bluuebunny/crossref_metadata_2025 huggingface dataset:
A magnetic analog of pressure–strain interaction
Authors: Barbhuiya M. Hasan , Cassak P. A.
Published: December 2024

We study the evolution equation for magnetic energy density for a non-relativistic magnetized plasma in the (Lagrangian) reference frame comoving with the electron bulk velocity. Analyzing the terms that arise due to the ideal electric field, namely, perpendicular electron compression and magnetic field line bending, we recast them to reveal a quantity with a functional form analogous to the often-studied pressure–strain interaction term that describes one piece of internal energy density evolution of the species in a plasma, except with the species pressure tensor replaced by the magnetic stress tensor. We dub it the “magnetic stress–strain interaction.” We discuss decompositions of the magnetic stress–strain interaction analogous to those used for pressure–strain interaction. These analogies facilitate the interpretation of the evolution of the various forms of energy in magnetized plasmas and should be useful for a wide array of applications, including magnetic reconnection, turbulence, collisionless shocks, and wave–particle interactions. We display and analyze all the terms that can change magnetic energy density in the Lagrangian reference frame of the electrons using a particle-in-cell simulation of magnetic reconnection.
Strong texturing and van der Waals transferability of Mo/Al0.65Sc0.35N/Mo films on 2D-MoS2 monolayers
Authors: Kim Jun-young , Tong Shi Wun , Chen Mingxi , Zhang Mingsheng , Lim Poh Chong , Chai Jianwei , Teo Siew Lang , Lin Ming , Chi Dongzhi
Published: December 2024

Van der Waals epitaxy and transfer of functional layers are crucial technologies for achieving monolithic 3D integration in advanced electronics. Two-dimensional transition metal dichalcogenides, such as 2D-MoS2, exhibit strong growth texturing effects and excellent van der Waals transferability for metal and semiconductor layers deposited on top of them. In this study, we demonstrate strong texturing and layer transferability of piezoelectric Al0.65Sc0.35N layers when utilizing Mo seed layers on 2D-MoS2. With the presence of 2D-MoS2, we achieve textured growth of Al0.65Sc0.35N layers with thinner seed layers and lower piezoelectric thicknesses. Furthermore, these deposited stacks can be easily peeled off from their growth substrates through conventional layer transfer techniques, making them highly suitable for vertical integration of functional layers.
Influence of intrinsic defects in CdTe and CdZnTe on the microstructure, magnetic, and optical properties of the system
Authors: Wei Wenjing , Jin Weiliang , Luo Jieqiong , Lv Liangliang , Li Gongping
Published: December 2024

Intrinsic defects can have an effect on the microstructure of semiconductor materials, which can change the electronic structure of the material and ultimately alter its optical and magnetic properties. In this study, first-principles calculations are performed to demonstrate that the defect formation energies of VTe and ZnCd + VTe are lower under Cd-rich conditions. Conversely, under Te-rich conditions, with the exception of Tei, the defect formation energies for TeCd, VCd, ZnCd + TeCd, and ZnCd + VCd are lower, indicating that these defects exhibit greater stability within the system. Furthermore, it is demonstrated that VCd, CdTe, and TeCd introduce magnetic moments into the CdTe system, with VCd contributing the largest magnetic moment. Additionally, composite defects formed by ZnCd and VCd, CdTe, and TeCd also induce spin polarization and introduce magnetic moments. However, the synergistic effect of ZnCd on CdTe defects is significant, reducing the magnetic moment introduced by the CdTe defects. Moreover, ZnCd + VTe composite defects, VTe + VCd composite defects, and VTe, Cdi, and Tei do not introduce magnetic moments into the system. For the CdTe and ZnCd + CdTe defect systems, there is a notable impact on the optical properties, such as the refractive index and reflectance, compared to the perfect CdTe system. When CdTe defects are present, defect energy levels are introduced within the bandgap, affecting electronic transitions between energy bands, which, in turn, influences the magnetic and optical properties of the system. Additionally, it is found that the optical properties of CdTe systems containing intrinsic or composite defects are isotropic, exhibiting weak absorption in the visible light range. However, VTe and TeCd defects can enhance the absorption of visible light to some extent.
The ultralow thermal conductivity of Cs2SnI6 by filling interstitial voids with Mg2+ ions
Authors: Xiao Xianfeng , Liang Ziqi , Yao Qin , Chen Lidong
Published: December 2024

Metal halide perovskites (MHPs) have received considerable attention due to their intrinsically disordered structures, leading to abnormally low thermal conductivity, which is beneficial for energy harvesting applications. Compared with organic–inorganic hybrid MHPs, all inorganic MHPs exhibit better thermal stability, but thermal conductivity is relatively high, about twice that of hybrid MHPs. In this study, we investigate an all-inorganic vacancy-ordered double perovskite, Cs2SnI6, characterized by a cage-like structure with an octahedral interstitial radius of approximately 1.638 Å, allowing for the accommodation of various metal ions. We successfully introduced Mg2+ ions as guest fillers into the octahedral interstices of Cs2SnI6. The weak ionic bonds formed by Mg2+ in these oversized interstices induce vibrations that enhance atomic disorder and anharmonicity within the structure. As a result, we achieved an exceptionally low thermal conductivity of κ = 0.11 W m−1 K−1 at room temperature in Mg0.102Cs2SnI6, representing a 21% reduction compared to the undoped sample and marking one of the lowest values reported for MHPs. This research offers a novel approach to effectively regulate disorder and significantly reduce the thermal conductivity of all-inorganic MHPs.
Optical study of valence band splitting and resonant acceptor states in Cu2GeS3 microcrystals
Authors: Krustok Jüri , Kaupmees Reelika , Kokla Joel , Kauk-Kuusik Marit
Published: December 2024

Single microcrystals of Cu2GeS3 (CGS) were grown in molten LiI salt. According to x-ray diffraction measurements, all of the samples were made up entirely of CGS crystals. Raman spectra and photoluminescence (PL) at room temperature revealed two different types of crystals. Type A crystals displayed an asymmetric PL band at about 1.57 eV, while type B crystals displayed extra bands at 1.673, 1.587, and 1.474 eV. Raman spectra of both types were also different. The existence of two band-to-band recombinations, connected to split valence bands V1 and V2, is one explanation for the shape of the type B PL spectrum. It was discovered that the spin–orbit splitting energy was 0.11 eV. PL bands at 1.474 and 1.587 eV were related to acceptor levels coupled with V1 and V2 valence bands, respectively. For the V2 valence band, the depth of the resonant acceptor state was 0.09 eV. The acceptor level linked to the V1 valence band was also found to have the same value. To measure external quantum efficiency (EQE) spectra, monograin solar cells made from our microcrystals were used. The derivative of the EQE spectrum results in two distinct peaks, split by 0.11 eV. The inflection point minima are at 1.62 and 1.73 eV. We propose a model for various energy levels based on these findings.
Analysis of atomization characteristics in submerged top-blowing with a swirling spray lance
Authors: Zhao Yutang , Zhang Xiaohui , Fan Xiaofeng , Wang Hua
Published: December 2024

To investigate the atomization characteristics of the submerged top blow of the swirling spray lance, a corresponding spray lance model is established using hydrodynamic calculation methods, and the independence and accuracy of the model are verified. The calculation results show that during the atomization process of the swirling lance submerged injection, the penetration of the oil droplets first increases and then stabilizes over time. The oil droplets undergo secondary fragmentation near the gas–liquid interface, and the total Sauter mean diameter of the oil droplets rapidly decreases after approximately 0.004 s of injection, eventually stabilizing. Additionally, the larger the oil load, the larger the mean Sauter diameter of the captured oil droplets, leading to a higher total Sauter diameter. Furthermore, as the atomization temperature increases, the Sauter mean diameter of the captured oil droplets on the capture surface decreases. The results show that the rotary lance can effectively improve the atomization characteristics of submerged blowing, which is conducive to improving the melting quality, melting efficiency, and fuel utilization.
Slickwater residues in shale multi-scale pore structures
Authors: Li Jun , Ning Zhengfu , Li Qiang , Huang Qiming
Published: December 2024

Slickwater fracturing can significantly enhance shale gas production. However, following fracturing operations, a portion of the slickwater will inevitably remain in the reservoir, thereby altering the pore structure of the shale reservoir and impacting shale gas output. By slickwater, we mean a fluid mixture composed of water, friction reducers, and various additives, typically used in hydraulic fracturing to facilitate the creation of fractures in the reservoir. This study focuses on investigating the influence of slickwater on the multi-scale pore structure of shale reservoirs through various experimental techniques, including high-pressure mercury intrusion, low-temperature nitrogen adsorption, and low-temperature carbon dioxide adsorption experiments. The findings reveal that under pressure, slickwater infiltrates shale pores, with higher concentrations accumulating in macropores and mesopores. Additionally, increased pressure or slickwater concentration exacerbates damage to the pore structure. Fractal analysis further demonstrates that slickwater obstructs the pore structure and diminishes the complexity of the pore network, while adhering to rough surfaces to reduce shale surface roughness. Consequently, slickwater trapped in shale obstructs shale gas diffusion and thus reduces shale gas production.
A direct reconstruction method for radiating sources in Maxwell’s equations with single-frequency data
Authors: Harris Isaac , Le Thu , Nguyen Dinh-Liem
Published: December 2024

This paper presents a fast and robust numerical method for reconstructing point-like sources in the time-harmonic Maxwell’s equations given Cauchy data at a fixed frequency. This is an electromagnetic inverse source problem with broad applications, such as antenna synthesis and design, medical imaging, and pollution source tracing. We introduce new imaging functions and a computational algorithm to determine the number of point sources, their locations, and associated moment vectors, even when these vectors have notably different magnitudes. The number of sources and locations are estimated using significant peaks of the imaging functions, and the moment vectors are computed via explicitly simple formulas. The theoretical analysis and stability of the imaging functions are investigated, where the main challenge lies in analyzing the behavior of the dot products between the columns of the imaginary part of the Green’s tensor and the unknown moment vectors. Additionally, we extend our method to reconstruct small-volume sources using an asymptotic expansion of their radiated electric field. We provide numerical examples in three dimensions to demonstrate the performance of our method.
Micro-target localization algorithm based on improved local contour extraction and feature point matching
Authors: Li Dongjie , Guo Xuening , Zhang Fuyue , Rong Weibin , Yang Liu , Zhang Yu , Liang Yu
Published: December 2024

Images at the micrometer level usually have high resolution and contain a large amount of detailed information, and traditional vision algorithms are designed for macroscopic images, making it difficult to achieve accurate target localization at the microscopic scale. In this paper, we propose a micro-target localization algorithm based on improved local contour extraction and feature point matching to address the problems of low accuracy and time-consuming operation point localization under microscopic vision due to uneven illumination, angular shift of micro-targets, and occlusion. In the horizontal perspective, a light source correction algorithm based on the morphological algorithm and an edge enhancement algorithm based on Fourier transform is proposed to improve the accuracy of threshold segmentation and edge extraction, and a contour feature extraction algorithm based on Normalized Cross-Correlation template matching and improved Otsu’s thresholding method is utilized to achieve high-precision localization of multi-targets in micro-scale. In the vertical perspective, a Binary Robust Invariant Scalable Keypoints matching algorithm based on spatial feature screening is proposed to solve the problems of feature point mismatch and inaccurate localization of traditional algorithms in case of angular offset and occlusion of micro-targets. Finally, experiments were conducted on the microscopic vision operating system and experimentally compared with cutting-edge methods to verify the feasibility and superiority of the present method. The experimental results show that the proposed algorithm in this paper has an average error of 1.023 pixels and an average elapsed time of 109.08 ms, exhibits higher stability in the presence of light source interference, angular offset, and occlusion of micro-targets, and significantly improves both localization accuracy and efficiency.
Automatic meter reading via simulated water meter wheel rotation data generation
Authors: Zhao Qianhui , Zhu Guanhua , Huang Quansi
Published: December 2024

With the rapid development of smart cities, automated meter reading (AMR) technology, as a crucial part of the infrastructure, has garnered widespread attention. This paper addresses the issues of data insufficiency and imbalanced sample distribution in AMR technology by constructing a simulated water meter digit generator that automatically generates water meter data images and their corresponding label files. Furthermore, to tackle the challenge of semi-character recognition, the model’s learning capability is enhanced by increasing the semi-character data samples and introducing auxiliary features. Finally, a counting area extraction method that combines object detection algorithms with perspective transformation techniques is introduced into the existing AMR framework, effectively resolving problems related to image skew correction and perspective distortion. Experimental results demonstrate that, compared to the original dataset, training with the enhanced dataset proposed in this paper significantly improves the model’s performance in recognizing water meter digits, particularly showing advantages in semi-character recognition, thereby providing new insights and solutions for the development of AMR technology.
Optimization of the design of a single-sided magnetic resonance magnet array for improved T2 estimation accuracy
Authors: Miao Ruixin , Ren Chunpeng , Jiang Chuandong , Wang Qingyue , Wang Yunzhi , Yu Xiangqian
Published: December 2024

Single-sided magnetic resonance (SSMR) technology has a compact structure and great potential for use in mobile and nondestructive detection of large aqueous materials. As the detection depth increases, the magnetic field gradient generated by the magnetic resonance magnet placed on one side weakens, leading to a large distortion of T
2, thereby significantly impeding accurate estimation of the pore size distribution within the detection target. In this study, to address this problem, the distortion in the region of interest (ROI) is significantly reduced by optimizing the size and arrangement of the SSMR magnet array. First, to evaluate the T
2 distortion within the ROI, we developed a T
2 distortion loss function based on α and θ, which are key parameters of the spin echo (SE) signal. We then combined the nonlinear constraints with the loss function to form a Lagrangian function, which was solved via the Newton iteration method to obtain the magnet array parameters. The magnet array is called the AT magnet array. The T
2 distortion was quantitatively evaluated by calculating the SE signal generated by the AT magnet array in the ROI. Furthermore, we compared the detection results obtained with the AT and the semi-annular (SA) magnet array. The results showed that within the 3 cm × 3 cm target range of a 10 cm depth, the AT magnet array had a smaller T
2 distortion of only 1.3%. After the ROI was expanded to 5 cm × 5 cm, the T
2 distortion of the SE signal measured by the AT magnet array was 6%, which met the SSMR detection accuracy requirements in this range. Therefore, the optimized design of the magnet array based on α and θ provides a theoretical basis for obtaining SE signals with low T
2 distortion at large depths and over large areas via SSMR.
A rapid identification technique for rice adulteration based on improved YOLOV8 model
Authors: Zhang Yuan , Xing Xiao , Zhu Lei , Li Xin , Wang JiaNing , Du YanPing , Han Rui
Published: December 2024

Rice classification and quality testing are essential to ensure its safety and quality, and can effectively reduce food economic losses associated with rice, which is currently the subject of repeated reports of rice adulteration. For this reason, according to the experimental requirements, we selected the smallest and lightest version of YOLOv8n in the YOLOv8 series, and optimised and proposed the lightweight and efficient Faster-YOLO algorithm, which is more suitable for rice adulteration classification and recognition tasks, on the basis of the YOLOv8n algorithm. Firstly, this paper introduces the Group Convolutional Hybrid Attention Mechanism, which combines channel information and spatial information, and embeds it in the last layer of the Backbone network, which enhances the feature representation capability of the model by focusing on the key information to suppress the noise. Secondly, the C2F module in the Backbone part adopts the design of combining Faster and C2F to enhance the feature fusion capability and reduce the number of parameters and computational complexity of the model. Finally, the collected data are augmented with multiple aspects to simulate different environments and compared with multiple attention mechanisms and deep learning models. The experimental results show that the method proposed in this paper is superior in classification and recognition performance, with recognition accuracy of 93.4%, precision of 96.5%, recall of 96%, and F1 score of 96.2%. In this paper, the accuracy is improved by 1.1%, 2.4%, 6.9%, 7.5%, 13.1%, 7.9%, 7.1%, and 7.1% compared to yolov8n, yolo11, yolov5, EfficientNetV2, MobileNetV3, Restnet18, and VGG19 image classification methods, respectively. It is demonstrated that Faster-YOLO provides a strong basis for the rapid identification of rice adulteration by reducing the weight of the model while improving the detection and identification capabilities.
Nonlinear sliding mode control of flying wing aircraft under wind disturbance
Authors: Song Yuecheng , Zhao Wen , Liu Zhenbao , Han Junwei , Dang Qingqing
Published: December 2024

For flying wing aircraft, stabilization has always played a key role, and many studies have focused on stabilization. One major problem is anti-wind disturbance performance. However, few studies have been conducted on this topic. In this paper, a modified nonlinear control strategy is introduced. First of all, the aircraft is modeled in a nonlinear form, and a modified sliding surface is applied. Then, a recurrent neural network is introduced to mitigate the wind affection in different flight situations. Finally, the simulation is applied to prove the effectiveness of the proposed method. The simulation clearly shows that the proposed method works well in a large range of windy environments and flying states, indicating that the proposed method is effective for flying wings in windy environments.
MBE-YOLOv8: enhancing building crack detection with an advanced YOLOv8 framework
Authors: Zhang Zhen , Hu Zhibo , Chen Kexin , Zhou Qi , Zhang Hongxia
Published: December 2024

Buildings, over prolonged periods, are susceptible to developing various types of cracks, which are often small and exhibit low contrast, leading to challenges in accurate detection. Missed detections and false positives due to these characteristics can result in delayed repairs, thereby compromising structural integrity and safety. Therefore, real-time detection of building cracks is essential to maintain the longevity and safety of infrastructures. In response to these challenges, we present an optimized version of the YOLOv8 model, referred to as MBE-YOLOv8, designed specifically for building crack detection. The core enhancement involves restructuring the backbone of YOLOv8 with the integration of the multi-dimensional collaborative attention mechanism, significantly improving feature interrelationships and the extraction capabilities of the backbone network. Additionally, we introduced a Weighted Feature Fusion Network (BiFPN) and developed a novel BiFPN-L structure to enhance feature fusion and detection accuracy, particularly for small targets. The efficient channel attention (ECA) mechanism was also incorporated into the model’s neck, leading to the design of a new EC2f structure that improves the model’s adaptability to scale variations and overall feature extraction efficiency. A comparative analysis with the original YOLOv8 model demonstrated that MBE-YOLOv8 achieved performance improvements with P, R, and mAP@0.5 values of 78.6%, 67.0%, and 73.4%, respectively. These figures represent increases of 4.8, 3.8, and 4.1 percentage points compared to the previous version of the YOLOv8 model. This advancement has significantly bolstered the capability to detect cracks in buildings. Furthermore, the enhanced model preserves a compact size of 3.0 M while sustaining a high frame rate (FPS), rendering it highly deployable for applications related to crack detection.
Deep adaptively dynamic edge graph convolution network with attention weight and high-dimension affinity feature graph for rotating machinery fault diagnosis
Authors: Jiang Zhichao , Liu Dongdong , Cui Lingli
Published: December 2024

The graph neural network (GNN) has emerged as an effective way to mine relationships between data due to its powerful modeling capability for graph structure data, and it has garnered significant attention from researchers for intelligent fault diagnosis tasks. However, the adjacency matrix of most GNN models with deep architecture is always fixed during the aggregation process, and the edge connection relationship cannot be adaptively adjusted, which limits their performance for feature representation. Moreover, for few-shot diagnosis scenarios, the generalization performance of deep GNN models will be further degraded due to fixed receptive fields and limited training samples. To address these issues, a deep adaptively dynamic edge graph convolution network (DADE-GCN) with attention weight and a high-dimension affinity feature graph is proposed. First, a deep adaptively dynamic edge graph convolutional module with attention weight (DADE-GCNWAW) is developed to dynamically adjust the receptive field in different graph convolution layers. Subsequently, the output features of different layers are fused by a self-attention mechanism. Second, to overcome the effect of the time-shift problem existing in vibration signals and capture accurate interdependencies between data, a high-dimension affinity feature graph construction method is proposed to construct graph structure data. The effectiveness of the proposed method is quantitatively verified by two rotating machinery datasets, which indicate that the proposed DADE-GCN model can achieve average diagnosis accuracies of 98.80% in both the two few-shot diagnosis tasks, which outperform several state-of-the-art recognition methods.
Tuning specific absorption rate of Mn ferrite nanoparticles synthesized by a thermal decomposition method with different Mn concentrations
Authors: Oroujizad Sahar , Kashi Mohammad Almasi , Montazer Amir H
Published: December 2024

A thermal decomposition method is used to synthesize monodisperse Mn ferrite nanoparticles (NPs) by changing Mn concentration from 0.1 to 0.8 mmol. The effects of Mn concentration on structural, compositional, morphological, magnetic, and hyperthermia properties are investigated. Transmission electron microscopic images show that the morphology of the NPs changes from flower-like to polygonal with increasing the Mn concentration. The saturation magnetization reaches a maximum value of 48.32 emu g−1 and a minimum value of 11.09 emu g−1 with changing the Mn concentration, whereas the coercivity value decreases from 12.6 to 5.3 Oe. The first-order reversal curve analysis enables the estimation of superparamagnetic contribution of the Mn ferrite NPs in the range of 21%–59.5%. The highest specific absorption rate value is obtained to be 385.37 W g−1 for Mn0.1Fe2.9O4 NPs with the maximum superparamagnetic contribution using a manganese concentration of 0.4 mmol.
Unsupervised deep learning-based medical image registration: a survey
Authors: Duan Taisen , Chen Wenkang , Ruan Meilin , Zhang Xuejun , Shen Shaofei , Gu Weiyu
Published: December 2024

In recent decades, medical image registration technology has undergone significant development, becoming one of the core technologies in medical image analysis. With the rise of deep learning, deep learning-based medical image registration methods have achieved revolutionary improvements in processing speed and automation, showing great potential, especially in unsupervised learning. This paper briefly introduces the core concepts of deep learning-based unsupervised image registration, followed by an in-depth discussion of innovative network architectures and a detailed review of these studies, highlighting their unique contributions. Additionally, this paper explores commonly used loss functions, datasets, and evaluation metrics. Finally, we discuss the main challenges faced by various categories and propose potential future research topics. This paper surveys the latest advancements in unsupervised deep neural network-based medical image registration methods, aiming to help active readers interested in this field gain a deep understanding of this exciting area.
Characterization and controllability of radiated power via extrinsic impurity seeding in strongly negative triangularity plasmas in DIII-D
Authors: Eldon D , Casali L , Bykov I , Chrystal C , Erickson K , Hyatt A W , Leonard A W , Moser A L , Nelson A O , Odstrčil T , Paz-Soldan C , Pederson T , Scotti F , Shen H , Thome K E , Wang H Q , Welsh A , Wilks T M
Published: December 2024

Experiments with extrinsic impurity seeding in strongly negative triangularity shapes in DIII-D achieved radiated power fractions (relative to input power) of up to ≈85% total radiation and ≈55% core radiation in steady-operating conditions. The relationship between core and total radiation was sensitive to impurity species and input power. Attempts to reach higher radiation levels via higher impurity flows resulted in radiative collapse disruptions. Nitrogen, neon, argon, and krypton were tested. Injection was by gas puffing, usually controlled by feeding back real-time estimates for core or total radiating fractions (

P
rad

/

P
input

). Argon and krypton were controlled by feeding back total radiating fraction, whereas neon was controlled by feeding back the core radiating fraction, due to the lower efficiency of neon as a divertor radiator. Nitrogen flows were pre-programmed. Reasonable total

P
rad

control target following was achieved with argon or krypton. Control was more challenging with the neon/core radiation configuration, which was more prone to slow response and overshooting of the control target. Poor particle removal contributed to the control challenge: neon particle inventory within the last closed flux surface was roughly constant for up to 1 s (the longest duration tested) after neon injection was halted. However, separate experiments with laser-blow off of non-recycling impurities measured a short impurity confinement time, on the scale of the energy confinement time of ∼100 ms. Modeling with the Aurora impurity transport simulation matched experimental neon densityprofiles with full recycling (R = 1.0) and weak pumping but predicted rapid decreases in neon inventory if pumping were increased or recycling decreased. This indicates that changes outside the confined plasma (adding a well-placed pump) would improve controllability for all highly recycling species.
Gyrokinetic electromagnetic particle simulations in triangular meshes with C1 finite elements
Authors: Lu Zhixin , Meng Guo , Hatzky Roman , Sonnendrücker Eric , Mishchenko Alexey , Chen Jin , Lauber Philipp , Zonca Fulvio , Hoelzl Matthias
Published: December 2024

The triangular mesh-based gyrokinetic scheme enables comprehensive axis-to-edge studies across the entire plasma volume. Our approach employs triangular finite elements with first-derivative continuity (C1), building on previous work to facilitate gyrokinetic simulations. Additionally, we have adopted the mixed variable/pullback scheme for gyrokinetic electromagnetic particle simulations. The filter-free treatment in the poloidal cross-section with triangular meshes introduces unique features and challenges compared to previous treatments using structured meshes. Our implementation has been validated through benchmarks using ITPA-toroidicity-induced Alfvén eigenmode parameters, showing its capability in moderate to small electron skin depth regimes. Additional examinations using experimental parameters confirm its applicability to realistic plasma conditions.
JET Active Gas Handling System–operating experience and lessons learned from recent D-T campaigns
Authors: George Robert , Bickerton Sarah , Cahill Peter , Dalgliesh Peter , Davies Sophie , Franklin Owen , Hayes Nathanya , Jackson Tamsin , Kennedy David , Knight Maddie , Lefebvre Xavier , O’Callaghan James , Olney Ross , Papadopoulos Giannakis , Peyman Mo , Sanni Fatimah , Staniec Paul , Withycombe Alex , Walker Richard , Wakeling Ben ,   The JET Operations Team
Published: December 2024

The Active Gas Handling System (AGHS) stores, supplies and re-processes tritium for the JET fusion experiment. The plant had not operated in this capacity in recent years and required upgrade and recommissioning to enable use during the latest JET tritium campaigns. Thousands of tritium transfers and operations have now been performed with over 1 kg tritium in total supplied to JET and subsequently recovered and reprocessed. This paper summarises AGHS plant operations providing examples from the recent campaigns, and presents the knowledge gained and lessons learnt. A summary of AGHS sub-system upgrades and usage during campaigns is presented. This paper includes data captured from those operations, which have been extracted from the control system as part of a wider AGHS data capture project. Findings are presented from an initiative to capture operator knowledge from AGHS, which brings together operational team input in working groups, a targeted survey and an ideas repository. Key operations are discussed with reference to plant data presented graphically. Operational challenges and lessons learnt are presented from which improvements to design and operations have been proposed. Topics discussed include system design and limitations, process control and automation, tritium accountancy, operating instructions, and ergonomics. Many of the lessons learnt and improvements presented here are relevant to the wider fusion community planning to design and operate tritium plants.
Compression–twist coupling and mechanical performances of Kresling origami-inspired periodic lattice panels
Authors: Li Zhen , Ni Junhao , Wang Zhidong , Wang Xinhao , Kang Zhengyang
Published: December 2024

The design and development of periodic metamaterials are of great significance for the flexible scaling of structures and the control of their performance. This paper advances the state of the art by proposing a Kresling origami-inspired periodic lattice structure and investigating the compression–twist coupling (CTC) and mechanical properties from a single element to a multi-element structure. The lattice element is designed and fabricated using 3D printing method, and its twisting and mechanical properties are investigated both experimentally and numerically. Then, the multi-element panel is created by proper arrangement of the elements. The mechanism of CTC characteristic under multi-element conditions is revealed through force analysis, and the connection between the performance of the single element and the multi-element panel is discussed. For the multi-element panel, the compression–twist performance weakens as the scale increases. However, the contribution of each element to the overall mechanical properties of the panel stabilizes once the panel reaches a size of 3 × 3 or larger. A lightweight hollow design method is also proposed by removing the elements in the central area of the panel. Comparisons between the regular and hollow panels show that the hollow design has minimal impact on the compression–twist performance and the mechanical responses of the elements in the panel. The overall force and energy absorption properties are proportional to the number of elements. Therefore, the lightweight design can tailor the mechanical properties while maintaining consistent compression–twist performance. Additionally, the proposed structure is compared with traditional 3D chiral structure, the potential advantages in compression–twist performance and energy absorption are discussed.
K-band dual-band superconducting bandpass filter using uneven coupled SIRs and stub-loaded combining network
Authors: Chen Peng , Ren Peng , Yang Kai
Published: December 2024

A K-band millimeter dual-band superconducting filter with uneven coupled step-impedance resonators (SIRs) and stub-loaded combining network is proposed in this paper. The novel uneven internally coupled SIR introduces a notch to the classical internally coupled SIR, enhancing the Q-factor for narrow-band filter design. The performance of the uneven coupled SIR is theoretically analyzed, and two single-passband superconducting filters based on the proposed resonator are designed and demonstrated its high Q-factor. A novel stub-loaded combining network is then investigated theoretically to integrate the two single passband filters into a dual-band filter. To validate the design concept, a dual-band superconducting filter is designed on a magnesium oxide (MgO) substrate using the yttrium barium copper oxide superconducting film. The measured results reveal insertion losses of 0.91–1.2 dB of the first passband at 24.21–24.41 GHz with the bandwidth of 0.82% and 0.43–1.3 dB of the second passband at 24.67–25.2 GHz with the bandwidth of 2.12%, respectively. Both passbands exhibit return loss levels exceeding 8 dB, a maximum out-of-band suppression of approximately 65 dB, and a rejection level of about 35 dB between the two passbands.
Next-generation cybersecurity strategies for 3D printing in high-intensity manufacturing
Authors: Moulika G , Palanisamy Ponnusamy
Published: December 2024

This research examines the key factors that influence optimal results in 3D printing, including print speed, temperature, layer thickness and material selection. Specifically, it explores the impact of materials such as acrylonitrile butadiene styrene (ABS), nylon, polylactic acid (PLA), and polyethylene terephthalate glycol (PETG) on the 3D printing process and the decision-making involved in achieving the best results. It provides a comprehensive review of the impact of these variables on print quality, drawing on existing studies and experimental data. The findings indicated that print speed of 66 mm s−1, temperature of 218 °C, layer thickness of 0.2 mm and use of PLA material gave the best results. In addition, the research explores the use of Support Vector Machine (SVM) modeling to predict and improve print quality based on these parameters. Research confirms that through statistical analysis of test data, optimal print settings can be effectively identified. Beyond print quality, the research also addresses critical cybersecurity vulnerabilities in 3D printing systems, particularly related to their integration with IT networks. It highlights the importance of analyzing network traffic to detect vulnerabilities, improve system performance, and strengthen cybersecurity measures. The application of machine learning techniques for anomaly detection is explored as a means of developing risk management strategies and ensuring compliance with auditing standards. Finally, the research discusses the role of blockchain technology in securing machine-to-machine communication (M2M) within the 3D printing environment, as well as ensuring data integrity and confidentiality.
Synthesis of zinc oxide-doped reduced graphene oxide (rGO) nanocomposites on visible light-driven photocatalytic and antibacterial activity applications
Authors: Thuy Pham Thi , Hue Bui Thi Cam , Sang Nguyen Xuan , Thanh Thuy Le Thi , Lieu Phuoc Long
Published: December 2024

In this study, reduced graphene oxide (rGO), ZnO nanocomposites, and zinc oxide-doped reduced graphene oxide (ZnO/rGO) nanocomposites were successfully synthesized via the sol–gel method and investigated for the removal of methyl blue (MB) dye and antibacterial activity under visible light irradiation. The synthesized nanocomposites were characterized using XRD, SEM, EDX, FTIR, UV–vis DRS, and BET techniques to analyze the crystallographic structure, phase, surface morphology, and different functional groups in the prepared catalysts. The ZnO/rGO nanocomposites demonstrated a great photocatalytic performance over 98% degradation of 20 mg L−1 of methylene blue (MB) dye within just 90 min under visible light. A heterojunction material achieved a higher 20% than that of the ZnO single-phase. Among the prepared photocatalysts, the nanocomposite with 0.2 grams rGO demonstrated the best results. Reusability studies revealed that ZnO/rGO catalysts maintained over 90% efficiency up to three cycles, with rGO serving as an effective adsorbent and ZnO providing catalytic activity. In addition, the antibacterial activity of the nanocomposites was evaluated against both Gram-positive and Gram-negative bacteria, showing significant inhibition due to the photocatalytic generation of reactive oxygen species. These findings suggest that ZnO/rGO nanocomposites are promising materials for environmental remediation and antibacterial applications.
Physicians Who Perceived the Rudiments of the Art of Medicine and Initiated the Practice of That Art
Authors: Usaybiʿah Ibn Abi¯
Published: December 2024

This chapter covers the semi-divine Asclepius, the originator of medicine and considered by Ibn Abī Usaybiʿah to have been a real historical figure. He is important as he bridges the gap between the divine and human, and his place in the hierarchy of physicians is...
Arab and Other Physicians of the Earliest Islamic Period
Authors: Usaybiʿah Ibn Abi¯
Published: December 2024

Ibn Abī Usaybiʿah now moves to his own world, chronicling the Arabs and physicians of the early Islamic period. The chapter starts with a contemporary of the Prophet Muhammad, the semi-legendary al-Hārith ibn Kaladah, accounts of whom were elaborated over time to the point where...
Physicians Who Translated Works on Medicine and Other Subjects from Greek Into Arabic, and Their Patrons
Authors: Usaybiʿah Ibn Abi¯
Published: December 2024

This text of this short chapter has not been included in this edition. In it are listed thirty-eight translators and eleven patrons ‘other than caliphs’. None have more than four or five lines of description.

The translators appear to be listed randomly and several, such...
Physicians Who Were Prominent in the Western Lands and Settled There
Authors: Usaybiʿah Ibn Abi¯
Published: December 2024

The Muslim West (the Maghrib), including al-Andalus or Muslim Spain, is represented here. Among the Andalusians there are several who later acquired both fame and Latinized names in Europe, including the physician and poet Ibn Zuhr (Avenzoar) and the philosopher and great commentator of Aristotle,...
Famous Syrian Physicians
Authors: Usaybiʿah Ibn Abi¯
Published: December 2024

This final, longest chapter lists the physicians of al-Shām, the old Arabic name for Syria, loosely corresponding to Greater Syria or what used to be called the Levant. Thirteen of these physicians were known personally to Ibn Abī Usaybiʿah. including his paternal uncle, Rashīd al-Dīn...
Preface of Ibn Abī Usaybi ʿ Ah
Authors: Usaybiʿah Ibn Abi¯
Published: December 2024

The preface is included in its entirety. Here Ibn Abī Usaybiʿah sets out his reasons for writing the book and what he hopes to achieve. He points out the importance of good health and thus of the art of medicine, reminding the reader that knowledge...
Aristotle’s account of the human capacity for thinking
Authors: Corcilius Klaus , Falcon Andrea , Roreitner Robert
Published: December 2024

De anima III 4–5 is narrowly focused on the definition of a highly specialized form of thinking: the structurally simple, necessarily true, non-propositional grasping of essences. For Aristotle, this form of thinking grounds the possibility of all the other, more familiar, kinds of thinking. The chapter argues that Aristotle has an explanatory account of human thinking capable of accounting for key features of human thinking such as objectivity, universality, and necessity. It is argued that Aristotle achieves this by way of two key moves: namely, an account of thinking as matterlessness of a certain kind, and the claim that episodes of human thinking of essences for their actualization depend on the existence of a self-thinking separate essence.
The principles of propositional thought
Authors: Corcilius Klaus , Falcon Andrea , Roreitner Robert
Published: December 2024

This chapter argues that De anima III 6 contains a unitary and coherent argument that fits tightly into the overall context of Aristotle’s account of the thinking capacity. In De anima III 6 Aristotle faces the obvious question of how the capacity of grasping essences analyzed in the previous chapters can account for the other kinds of thinking. It is argued that Aristotle makes both the truth and the unity of propositional thinking depend on the grasping of essences. The chapter’s central claim is that we can see this once we realize that in De anima III 6 Aristotle distinguishes between two kinds of “dividing” propositions (and two corresponding kinds of adiaireta): namely, either dividing them into their structural elements (subject and predicate terms) or dividing them by means of explanatory middle terms.
Nous and nature
Authors: Corcilius Klaus , Falcon Andrea , Roreitner Robert
Published: December 2024

This chapter explains how Aristotle’s treatment of nous, which is an integral part of De anima, relates to the program of his natural philosophy. It further spells out what kind of contribution the inquiry into nature can make toward explaining the phenomena of our intellectual life for which nous is the ultimate explanans. It also addresses the controversial question concerning the sense in which human nous is—and the sense in which it isn’t—separable from the other parts of the soul and from the body. The chapter sheds new light on the specific status of Aristotle’s inquiry into nous within his De anima, resisting both its straightforward subsumption under natural philosophy and the idea that An. III 4–8 is an excursus into first philosophy.
Conclusion: Aristotle on nous
Authors: Corcilius Klaus , Falcon Andrea , Roreitner Robert
Published: December 2024

This short conclusion summarizes the main results reached in this in-depth study of de anima III 4–8. They can be introduced with the use of four key ideas: rationalism, essentialism, separatism, embeddedness in the cognitive soul. Aristotle believes that thought is a distinct form of cognition, irreducible to perception. It consists in the ability to grasp the essences of things. Nous understood as the principle of thought is separate from nature and yet integrated into the cognitive system that we call the cognitive soul.
The Market in English School Perspective
Authors: Buzan Barry , Falkner Robert
Published: December 2024

This chapter has two main purposes. First, it sets out the English School’s conceptual toolbox and vocabulary: international system, international society, and world society; the inter-polity/state, transnational and interhuman domains; and distinctions between first and second order societies, pluralism and solidarism, and primary and secondary institutions. Second, it reviews how the economic sector generally, and the market in particular, have been discussed in the English School literature, reviewing contributions by James Mayall, Kalevi Holsti, Andrew Hurrell, Barry Buzan, and Louis Pauly. It also explains why there has been so little linkage between the English School and International Political Economy.
Introduction
Authors: Melnyk Andrew
Published: December 2024

This chapter poses the book’s central question and previews the chapters to follow. The question concerns physicalism (or materialism) about phenomenal properties (or qualia). If the phenomenal properties of sensations really are physical or physically realized properties, as physicalism entails, why is it that, when we introspect them, they seem to us so strongly not to be? The question refers to the intuition of distinctness, which we experience when, for example, we attend introspectively to the phenomenal redness of a current visual sensation, and it seems to us that that very property could not literally be a physical property of neural activity in our brain. The book argues that the intuition has had an unrecognized influence on the debate about phenomenal properties, but that it gives us no reason to disbelieve physicalism. After surveying previous attempts to explain the intuition consistently with physicalism, it elaborates a novel explanation of why we have the intuition.
Second Canto
Authors: Ludovico Ariosto
Published: December 2024

1–2 Introductory.

3–23 Rinaldo pursues Angelica.

24–30 Rinaldo sails for England.

30–62 Pinabello tells Bradamant of the enchanted castle.

62–76 Pinabello plots against Bradamant.

Love, what makes you so unjust? Why can you never take heed of our own desires ? Whence comes it,...
Third Canto
Authors: Ludovico Ariosto
Published: December 2024

1–4 Introductory.

4–19 Bradamant at Merlin’s tomb.

20–62 Bradamant’s posterity revealed by the Sorceress.

63–77 Bradamant prepares to encounter Brunello.

Who will give me the voice and eloquence to do justice to so lofty a subject? Who will lend wings to my verses that...
Fifth Canto
Authors: Ludovico Ariosto
Published: December 2024

1–3 Introductory.

4–74 Dalinda tells Rinaldo of Polynex’s plot against Guinevere.

75–92 Rinaldo discloses Polynex’s treachery and slays him.

Every species of beast which dwells on this earth lives in peace among its kind—and if fight it must, yet the male will never attack...
Ninth Canto
Authors: Ludovico Ariosto
Published: December 2024

1–2 Introductory.

2–17 Orlando searches for Angelica.

18–56 Orlando meets Olympia, who tells him her sad tale.

57–94 Orlando takes up Olympia’s cause, then resumes his search for Angelica.

Cruel, treacherous Love! See what it can do to a heart, once conquered! It can...
Twelfth Canto
Authors: Ludovico Ariosto
Published: December 2024

1–22 Orlando seeks Angelica in the enchanted palace.

23–65 Angelica misleads Orlando, Sacripant and Ferrau.

66–94 Orlando defeats a Saracen host, and comes to a cave.

When Ceres, after visiting her mother on Mount Ida, sped back to the secluded valley where Mount Etna...
Fourteenth Canto
Authors: Ludovico Ariosto
Published: December 2024

1–9 Introductory.

10–27 The parade of the Saracen troops.

28–64 Mandricard seeks Orlando and abducts Doralice.

65–74 Preparations for the storming of Paris.

75–98 The Archangel Michael’s mission.

99–134 The storming of Paris, and Rodomont’s assault on the walls.

In the successive assaults and...