bluuebunny/crossref_metadata_2025_split huggingface dataset:
An object detection method for catenary component images based on improved Faster R-CNN
Authors: Wu Changdong , He Xu , Wu Yanliang 
Published: May 2024

Abstract
Catenary components are an important part of electrified railways. Especially for catenary support devices, there are various types of components with significant differences in scale. According to statistical data, there is a high risk of failure for the catenary support device components during the operation of the catenary system. Therefore, in order to ensure the safe operation of the railways, it is critical to accurately locate and recognize the components in the catenary images. In this paper, we propose an improved method based on faster region-based convolutional neural networks (Faster R-CNN) framework to realize the detection and extraction of the components on the catenary support devices. Firstly, the anchor box parameters are reset using the K-means clustering method, which greatly improves the localization precision of the predicted box. Secondly, scaled exponential linear units activation function is introduced to improve the algorithm performance. Moreover, ResNet-34, the backbone of Faster R-CNN, is optimized. We design a transition structure for multi-scale filter combination convolution to avoid missing feature information and eliminate some redundant convolution structures. This modification substantially enhances the capability of the model to recognize a wide variety of component types. Finally, we conduct some control experiments comparing with single shot multibox detector and you only look once (YOLO) series (YOLOv3, YOLOv5 and YOLOv7) models. They are faster but less accurate, especially for small objects. The results show that the proposed method has better detection performance, achieving a mean average precision of 96.50% and running at 17.79 frames per second. In addition, our model has the highest average recall of 69.27%, which is 2.66% higher than the original model.
Zinc oxide nanoparticles encapsulated in alginate beads: a promising and recyclable adsorbent for simultaneous uptake of toxic metals
Authors: Çevik Tuğba Nur , Kivilcimdan Moral Çiğdem 
Published: May 2024

Abstract
Heavy metal toxicity is a known problem and various methods are used for treatment. Adsorption has some advantages and it would be promising if environmentally friendly and cheap materials were utilized. Alginate and zinc oxide nanoparticles were selected and composite alginate beads were used for the removal of mixed metals from aqueous solutions. Batch and column experiments were conducted to determine some parameters’ effects and the adsorbent’s real application potential. According to the batch experiments, zinc oxide nanoparticles to alginate ratio of 0.5 g g−1, and pH levels nearby to the neutral range led to better metal removals. 0.5 ml min−1 of flow rate supplied better metal removal efficiencies in columns, with the highest treatment as 86% of Pb2+. Acid treatment can be successfully applied for the regeneration of the adsorbent, at least three times only with a 4% reduction in the adsorption efficiency. Heavy metal uptake was compatible with the pseudo 2nd order model indicating chemisorption as a dominant mechanism. Also, the intraparticle diffusion model illustrated adsorption might govern more than one step. The Langmuir model had the best fit and suggested monolayer covering for Pb2+, 76.3 mg g−1. Alginate-based nanocomposite beads were useful for mixed metal removal and could be used.
Continuous monitoring methods of cerebral compliance and compensatory reserve: a scoping review of human literature
Authors: Islam Abrar , Froese Logan , Bergmann Tobias , Gomez Alwyn , Sainbhi Amanjyot Singh , Vakitbilir Nuray , Stein Kevin Y , Marquez Izabella , Ibrahim Younis , Zeiler Frederick A 
Published: May 2024

Abstract

Objective. Continuous monitoring of cerebrospinal compliance (CC)/ cerebrospinal compensatory reserve (CCR) is crucial for timely interventions and preventing more substantial deterioration in the context of acute neural injury, as it enables the early detection of abnormalities in intracranial pressure (ICP). However, to date, the literature on continuous CC/CCR monitoring is scattered and occasionally challenging to consolidate. Approach. We subsequently conducted a systematic scoping review of the human literature to highlight the available continuous CC/CCR monitoring methods. Main results. This systematic review incorporated a total number of 76 studies, covering diverse patient types and focusing on three primary continuous CC or CCR monitoring metrics and methods—Moving Pearson’s correlation between ICP pulse amplitude waveform and ICP, referred to as RAP, the Spiegelberg Compliance Monitor, changes in cerebral blood flow velocity with respect to the alternation of ICP measured through transcranial doppler (TCD), changes in centroid metric, high frequency centroid (HFC) or higher harmonics centroid (HHC), and the P2/P1 ratio which are the distinct peaks of ICP pulse wave. The majority of the studies in this review encompassed RAP metric analysis (n = 43), followed by Spiegelberg Compliance Monitor (n = 11), TCD studies (n = 9), studies on the HFC/HHC (n = 5), and studies on the P2/P1 ratio studies (n = 6). These studies predominantly involved acute traumatic neural injury (i.e. Traumatic Brain Injury) patients and those with hydrocephalus. RAP is the most extensively studied of the five focused methods and exhibits diverse applications. However, most papers lack clarification on its clinical applicability, a circumstance that is similarly observed for the other methods. Significance. Future directions involve exploring RAP patterns and identifying characteristics and artifacts, investigating neuroimaging correlations with continuous CC/CCR and integrating machine learning, holding promise for simplifying CC/CCR determination. These approaches should aim to enhance the precision and accuracy of the metric, making it applicable in clinical practice.
Fast ion confinement in the presence of core magnetic islands in Wendelstein 7-X
Authors: Lazerson Samuel A , Geiger Joachim , Kulla David , LeViness Alexandra , Bozhenkov Sergey , Killer Carsten , Ogawa Kunihiro , Isobe Mitsutaka , McNeely Paul , Rust Norbert , Hartmann Dirk ,   the W7-X Team
Published: May 2024

Abstract
The effect of magnetic islands in the core region of Wendelstein 7-X (W7-X) on fast ion confinement is explored through simulations with the BEAMS3D code. A magnetic configuration where the

n

/

m
=
5

/

5

island chain is shifted to

r

/

a
∼
0.7

allows the exploration of core island physics in W7-X. The control coil system on W7-X allows the tuning of the island size either increasing the island width or decreasing it. A coupling of the BEAMS3D code to the FIELDLINES code provides a versatile mechanism for incorporating magnetic islands and stochastic regions into the BEAMS3D code. Collisionless simulations suggest that the presence of core islands degrade the confinement of passing particles in the region of the island chain. Full neutral beam simulations of W7-X show a similar behavior with confinement decreasing as the island width is increased. Comparisons between a vacuum magnetic field and low beta HINT2 simulation are made showing similar fast ion behavior. Measurements of lost fast ions in W7-X confirm this trend with the control coil suppressed island configuration showing lower losses than that with no control coils applied. Simulations of fast ion wall loads are performed suggesting no drastic change in loss pattern and a slight reduction in losses with minimized islands.
Delocalization and higher-order topology in a nonlinear elastic lattice
Authors: Yi Jianlin , Chen Chang Qing 
Published: May 2024

Abstract
Topological elastic waves provide novel and robust ways for manipulating mechanical energy transfer and information transmission, with potential applications in vibration control, analog computation, and more. Recently discovered higher-order topological insulators (HOTIs) with multidimensional and hierarchical edge states can further expand the capabilities of topological elastic waves. However, the effects of nonlinearity on elastic HOTIs remain elusive. In this paper, we propose a nonlinear elastic higher-order topological Kagome lattice. After briefly reviewing its linear properties, we explore the effects of nonlinearity on the higher-order band topology and topological states. To do this, we have developed a method to calculate approximate nonlinear modes in order to identify the bulk polarization and probe the higher-order topological phase in the nonlinear lattice. We find that nonlinearity induces unusual delocalization of topological corner states, band crossing, and higher-order topological phase transition. The delocalization reveals that intracell hardening nonlinearity leads to direct delocalization of topological corner states while intracell softening nonlinearity first enhances and then reduces localization. The nonlinear higher-order topological phase is amplitude dependent, and we demonstrate a transition from a trivial to a non-trivial phase, enabling amplitude induced topological corner and edge states. Additionally, this phase transition corresponds to the closing and reopening of the bandgap, accompanied by an unusual band crossing. By examining the band topology before and after the band crossing, we find that the bulk polarization becomes quantized with respect to amplitude and can predict higher-order topological phases in nonlinear lattices. The obtained results are expected to be beneficial for the development of tunable and robust elastic wave devices.
Novel vacancy-ordered RbKGeCl6 and RbKGeBr6 double perovskites for optoelectronic and thermoelectric applications: an ab-initio DFT study
Authors: Pingak Redi Kristian , Harbi Amine , Moutaabbid M , Nitti Fidelis , Sianturi Hery L , Johannes Albert Z , Hauwali Nikodemus U J 
Published: May 2024

Abstract
The present study examines the key characteristics of new vacancy-ordered halide double perovskites, RbKGeCl6 and RbKGeBr6, encompassing the elastic, structural, mechanical, optoelectronic, and thermoelectric properties. The Density Functional Theory (DFT) was employed to perform the calculation of the properties, facilitating the evaluation of their potential applications in optoelectronic and thermoelectric devices. The DFT calculation was conducted using the Quantum Espresso package alongside the thermo_pw tool and the BoltzTraP codes. The results revealed that the two proposed compounds possess both chemical and mechanical stability with optimized lattice constants recorded at 10.14 Å and 10.72 Å for RbKGeCl6 and RbKGeBr6, respectively. The evaluation of the elastic properties of the materials suggested reasonably high mechanical moduli of the materials. Based on the calculated electronic properties, the materials are classified as direct gap semiconductors, with energy gap values of 2.11 eV for RbKGeCl6 and 0.80 eV for RbKGeBr6 using the GGA-PBE functional. Furthermore, the use of the SCAN approximation yields more reliable energy gap of 2.51 eV and 1.08 eV for the respective compounds. The materials exhibited a high absorption coefficient and a significantly low reflectivity within the visible-ultraviolet energy spectrum. These findings strongly suggest the promising properties of the materials under study for optoelectronic applications. Furthermore, the calculated thermoelectric properties of the materials, particularly the figure of merit, revealed the materials’ potential use as thermoelectric materials. The calculated figure of merit values of RbKGeCl6 and RbKGeBr6 were found to range from 0.73 to 0.75, respectively, between 300 K and 800 K. Despite being lower, these values are comparable to those of some well-established materials including SiGe alloys (0.95), Bi2Te3 (≈0.90), and PbTe (≈0.80).
Ultrafast active plasmonic switch based on the broadband high absorption of monolayer graphene with high modulation depth
Authors: Najafgholinezhad Samira , Pourmahyabadi Maryam 
Published: May 2024

Abstract
Optical switches based on plasmonic nanostructures are of great interest due to their high speed performance. To improve the broadband switching performance, a plasmonic design based on metal-insulator-metal (MIM) structure and monolayer graphene (as an active layer) is proposed. In this scheme, the light absorption of the monolayer graphene and the optical bandwidth are increased due to magnetic dipole resonance and magnetic coupling effect. The numerical simulation results of the proposed structure reveal that high absorption is achieved at the wavelength of 1.55 ‌μm which is 67% and 93% for the monolayer graphene and the whole structure, respectively. This structure has a high absorption modulation depth which can be reached nearly 100% around the interband transition position in a wide wavelength range from 1 μm to 2.5 ‌‌‌‌‌μm. Also, regarding its short response time of 10 fs, this structure can be used as an ultrafast switch. In addition, the equivalent circuit model of the structure is derived from the transmission line model (TLM) that its results are in a very good agreement with the numerical simulation results.
A two-dimensional chaotic model and its application in image encryption
Authors: Lei RongQing , Liu LingFeng 
Published: May 2024

Abstract
In this paper, we propose a rule that follows a time-varying delay construction method and construct a time-varying delay scheme based on it. This construction scheme is also combined with a polynomial to obtain a novel two-dimensional chaotic model. Both mathematical analysis and experimental results show that the model satisfies the chaos condition. Good experimental results have been achieved in complexity analysis, information entropy analysis, and Auto-correlation analysis, and have certain competitiveness. The obtained chaotic model is also applied to the image encryption algorithm. The experimental results show that the encryption algorithm has high security and can effectively resist noise attacks, shear attacks, differential attacks.
Closed-form asymptotic solution for the transport of chlorine concentration in composite pipes
Authors: Mubaraki Ali M , Nuruddeen Rahmatullah Ibrahim , Gómez-Aguilar J F 
Published: May 2024

Abstract
Recently, some researchers have revisited the analysis of chlorine transportation in cylindrical pipes by deploying a coupling between the Laplace transform method and the complex analysis’ residue approach for inverting complex integrals. This method yielded interesting results after the incorporation of root-finding numerical schemes. Thus, away from incorporating numerical tools, the present study makes consideration of the same formulation of chlorine transport in a single-layered pipe and further extends it to the case of a bi-layered pipe using the hybrid of the Laplace transform method and the asymptotic approximations method. The need for asymptotic approximations for the modified Bessel functions, which arise in the reduced ordinary differential equations, necessitates the quest for closed-form analytical solutions, which are largely considered benchmark solutions for numerical investigations. Moreover, the obtained closed-form asymptotic solutions have been examined graphically; where it was observed that both the radial diffusion coefficient η and the spatial radial variable are contributory in the transport of chorine concentration in the media.
Attention-guided graph structure learning network for EEG-enabled auditory attention detection
Authors: Zeng Xianzhang , Cai Siqi , Xie Longhan 
Published: May 2024

Abstract

Objective: Decoding auditory attention from brain signals is essential for the development of neuro-steered hearing aids. This study aims to overcome the challenges of extracting discriminative feature representations from electroencephalography (EEG) signals for auditory attention detection (AAD) tasks, particularly focusing on the intrinsic relationships between different EEG channels. Approach: We propose a novel attention-guided graph structure learning network, AGSLnet, which leverages potential relationships between EEG channels to improve AAD performance. Specifically, AGSLnet is designed to dynamically capture latent relationships between channels and construct a graph structure of EEG signals. Main result: We evaluated AGSLnet on two publicly available AAD datasets and demonstrated its superiority and robustness over state-of-the-art models. Visualization of the graph structure trained by AGSLnet supports previous neuroscience findings, enhancing our understanding of the underlying neural mechanisms. Significance: This study presents a novel approach for examining brain functional connections, improving AAD performance in low-latency settings, and supporting the development of neuro-steered hearing aids.
Research on the efficient process-oriented structural optimization method of the large-scale vacuum cryostat for fusion reactors
Authors: Yu Qingzhou , Xu Hao , Chen Zhaoxi , Yang Qingxi 
Published: May 2024

Abstract
An efficient optimization design for the large and complex components of fusion reactors is crucial to address the engineering design requirements and further promote technical standardization. Based on research status, current engineering designs for fusion reactors have some deficiencies, such as time and energy wastage, inefficiency, and difficulties in covering the typical ‘multi-variable multi-objective’ design requirements. These are pressing and common problems that urgently need to be overcome. To deal with the aforementioned technical challenges, it is vitally important to design an efficient, precise, and normalized approach that is tailored for the development of future fusion reactors. Therefore, this paper proposes a process-oriented optimization design method, which involves Coupled external parameterized modeling, Experimental points design, Response surface optimization, and Structural integrity validation (CERS), to improve the currently inefficient design methods. And the vacuum cryostat, the largest and complex component of a tokamak, is taken as an example to present the basic procedures of CERS. Firstly, the functions, basic structures, load types, analysis methods, and verification criteria of the cryostat are presented in detail. Then, real-time data interaction between external global parametric variables and ANSYS via coupling is established by CERS, which achieves parametric modeling of the cryostat and efficient experimental point design and optimization analysis with multi-variables and multi-objectives in an automatic way. Subsequently, this study demonstrates the significance and sensitivity of various structural parameters of the cryostat from such objectives as maximum deformation, maximum equivalent stress, and total mass. And the optimal set of its structural parameters is obtained by establishing a mathematical optimization model. Finally, the structural integrity is verified. The results indicate that the optimized cryostat maintains a minimum safety margin of 23% and will not suffer fatigue damage under various load events during its service. Moreover, the nonlinear buckling load multiplier

∅

is 5.4, obtained by analyzing the load-displacement curve of the cryostat according to the zero-curvature criterion. This shows that the designed cryostat is stable enough. The proposed method is simple, efficient, and reliable, and can be applied to both the cryostat and other complex components of fusion reactors in engineering design fields. It has great value of practical technical reference and can further promote the standardization of engineering design technology for future fusion reactors.
Global fluid simulation of plasma turbulence in stellarators with the GBS code
Authors: Coelho A.J. , Loizu J. , Ricci P. , Tecchiolli Z. 
Published: May 2024

Abstract
The implementation of three-dimensional magnetic fields, such as the ones of stellarators, in the GBS code (Ricci et al 2012 Plasma Phys. Control. Fusion
54 124047; Giacomin et al 2022 J. Comput. Phys.
464 111294) is presented, and simulation results are discussed. The geometrical operators appearing in the drif-reduced Braginskii equations evolved by GBS are expanded considering the typical parameter ordering of stellarator configurations. It turns out that most of the operators have a similar structure as the one implemented in the tokamak axisymmetric version of the code. In particular, the perpendicular laplacian only acts on the poloidal plane, which avoids the need of a three-dimensional solver for the electrostatic potential. The simulation of an island divertor stellarator is then presented, showing the derivation of the magnetic equilibrium in detail and extending the results in (Coelho et al 2022 Nucl. Fusion
62 074004). Although the island magnetic field-lines divert the plasma towards the strike points of the walls, the islands do not seem to have a significant impact on the turbulence properties. The dominant mode, identified as interchange-driven, is field-aligned and breaks the stellarator toroidal symmetry. The radial and poloidal extensions of the mode are of the same order, in contrast to typical tokamak simulations. This has consequences on the poloidal dependence of turbulent transport.
Socioeconomic distributional impacts of evaluating flood mitigation activities using equity-weighted benefit-cost analysis
Authors: Lockwood Joseph W , Oppenheimer Michael , Lin Ning , Gourevitch Jesse 
Published: May 2024

Abstract
As the global impact of climate change intensifies, there is an urgent need for equitable and efficient climate adaptation policies. Traditional approaches for allocating public resources for climate adaptation that are based on economic benefit-cost analysis often overlook the resulting distributional inequalities. In this study, we apply equity weightings to mitigate the distributional inequalities in two key building and household level adaptation strategies under changing coastal flood hazards: property buyouts and building retrofit in New York City (NYC). Under a mid-range emissions scenario, we find that unweighted benefit cost ratios applied to residential buildings are higher for richer and non-disadvantaged census tracts in NYC. The integration of income-based equity weights alters this correlation effect, which has the potential to shift investment in mitigation towards poorer and disadvantaged census tracts. This alteration is sensitive to the value of elasticity of marginal utility, the key parameter used to calculate the equity weight. Higher values of elasticity of marginal utility increase benefits for disadvantaged communities but reduce the overall economic benefits from investments, highlighting the trade-offs in incorporating equity into adaptation planning.