bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the impact of customer concentration on stock price crash risk
Authors: Afghahi Mahla , Nassirzadeh Farzaneh , Askarany Davood 
Published: July 2024

AbstractThis paper, rooted in agency theory, explores the intricate relationship between stock price crash risk and customer concentration within the context of Iran, a developing nation. Utilising innovative indicators to measure corporate and government customers, we address inconsistent findings in existing research and offer fresh insights into stock price crash risk dynamics. Focusing on 82 companies listed on the Tehran Stock Exchange from 2013 to 2020, our study employs a robust methodological framework, including panel data, multiple regression and three distinct metrics to measure customer concentration. Specifically, we introduce the proportion of significant customer sales, the Herfindahl-Hirschman Index, and a Ranking Index based on substantial customer sales. Our investigation reveals a noteworthy inverse relationship between the highest concentration level of corporate customer concentration, as measured by the Ranking Index, and stock price crash risk. Similarly, we establish an inverse association between the Ranking Index for government customer concentration and stock price crash risk. Moreover, institutional investors positively influence the correlation between corporate customer concentration and stock price crash risk but do not exert a discernible impact on the relationship between government customer concentration and stock price crash risk.
Big data analytics capability and social innovation: the mediating role of knowledge exploration and exploitation
Authors: Wang Nan , Chen Baolian , Wang Liya , Ma Zhenzhong , Pan Shan 
Published: July 2024

AbstractWhile many organizations have successfully leveraged big data analytics capabilities to improve their performance, our understanding is limited on whether and how big data analytics capabilities affect social innovation in organizations. Based on the organizational information processing theory and the organizational learning theory, this study aims to investigate how big data analytics capabilities support social innovation, and how knowledge ambidexterity mediates this relationship. A total of 354 high-tech companies in China, this study shows that big data analytics management, big data analytics technology, and big data analytics personnel capabilities all have positive effects on social innovation. In addition, both knowledge exploration and knowledge exploitation play a mediating role in this process. Furthermore, a polynomial regression and response surface analysis shows that social innovation increases when knowledge exploration and knowledge exploitation are highly consistent but declines when knowledge exploration and knowledge exploitation are inconsistent. This study not only provides new perspectives for understanding how big data analytics capabilities contribute to social innovation, complementing the existing literature on big data analytics capabilities and social innovation, but also provides important practical guidance on how organizations can develop big data analytics capabilities to improve social innovation and solve social problems in the digital age.
Territorial control by non-state armed groups and gendered access to healthcare in conflict using a new complex adaptive systems framework
Authors: Lilja Jannie , Ferrari Giulia , Alvarado José , Fabich Laura-Alina , Kyzy Gulzhan Asylbek , Kenny Leah , Hossain Mazeda 
Published: July 2024

AbstractThe growing prevalence and influence of non-state armed groups (NSAGs) in armed conflict requires a deeper understanding of how their territorial control and contestation affect sub-national healthcare availability and outcomes, particularly with regards to gender dynamics. However, there are gaps in existing research in understanding how NSAG governance influences health care outcomes. Furthermore, a disconnect exists between the literature on international humanitarian interventions, NSAG governance and national health systems. Each perspective tends to prioritise a specific health service provider—whether NSAGs, State actors, or international humanitarian organisations—and often treats populations as homogenous. To address these gaps, we propose a complex adaptive system framework centred on the influence of territorial control for health services in intra-state conflict settings, with a gender lens. This systems framework accounts for the influence of all parties significant for health service delivery. It recognises that those governing the localised health system may differ from those physically delivering health services. Our framework enables empirical examination of health service delivery and outcomes. We apply the framework to three conflict-affected settings (Colombia, Iraq, Mali) using publicly available data and offer recommendations for policymakers and practitioners targeting health service provision in intra-state conflict contexts.
Broadband color routing with a single element nanoantenna for communication bands
Authors: Liu Xianghua , Li Ang , Liu Chenyang , Zhao Nengyang , Peng Jiahao , Gan Fengyuan , Lei Xinrui , Wang Ruxue , Wu Aimin 
Published: July 2024

Spectral routing techniques have attracted plenty of research attention for the past decades, as they enable light manipulation in both the frequency domain and the spatial domain, which is crucial for applications in on-chip spectroscopy, optical switching, and modern communications. Here, we demonstrate an ultra-compact asymmetric nanoplasmonic router for communication bands that routes O and C bands to opposite positions. The nanorouter consists of two uneven grooves that create bidirectional scattered optical fields, utilizing the interference between different optical modes inside the grooves. A broadband spectrum exceeding 100 nm and a maximum extinction ratio of 31 dB are achieved, providing new opportunities for nanophotonic color routing solutions and extensions to other areas such as imaging sensors and spectral measurements.
A terahertz solid-state source interferometer–polarimeter designed for long pulse discharges on EAST
Authors: Wang S. X. , Liu H. Q. , Zhang J. B. , Xu C. , Lian H. , Zou Z. Y. 
Published: July 2024

A 0.65 THz Solid-state Source Interferometer–Polarimeter (SSIP) with vertical viewing has been installed for line-integrated density and Faraday rotation measurements on Experimental Advanced Superconducting Tokamak (EAST). The SSIP utilizes three independent solid-state diode sources based on frequency multiplier (X48) to provide the probing beam at a fixed frequency of 0.65 THz with ∼2.5 mW output power, which provide an Intermediate Frequency (IF) with wide range, and the highest IF is up to ∼10 MHz. The mixers optimized for high sensitivity, ∼750 mV/mW, are used in the SSIP system, which permits multichannel interferometer–polarimeter on EAST with a low phase noise. The resolution of the integrated density is 3.3 × 1017 m−2, and the Faraday rotation is about 1.5°. The density measurement has been implemented with IF ∼0.85 MHz, in a plasma with plasma current ∼300 kA on EAST. The line-averaged density, 3.5 × 1019 m−3, measured by the SSIP shows good agreement with the results measured by the POlarimeter–INTerferometer (POINT) system and the CO2 dispersion interferometer system in the same discharge.
臘羅彝語的度量短語
Authors: Bu Weimei , Liu Hongyong 
Published: July 2024

抽象的
臘羅彝語包含兩類不同的度量短語：出現在謂語動詞前的光桿度量短語以及出現在「度量短語+dɛ⁵⁵+名詞」結構中的度量短語。光杆度量短語語義上指向句中充當論元的光桿名詞，但句法上須先與謂語動詞組合，此類分裂式度量短語只具有單調性解讀。「度量短語+dɛ⁵⁵+名詞」結構具有歧義，既允許單調性解讀，也允許非單調性解讀，這兩種不同的語義解讀分別對應兩種不同的句法結構：準切分結構和定中結構。臘羅彝語度量短語的句法分佈進一步驗證了度量短語的單調性假設，具有重要的語言類型學價值。
An accelerated inexact Newton regularization scheme with a learned feature-selection rule for non-linear inverse problems
Authors: Long Haie , Zhang Ye , Gao Guangyu 
Published: July 2024

Abstract
With computational inverse problems, it is desirable to develop an efficient inversion algorithm to find a solution from measurement data through a mathematical model connecting the unknown solution and measurable quantity based on the first principles. However, most of mathematical models represent only a few aspects of the physical quantity of interest, and some of them are even incomplete in the sense that one measurement corresponds to many solutions satisfying the forward model. In this paper, in light of the recently developed iNETT method in (2023 Inverse Problems
39 055002), we propose a novel iterative regularization method for efficiently solving non-linear ill-posed inverse problems with potentially non-injective forward mappings and (locally) non-stable inversion mappings. Our approach integrates the inexact Newton iteration, the non-stationary iterated Tikhonov regularization, the two-point gradient acceleration method, and the structure-free feature-selection rule. The main difficulty in the regularization technique is how to design an appropriate regularization penalty, capturing the key feature of the unknown solution. To overcome this difficulty, we replace the traditional regularization penalty with a deep neural network, which is structure-free and can identify the correct solution in a huge null space. A comprehensive convergence analysis of the proposed algorithm is performed under standard assumptions of regularization theory. Numerical experiments with comparisons with other state-of-the-art methods for two model problems are presented to show the efficiency of the proposed approach.
Fabrication of microneedles using wire electric discharge machining and improving surface quality by electrochemical polishing
Authors: Sarkar Partha , Sidpara Ajay M 
Published: July 2024

Abstract
Microneedle (MN) arrays have many applications in biomedical engineering to deliver drugs transdermally or extract biomarkers from the interstitial fluid from the human skin. Several methods have been developed to fabricate different sizes and shapes of MN using polymers, ceramics and metals. However, most of these methods require expensive sophisticated machines and clean room facilities. So, it is difficult to fabricate microneedle arrays in large quantities at a reasonable cost. This study reports the fabrication of a high-quality stainless steel master pattern for an MN array using a wire-cut electric discharge machining process followed by electrochemical polishing (ECP). Different densities of a 5 × 5 array of microneedles with pyramidal shapes were fabricated by machining channels onto the workpiece surface in a criss-cross pattern. A systematic experimental study was carried out with reference to the offset between the two consecutive channel faces and the depth of channels. The output parameters are MN height (MNH), MN base (MNBW) and tip width (MNTW). The average needle tip width, base width, and height of microneedles were found to be 55.3 ± 5 µm, 679.8 ± 10 µm, and 914.7 ± 19 µm. Finally, the sharpness of the MN tips and the overall surface finish of the MN array were improved with ECP. The reductions in MNH, MNBW, and MNTW were reported to be −18.3%, −9.7%, and −95.4%, respectively, with a final tip width of 2.55 ± 1.62 µm. The MNs’ tip angle was reported to be 32.52° ± 1.56.
Exploring the origin of stronger survival of polarized vortex beams through scattering media
Authors: Paranjape Atharva , Guchhait Shyamal , B S Athira , Ghosh Nirmalya 
Published: July 2024

Abstract
Laguerre–Gaussian (LG) beams carrying orbital angular momentum (OAM) have shown promise in deep tissue imaging, medical diagnostics, and optical communication due to their robust propagation properties through scattering media. The insight on the mechanism for stronger survival of OAM carrying beam in tissue-like turbid media is expected to contribute towards a better understanding of light transport in the presence of scattering, as well as guide optimization of the intensity, phase, and polarization structure of light for use in biomedical applications like in tissue imaging. We examine the scattering properties by studying the propagation of polarized vortex beams transmitted through tissue-like turbid scattering media. We demonstrate that the intensity profile has a much more profound effect on depolarization than the phase profile for LG beams. Our results indicate that the observed stronger propagation for the higher-order LG beams is due to a higher anisotropy factor g, as seen by the incident beam. We have performed the degree of polarization measurements for the forward scattered light in the case of both LG beams and perfect vortex beams with varying topological charges. A comparison between the observed depolarization trends for the two classes of OAM-carrying beams suggests that the robust scattering properties of the LG beams originate from the intensity profile while the phase profile does not seem to play a major role in the stronger survival of OAM-carrying beam in turbid media.
Harnessing BN co-doping for superior thermal transport in phagraphene monolayer
Authors: Asfakujjaman  , Ghosh Mainak , Chowdhury Suman , Jana Debnarayan 
Published: July 2024

Abstract
In this study, we thoroughly explored the thermal transport and thermoelectric properties of BN-co-doped phagraphene structures in the context of first-principles computations combined with machine learning interatomic potential (MLIP) techniques. Our results demonstrate that doping positions can critically tune the thermal properties, offering potential advantages for both thermoelectric and heat transfer applications. Notably, enhanced thermal conductivity has been obtained for phagraphene with 10

%

co-doping. Additionally, the rectangular structural symmetry of phagraphene plays an important role for targeted thermal transport. Further, we observe negative Grüneisen parameter in these structures, suggesting negative thermal expansion. This will serves as an unique mechanism for controlling the thermal conductivity at different frequencies. Interestingly, n-type behavior of the structures is indicative of its negative Seebeck coefficient within the temperature range of 300–900 K. Moreover, these structures display significantly larger electrical conductivity compared to other two-dimensional (2D) materials. Apart from that, the calculated figure of merit of the structures under a constant relaxation time at 300 K shows considerably better response for some specific doped structures. We believe this study will play an important role in understanding the importance of structural modifications in tailoring the thermal properties of carbon-based 2D systems.
Novel ground state structures of N-doped LuH3
Authors: Verma Ashok K , Mishra Ajay K , Modak P 
Published: July 2024

Abstract

Ab-initio crystal structure searches have played a pivotal role in recent discoveries of high-Tc hydride superconductors under high pressure. Using evolutionary crystal searches, we predict novel ground state structures of N-doped LuH3 at ambient conditions. We find an insulating ground state structure for LuN0.125H2.875 (∼1.0 wt.% N), contrary to earlier studies where assumed structures were all metallic. This insulating behavior of ground state was found to persist up to ∼45 GPa. However our crystal structure searches revealed a metallic state for an H-deficient variant of LuN0.125H2.875. We study bonding characteristics of important structures by calculating electronic density of states, electronic-localization functions and Bader charges. Our Bader charge analysis shows that insulators have both H+ and H− ions whereas metals have only H− ions. We find that H+ ions are bonded to N atoms via a very short covalent bond. Thus we identify a clear relationship between formation of N–H bonds and insulating behavior of materials. Besides this, we perform crystal structure searches for three more compositions with higher N-content (>1.0 wt.%). Analysis of electronic properties shows that the ground states of these compositions are insulator.
High dynamic range structured illumination microscopy based on per-pixel coding
Authors: Qu Tong , Chai Changchun , Guo Jiahui , Wang Shuai , Ye Zhuohang , Li Zehao , Liu Xiaojun 
Published: July 2024

Abstract
Structured illumination microscopy (SIM) can achieve optical sectioning with high resolution, and have aroused extensive research interest. In SIM, a set of high-contrast illumination patterns are projected onto the sample to modulate the surface height information, and then, a decoding algorithm is applied to the modulated pattern images for high-quality optical sectioning. Applied to samples with large dynamic range of reflectivity, however, SIM may fail to achieve high quality sectioning for accurate surface reconstruction. Herein, an active digital micromirror device (DMD) based illumination method using per-pixel coded strategy is proposed in SIM to realize high-quality measurement for surface with complex reflection characteristics. In this method, the mapping relationship between DMD and the camera is established pixels by pixels, which enables the illumination intensity on the sample surface can be flexibly modulated by DMD pixel-level modulation corresponding to reflectivity distribution of the surface, and allows the camera pixels always to have reasonable exposure intensity for high precision measurement. More importantly, we put forward an adaptive light intensity control algorithm to improves the signal-to-noise ratio of acquired images without compromising modulation depth of pattern and measurement efficiency. Extensive comparative experiments were conducted and demonstrated that the proposed method can retrieve the surface morphology information of micro-scale complex reflectivity surfaces with high accuracy.
Signal enhancement method for gearboxes fault diagnosis in robotic flexible joint
Authors: Li Jianlong , Liu Xiaoqin , Wu Xing , Wang Dongxiao , Xu Kai , Lin Sheng 
Published: July 2024

Abstract
Motor current signal analysis (MCSA) provides a non-intrusive approach to fault diagnosis. However, the fault impact reacting in the current is reduced due to the presence of flexible structures in the transmission path from the fault source to the motor. Therefore, this paper proposes a method to enhance the frequency domain of the current signal of a single mechanical fault through a transfer model between motor torque and link vibration. First, the joint system dynamics model was developed based on a three-inertia simplified model. The transfer model of motor torque and link vibration was defined based on the system dynamics. The link vibration is then estimated based on the transfer model and electromagnetic torque. Link vibration signal is considered as an enhancement of the torque signal. Finally, the link vibration signature analysis is performed instead of MCSA. The experimental results show that the method is effective in enhancing the features of individual mechanical faults and improving the fault diagnosis performance.
A novel deformation measurement method for rotating blade based on PSO-ILS image correlation matching and mismatch correction
Authors: Wu Huilin , Sun Chuanzhi , Liu Yongmeng , Zou Limin , Tan Jiubin 
Published: July 2024

Abstract
Aiming at the problem of small measurement range and difficult measurement of traditional contact sensor method in the rotating state of aero-engine blades, this paper proposes a novel deformation measurement method for rotating blade based on image correlation matching and mismatch correction. Firstly, a Particle Swarm Optimization-Iterative Local Search image intelligent matching algorithm is proposed, which effectively balances global search and local optimization, and the image matching displacement accuracy reaches 10−3 pixel. Secondly, a mismatch point detection method based on multi-scale local Root Mean Square is proposed, and the high-precision detection of mismatch points is realized by considering the influence of local structure. Finally, through the hierarchical refinement of the sub-pixel level mismatch point correction method, the mismatch point is corrected in the two iterative stages of global search and local optimization. The corrected mismatch point response value K is reduced by 99% compared with that before correction, which further improves the accuracy of deformation field calculation. In the experiment, the deformation of the rotating blade of 4500 RPM is measured, which proves that the image intelligent matching algorithm and the deformation field calculation method proposed in this paper can provide new methods and technical support for the accurate measurement of the blade surface deformation.
Half-wave voltage controllable optical voltage sensor with arbitrary electric field direction modulation*
Authors: Lin Yifan , Xu Qifeng , Li Jun , Xie Nan , Yang Yang 
Published: July 2024

Abstract
An optical voltage sensor with an arbitrary electric field direction modulation (AEFDM) mode is proposed to increase the half-wave voltage. The mode is realized by heterogeneous electrodes arranged in a center-symmetric way, and generates an electric field with a direction at an arbitrary angle to the light propagation direction. The finite element method and coupling wave theory are used to design and optimize the electrodes and field distribution. The experimental results show that heterogeneous electrodes and AEFDM mode are able to regulate the sensor’s half-wave voltage in a range from 1 to 30 times (47–1409 kV), with 0.5 class accuracy and 99.99% linearity. This novel AEFDM method proposes a new electrode shape and position, reducing temperature drift to 50% compared to solid-state voltage divider method.
SNW YOLOv8: improving the YOLOv8 network for real-time monitoring of lump coal
Authors: Wu Ligang , Chen Le , Li Jialong , Shi Jianhua , Wan Jiafu 
Published: July 2024

Abstract
Due to its large size of coal and high mining output, lump coal is one of the hidden risks in mining conveyor damage. Typically, lump coal can cause jamming and even damage to the conveyor belt during the coal mining and transportation process. This study proposes a novel real-time detection method for lump coal on a conveyor belt. The space-to-depth Conv (SPD-Conv) module is introduced into the feature extraction network to extract the features of the mine’s low-resolution lump coal. To enhance the feature extraction capability of the model, the normalization-based attention module (NAM) is combined to adjust weight sparsity. After loss function optimization using the Wise-IoU v3 (WIoU v3) module, the SPD-Conv-NAM-WIoU v3 YOLOv8 (SNW YOLO v8) model is proposed. The experimental results show that the SNW YOLOv8 model outperforms the widely used model (YOLOv8) in terms of precision and recall by 15.82% and 11.71%, respectively. Significantly, the real-time detection speed of the SNW YOLOv8 model is increased to 192.93 f s−1. Compared to normal models, the SNW YOLO v8 model overcomes the disadvantages of normal models, such as being overweight, and the parameters of SNW YOLO v8 are reduced to only 6.04 million with a small model volume of 12.3 MB. Meanwhile, the floating point of SNW YOLOv8 is significantly reduced. Consequently, it demonstrates excellent lump coal detection performance, which may open up a new window for coal mining optimization.