bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic simulation research on urban green transformation under the target of carbon emission reduction: the example of Shanghai
Authors: Shang Hua , Yin Hailei 
Published: October 2023

AbstractThis paper aimed to predict the trend of carbon emissions during the green transformation process in Shanghai, with a focus on the city’s urban system structure. Green development has become an inevitable trend in urban progress, as traditional urban development has led to severe environmental problems caused by the emissions of a large amount of carbon dioxide. This study was motivated by the need for cities to actively pursue green transformation and achieve carbon peaking targets. Through a literature analysis, it was found that urban green transformation is influenced by various factors such as economy, energy, population, technology, and policy. Furthermore, carbon dioxide emissions primarily arise from fossil fuels and are regulated by carbon emission trading (CET) policies. With this knowledge, the urban system was divided, and the flow of carbon was analyzed. Using the general methodology of the IPCC, the carbon production resulting from energy consumption in Shanghai from 2014 to 2019 is calculated to construct an urban system dynamic (SD) model, which is used to predict the carbon emissions expected during the green transformation from 2020 to 2025. The key findings of the study are as follows: (1) The dynamic model of the urban green transformation system proved to be effective in predicting carbon emissions. (2) Based on the current status of green transformation in Shanghai, the city is capable of achieving its expected carbon emission peaking target by 2025. (3) The progress and timing of green transformation and carbon peaking in Shanghai vary across different scenarios, highlighting the importance of collective adjustments to identify the most appropriate path for urban green transformation. These findings provide valuable insights for cities seeking to adopt green development measures, facilitating the acceleration of their green transformation efforts and early attainment of carbon peaking targets.
Movement of Carnaby’s Cockatoo (Zanda latirostris) across different agricultural regions in Western Australia
Authors: Rycken Sam , Warren Kristin S , Yeap Lian , Jackson Bethany , Mawson Peter R. , Dawson Rick , Shephard Jill M. 
Published: October 2023

Context Carnaby’s cockatoos in Western Australia are experiencing ongoing population declines. Despite being highly mobile and adaptable, this endangered species has been impacted by fragmentation of its habitat, with an ongoing need for research on its movements in regional areas across its range to gain an understanding of habitat requirements, and to inform conservation plans. Aims This study aimed to determine whether regional differences in movement (distances travelled, revisitations and home range) exist for foraging and roosting behaviour for this species. Methods Movement analysis of satellite-tagged Carnaby’s cockatoos (n = 11) across three agricultural regions was conducted. Key results When comparing distances between roosts and daily foraging behaviour, no significant differences were found between regions (P ≥ 0.05). Resident home ranges (home ranges in areas of resident daily movement) of flocks were much larger in the Esperance region, however, showing differences in movement patterns between regions. Conclusions Because flocks were similar in size (n = ±300) between regions and used a similar amount of native vegetation for foraging (±20%), we concluded that movement may have been influenced by the spatial separation of patches of native vegetation. In addition, key foraging habitat often occurred within patches of non-native foraging species. Implications The information derived from this research has proven valuable in assessing the use of native vegetation in the landscape, identifying key habitat and determining daily and seasonal movement patterns. In addition, the importance of non-native food sources must be recognised and protection of native and non-native food sources must play a critical role in the species’ conservation management.
Discursive positioning of doctors and e‑patients in online medical consultations in China
Authors: Zhang Yu 
Published: October 2023

Abstract
This study investigates the identity positioning of doctors and e‑patients in online medical consultations (OMCs)
in China from the perspective of poststructuralist discourse analysis. Adopting positioning theory as the analytical framework,
the study examines 100 asynchronous text-based OMCs with the purpose of identifying the positions of the OMC participants and the
pragmatic function of these positions. The study found that the identity of e‑patients and doctors reflects multiple positions
that are constructed and negotiated in the OMC discourse, including the emotional support seeker/giver position, the online
buyer/seller position, the peer position, and the ‘family member’ position. Taken together, these positions can help establish an
affective relationality between doctors and e‑patients, which contributes to a positive image of the participants and to the
empowerment of e‑patients in particular.
Optimal design of strain sensor placement for distributed static load determination
Authors: Morris Benjamin K , Davis R Benjamin 
Published: October 2023

Abstract
In many applications it is desirable to inverse-calculate the distributed loading on a structure using a limited number of sensors. Yet, the calculated loads can be extremely sensitive to the placement of these sensors. In the case of predicting point loading applied at a known location, best results are typically achieved when one sensor is collocated with the force. However, the extension of this rule to distributed loading remains uncertain, and even simple sensor system design scenarios often require the designer to directly optimize the sensor placements using a numerical model. In an effort to provide designers with guidance, we identify optimal sensor configurations for predicting static distributed loads on beams with classical boundary conditions. An influence coefficient method, wherein the strain is related linearly to the static load, is used to estimate the applied forces. The loading distribution on the structure is assumed to be either a piece-wise linearly-distributed load or a uniformly-distributed load, allowing for distributed loads to be estimated using the magnitudes of a small number of control points. Given the simplicity of the beam structure, the equations of the influence coefficient method are derived analytically, which allows for the sensor placement to be specified using continuous optimization methods. The condition number of the influence coefficient matrix is used as a surrogate for error during optimization. ‘Rules of thumb’ for sensor placement are presented based on the optimization results. Results show that the optimal and rule-of-thumb sensor configurations are more resistant to input noise than naïve configurations, with the rule-of-thumb configurations yielding similar force predictions relative to the optimal configurations. We expect the rules of thumb to be useful guidelines for engineers designing tests on beam-like structures such as aircraft wings or marine propellers where the inverse calculation of distributed loads is of interest.
Effect of the number of magnetic matrices on particle capture in high gradient magnetic separation
Authors: Tian Yu , Cao Quanliang 
Published: October 2023

Abstract
A comprehensive understanding of the capture process involving matrices in high gradient magnetic separation (HGMS) is crucial for the design and improvement of matrix performance. However, few existing studies have paid attention to the influence of the number of magnetic matrices on the capture process. In this work, we numerically investigate this issue in both longitudinal and transversal HGMS systems, where multiple scenarios with different particle sizes, flow rates and matrix spacing are considered. Interestingly, we show that in most cases, increasing the number of magnetic matrices along the flow direction has little to no influence on the capture radius. It has a certain effect on improving the capture radius only in a few specific cases, such as when dealing with large particles at low flow rates with closely spaced matrices or when working with small particles at high flow rates with widely spaced matrices. These phenomena are related to the appearance of repulsive magnetic forces around matrices and the distribution characteristics of magnetic forces. The obtained results indicate that, in the design of the practical HGMS system, simply increasing the number of matrices along the flow direction may not be a reasonable or effective strategy for enhancing capture performance.
Black phosphorene/SnSe van der Waals heterostructure as a promising anchoring anode material for metal-ion batteries
Authors: Ahmed Dildar , Muhammad Nisar , Ding Z J 
Published: October 2023

Abstract
Black phosphorene (BP) is a glowing two-dimensional semiconducting layer material for cutting-edge microelectronics, with high carrier mobility and thickness-dependent band gap. Here, based on van der Waals (vdW)-corrected first-principles approaches, we investigated stacked BP/tin selenide (BP/SnSe) vdW heterostructure as an anode material for metal ion batteries, which exhibits a significant theoretical capacity, along with relatively durable binding strength compared to the constituent BP and SnSe monolayers. Our calculations demonstrated that the Li/Na adatom favors insertion into the interlayer region of BP/SnSe vdW heterostructure owing to synergistic interfacial effect, resulting in comparable diffusivity to the BP and SnSe monolayers. Subsequently, the theoretical specific capacities for Li/Na are found to be as high as 956.30 mAhg−1 and 828.79 mAhg−1, respectively, which could be attributed to the much higher storage capacity of Li/Na adatoms in the BP/SnSe vdW heterostructure. Moreover, the electronic structure calculations reveal that a large amount of charge transfer assists in semiconductor-to-metallic transition upon lithiation/sodiation, ensuring good electrical conductivity. These simulations verify that the BP/SnSe vdW heterostructure has immense potential for application in the design of metal-ion battery technologies.
Gaussian and Gaussian-pulsed-like Fermi velocity graphene structures
Authors: García-Cervantes H , Escalera Santos G J , García-Rodríguez F J , Rodríguez-González R , Rodríguez-Vargas I 
Published: October 2023

Abstract
Gaussian and Gaussian-related structures are quite attractive due to its versatility to modulate the electronic transport, including its possibility as electron filters. Here, we show that these non-conventional profiles are not the exception when dealing with Fermi velocity barriers in monolayer graphene. In particular, we show that Gaussian Fermi velocity graphene barriers (G-FVGBs) and Gaussian-pulsed-like Fermi velocity graphene superlattices (GPL-FVGSLs) can serve as electron band-pass filters and oscillating conductance structures. We reach this conclusion by theoretically studying the transmission and transport properties of the mentioned structures. The study is based on the continuum model, the transfer matrix method and the Landauer–Büttiker formalism. We find nearly flat transmission bands or pass bands for G-FVGBs modulable through the system parameters. The pass bands improve as the maximum ratio of Fermi velocities (

ξ

m
a
x

) increases, however its omnidirectional range is reduced. These characteristics result in a decaying conductance (integrated transmission) with

ξ

m
a
x

. The integrated transmission remains practically unaltered with the size of the system due to the saturation of the electron pass band filtering. In the case of GPL-FVGSLs the GPL profile results in regions of high transmission probability that can merge as flat transmission minibands if the pulse fraction and the superlattice parameters are appropriately tuned. The GPL profile also results in conductance (integrated transmission) oscillations that can be multiplied or reduced in number by adjusting the pulse fraction as well as the superlattice parameters.
Quantitative assessment for tooth crack of the sun gear in a planetary gearbox
Authors: Wang Jian , Liu Xianzeng , Zhang Jun 
Published: October 2023

Abstract
The sun gear in a planetary gearbox is prone to generate tooth crack due to its much more severe load conditions than other gears. The cracked sun gear will evolve into distinct tooth breakages and thus may deteriorate the operation status and even cause catastrophic loss of the whole transmission system. To avoid tooth crack induced malfunction of the planetary gearbox, the tooth crack of sun gear should be accurately identified during the early stage. Therefore, a novelty quantitative assessment methodology for tooth crack damage is proposed, which is a mathematical model for crack propagation of the sun gear in planetary gearboxes based on vibration acceleration signal. Firstly, the quantitative relationship between the crack propagation parameters along the gear thickness and width directions and the time-varying mesh stiffness is analytically formulated. The analytical time-varying mesh stiffness formulation is incorporated into a translational–torsional dynamic model to reveal the effects of crack propagation on the vibration signal of internal and external meshing pairs in the planetary gearbox. Secondly, a quantitative mapping function is established by taking the cracked section area as the variable and the residual of the summed envelope spectrum amplitude of the vibration acceleration signal as the assessment index. Finally, a numerical simulation as well as an experimental test is conducted and compared to verify the correctness of the proposed assessment methodology. We believe that the established model and the corresponding index provide a physically intuitive yet mathematically quantitative reference for diagnosing tooth crack in planetary gearboxes.
Linearity and nonlinearity of silicon photodiodes for accurate absolute optical flux measurements: a review
Authors: Tanabe Minoru 
Published: October 2023

Abstract
The accurate evaluation of linearity for an Si photodiode (PD) with respect to the incident optical flux is of great importance to determine a highly accurate range for the absolute optical flux that is more than six orders of magnitude. As such, various evaluation methods of linearity and nonlinearity have been proposed, and their feasibilities have been demonstrated. These methods can cover the flux range more than six orders of magnitude and the wavelength regions from ultraviolet to near-infrared, which are comprised in an Si PD. This paper describes previous accurate nonlinearity evaluation systems, experimentally measured nonlinearity results and their numerical analyses. The findings of this study could contribute to the accurate absolute optical flux measurements by using Si PDs.
A Gabor filter based weak crack detection method for glassivation passivation parts wafer
Authors: Lang Sizhe , Zheng Fei , Li Panyu , Meng Chao 
Published: October 2023

Abstract
Crack defects on the surface of glassivation passivation parts (GPP) wafers are a significant factor leading to chip functional failure. Thus, efficient and stable surface defect detection is required to ensure product quality. However, existing detection methods do not handle weak crack defects on the wafer surface with an inhomogeneous texture background effectively. To overcome this challenge, we propose a weak crack defect detection method for GPP wafers with complex backgrounds. First, a weak crack feature enhancement method is proposed based on the Gabor filter with different orientations. Then, the crack candidates are generated using the least-squares method to transform the shape-based information into a line segment and direction independence judgment. Finally, a line segment clustering method is implemented for the final crack defect recognition. Experimental results demonstrate that the proposed defect detection method works effectively and robustly with inhomogeneous texture backgrounds and satisfies the requirement of a real-time detection system.
Thermodynamical and spectral phase transition for local diffeomorphisms in the circle
Authors: Bomfim Thiago , Carneiro Victor 
Published: October 2023

Abstract
It is known that all uniformly expanding dynamics have no phase transition with respect to Hölder continuous potentials. In this paper we show that given a local diffeomorphism f on the circle, that is neither a uniformly expanding dynamics nor invertible, the topological pressure function

ℝ
∋
t
↦

P

t
o
p

(
f
,
−
t
log
|
D
f

|
)

is not analytical. In other words, f has a thermodynamic phase transition with respect to geometric potential. Assuming that f is transitive and that Df is Hölder continuous, we show that there exists

t

0

∈
(
0
,
1
]

such that the transfer operator

L

f
,
−
t
log

|

D
f

|

, acting on the space of Hölder continuous functions, has the spectral gap property for all

t
<

t

0

and has not the spectral gap property for all

t
⩾

t

0

. Similar results are also obtained when the transfer operator acts on the space of bounded variations functions and smooth functions. In particular, we show that in the transitive case f has a unique thermodynamic phase transition and it occurs in t
0. In addition, if the loss of expansion of the dynamics occurs because of an indifferent fixed point or the dynamics admits an absolutely continuous invariant probability with positive Lyapunov exponent then

t
0

=
1.
Constructive proofs for localised radial solutions of semilinear elliptic systems on
Rd
Authors: Bouwe van den Berg Jan , Hénot Olivier , Lessard Jean-Philippe 
Published: October 2023

Abstract
Ground state solutions of elliptic problems have been analysed extensively in the theory of partial differential equations, as they represent fundamental spatial patterns in many model equations. While the results for scalar equations, as well as certain specific classes of elliptic systems, are comprehensive, much less is known about these localised solutions in generic systems of nonlinear elliptic equations. In this paper we present a general method to prove constructively the existence of localised radially symmetric solutions of elliptic systems on

R

d

. Such solutions are essentially described by systems of non-autonomous ordinary differential equations. We study these systems using dynamical systems theory and computer-assisted proof techniques, combining a suitably chosen Lyapunov–Perron operator with a Newton–Kantorovich type theorem. We demonstrate the power of this methodology by proving specific localised radial solutions of the cubic Klein–Gordon equation on

R

3

, the Swift–Hohenberg equation on

R

2

, and a three-component FitzHugh–Nagumo system on

R

2

. These results illustrate that ground state solutions in a wide range of elliptic systems are tractable through constructive proofs.
Numerical finite-gap integration of the Zabusky–Kruskal problem
Authors: Li YuQi 
Published: October 2023

Abstract
The Zabusky–Kruskal problem (ZKP) is well-known ever since Zabusky and Kruskal performed their famous numerical experiment. It has become a benchmark for testing numerical schemes. However, the solution of the ZKP has no analytical expression and its long-time numerical integration is notoriously difficult. Now, after decades of effort both to develop new algorithms and to improve their performance, the best existing algorithm approaches machine accuracy for moderate evolution time. Here we solve the ZKP with high accuracy using the method of numerical finite-gap integration. The windfalls of the high accuracy are abundant: Many new analytical properties are discovered from the numerical results. The algorithms presented here can be regarded as a paradigm for high-accuracy numerical integration of large-genus algebro-geometric solutions.
Mechanical properties prediction of ferrite ductile iron via machine learning
Authors: Gu Shiyu , Yao Zhixuan , Li Mingwei , Qu Nan , Bu Erjun , Bai Xinshe , Liu Yong , Lai Zhonghong , Zhu Jingchuan 
Published: October 2023

Abstract
The rapid development of the wind power industry requires ductile iron to maintain high toughness while improving strength. Machine learning offers the possibility to accelerate various aspects of material development and performance optimization. In this paper, we established a composition-property dataset for ferritic ductile iron, and a variety of machine learning algorithms are compared to construct a composition-property model for ferritic ductile iron finally. The composition is chosen as the model input, and the outputs are four properties: tensile strength, Brinell hardness, yield strength and elongation. The correlation coefficients of the models constructed are above 0.96, and the mean absolute percentage errors are below 5%. The mean relative error between the model predictions and the experimental values is 4.43%, which effectively verifies the reliability of the composition-properties model of ductile iron constructed. This paper also uses the machine learning model to predict the effect law of each element content on the mechanical properties of ductile iron, and uses thermodynamic prediction of phase composition to verify the reliability of the machine learning method to predict the mechanical properties of ductile iron, which provides strong guidance for the design of new ductile iron with high strength and high plasticity at room temperature.
Generation of 1 GB full entropy random numbers with the enhanced-NRBG method
Authors: Aggarwal Deepika , Balaji R Karthick , Ghatikar Rohit , Chennuri Sruthi , Banerjee Anindita 
Published: October 2023

Abstract
Random numbers have significant applications in fundamental science, high-level scientific research, cryptography and several other areas where there is a pressing need for high-quality random numbers. We present an experimental demonstration of a non-deterministic random bit generator from a quantum entropy source and a deterministic random bit generator mechanism to provide high quality random numbers of 1 GB data size. Quantum entropy is realized by a series of quantum chips based on radioactive isotope Americium-241. The extracted raw random numbers are further post-processed to generate a high-entropy seed for the hash based deterministic random bit generator. We discuss the implementation of randomness extraction algorithm and Hash-DRBG algorithm in detail. The random numbers pass all the randomness measures provided in standard statistical test suites.