from completely unrelated distributions with random variables X
1 and X
2 that have completely different scales of variation.
Tribological effects of varying volumetric energy density in additive manufacturing of inconel 718
Authors: Paramasivam Premkumar , Natesan Sathishkumar , Antony Sebastian Ruskin Bruce , Vijayakumar Sriiram
Published: November 2024

This study investigates the novel effects of varying volumetric energy density (VED) ratios on the tribological characteristics of Inconel 718 alloy fabricated using Laser Powder Bed Fusion (LPBF) process. Nine VED ratios were investigated, and samples underwent non-contact surface roughness tests, Vickers microhardness tests, and residual stress analysis. Notably, this study identified specific VED conditions where superior wear resistance was achieved, contributing new insights into optimizing LPBF parameters for tribological performance. Based on preliminary analysis, samples 1, 3, and 8 were selected for ball-on-disc wear testing. Sample 8, fabricated with 330 W laser power, 50 mm s−1 scan speed, 0.10 mm hatch spacing, and 0.05 mm layer thickness, demonstrated superior tribological behaviour with a 32.12% and 52.11% lower friction coefficient and 31% and 29.92% less mass loss compared to samples 1 and 3, respectively. The presence of γ-Ni, γ′-Ni3 (Al, Ti), γ-FCC, and γ′-L12 phases, along with microstructural features such as columnar and cellular dendritic structures, were confirmed via SEM and x-ray diffraction analyses. This study’s novel findings contribute valuable knowledge for optimizing Inconel 718 production via LPBF, particularly in enhancing wear resistance through tailored VED settings.
Design and research of high voltage β-Ga2O3/4H-SiC heterojunction LDMOS
Authors: Bian Daqing , Luan Suzhen
Published: November 2024

In recent years, gallium oxide (Ga2O3), one of the ultra-wide band-gap semiconductor materials, has been regarded as one of the most promising materials in the field of high-voltage and high-power electronic devices in the future because of its unique electrical properties and low preparation cost. However, it is difficult for β-Ga2O3 materials to form effective P-type doping, so the PN junction is not formed in most of its power devices, which greatly limits the improvement of its voltage resistance. A novel lateral double-diffused metal-oxide-semiconductor field-effect transistor (LDMOS) is proposed to realize a junction β-Ga2O3 power device and improve the voltage resistance performance of β-Ga2O3 power devices. In this device, a β-Ga2O3 power device with a junction is realized by using P-type 4H-SiC to form a PN junction with N-type β-Ga2O3, and the voltage resistance of the β-Ga2O3 power device is improved. Sentaurus TCAD software was used to simulate the device structure and electrical performance. The device is optimized by adjusting the length of the drift zone, drift zone concentration, SiC channel concentration, and gate oxide thickness. Optimized, the device exhibits a positive threshold voltage of 3.42 V, a breakdown voltage of 2203 V, a specific on-resistance of 7.80 mΩ·cm2, and a power figure of merit of 622 MW cm−2. The results show that the heterojunction device is significant for realizing high-performance junction β-Ga2O3 power devices.
Accelerating graph-based tracking tasks with symbolic regression
Authors: Soybelman Nathalie , Schiavi Carlo , Di Bello Francesco A , Gross Eilam
Published: November 2024

The reconstruction of particle tracks from hits in tracking detectors is a computationally intensive task due to the large combinatorics of detector signals. Recent efforts have proven that ML techniques can be successfully applied to the tracking problem, extending and improving the conventional methods based on feature engineering. However, complex models can be challenging to implement on heterogeneous trigger systems, integrating architectures such as field programmable gate arrays (FPGAs). Deploying the network on an FPGA is feasible but challenging and limited by its resources. An efficient alternative can employ symbolic regression (SR). We propose a novel approach that uses SR to replace a graph-based neural network. Substituting each network block with a symbolic function preserves the graph structure of the data and enables message passing. The technique is perfectly suitable for heterogeneous hardware, as it can be implemented more easily on FPGAs and grants faster execution times on CPU with respect to conventional methods. While the tracking problem is the target for this work, it also provides a proof-of-principle for the method that can be applied to many use cases.
Divine Power
Authors: Ballesteros Bernardo
Published: November 2024

The chapter continues the discussion of divine rulership by offering a close reading of the Babylonian flood epic Atra-ḫasīs (§1) and starting to compare notions of divine power in Mesopotamian and early Greek epic (§2). Atra-ḫasīs narrates the earliest history of humankind from its creation. In the poem, kingship among the Babylonian gods displays its fundamental characteristics paradigmatically, particularly its being an office distinct from the person of the ruler, and its being in constant need of correction. The chapter connects these features to Sumero-Akkadian conceptions of ‘divine powers/offices’ (me/parṣū). In so doing, it integrates the results of the previous investigation of Chaoskampf and other Mesopotamian narratives while also establishing parameters for a broader comparison involving Greek notions of ‘divine powers/honours’ (timai). The Greek emphasis on the inextricable link between Zeus’ faculty to rule (timē) and his person helps us contrast Babylonian and early Greek epic ideas about divine rulership.
The urbanization of conflict? Patterns of armed conflict and protest in Africa
Authors: Dorward Nick
Published: November 2024

Is the geography of armed conflict in Africa becoming more urban? To answer this question, I link georeferenced data on the timing and location of armed conflict and protest events to continent-wide geospatial data on human settlement patterns. Comparing rates of conflict and contention in rural versus urban areas over time, I argue that, contrary to conventional wisdom, claims surrounding the ‘urbanization of conflict’ in Africa are premature. I find that the urbanization of conflict hypothesis only holds in North Africa, where armed conflict and protest are both increasingly urban phenomenon. In contrast, while the frequency of urban protest in sub-Saharan Africa has also increased substantially, conventional armed conflicts in rural areas have also risen over the same period. My study provides a quantitative summary of key patterns and trends in protest and conflict in Africa contributing to ongoing debates surrounding the frequency and character of violent and non-violent political contests on the continent.