bluuebunny/crossref_metadata_2025 huggingface dataset:
A review of viral and parasitic infections in wild deer in Australia with relevance to livestock and human health
Authors: Huaman Jose L. , Helbig Karla J. , Carvalho Teresa G. , Doyle Mark , Hampton Jordan , Forsyth David M. , Pople Anthony R. , Pacioni Carlo
Published: July 2023

Wild animals harbour a diverse range of pathogens. In Europe and North America, cervids (Family Cervidae) can act as reservoirs for viral, prion, bacterial, and parasitic infections. Wild deer often inhabit agricultural land, therefore representing a biosecurity risk due to their potential ability to transmit diseases to livestock. Multiple studies have investigated the infection status of wild deer in Australia, mostly during the 1970s and 1980s, and deer populations have increased greatly in abundance and distribution since then. Those studies provide an important baseline for the pathogens carried by wild deer in Australia but are limited by small sample size, the small number of deer species studied, and the disease detection methods used. Recent investigations using ELISA (Enzyme-Linked Immunosorbent Assay), PCR-based assays, and next-generation sequencing have substantially increased our understanding of viral and parasitic infections in Australian deer. These studies indicate that deer may act as reservoirs for pathogens such as Pestivirus, Neospora caninum and Entamoeba bovis. The use of next-generation sequencing has led to the discovery of novel viruses such as Picobirnavirus and a novel species of the genus Bopivirus, both of which pose transmission risks for domestic animals. Recent research confirms that wild deer could be a future source of viral and parasitic infections for domestic livestock and other wildlife species.
Pampas fox spatial and temporal variation in Argentinean agroecosystems
Authors: Gorosábel Antonella , Barral María Paula , Bernad Lucía , Muñoz Sebastián Darío , Bernardos Jaime , Pedrana Julieta
Published: July 2023

Context Agricultural activities have reduced wildlife natural habitats and increased the spatial overlap between animals’ distribution and human activities. However, carnivores with a broad diet and flexible habitat requirements can tolerate human-induced environmental changes. Thus, identifying changes in their densities and spatial distribution are important factors to take into consideration when working towards minimising human–carnivore conflict. Aims Our aim was to identify the main environmental and human variables influencing Pampas fox density and to produce density maps in the reproductive and non-reproductive seasons. Methods We performed spotlight counts at night, following the line transect method in the non-reproductive and reproductive seasons during two consecutive years. We also obtained landscape, human-impact and environmental spatial variables using remote sensing data and Geographic Information Systems. We modelled and mapped the Pampas fox’s spatial density using Density Surface Models. Key results We found that disturbance by human activities and landscape configuration influenced the spatial variation of the Pampas fox density across time and space. We registered a positive association between the number of foxes and the proximity to urban areas and paved roads, and we also found higher densities near grasslands areas and less modified habitats varying with the season and year. A higher density of foxes was observed in the non-reproductive season compared with the reproductive season. Conclusions and Implications This study provides insight on the variation in Pampas fox densities across agroecosystems. It highlights the relevance of more naturalised and protected habitats to sustain the Pampas fox population in highly fragmented landscapes, but also shows a positive association with disturbed areas. The spatial information developed in this study is useful to identify areas where ecosystem services could be encouraged, helping to maintain the ecosystems’ equilibrium and biodiversity conservation, and develop new management programs creating human–wildlife coexistence.
The human milk component
myo
-inositol promotes neuronal connectivity
Authors: Paquette Andrew F. , Carbone Beatrice E. , Vogel Seth , Israel Erica , Maria Sarah D. , Patil Nikita P. , Sah Saroj , Chowdhury Dhrubajyoti , Kondratiuk Ilona , Labhart Beau , Morrow Ardythe L. , Phillips Shay C. , Kuang Chenzhong , Hondmann Dirk , Pandey Neeraj , Biederer Thomas
Published: July 2023

Effects of micronutrients on brain connectivity are incompletely understood. Analyzing human milk samples across global populations, we identified the carbocyclic sugar
myo
-inositol as a component that promotes brain development. We determined that it is most abundant in human milk during early lactation when neuronal connections rapidly form in the infant brain.
Myo
-inositol promoted synapse abundance in human excitatory neurons as well as cultured rat neurons and acted in a dose-dependent manner. Mechanistically,
myo
-inositol enhanced the ability of neurons to respond to transsynaptic interactions that induce synapses. Effects of
myo
-inositol in the developing brain were tested in mice, and its dietary supplementation enlarged excitatory postsynaptic sites in the maturing cortex. Utilizing an organotypic slice culture system, we additionally determined that
myo
-inositol is bioactive in mature brain tissue, and treatment of organotypic slices with this carbocyclic sugar increased the number and size of postsynaptic specializations and excitatory synapse density. This study advances our understanding of the impact of human milk on the infant brain and identifies
myo
-inositol as a breast milk component that promotes the formation of neuronal connections.
Preexisting social ties among Auschwitz prisoners support Holocaust survival
Authors: Bělín Matěj , Jelínek Tomáš , Jurajda Štěpán
Published: July 2023

Survivor testimonies link survival in deadly POW camps, Gulags, and Nazi concentration camps to the formation of close friendships with other prisoners. To provide evidence free of survival bias on the importance of social ties for surviving the Holocaust, we study individual histories of 30 thousand Jewish prisoners who entered the Auschwitz-Birkenau concentration camp on transports from the Theresienstadt ghetto. We ask whether the availability of potential friends among fellow prisoners on a transport influenced the chances of surviving the Holocaust. Relying on multiple proxies of preexisting social networks and varying social-linkage composition of transports, we uncover a significant survival advantage to entering Auschwitz with a larger group of potential friends.
Microstructural evolution of Ag-0.20wt-%Mg-0.19wt-%Ni alloy in under-oxidized condition
Authors: Li ZiYang , Huang Kai , Zhu Gang , Zuo XinLang , Chen ChengCheng
Published: July 2023

The under-oxidized condition (insufficient internal oxidation) for Ag-0.20Mg-0.19Ni (in wt-%) alloy was conducted at 650°C for 2 h, and the microstructural evolution in the alloy was investigated. The average grain size of the oxidized region and the unoxidized region are 3.82  µm and 3.86 [Formula: see text]m, respectively. The results suggest that the oxides enriched at grain boundaries do not hinder grain growth in the under-oxidized condition. The hardness of the oxidized region increases significantly, while the hardness of the unoxidized region decreases due to recrystallization. Both the number and the distribution area of MgO precipitates at the grain boundaries are increased with the internal oxidation time. Additionally, small MgO precipitates merge to form larger oxide particles with the internal oxidation time.
Determining Lamé coefficients by the elastic Dirichlet-to-Neumann map on a Riemannian manifold
Authors: Tan Xiaoming , Liu Genqian
Published: July 2023

For the Lamé operator

with variable coefficients λ and µ on a smooth compact Riemannian manifold (M, g) with smooth boundary

∂
M

, we give an explicit expression for the full symbol of the elastic Dirichlet-to-Neumann map

Λ

λ
,
μ

. We show that

Λ

λ
,
μ

uniquely determines the partial derivatives of all orders of the Lamé coefficients λ and µ on

∂
M

. Moreover, for a nonempty smooth open subset

Γ
⊂
∂
M

, suppose that the manifold and the Lamé coefficients are real analytic up to Γ, we prove that

Λ

λ
,
μ

uniquely determines the Lamé coefficients on the whole manifold

M
ˉ

.
Subsampling in ensemble Kalman inversion
Authors: Hanu Matei , Latz Jonas , Schillings Claudia
Published: July 2023

We consider the ensemble Kalman inversion (EKI) which has been recently introduced as an efficient, gradient-free optimisation method to estimate unknown parameters in an inverse setting. In the case of large data sets, the EKI becomes computationally infeasible as the data misfit needs to be evaluated for each particle in each iteration. Here, randomised algorithms like stochastic gradient descent have been demonstrated to successfully overcome this issue by using only a random subset of the data in each iteration, so-called subsampling techniques. Based on a recent analysis of a continuous-time representation of stochastic gradient methods, we propose, analyse, and apply subsampling-techniques within EKI. Indeed, we propose two different subsampling techniques: either every particle observes the same data subset (single subsampling) or every particle observes a different data subset (batch subsampling).
Rydberg-dressed Bose–Einstein condensate with spin–orbit coupling confined in a radially periodic potential
Authors: Tu Pu , Wang Qingqing , Shao Kaihua , Zhao Yuexing , Ma Jinping , Su Ruiming , Shi Yuren
Published: July 2023

The use of Rydberg dressing technology to achieve long-range soft-core interaction in Bose–Einstein condensates (BECs) opens up new avenues for exploration of supersolid and its related phenomenon. We investigate the ground state of a two-component spin–orbit-coupled BECs with both long-range soft-core and contact interactions in radially periodic potentials. Our results show that the ground-state structures of the system are strongly influenced by spin–orbit coupling, contact interactions, long-range soft-core interactions, and the amplitude of the external potential. We find that such parameters can been used to induce desired ground-states structures, such as necklace structure of lump, striped standing wave, and especially ring dark soliton. Furthermore, we observe that the long-range soft-core interactions are used to manipulate the transition between miscible-immiscible phases like contact interactions. Our research provides another degree of freedom for manipulating supersolids in spin–orbit-coupled BECs.
The influence of electric circuit parameters on NOx generation by transient spark discharge
Authors: Janda Mário , Hensel Karol , Machala Zdenko , Field Thomas A
Published: July 2023

Nitrogen fixation, production of NO and NO2 from N2 and O2 in air, has been investigated with transient spark self-pulsing DC discharges. NO production is boosted by the addition of capacitors and an inductor to the electrical circuit which drives the discharge. The quantity of NO produced per joule of electrical input energy is doubled, though the quantity of NO2 produced drops. The yield of NO is also increased because the modified circuit enables higher discharge currents to be used. NO concentrations as high as 2000 ppm were obtained with input energy densities of around 300 J per liter of input gas, whilst NO2 concentrations were around 150 ppm. This simple modification of the driving circuit may have potential for optimizing the plasma chemistry with other input gas mixtures and for scaling up nitrogen fixation from air.
Dynamic modeling and performance evaluation of piezoelectric impact drive system based on neural network
Authors: Chen Wenhao , Xia Haojie , Song Rencheng , Pan Chengliang
Published: July 2023

In metrology and industrial design, the evaluation of measurement uncertainty and error is crucial to the measurement process. The Guide to the Expression of Uncertainty in Measurement and its supplementary documents have established a unified framework and standard for evaluating measurement uncertainty. However, a reasonable method for evaluating dynamic measurement uncertainty has not yet been proposed. By analyzing the dynamic measurement system, and using the long short-term memory time neural network to model the nonlinear dynamics represented by a piezoelectric drive platform, this paper evaluates the system’s dynamic measurement uncertainty through deep integration methods. Bayesian theory is used to propagate probability densities, and experimental results demonstrate the effectiveness of this method for assessing dynamic measurement uncertainty.
Dimensional measurement of anti-stress cone of HV cable joints based on 3D point cloud
Authors: Zheng Zhihao , Gao Yuqun , He Zebin , Wang Chaoyang , Xie Hao , Liu Guihua
Published: July 2023

To solve the problem of automatic measurement of anti-stress cone of high voltage cable joints, a measurement algorithm based on 3D point cloud is proposed. Firstly, denoising and coordinate adjustment of point cloud of a cable joint are realized. Then the characteristic curve model of fitting circle radius indicating structure characteristic of cable joints is constructed by fitting circles with random sample consensus algorithm. After that, the discrete points on the characteristic curve are extracted according to the characteristics such as the fluctuation range of the characteristic curve for straight line fitting and the intersection of the fitted lines is calculated to complete the segmentation of the anti-stress cone area of the cable joint. Finally, the parameter measurement of the anti-stress cone was completed according to the structure of the anti-stress cone, and the error correction post-processing was performed. Two types of cable joint point clouds with standard dimensions and surface defects were used for measurement experiments, the absolute errors of the measurement results are less than 0.2 mm and 1.0 mm respectively, and the relative errors are less than 0.25% and 2% respectively, indicating that the proposed method has high robustness and measurement accuracy, which meet the measurement requirements in engineering practice.
An explainable unsupervised learning framework for scalable machine fault detection in Industry 4.0
Authors: Asutkar Supriya , Tallur Siddharth
Published: July 2023

Despite the diverse number of machine learning algorithms reported in the literature for machine fault detection, their implementation is mainly confined to laboratory-scale demonstrations. The complexity and black-box nature of machine learning models, the processing cost involved in appropriate feature extraction, limited access to labeled data, and varying operating conditions are some of the key reasons that curtail their implementation in practical applications. Furthermore, most such models serve as decision support tools, aiding domain experts in root cause analysis, and are not truly autonomous by themselves. To address these challenges, we present a lightweight autoencoder-based unsupervised learning framework to accurately identify machine faults against the changing operating conditions in a real-world scenario. The fault detection strategy is further strengthened by a model agnostic Shapley Additive exPlanations (SHAP)-based method (kernel SHAP) for identifying the most prominent features contributing to fault detection inference, the findings of which are then explored for identifying trends and correlations among prominent features and various types of faults. The framework is validated using two widely used and publicly available datasets for machine condition monitoring, as well as a large industrial dataset comprising 18 machines installed at three factories in India, monitored for several months.
Study on the water detection using the flowmeter method at low temperatures
Authors: Geng Jian , Wang Xiaodong , Ren Zhengyi , Xi Zhenhua , Li Lishan , Zhang Hai , Tao Wenze , Guo Meiru
Published: July 2023

To prepare for the lunar water exploration in the Chinese Lunar Exploration Project IV, a new apparatus for studying characteristics of the water vapor conductance and water detection at low temperatures was built based on the flowmeter method, and the performance of the miniature time-of-flight mass spectrometer (TOF-MS) for water detection in the range −20 to 20 °C was measured. The through-put within the range of 3 × 10−9–9 × 10−6 Pa m3 s−1 was provided at temperatures in the range −60 to 20 °C. The conductance of the orifice with a diameter of 21 µms for three gases (N2, Ar, and H2O) was measured at low temperatures. The diameter change of the metal orifice caused by the cold contraction in the molecular flow state is the main factor affecting the conductance, and the viscosity characteristic of gas in the viscous flow state is the main factor affecting the conductance. Therefore, the conductance of the orifice increases with the decreasing temperature when the through-put is high. In addition, the water vapor can be stably supplied by the orifice under low temperatures, and the conductance of water vapor through the orifice is measured through the on-line method and the time-ratio method. The adsorption rate and amount of water vapor on the metal surface increase with the decreasing temperature, hence the concentration of water molecules in the test dome significantly decreases as the temperature decreases. Finally, the through-put of water vapor of 8.75 × 10−8 Pa m3 s−1 was detected by the miniature TOF-MC at −20 °C on the apparatus.
Bearings fault diagnosis method based on MAM and deep separable dilated convolutional neural network
Authors: Lei Chunli , Shi Jiashuo , Ma Shuzhen , Xue Linlin , Jiao Mengxuan , Li Jianhua
Published: July 2023

Aiming at the problems of traditional fault diagnosis methods that do not represent the time correlation between signals, low recognition accuracy under complex working conditions and noise interference and too many parameters, a bearing fault diagnosis method based on mixed attention mechanism (MAM) and deep separable dilated convolution neural network (DSDCNN) is proposed. Firstly, a Markov transfer field encoding method is used to transform the original one-dimensional vibration signal into a two-dimensional feature image with temporal correlation. Secondly, a deep separable convolution algorithm is presented by taking advantage of the low computational complexity of deep separable convolution and the ability of dilated convolution to expand the receptive field under the condition of invariable number of parameters. Then, the MAM is designed to make the model capture the feature dependency of the feature map in spatial and channel dimensions, and the MAM-DSDCNN model is constructed. Finally, the fault diagnosis performance of the proposed model is verified with two different data sets. The results show that the average recognition accuracy of MAM-DSDCNN reaches 99.63% under variable load conditions, 99.42% under variable speed conditions, 94.26% under noisy environment with the signal-to-noise of 0 dB, which prove that the model has higher recognition accuracy, stronger generalization and noise immunity performance than other deep learning algorithms.
A distributed multi-area power system state estimation method based on generalized loss function
Authors: Chen Tengpeng , Liu Fangyan , Li Po , Sun Lu , Amaratunga Gehan A J
Published: July 2023

For power system state estimation, the measurement noise is usually assumed to follow the Gaussian distribution, and the widely used estimator is the weighted least squares (WLS). However, the Gaussian distribution assumption is not always true, and the performance of WLS becomes bad when the measurement noise is non-Gaussian. In this paper, a new distributed state estimation (SE) method is proposed for multi-area power systems. The proposed distributed method is based on the generalized loss function so that it can reduce the influence of non-Gaussian noise and bad data. Further, thanks to the matrix-splitting technology, the proposed distributed method can be implemented in a distributed way so that the computation time in each local area can be reduced. The simulation results carried out in the IEEE 30-bus and 118-bus systems verify the robustness and effectiveness of the proposed distributed SE method.
Ni6Se5, an unexplored transition metal chalcogenide of formula M(n+1)X
n
(2 ≤ n ≤ 8), for high-performance hybrid supercapacitor and Li-ion battery application
Authors: Dey Nikita , Raha Himadri , Das Debasish , Ray Samit Kumar , Guha Prasanta Kumar
Published: July 2023

This work reports an in situ, one-step hydrothermal preparation procedure of a binder-free electrode growth of Ni6Se5 on nickel foam (Ni6Se5/NF) with a rod-like structure. Ni6Se5 is an enveloped transition metal chalcogenides of formula M(n+1)X
n
(where 2 ≤ n ≤ 8, M is a transition metal and X is chalcogen) of the nickel selenide family. The Ni6Se5/NF electrode described here demonstrates an exceptional lifetime of 81% capacitance retention over 20000 cycles and a high specific capacitance of 473.5 Fg−1 at a current density of 4 Ag−1. The Ni6Se5/NF/activated carbon asymmetric supercapacitor (SC) exhibits a remarkable 97.3 Whkg−1 energy density and a 2325 Wkg−1 power density. Ni6Se5 served as an active electrode material in SC applications and offered exceptional power density and long cycle life. Ni6Se5/NF, used as an anode for Li-ion batteries, has a lithium storage capacity of 939.7 mAhg−1 at 100 mAg−1 current density. Ni6Se5’s (active electrode material) excellent energy storage capability, which was previously unreported, is particularly beneficial for electrochemical energy storage device applications.
Simulations of driven breathing modes of a magnetically shielded Hall thruster
Authors: Perales-Díaz J , Domínguez-Vázquez A , Fajardo P , Ahedo E
Published: July 2023

The operation of a 5 kW-class magnetically shielded Hall effect thruster with sinusoidal modulation of the discharge voltage is investigated through simulations with a 2D axisymmetric hybrid (particle-in-cell/fluid) code. The dynamic response of the thruster for different modulation amplitudes and frequencies is presented and discussed. The analysis of partial efficiencies contributing to thrust efficiency allows identifying counteracting effects limiting net gains in performance figures. Voltage modulation enhances the amplitude of plasma oscillations and can effectively control their frequency when the modulation frequency is close to that of the natural breathing mode (BM) of the thruster. The 2D plasma solution reveals that the dynamics of the ionization cycle are governed by the electron temperature response, enabling a driven BM at the modulation frequency. For modulation frequencies far from the natural BM one, voltage modulation fails to control the plasma production via the electron temperature, and the natural BM of the thruster is recovered. High order dynamic mode decomposition applied to the 2D plasma solution permits analyzing the complex spatio-temporal behavior of the plasma discharge oscillations, revealing the main characteristics of natural and externally driven modes.
A 35 V–5 V monolithic integrated GaN-based DC–DC floating buck converter
Authors: Zhu Yuhao , Su Haodong , Li Fan , Li Ang , Lei Xiaohaoyang , Cui Miao , Lai Wen-Cheng , Wen Huiqing , Liu Wen
Published: July 2023

The paper presents the development of a GaN DC–DC power converter with a pre-driver module and power device based on a monolithic integrated GaN E/D-mode metal–insulator–semiconductor high electron mobility transistors (MIS-HEMTs) platform. The pre-driver module with direct coupled field effect transistor logic circuit structure has been monolithically integrated with a GaN power transistor on a Si-based AlGaN/GaN commercial epitaxial wafer. The MIS-HEMTs structure adopts an insulated gate dielectric layer to suppress the leakage current and increase gate voltage robustness. The GaN-based floating buck converter employs a 1 mH inductor and a 9 μF capacitor to achieve 35 V–5 V power conversion. As a result, the pre-driver module is capable of delivering a 10 V driving voltage. GaN monolithic integration of the pre-driver module and power device can reduce the system area in the DC–DC application, which allows for an integrated chip size of 1.8 mm2.
Design and performance study of a piezoelectric beam conveyor based on the standing wave principle
Authors: Wu Zhiwei , Li Chaofeng , Zhu Binbin , Li Ying
Published: July 2023

Due to the interference of the magnetic field, regular motors are not suitable for precision transport in strong magnetic fields. With their insensitivity to magnetic fields, piezoelectric materials can be used to develop novel conveyors to bridge that gap. This paper aims to develop a simple piezoelectric beam conveyor based on the standing wave principle, and explore the effect of the height of the teeth on the piezoelectric beam and the number of piezoelectric plates on the motion. Based on the Euler–Bernoulli beam theory and Lagrange equation, the Chebyshev polynomial is used as the admissble displacement function to establish the numerical model. And the ANSYS is used to verify the correctness of the numerical model calculation results. It is analyzed the effect of tooth height on motion efficiency from theory and experiment, respectively. And the effects of voltage amplitude, frequency, preload force, and the driving quantity of piezoelectric plates on the slider motion speed and driving force are discussed. The conclusion is informative for the selection of tooth and preload force.
Low power single flux quantum qubit control circuit without high-frequency input
Authors: Weng Bicong , Peng Wei , Ren Jie
Published: July 2023

The use of high-frequency input signals from room-temperature microwave sources makes it difficult to scale up the number of quantum bits in universal quantum computers. To address this issue, superconducting single flux quantum (SFQ) integrated circuits are being explored as suitable candidates for qubit manipulation in universal quantum computers. This paper deals with a scalable SFQ qubit control circuit (SQCC) structure that requires only low-frequency input. The circuit mainly consists of a pulse generator and a counter, that output the SFQ pulse train with adjustable frequency and a controllable number of pulses, which is applicable to control single-qubit Clifford operations. The design of low-voltage rapid single flux quantum (LV-RSFQ) and energy-efficient rapid single flux quantum (ERSFQ) for the SQCC achieves low power consumption and provides a basis for scaling up SQCC to control more qubits. The proposed circuits are fabricated under the SIMIT-Nb03 process and successfully pass test verification. The achieved test results reveal that the adjustable output frequency ranges of the SQCC based on the LV-RSFQ and ERSFQ designs in order are [2.40, 8.11] GHz and [4.81, 5.14] GHz. In the operating frequency range, the circuit is able to generate the correct number of SFQ pulses under control. The controllable number range is from 1 to 128. When the circuits operate at 5 GHz, the total power consumptions of the above circuits in order are 23.88 μW and 6.2 μW. All input signals are low-frequency signals, which frees the control of large-scale qubits from limitations caused by high-frequency inputs produced by room-temperature microwave sources.
Influences of quenching treatment and cobalt-doping on the thermally activated flux-flow behavior in KCa2(Fe 1−x
Co
x
)4As4F2
Authors: Liu Yixin , Wang Teng , Xu Zulei , Hong Wenshan , Peng Wei , Lin Zhi-Rong , Luo Huiqian , Mu Gang
Published: July 2023

Owing to the unique double-FeAs-layered structure between neighboring insulating layers, the 12442-type Fe-based superconductors are expected to host rich vortex phenomena in the mixed state. Here, we report a systematic investigation on the influences of quenching treatment and cobalt-doping on the magnetic vortex dynamics of KCa2(Fe

1
−
x

Co
x
)4As4F2 (x = 0, 0.1) single crystals via electrical transport measurements. It is found that the slopes of the upper critical field near Tc
,

d

μ
0

H

/

d

T

|

T
c

along both directions (

H
⊥
c

and

H
∥
c

), are doubled by the cobalt-doping with x = 0.1. The activation energy is acquired by analyzing the Arrhenius plots, which shows a H
−α
dependence with a change in the exponent α at around 3 T, indicating the evolution of the dominant pinning mechanisms in different field regions. Importantly, the quenching treatment obviously enhances the magnitude of activation energy and critical current density J
c, which can be suppressed by the introduction of cobalt-doping. Possible mechanisms for such evolutions of these important parameters are discussed. Our results emphasize the important role of quenching treatment in enhancing the activation energy and critical current density in 12442 system.
A new Abel inversion algorithm by using legendre polynomials
Authors: Pang Mingqi , Shi Zelin , Liu Haizheng , Dan Liu  , Zhang Daijun
Published: July 2023

Abel’s integral equation is frequently used in many areas of physics to reconstruct the radial physical quantity distribution from its projection data. In this paper, a new effective and accurate Abel inversion algorithm based on shifted Legendre polynomials is proposed and analyzed. The proposed method is derivative-free and singularity-free. Both the input projection data and the unknown solutions of the Abel’s integral equation are approximately expressed as Legendre expansions. A Legendre operational matrix of integral is constructed and then reduced to a discrete algebraic sum, which makes it easy and fast to compute the coefficients matrix of approximate solutions for the inverse Abel transform. Finally, the accuracy and stability are proved and then illustrated by some numerical experiments widely used in plasma diagnostics.
Optical and electrical modeling of CZTSSe based thin-film solar cells
Authors: Mohamed H A , Taya YA , Ali Sh S , Mohamed W S
Published: July 2023

This research utilized an optical and electrical model to examine the impact of optical and recombination losses on the short circuit current density, J

sc
, and conversion efficiency of thin-film solar cells based on n-CdS/p-CZTSSe with ITO frontal charge-collecting contacts. By analyzing the optical properties of the components, we were able to calculate the amount of light that was lost as a result of absorption in the ITO and CdS layers and as a result of reflection at all interfaces. The impact of using antireflection coating on the optical losses was studied. Recombination losses were calculated quantitatively by varying the CZTSSe thickness and depletion area width. It was found that the antireflection layer reduced the optical losses up to 20%. The minimum value of the recombination losses is about 11% of what is observed at a width more than 1 μm, and that the width of the depletion layer has a significant impact in the value of J

sc
. Most of the incoming photons were absorbed by a layer of CZTSSe 3–4 μm thick. At these thicknesses, the recombination losses were considered low and recorded 16%. At reasonable values for the parameters employed, the efficiency of 14% is achievable.
The Detection of Possible γ-Ray Quasi-periodic Modulation with ∼600 days from the Blazar S2 0109+22
Authors: Zhang Haoyang , Wu Fan , Dai Benzhong
Published: July 2023

In this work, we analyzed the long-term γ-ray data by a Fermi Large Area Telescope of blazar S2 0109+22, ranging from 2008 to 2023. The quasi-periodic oscillations (QPOs) of blazars aided in investigating the physical properties of internal supermassive black holes, the nature of variability, and the underlying radiation mechanism. We employed four different methods—Weighted Wavelet Z-transform, Lomb–Scargle periodogram, REDFIT and phase folded light curve analysis, for searching QPO signals. Our analysis identified a possible QPO behavior with a periodicity of ∼600 days in 2013 November–2023 January at a significance level of ∼3.5σ. This QPO signal sustained ∼9 yr, corresponding to 5.6 cycles, which was in good agreement with the previously observed periodicity of ∼657 days in radio. We explained this phenomenon based on the accretion model and the lighthouse effect, in a binary black hole system.
Effect of surface modification on the radiation stability of diamond ohmic contacts
Authors: Mu 牟 Lian-Xi 恋希 , Zhao 赵 Shang-Man 上熳 , Wang 王 Peng 鹏 , Yuan 原 Xiao-Lu 晓芦 , Liu 刘 Jin-Long 金龙 , Zhu 朱 Zhi-Fu 志甫 , Chen 陈 Liang-Xian 良贤 , Wei 魏 Jun-Jun 俊俊 , Ou-Yang 欧 Xiao-Ping 阳晓平 , Li 李 Cheng-Ming 成明
Published: July 2023

The ohmic contact interface between diamond and metal is essential for the application of diamond detectors. Surface modification can significantly affect the contact performance and eliminate the interface polarization effect. However, the radiation stability of a diamond detector is also sensitive to surface modification. In this work, the influence of surface modification technology on a diamond ohmic contact under high-energy radiation was investigated. Before radiation, the specific contact resistivities (ρ
c) between Ti/Pt/Au-hydrogen-terminated diamond (H-diamond) and Ti/Pt/Au-oxygen-terminated diamond (O-diamond) were 2.0 × 10−4 Ω⋅cm2 and 4.3 × 10−3 Ω⋅cm2, respectively. After 10 MeV electron radiation, the ρ
c of Ti/Pt/Au H-diamond and Ti/Pt/Au O-diamond were 5.3 × 10−3 Ω⋅cm2 and 9.1 × 10−3 Ω⋅cm2, respectively. The rates of change of ρ
c of H-diamond and O-diamond after radiation were 2550% and 112%, respectively. The electron radiation promotes bond reconstruction of the diamond surface, resulting in an increase in ρ
c.
Analytical wave solutions of an electronically and biologically important model via two efficient schemes
Authors: Huang Qingbo , Zafar Asim , Raheel M. , Bekir Ahmet
Published: July 2023

We search for analytical wave solutions of an electronically and biologically important model named as the Fitzhugh–Nagumo model with truncated M-fractional derivative, in which the expa function and extended sinh-Gordon equation expansion (EShGEE) schemes are utilized. The solutions obtained include dark, bright, dark-bright, periodic and other kinds of solitons. These analytical wave solutions are gained and verified with the use of Mathematica software. These solutions do not exist in literature. Some of the solutions are demonstrated by 2D, 3D and contour graphs. This model is mostly used in circuit theory, transmission of nerve impulses, and population genetics. Finally, both the schemes are more applicable, reliable and significant to deal with the fractional nonlinear partial differential equations.
Research on Plastic Deformation of Rolled Pieces of Four-power rolling Mill Based on Deform
Authors: Du Chunkuan , Ni Xiao
Published: July 2023

Aiming at the problems of large cross-section size change and low shape and position accuracy of the workpiece rolled by the four-power rolling mill, based on analyzing the plastic deformation mechanism of metal crystals, the rolling simulation was carried out by deform software to analyze the variation of section plastic deformation height and equivalent stress distribution of the rolled workpiece section. The results show that under the action of mutual vertical rolling force, the large plastic deformation with a length of about 2mm occurs in the local area of 45 ° diagonal at the end of the section, and the maximum height dimension increases by 4.5% relative to the blank height dimension. Its equivalent stress at the ends of both sides of the section is also the largest, and then gradually decreases and tends to be stable.
Research on Fault Diagnosis Method of Rolling Bearing Based on Variational Mode Decomposition and Gath-Geva Clustering
Authors: Zhang Chen , Fang Tao
Published: July 2023

For the hassle that the fault of the rolling bearing is challenging to identify, a method for identifying the damage degree of rolling bearing based on the combination of Variational Mode Decomposition (VMD) and Gath-Geva (GG) fuzzy clustering is proposed. The method decomposes the known rolling bearing fault signal by VMD, determines the number of decomposed modes based on the magnitude of the component frequency center, and forms the obtained eigenmode components into an initial eigenmatrix for singular value decomposition. The three largest singular values are selected as the input of the GG clustering algorithm, and the membership matrix and cluster center of the known fault signals are obtained. The damage degree of the rolling bearing is identified by the Hamming closeness between the initial membership matrix of the signal to be measured and the cluster centers with clear fault signal. Rolling bearings vibration data verify the effectiveness of the method. The experimental results show that the method in this paper can accurately extract the fault information contained in the vibration signal, realize the correct fault type identification, and provide a reliable basis for the rolling bearing fault diagnosis method.
Underwater acoustic beacon detection device based on Embedded System
Authors: Dong Shichao , Yao Shukun , Kang Lijin
Published: July 2023

Based on the current situation of large volume and single detection function of the underwater acoustic beacon detection device, combined with the requirements of multi-parameter detection of underwater acoustic beacon function and performance, an embedded underwater acoustic beacon multi-parameter detection device is developed. The detection device uses ARM as the core processor, carries Linux embedded system, and establishes QT graphical user interface. The detection device can realize the acoustic signal of underwater acoustic beacon Frequency, pulse width, period, sound source level, spectrum, and other multi-parameter detection and graphical display of the test results.
Multivariate polynomial regression based selection and analysis of process parameters for X-ray inspection of pipeline containing medium
Authors: Yang Xueming , Yan Hui , Luo Deting , Liu Qing , Wang Qiang
Published: July 2023

Pressure pipelines use pressure to transport gas, liquefied gas, and steam in the process of use. If there are defects in the pipeline, it is easy to leak or burst, and even cause secondary accidents. To ensure safety, it is necessary to inspect the pressure pipelines in use regularly. However, it is difficult for the pressure pipeline in use to empty the internal medium. Therefore, it is of great significance to inspect the defects of the industrial pressure pipeline under operating conditions. In this paper, X-ray testing experiments are carried out for weld defects of pipelines with the medium. Using the experimental data, multivariate polynomial regression equations of negative blackness and tube voltage, and other variables are established, which provides an effective tool for the formulation of the optimal process route for testing pressure pipelines containing medium.
Intelligent Circuit Breaker
Authors: Niu Wenhuan , Shi Hailong , Hou Xujie
Published: July 2023

This paper designs an intelligent protective circuit breaker, which can monitor the leakage, voltage, current, temperature, and other parameters in the user’s line in real-time through the built-in electric energy metering module, leakage, temperature sensors, and alarm according to the set alarm threshold. It can give early warning about the dangerous situation in the user’s line in advance. At the same time, it can upload to the cloud platform through the wireless communication module for remote detection, which can effectively reduce the risk of an electrical fire.
Nonlinear dynamics analysis of rotor system
Authors: Sun Hanzheng , Zhang Hongyuan , Zhou Qiuzhong
Published: July 2023

In order to get the motion of the disc core and bearing in the rotor system, the nonlinear dynamic model was established. The influence of the disc core and bearing under the action of different rotor speeds and different bearing clearances is analyzed by numerical calculation. The results show that the change of rotor speed will not have a great impact on the disc center, will affect the movement cycle and amplitude, which will have a slight impact on the bearing. The increase of clearance will change the overall movement of the disc center, especially in the initial stage of the system, which will have a greater impact on the bearing.
Decreasing surface chlorophyll in the tropical ocean as an indicator of anthropogenic greenhouse effect during 1998–2020
Authors: Tian Feng , Zhang Rong-Hua
Published: July 2023

Available satellite data reveal a decreasing trend in surface chlorophyll (SChl) over the entire tropical ocean until 2020. Where contributions by internal variability and external forcing remain unclear. Here, state-of-the-art climate model simulations are analyzed to show that external forcing significantly contributes to the decreasing SChl trend. In contrast, internal variability plays a weak or even offsetting role. As for the underlying processes, anthropogenic greenhouse emissions lead to a remarkable reduction in SChl over the tropical oceans, whereas industrial aerosol load facilitates a considerable increase in SChl in the western tropical Pacific. In addition, the negative phase of the interdecadal Pacific variability during 1998–2020 contributes to an increase in SChl, while the impact from the Atlantic multidecadal variability is relatively weak in facilitating a decrease in SChl. Overall, these results imply that the impact of anthropogenic forcing has emerged as indicated in the tropical marine ecosystem.
Lactate in exhaled breath condensate and its correlation to cancer: challenges, promises and a call for data
Authors: Ruzsányi Veronika , Kalapos Miklós Péter
Published: July 2023

Owing to its connection to cancer metabolism, lactate is a compound that has been a focus of interest in field of cancer biochemistry for more than a century. Exhaled breath volatile organic compounds (VOCs) and condensate analyses can identify and monitor volatile and non-VOCs, respectively, present in exhaled breath to gain information about the health state of an individual. This work aims to take into account the possible use of breath lactate measurements in tumor diagnosis and treatment control, to discuss technical barriers to measurement, and to evaluate directions for the future improvement of this technique. The use of exhaled breath condensate (EBC) lactic acid levels in disorders other than cancer is also discussed in brief. Whilst the use of EBC for the detection of lactate in exhaled breath is a promising tool that could be used to monitor and screen for cancer, the reliability and sensitivity of detection are uncertain, and hence its value in clinical practice is still limited. Currently, lactate present in plasma and EBC can only be used as a biomarker for advanced cancer, and therefore it presently has limited differential diagnostic importance and is rather of prognostic value.
Reconnecting Memory and Recovering from Trauma: The Adaptation ofThe Deepfrom a Song to a Novella
Authors: Wang Longyan
Published: July 2023

The Deep (2019), a novella achieved through collective authorship by Rivers Solomon, Daveed Diggs, William Hutson, and Jonathan Snipes, is adapted from Clipping’s song of the same name ‘The Deep’ (2017). The novella contemplates collective memory, generational trauma, and identity issues. This article compares the song and novella, discusses how both song and novella express historical issues of slavery and contemporary issues of environmental destruction, traces diverse inspirational source materials, and examines the novella’s depictions of negotiation and reconciliation between individual versus communal identities within a context of generational trauma. This article argues that, with wajinru representing a bridging of humanity and nature, and with complex thematic interplay between forgetting, remembrance, and healing, the novella constitutes an Afrofuturist, magical realist, counternarrative challenge to dominant historical narratives, and illuminates the importance of reconnecting communal memory to individual identity-construction for recovering from generational trauma, and of building a more utopian world through cultivating love that transcends species and gender. In addition, this article analyzes how Solomon’s novella and its diverse source materials highlight the palimpsestic and intertextual nature of artistic adaptations and encourage audiences to engage in egalitarian, boundary-defying cultural production, and innovative blurring of genres, media, and authorship.
Analysis of host plant availability and use by 2 species of soldier beetles (Coleoptera: Cantharidae) using community-gathered digital specimens
Authors: Catron Katlyn A , Hennen Derek A , Wagner Jennie F , Brown Bryan L , Weber Donald C , Kuhar Thomas P
Published: July 2023

Digital specimens collected by community members are a largely untapped source of entomological data. By mining and curating data from photo observations uploaded to online community data repositories, researchers can utilize this wealth of information to address questions about predator–prey interactions, phenotypic variation within species, plant–pollinator interactions, and a host of other topics. We mined data from photo observations on the community science website iNaturalist to investigate patterns in host plant availability and affiliation by 2 species of soldier beetles, Chauliognathus marginatus (F.) and Chauliognathus pensylvanicus (De Geer). Chauliognathus marginatus was observed with white flowers more than expected based on their potential availability, while C. pensylvanicus was observed with yellow flowers over all other flower colors and more than expected based on their potential availability. Communities of flowers available to, and observed with, C. marginatus and C. pensylvanicus differed significantly at the family and genus levels. To our knowledge, this is the first study to utilize a dataset mined and curated from community science photo observations to address species-specific behavior and ecology questions. With appropriate study design and analytical methods, these types of data could prove invaluable in future investigations of a variety of entomological and ecological questions.
Translation of a Claims-Based Frailty Index From the International Classification of Diseases, Ninth Revision, Clinical Modification to the Tenth Revision
Authors: Duchesneau Emilie D , Shmuel Shahar , Faurot Keturah R , Park Jihye , Musty Allison , Pate Virginia , Kinlaw Alan C , Stürmer Til , Yang Yang Claire , Funk Michele Jonsson , Lund Jennifer L
Published: July 2023

The Faurot frailty index (FFI) is a validated algorithm that uses enrollment and International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)–based billing information from Medicare claims data as a proxy for frailty. In October 2015, the US health-care system transitioned from the ICD-9-CM to the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM). Applying the Centers for Medicare and Medicaid Services General Equivalence Mappings, we translated diagnosis-based frailty indicator codes from the ICD-9-CM to the ICD-10-CM, followed by manual review. We used interrupted time-series analysis of Medicare data to assess the comparability of the pre- and posttransition FFI scores. In cohorts of beneficiaries enrolled in January 2015–2017 with 8-month frailty look-back periods, we estimated associations between the FFI and 1-year risk of aging-related outcomes (mortality, hospitalization, and admission to a skilled nursing facility). Updated indicators had similar prevalences as pretransition definitions. The median FFI scores and interquartile ranges (IQRs) for the predicted probability of frailty were similar before and after the International Classification of Diseases transition (pretransition: median, 0.034 (IQR, 0.02–0.07); posttransition: median, 0.038 (IQR, 0.02–0.09)). The updated FFI was associated with increased risks of mortality, hospitalization, and skilled nursing facility admission, similar to findings from the ICD-9-CM era. Studies of medical interventions in older adults using administrative claims should use validated indices, like the FFI, to mitigate confounding or assess effect-measure modification by frailty.