bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysing effective social media communication in higher education institutions
Authors: Capriotti Paul , Zeler Ileana 
Published: October 2023

AbstractThis paper aims to analyse the institutional communication of universities on social media by conducting a content analysis of the communication strategy of 70 higher education institutions (in the United States, Europe and Latin America). The study focuses on three social networks (Facebook, LinkedIn and Twitter) and the analysis three dimensions of social media institutional communication: posting, interactivity and content. Findings reveal that while most universities demonstrate a passive centripetal performance to posting, there is a significant divergence in relation to the level of activity. The study highlights that interactivity focus is predominantly characterised by monologues, despite institutions increasingly integrating various communication resources to foster stakeholder interaction. The majority of universities tend to prioritize exclusive or dominant content combination, with organizational content exhibiting a significantly greater presence. By an integrated analysis of these three key dimensions on social media, this paper this paper offers valuable insights for both academics and practitioners. It contributes to the scholars by facilitating further academic research on social media institutional communication and provides professionals with a practical guide for strategically managing communication on social media.
A sustainable solution to promote interest-based municipal solid waste management
Authors: Xin Fangkun , Wan Xingyue 
Published: October 2023

AbstractIncineration is a crucial option for municipal solid waste (MSW) management. How to deal with the “Not In My Back Yard” (NIMBY) movement in the construction of incineration stations has become a global public policy issue. This paper explores the impact of local authorities on MSW management when incineration is adopted to process municipal waste. The study uses four open cases from news reporting as the research data and applies the social network analysis (SNA) method for empirical analysis. Our results suggest that intervention by local authorities significantly improves the level of MSW management. The paper shows the following promotion mechanism: local authorities reconstructed the selected incentives of the residents who participated in the NIMBY movements based on their interests rather than on oppression. This is fundamentally different from the literature on how centralized regimes deal with protests. This paper addresses the need to research incineration stations’ impact on MSW management. It provides a specific reference for formulating policy recommendations that are relevant to green finance for MSW management.
A nonperturbative approach to Hawking radiation and black hole quantum hair
Authors: Wang Lan 
Published: October 2023

Abstract
We present a nonperturbative derivation of the subleading order in Hawking radiation based on diffeomorphism symmetry breaking during black hole evaporation. The diffeomorphism group of horizon admits a nontrivial phase factor which encodes information about infalling matter during formation. This nonintegrable phase represents the black hole quantum hair as it arises from the diffeomorphisms that change the physical state of the black hole. During evaporation, the decrease in total area breaks the diffeomorphism symmetry and leads to a dynamical shift in that phase factor. This shift affects the usual Hawking spectrum via dispersion relation and results in the subleading term in Hawking radiation. The higher order terms are locally insensitive to the Unruh radiation due to the lack of diffeomorphism groups on the local Rindler horizon at the low energy scale. This explains the generic difference between Hawking radiation and Unruh radiation. In addition, this phase shift indicates the decrease of the total number of degrees of freedom in horizon phase space during evaporation as past Page time. This enables us to escape from the firewall paradox and provide an account for the resolution to the information paradox.
Plasma characteristics of medium voltage AC air arc discharge and its application on arc electrical parameters calculation
Authors: Zhou Tong , Yang Qing , Yuan Tao , He Hengxin , Liu Hongwen 
Published: October 2023

Abstract
Medium voltage (MV) AC air arcs occur frequently in distribution networks. An electric arc can easily cause electrical fires, leading to serious accident consequences. Obtaining the electrical characteristics of arc faults through arc models is a crucial measure to detect and prevent arc faults. The arc electrical characteristics are affected by many factors such as the ambient air pressure, current magnitude, and arc length, and it is difficult to describe it in an analytical form. The widely used conventional black-box arc model reflects the influence of multiple factors on the electrical characteristics of arcs through fitting or empirical formulae. The model ignores the intrinsic physical and chemical processes, and the applicable range of the model is limited. Focusing on this problem, based on the physicochemical processes of the arc in the arcing and post-arcing stages, a relationship between the electrical and plasma characteristics of the MV AC air arc was established. Subsequently, the arc plasma characteristics were determined experimentally, and were applied to the calculation of the arc electric characteristics. Finally, the calculation results of the arc electrical characteristics were verified using the experimental results, providing a basis for related model improvements and applications.
Contrastive learning via swapped cluster assignments for bearing fault diagnosis
Authors: Wang Kai , Liu Chun , Chen Hongtian , Xiu Xianchao 
Published: October 2023

Abstract
In industrial scenarios, machinery and equipment operate in environments with many uncontrollable factors. These factors have a significant impact on vibration signals. For instance, differences in rotational speeds can make the collected data inconsistent. As a result, the tags collected from industrial environments are untrustworthy. It is impossible to know how many types of vibration signals are included in the dataset. In this paper, we propose a self-supervised pre-training method for bearing fault diagnosis called contrastive learning via swapped cluster assignments (CLSCA). Technically, CLSCA is based on momentum contrast (MoCo) and uses an unsupervised clustering algorithm to replace the classification of positive and negative samples in MoCo. By autonomously extracting representations from unlabelled datasets and then generating pseudo-labels using a clustering algorithm, CLSCA is able to learn in a self-supervised manner. When the value of the clustering center is in the appropriate range, the classification accuracy of CLSCA is improved by about

4
%

compared to MoCo.
Cross-medium imaging model and calibration method based on refractive optical path for underwater morphology measurement
Authors: Ding Tianhao , Sun Chen , Chen Jubing 
Published: October 2023

Abstract
Full-field optical morphology measurement methods are widely used in the shape measurement of underwater targets. The existing models and calibration methods in air could be invalid due to the refraction of light. To deal with these problems, this paper develops a cross-medium imaging model and a relative calibration method. In the modeling, the actual refraction optical path is considered when using arbitrary transparent structures. In the calibration, the accurate parameters of the model are first determined in the air environment and then updated by the refraction index replacement strategy. By using these methods, the accurate restoration of the morphology of objects in any medium is realized, and the inconvenience of underwater calibration process in prior methods can be avoided. The results of conducted experiments show that the accuracy of measurement can achieve 0.42%, which illustrates the validity of the proposed model and the precision of the proposed calibration method.
A method for compensating random errors in MEMS gyroscopes based on interval empirical mode decomposition and ARMA
Authors: Zeng Xin , Xian Sujie , Liu Kun , Yu Zhuolin , Wu Zhilin 
Published: October 2023

Abstract
The random error in micro-electro-mechanical systems (MEMS) gyroscopes is one of the major aspects that limit measurement accuracy. In order to address the inaccurate extraction of noise and trend during the signal preprocessing, as well as the subjectivity in autoregressive moving average (ARMA) model ordering, this paper proposes a method based on interval empirical mode decomposition and ARMA model. In the proposed method, the original signal is decomposed into a series of intrinsic mode functions (IMFs) and a residual through empirical mode decomposition (EMD). Based on the Hellinger distance and autocorrelation function, IMFs are then classified into noise IMFs, hybrid IMFs, and signal IMFs. The improved sand cat swarm optimization is utilized to optimize the ordering process of the ARMA model. The improved adaptive filter is adopted to compensate the random error, and the compensated signal is reconstructed with the signal IMFs and residual to obtain the final output. Experiments show that under static conditions, the proposed method could reduce the root mean square error (RMSE) by 52.6% and 33.3%, respectively, compared with the traditional EMD and ARMA methods. Under dynamic conditions, the proposed method could reduce the RMSE by 51.1% and 37.1%, respectively, compared with the traditional EMD and ARMA methods. The proposed method could effectively compensate the random error and improve the measurement accuracy of MEMS gyroscopes.
Conventional and pulsed hybrid triboelectric nanogenerator with tunable output time and wider impedance matching range
Authors: Shang Wanyu , Gu Guangqin , Ruan Haoran , Gu Guangxiang , Zhang Wenhe , Zhang Zhihao , Cheng Gang , Du Zuliang 
Published: October 2023

Abstract
Sliding grating-structured triboelectric nanogenerators (SG-TENGs) can multiply transferred charge, reduce open-circuit voltage, and increase short-circuit current, which have wide application prospects in self-powered systems. However, conventional SG-TENGs have an ultrahigh internal equivalent impedance, which reduces the output voltage and energy under low load resistances (<10 MΩ). The Pulsed SG-TENGs can reduce the equivalent impedance to near zero by introducing a synchronously triggered mechanical switch (STMS), but its limited output time causes the incomplete charge transfer under high load resistances (>1 GΩ). In this paper, a conventional and pulsed hybrid SG-TENG (CPH-SG-TENG) is developed through rational designing STMS with tunable width and output time. The matching relationship among grid electrode width, contactor width of STMS, sliding speed, and load resistance has been studied, which provides a feasible solution for simultaneous realization of high output energy under small load resistances and high output voltage under high load resistances. The impedance matching range is extended from zero to at least 10 GΩ. The output performance of CPH-SG-TENG under low and high load resistances are demonstrated by passive power management circuit and arc discharge, respectively. The general strategy using tunable STMS combines the advantages of conventional and pulsed TENGs, which has broad application prospects in the fields of TENGs and self-powered systems.
Structure, stability and electronic properties of zirconium nitride nanoclusters
Authors: Bhagowati Purbajyoti , Sahariah Munima B 
Published: October 2023

Abstract
Zirconium nitride (ZrN) is an industrial material having very high melting point, hardness and chemical stability. Compared to the bulk ZrN, its nanoclusters (NCs) are rarely explored. In this report, we generate a few ZrN NCs using ab initio molecular dynamics simulation. We investigate their electronic properties in terms of Bader charge, electron localization function and density of states. The obtained results are compared with their bulk counterpart. We also study the static and dynamical stability of the NCs with the help of binding energy, density of states and phonon dispersion spectra. The electron localization function of bulk ZrN is reported here for the first time to better understand its often confusing bonding behaviour.
Numerical investigation reveals challenges in measuring the contrast recovery coefficients in PET
Authors: Bayerlein Reimund , Spencer Benjamin A , Abdelhafez Yasser G , Cherry Simon R , Badawi Ramsey D , Omidvari Negar 
Published: October 2023

Abstract

Objective. Contrast recovery coefficient (CRC) is essential for image quality (IQ) assessment in positron emission tomography (PET), typically measured according to the National Electrical Manufacturers Association (NEMA) NU 2 standard. This study quantifies systematic uncertainties of the CRC measurement by a numerical investigation of the effects from scanner-independent parameters like voxel size, region-of-interest (ROI) misplacement, and sphere position on the underlying image grid. Approach. CRC measurements with 2D and 3D ROIs were performed on computer-generated images of a NEMA IQ-like phantom, using voxel sizes of 1–4 mm for sphere diameters of 5–40 mm—first in absence of noise and blurring, then with simulated spatial resolution and image noise with varying noise levels. The systematic uncertainties of the CRC measurement were quantified from above variations of scanner-independent parameters. Subsampled experimental images of a NEMA IQ phantom were additionally used to investigate the impact of ROI misplacement at different noise levels. Main results. In absence of noise and blurring, systematic uncertainties were up to 28.8% and 31.0% with 2D and 3D ROIs, respectively, for the 10 mm sphere, with the highest impact from ROI misplacement. In all cases, smaller spheres showed higher uncertainties with larger voxels. Contrary to prior assumptions, the use of 3D ROIs did not exhibit less susceptibility for parameter changes. Experimental and computer-generated images both demonstrated considerable variations on individual CRC measurements when background coefficient-of-variation exceeded 20%, despite negligible effects on mean CRC. Significance. This study underscores the effect of scanner-independent parameters on reliability, reproducibility, and comparability of CRC measurements. Our findings highlight the trade-off between the benefits of smaller voxel sizes and noise-induced CRC fluctuations, which is not considered in the current version of the NEMA IQ standards. The results furthermore warrant adjustments to the standard to accommodate the advances in sensitivity and spatial resolution of current-generation PET scanners.
MB-DECTNet: a model-based unrolling network for accurate 3D dual-energy CT reconstruction from clinically acquired helical scans
Authors: Ge Tao , Liao Rui , Medrano Maria , Politte David G , Williamson Jeffrey F , O’Sullivan Joseph A 
Published: October 2023

Abstract

Objective. Over the past several decades, dual-energy CT (DECT) imaging has seen significant advancements due to its ability to distinguish between materials. DECT statistical iterative reconstruction (SIR) has exhibited potential for noise reduction and enhanced accuracy. However, its slow convergence and substantial computational demands render the elapsed time for 3D DECT SIR often clinically unacceptable. The objective of this study is to accelerate 3D DECT SIR while maintaining subpercentage or near-subpercentage accuracy. Approach. We incorporate DECT SIR into a deep-learning model-based unrolling network for 3D DECT reconstruction (MB-DECTNet), which can be trained end-to-end. This deep learning-based approach is designed to learn shortcuts between initial conditions and the stationary points of iterative algorithms while preserving the unbiased estimation property of model-based algorithms. MB-DECTNet comprises multiple stacked update blocks, each containing a data consistency layer (DC) and a spatial mixer layer, with the DC layer functioning as a one-step update from any traditional iterative algorithm. Main results. The quantitative results indicate that our proposed MB-DECTNet surpasses both the traditional image-domain technique (MB-DECTNet reduces average bias by a factor of 10) and a pure deep learning method (MB-DECTNet reduces average bias by a factor of 8.8), offering the potential for accurate attenuation coefficient estimation, akin to traditional statistical algorithms, but with considerably reduced computational costs. This approach achieves 0.13% bias and 1.92% mean absolute error and reconstructs a full image of a head in less than 12 min. Additionally, we show that the MB-DECTNet output can serve as an initializer for DECT SIR, leading to further improvements in results. Significance. This study presents a model-based deep unrolling network for accurate 3D DECT reconstruction, achieving subpercentage error in estimating virtual monoenergetic images for a full head at 60 and 150 keV in 30 min, representing a 40-fold speedup compared to traditional approaches. These findings have significant implications for accelerating DECT SIR and making it more clinically feasible.
Image reconstruction from truncated fan-beam projections along a circular trajectory using the virtual fan-beam method
Authors: Charles Mathurin , Clackdoyle Rolf , Rit Simon 
Published: October 2023

Abstract

Objective. In this paper, we investigate how the virtual fan-beam (VFB) method can be used to perform mathematically correct 2D reconstruction in a region-of-interest (ROI), using truncated fan-beam projections acquired on a circular scan, for truncation that only occurs on one side of the object. Approach. We start by choosing a virtual fan-beam trajectory and specifying how to obtain the corresponding virtual projections. Then, three VFB formulas are obtained by applying known super-short-scan (SSS) formulas to this virtual trajectory. Two of them perform the backprojection in a virtual parallel geometry and the third in the virtual fan-beam geometry. Next, we develop two VFB formulas that perform the backprojection step in the fan-beam acquisition geometry. Main results. We present five VFB reconstruction formulas for this truncation setting. To our knowledge, the two VFB formulas performing the backprojection in the fan-beam acquisition geometry are new. Moreover, the five VFB formulas presented here obtain accurate reconstruction in a larger ROI than what has been previously reported in the literature in the same setting. A complete mathematical derivation of these five VFB formulas is given, and their implementation is described step by step. Numerical simulations, using the Forbild head and thorax phantoms, demonstrate the efficacy of these formulas. A spatial resolution analysis and a variance study indicate minor differences between these five VFB formulas. Significance. This work shows that many different VFB formulas can be applied to perform mathematically correct 2D reconstruction in a ROI, in case of truncated fan-beam projections acquired on a circular scan. Moreover, the two new VFB formulas, with backprojection in the acquisition geometry, may open the path for an extension of the VFB method to 3D reconstruction from transversely truncated cone-beam projection acquired on a circular scan.
Modelling intermittent anomalous diffusion with switching fractional Brownian motion
Authors: Balcerek Michał , Wyłomańska Agnieszka , Burnecki Krzysztof , Metzler Ralf , Krapf Diego 
Published: October 2023

Abstract
The stochastic trajectories of molecules in living cells, as well as the dynamics in many other complex systems, often exhibit memory in their path over long periods of time. In addition, these systems can show dynamic heterogeneities due to which the motion changes along the trajectories. Such effects manifest themselves as spatiotemporal correlations. Despite the broad occurrence of heterogeneous complex systems in nature, their analysis is still quite poorly understood and tools to model them are largely missing. We contribute to tackling this problem by employing an integral representation of Mandelbrot’s fractional Brownian motion that is compliant with varying motion parameters while maintaining long memory. Two types of switching fractional Brownian motion are analysed, with transitions arising from a Markovian stochastic process and scale-free intermittent processes. We obtain simple formulas for classical statistics of the processes, namely the mean squared displacement and the power spectral density. Further, a method to identify switching fractional Brownian motion based on the distribution of displacements is described. A validation of the model is given for experimental measurements of the motion of quantum dots in the cytoplasm of live mammalian cells that were obtained by single-particle tracking.
Discharge in electrospraying of highly conductive aqueous solution coated with outer ionic liquid
Authors: Cheng Yufeng , Wang Weizong , Yan Jiaqi , Wang Zhancheng 
Published: October 2023

Abstract
Discharge in electrospraying can be applied in water decontamination, dental sterilization, and spectrometry of biological samples. The discharge in electrospraying of a single liquid like the aqueous solution or the ionic liquid has been investigated, which presents different discharge characteristics such as patterns, currents and frequencies. This paper puts forward a way to actively control the discharge characteristics of liquids electrospray beyond the limitation of their own physical properties, which was accomplished by utilizing the technique of coaxial electrospray to coat the concentrated sodium chloride (NaCl) aqueous solution with a layer of ionic liquid. Previously we used this method to suppress the discharge of NaCl solution and stably electrosprayed the NaCl solution. The discharge characteristics of coaxial electrospray and the effect of the applied voltage and the flow rates of both liquids on the discharge was investigated in detail. When being electrosprayed, the NaCl solution alone discharged with pre-onset mode, pulseless corona discharge mode and streamer discharge mode, while the ionic liquid and the coaxial electrospray only discharged with the streamer discharge mode with a conical liquid shape, and less droplets were formed during the transient cone-jet emission. After being coated with the outer ionic liquid, the current, frequency and onset voltage of the discharge of the inner aqueous solution all increased. The current and frequency of the discharge of the coaxial electrospray all increased as the applied voltage increased. In addition, a numerical simulation has been conducted, which confirmed that the inner aqueous solution was strongly shielded from the external electric field by the outer ionic liquid layer. Therefore, it is plausible to actively control the discharge characteristics of the liquids through adjusting the flow rates of both liquids, the applied voltage and choosing the suitable outer liquid.