bluuebunny/crossref_metadata_2025 huggingface dataset:
Tunneling spectroscopy of the α-and β-phases of In–Sn alloys and hydrostatically compressed indium
Authors: Revenko Yu. F. , Mostovoi V. M. , Svistunov V. M.
Published: December 2024

It is shown that tin impurities enhance while pressure weakens the superconducting properties and electron–phonon interaction in indium. The changes in the critical temperature in the α-phase of In–Sn alloys and in In under pressure are due primarily to changes in the lattice, while those in the β-phase are caused by a strong increase in the electronic parameter. The differences in the behavior of the Van Hove singularities in the phonon spectrum ωi, of the alloys and indium under pressure stem from the differences in the crystal structure deformations. The nonlinear changes in the superconducting parameters and frequencies ωi, at low impurity concentrations (2 at.% Sn) or under 6 kbar pressure are due to topological transitions in the Fermi surface of In, which causes lattice instability as a result of the electron–phonon interaction. This is the origin of the α ⇄ β phase transition.
Experimental investigations of Nb−NbOx−Pb tunnel junctions and theoretical interpretation of their behavior on the basis of the proximity effect
Authors: Berthel K. H. , Köhler H.-J. , Seidel P. , Blüthner K. , Weber P.
Published: December 2024

The temperature dependences of the current-voltage characteristic, the gap, and the critical Josephson current of Nb−NbOx−Pb tunnel junctions were studied. The experimental data reveal obvious deviations from the predictions of the BCS theory. Using a proximity-effect model for the niobium electrode and choosing appropriate parameters, such curves are calculated in good agreement with the experimental data. The structure of the niobium film near the barrier can be explained on the basis of the parameters mentioned.
Quantum anomalies in the inhomogeneous susceptibility of a metal in a magnetic field
Authors: Pamyatnykh E. A.
Published: December 2024

The wave vector dependence of the transverse magnetic susceptibility of the electron liquid of a metal in a quantizing magnetic field is studied, the wave vector being directed along the magnetic field. The orbital and spin contributions to the susceptibility, including their Fermi-liquid renormalization with account of the complete set of the Fermi-liquid interaction parameters, are calculated for small ratios of the energy of a cyclotron quantum to the Fermi energy. It is shown that both contributions have peaks, similar to the one-dimensional Kohn anomalies at a wave vector twice as large as the boundary wave vectors of electrons at each quantum level. At sufficiently low temperatures instabilities of the electron system are possible with respect to the formation of static spiral magnetization waves. These instabilities are related to peaks of the spin or orbital susceptibility. Conditions for observation of the predicted anomalies are discussed, and the instability generation temperatures are estimated.
Purity and orientation dependence of the internal friction of twinning-strained rhenium single crystals
Authors: Okovit V. S. , Elenskii V. A. , Kovtun G. P. , Chirkina L. A.
Published: December 2024

The influence of orientation, purity, and initial strain by twinning on the amplitude dependence of the low-frequency internal friction is studied. A possible pinning mechanism of the dislocation structure during initial straining by twinning is discussed. It is observed that the main contribution to pinning is from point defects generated during twinning. It is shown that the pinning of basal and prismatic dislocations by such defects is not the same. Speculations are offered as to the nature of the observed effect.
The ψ-function nodal surfaces and the conduction band of inert-gas crystals
Authors: Ratner A. M.
Published: December 2024

The outer electron is considered adiabatically with allowance for the permutation symmetry which leads to the expulsion of the electron from the inner region of the atom. The nodal surface of the ψ-function generated by the permutation symmetry enables a nonlocal adiabatic potential, with parameters determined by the atomic ionization potentials, to be constructed for the outer electron in the crystal. Because of the absence of long-range forces, in the case of inert-gas crystals the dispersion relation proves to be simple, thereby allowing the position of the band bottom, the deformation potential, and the effective mass to be calculated directly. It is shown that even a small nonlocality radically alters the character of the dependence of the effective mass on the radius of the inert atom.
Nonequilibrium phonons in point contacts between normal metals
Authors: Kulik I. O. , Omel’yanchuk A. N. , Yanson I. K.
Published: December 2024

It is shown that reabsorbtion of phonons in a microcontact made of normal metals leads to lattice heating to a temperature of Θ ≲ eV/4(V is the voltage across the junction). This leads to the appearance of a background in the dependence of d2V/dI2 on V, which is a complicated function of energy. However, the electron gas remains cold, i.e., it retains the temperature of the helium bath, which indicates the absence of additional broadening of the electron–phonon interaction function α˜2(ω)F(ω),reconstructed from the second derivative of the microjunction current-voltage characteristics.
Connecting the dots: tracking bull sharks from a provisioning site into the species’ river parturition sites in Fiji
Authors: Brunnschweiler J. M. , Marosi N. D. , Glaus K.
Published: December 2024

Context For sharks, information on the location and usage of critical habitats is rare. Marine protected areas (MPAs) have great potential to benefit shark populations but these rarely protect a species throughout its life stages or all critical habitats. The latter often includes parturition sites. Aims Pregnant bull sharks from the Shark Reef Marine Reserve in Fiji were tracked into riverine systems during three parturition seasons. Methods We tagged 31 female bull sharks with acoustic transmitters and placed acoustic receivers in the Rewa, Sigatoka, Navua and Ba Rivers on the island of Viti Levu between 2016 and 2018. Key results Fourteen bull sharks were detected by receivers placed in the four rivers for few, typically consecutive days during parturition season. Bull sharks were detected in the Rewa River during all three parturition seasons whereas sharks were detected in the Navua River only during the 2017/2018 season. Conclusions We have shown that Fiji’s rivers are critical for the completion of the bull shark’s life cycle. Implications Fiji has recognized the importance of conserving its population of bull sharks. Our results call for the implementation of protective measures for the species’ critical habitats.
Management of Two Peoples Bay Nature Reserve from 1967 to 1999
Authors: Danks Alan , Burbidge Andrew A. , Coy N. J. , Folley G. L. , Sokolowski R. E. S.
Published: December 2024

Context Two Peoples Bay Nature Reserve (TPBNR) is well known for two iconic species; the noisy scrub-bird (Atrichornis clamosus) and Gilbert’s potoroo (Potorous gilbertii), both having been rediscovered there. Aims This paper covers the management of the Reserve since its declaration in 1967 until 1999 in the context of the two iconic species, other species of interest, and visitors. Methods This paper is based on the authors’ experiences and information contained in archival files from several government departments. Key results At the time of the Reserve’s declaration, the department responsible for its management had few resources, with only four fauna wardens to cover the whole state of Western Australia. The first ‘reserves officer’ was appointed to TPBNR in 1970. Since then, a series of staff was responsible for the Reserve’s management, based primarily on fire and visitors. Since its inception, TPBNR has supported research into various aspects of its biota. Translocations of noisy scrub-birds from TPBNR commenced in 1983 and have resulted in several new populations with an increase in overall numbers. In 1985 the Department of Conservation and Land Management became responsible for the Reserve’s management and additional resources became available. Conclusions Management resources of TPBNR have grown from very limited, to today’s more comprehensive regional input supporting comprehensive species’ management as well as visitor and fire management. Implications The rediscovery of an iconic species gradually led to extensive scientific research and increasing resources for managing this celebrated nature reserve; a model for other areas where highly threatened species are rediscovered or known to exist.
Targeting DTX2/UFD1-mediated FTO degradation to regulate antitumor immunity
Authors: Cui Yan-Hong , Wei Jiangbo , Fan Hao , Li Wenlong , Zhao Lijie , Wilkinson Emma , Peterson Jack , Xie Lishi , Zou Zhongyu , Yang Seungwon , Applebaum Mark A. , Kline Justin , Chen Jing , He Chuan , He Yu-Ying
Published: December 2024

Here, we show that vitamin E succinate (VES) acts as a degrader for the m
6
A RNA demethylase fat mass and obesity-associated protein (FTO), thus suppressing tumor growth and resistance to immunotherapy. FTO is ubiquitinated by its E3 ligase DTX2, followed by UFD1 recruitment and subsequent degradation in the proteasome. VES binds to FTO and DTX2, leading to enhanced FTO–DTX2 interaction, FTO ubiquitination, and degradation in FTO-dependent tumor cells. VES suppressed tumor growth and enhanced antitumor immunity and response to immunotherapy in vivo in mouse models. Genetic FTO knockdown or VES treatment increased m
6
A methylation in the LIF (Leukemia Inhibitory Factor) gene and decreased LIF mRNA decay, and thus sensitized melanoma cells to T cell–mediated cytotoxicity. Taken together, our findings reveal the underlying molecular mechanism for FTO protein degradation and identify a dietary degrader for FTO that inhibits tumor growth and overcomes immunotherapy resistance.
Controllable autofocusing circular Pearcey Airyprime beam
Authors: Yang Shuo , Yu Peixin , Wu Binyu , Ge Xiaolu , Chen Chidao , Man Zhongsheng , Zhang Liping
Published: December 2024

This paper introduces a novel type of abrupt autofocusing beam called the circular Pearcey Airyprime beam (CPApB). Theoretical investigations and experimental verification of the propagation dynamics of the CPApB are conducted. Our results indicate that the focusing intensity of the CPApB is significantly higher than that of the circular Pearcey Airy beam (CPAB), reaching about twice that of the CPAB. Therefore, the CPApB exhibits superior autofocusing capability compared to the CPAB under identical conditions. Furthermore, the influence of different decay factors and astigmatism factors on the self-focusing characteristics of the CPApB are investigated. By delving into the underlying principles governing the CPApB, our findings offer new insights and establish foundational theories, aiming to enhance the efficient and precise control of the beam. The superior autofocusing characteristics of the CPApB are expected to be applied to various media.
A high-precision calibration method for nonlinear error coefficients of accelerometer components
Authors: Lu Kewen , Wang Xinlong , Nie Guanghao , Ding Wei
Published: December 2024

With the continuous improvement of measurement accuracy requirements for inertial devices, how to accurately calibrate nonlinear error coefficients of accelerometer components has become an important factor affecting the accuracy of the inertial navigation system. Centrifuge calibration method can continuously provide a specific force greater than 1 g, which can fully excite the nonlinear errors of accelerometer components and is a commonly used method for calibrating nonlinear error coefficients. However, on the one hand, traditional centrifuge speeds are often selected based on empirical experience, lacking a scientific determination method. This can lead to a decrease in the calibration accuracy of nonlinear error coefficients. On the other hand, the inability to accurately model the highly complex and time-varying test errors during actual calibration further reduces the calibration accuracy. Therefore, a high-precision calibration method for nonlinear error coefficients is proposed. Firstly, by introducing G-optimal experimental design criterion to minimize the maximum scaled prediction variance of output prediction values, the optimal speed combination is designed to achieve the highest accuracy in estimating nonlinear error coefficients. Based on the idea of semi-parametric regression, system errors caused by calibration test errors are treated as parameters to be estimated, and a high-precision nonlinear error coefficient calibration model is established. Then the influence of calibration test errors is eliminated by estimating and compensating the system errors. Centrifuge calibration test results show compared with the traditional method, the ranges and standard deviations of the repeated calibration results of the proposed method are reduced by more than 80.37% and 63.01%. This indicates that the proposed method can effectively eliminate the influence of calibration test errors and achieve high-precision calibration of nonlinear error coefficients.
Improving the performance of quantum well solar cells with photonic crystal
Authors: Liu Weiye , Guo Jiaping , Ding Ding , Tan Xinhui , Xu Haonan , He Lingyu , Zhang Wei , Han Lili , Wang Zhaowei , Gong Weihua , Qi Jinyun , Tang Xiansheng
Published: December 2024

The fabrication of quantum well solar cells with surface photonic crystal (SPC) and embedded photonic crystal (EPC) structures has resulted in solar cells with improved properties. When compared to reference solar cells (RSCs), the photoluminescence (PL) intensities of SPC solar cells and EPC solar cells have been enhanced by 89% and 114%, respectively. This indicates improved light absorption and emission characteristics in the presence of the periodic patterns (PCs). The short-circuit current (Isc) of EPC solar cells is 31% higher than that of RSCs, suggesting improved light absorption and carrier generation. On the other hand, SPC solar cells exhibit a 6% higher Isc compared to RSCs, and the open-circuit voltage has increased simultaneously. The fill factors (FF) of the solar cells are 84% for RSCs, 86% for SPC solar cells, and 76% for EPC solar cells. The higher FF in SPC solar cells suggests improved charge carrier collection efficiency. In terms of photoelectric conversion efficiency, SPC solar cells demonstrate a 10.6% increase, while EPC solar cells show a 7.7% increase. These improvements indicate that the incorporation of PCs in the solar cells enhances their ability to convert light into electrical energy. These findings highlight the potential of photonic crystals engineering for enhancing the performance of solar cells.
Editorial for focus on emerging processes and applications of atomic and molecular layer deposition
Authors: Meng Xiangbo , Elam Jeffrey W , Barry Sean
Published: December 2024

This Focus aims to provide a platform for the latest research progress in atomic and molecular layer deposition (ALD and MLD), which collects 10 original research articles and 2 review papers. The original research articles present new precursors, new processes, and new applications. The review papers give a timely summary on the surface chemistry of metal ALD processes and flexible electronics resulting from ALD and MLD, respectively. This ensemble forms a valuable collection that advances our understanding and knowledge of ALD and MLD, and inspires the continued development of these valuable technologies.
Patterning and nanoribbon formation in graphene by hot punching
Authors: Abbaspourmani AmirAli , Shivayogimath Abhay , Petersen Ritika S , Lyksborg-Andersen Anton , Hansen Thomas W , Keller Stephan S , Booth Timothy J
Published: December 2024

Large area graphene patterning is critical for applications. Current graphene patterning techniques, such as electron beam lithography and nano imprint lithography, are time consuming and can scale unfavorably with sample size. Resist-based masking and subsequent dry plasma etching can lead to high roughness edges with no alignment to the underlying graphene crystal orientations. In this study, we present hot punching as a novel and feasible method for patterning of chemical vapor deposition (CVD) graphene sheets supported by a polyvinylalcohol (PVA) layer. Additionally, we observe the effect of such hot punching on graphene supported by PVA via optical microscopy, Raman spectroscopy, AFM, and TEM, including wrinkling, strain and the formation of nanoribbons with crystallographically aligned and smooth edges due to fracturing. We present hot punching as a facile technique for the production of arrays of such nanoribbons.
An efficient deep unrolling network for sparse-view CT reconstruction via alternating optimization of dense-view sinograms and images
Authors: Sun Chang , Liu Yitong , Yang Hongwen
Published: December 2024

Objective. Recently, there have been many advancements in deep unrolling methods for sparse-view computed tomography (SVCT) reconstruction. These methods combine model-based and deep learning-based reconstruction techniques, improving the interpretability and achieving significant results. However, they are often computationally expensive, particularly for clinical raw projection data with large sizes. This study aims to address this issue while maintaining the quality of the reconstructed image. Approach. The SVCT reconstruction task is decomposed into two subproblems using the proximal gradient method: optimizing dense-view sinograms and optimizing images. Then dense-view sinogram inpainting, image-residual learning, and image-refinement modules are performed at each iteration stage using deep neural networks. Unlike previous unrolling methods, the proposed method focuses on optimizing dense-view sinograms instead of full-view sinograms. This approach not only reduces computational resources and runtime but also minimizes the challenge for the network to perform sinogram inpainting when the sparse ratio is extremely small, thereby decreasing the propagation of estimation error from the sinogram domain to the image domain. Main results. The proposed method successfully reconstructs an image (512 × 512 pixels) from real-size (2304 × 736) projection data, with 3.39 M training parameters and an inference time of 0.09 s per slice on a GPU. The proposed method also achieves superior quantitative and qualitative results compared with state-of-the-art deep unrolling methods on datasets with sparse ratios of 1/12 and 1/18, especially in suppressing artifacts and preserving structural details. Additionally, results show that using dense-view sinogram inpainting not only accelerates the computational speed but also leads to faster network convergence and further improvements in reconstruction results. Significance. This research presents an efficient dual-domain deep unrolling technique that produces excellent results in SVCT reconstruction while requiring small computational resources. These findings have important implications for speeding up deep unrolling CT reconstruction methods and making them more practical for processing clinical CT projection data.
Impact of image formation factors on material discrimination in spectral CT
Authors: Rajagopal Jayasai , Zarei Mojtaba , Vrbaski Stevan , Pritchard William F , Abadi Ehsan , Jones Elizabeth C , Samei Ehsan
Published: December 2024

Objective. The accuracy of material decomposition in spectral computed tomography (CT) depends on the information quality captured in image acquisition, a factor that cannot be adequately assessed using conventional image quality metrologies due to the multi-energy nature of spectral CT. This work used metrologies specific to spectral CT to evaluate the impact of acquisition conditions on the quality of spectral CT images and accuracy of material decomposition techniques. Approach. Computational phantoms were created with cylindrical shapes and variable sizes (20–40 cm), containing inserts of iodine and gadolinium (1–8 mg ml−1). The phantoms were imaged using a validated CT simulator modeling a clinical photon-counting CT scanner. The acquisitions were done at different detector energy thresholds (50–90 keV) and tube currents (25–250 mAs). The images were used to develop and train a data-driven material identification and quantification algorithm. Two spectral metrologies, multivariate contrast-to-noise ratio (CNR) and separability index, were used to characterize the impact of energy threshold, tube current, phantom size, and material concentration on signal quality. The results were interpreted in terms of figures of merit of accuracy for classification and mean absolute error (MAE) and root mean squared error (RMSE) for regression. Main results. Signal quality for iodine and gadolinium was maximized with a low energy threshold, high tube current, and small phantom size. While conventional CNR terms predicted variable image quality for two-thirds of all conditions, multivariate CNR was above 10 for half of those. Separability index showed that for a phantom size greater than 30 cm, a minimum of 75–110 mAs is required to separate 2 mg ml−1 of iodine and gadolinium. For both classification and regression tasks, a random forest model with a local statistics dataset provided the best performance. Across conditions, classification performance was 0.66–0.99 for I accuracy, 0.72–0.99 for Gd accuracy. Regression performance was 0.02–0.91 mg ml−1 I and 0.02–0.59 mg ml−1 Gd for MAE and 0.11–1.08 mg ml−1 I and 0.07-0.76 mg ml−1 Gd for RMSE. Significance. Multivariate CNR and separability index metrologies can predict material decomposition performance. Theses metrics demonstrated that the decomposition of iodine and gadolinium have higher separability when the acquisition is done at a lower energy threshold, with a higher tube current, and when the imaged object has a smaller size. Object size had the largest impact on metrics and decomposition performance.
Wave-packet trajectory analysis of the self-interference and cross-interference mechanisms in double-slit interference involving single electrons
Authors: Pan Junheng , Liu Shaoran , Zhang Bozhou , Tang Qiang , Tang Jau
Published: December 2024

In Copenhagen’s interpretation, a self-interference mechanism is assumed for a wave function to split and to pass through the slits simultaneously, then recombine and collapse to generate a dot signal on a detector. Its use of a single wave function to describe a whole ensemble without accounting for a particle’s individuality is incomplete. To better understand the single-electron double-slit interference, we use a wave-packet trajectory approach to track each electron’s dynamics and calculate the time-dependent interference intensity. We analyze the self-interference and cross-interference mechanisms to illustrate how an electron’s coherence length affects the self-interference and how it dictates the wave packet overlaps between adjacent electrons for the cross-interference mechanism to be effective. To circumvent a conflicting dilemma between the electron’s indivisibility and its wave-packet split while passing through the slits, we consider an alternate mechanism involving slit-induced quantized momentum. This mechanism preserves the electron’s indivisibility and avoids the illusive split, recombination and mysterious collapse of a single particle’s wave function.
Multiple-model-based adaptive state fusion estimation of IWMD-EV using SSUKF
Authors: Dou Guowei , Li Zhongxing , Xu Xing , Chen Te
Published: December 2024

To improve the preciseness degree and adaptive adjustment ability of the state acquisition system under multiple operating conditions, a vehicle state fusion estimation strategy using strong-tracking suboptimal unscented Kalman filtering (SSUKF) algorithm and adaptive weights is proposed. The vehicle models were established by comprehensively characterizing the multi-parameter mapping relationship under the kinematic, dynamic, and electromechanical coupling driving relationship of in-wheel motor drive electric vehicle (IWMD-EV). To improve estimation performance of vehicle state estimation system in face of nonlinear factors such as noise and interference, a vehicle kinematic-based observer (KO) and a dynamic-based observer (DO) were developed based on the SSUKF algorithm. In addition, to enhance the overall preciseness degree and its adaptive adjustment ability for large-scale road conditions, a state fusion estimation method with adaptive weight is presented by combining redundant information of multiple model observers. The results demonstrated that the proposed method can significantly improve the estimation preciseness degree and the adaptive ability for complex working conditions.
A novel multi remote sensing image encryption scheme exploiting modified zigzag transformation and S-Box
Authors: Niu Tong , Liu Yi , Gao Lin
Published: December 2024

This paper proposed a novel multi-image remote sensing image encryption algorithm. The proposed algorithm leverages a novel fractional-order chaotic system, an enhanced Zigzag scanning technique, and a refined S-box for robust encryption. Initially, the plain remote sensing images are transformed into a one-dimensional sequence using an extended Zigzag transformation. Subsequently, chaotic sequence indices, generated by the advanced fractional-order chaotic system, are utilized for pixel position scrambling. During the diffusion phase, two differently ordered diffusions were performed to enhance the algorithm’s resistance to chosen-plaintext attacks after the S-box based encryption. To further augment the security of the proposed scheme, an XOR operation is executed on each color channel of the encrypted images. Additionally, to expand the key space and strengthen resistance to chosen-plaintext attacks, the initial values and parameters involved in the algorithm are intricately tied to the SHA3–512 hash value of the plaintext image. The experimental results show that the proposed algorithm not only meet the demand of efficiency, but also could resist commonly used security attacks.
A DFT/TD-DFT study on the π-spacer effect of coumarin 102-Based dyes for dye-sensitized solar cells applications
Authors: Ebied Mostafa Saad
Published: December 2024

Developing new organic dyes with optimized electronic structures and superior light-harvesting capabilities is crucial for enhancing the efficiency of dye-sensitized solar cells (DSSCs). In the current study, four novel D-π-A organic dye molecules (MC1-MC4), with various π spacers, were designed based on Coumarin-102 dye to investigate their prospective uses in dye-sensitized solar cells (DSSCs). Therefore, DFT and TD-DFT calculations were utilized to explore the electronic structure and photophysical and photovoltaic properties of the designed dyes. Specifically, the optimized structures, electronic parameters, Frontier molecular orbitals (FMOs), Natural Bond Orbital (NBO) analysis, Density of States (DOS) analysis, and Global Reactivity Parameters (GRPs) were evaluated. The calculated values of the energy difference between HOMO and LUMO ranged from 2.63 to 2.97 eV, with the MC2 dye having the smallest band gap (2.63 eV). Furthermore, the influence of π spacers on the performance of DSSCs was studied by calculating the Non-Linear optical (NLO) characteristics, UV–vis spectra, and other important parameters determining the photovoltaic performance of DSSCs. The results show that MC2 exhibits the highest value of light-harvesting efficiency (0.96) and a more negative ΔGinject (−1.323 eV), indicating that MC2 would demonstrate a higher JSC and could theoretically be a better sensitizer of DSSC device.
In situ electrosynthesis, optimization and stability of AgNPs within chitosan: pullulan polymeric network
Authors: Zidan Mostafa M , Reicha Fikry M , Mansour-Gabr Mohamed M , Elmezayyen Ayman S
Published: December 2024

In this study, a systematic investigation to achieve a deeper understanding of the synergistic effect of chitosan (CS) and pullulan (PL) as a polymeric matrix on the in situ electrosynthesis AgNPs under applied voltage 1.5 V for 2 h. The process was applied using CS: PL blend with different ratio as electrolytic solution, reducing, and stabilizing agent avoiding using toxic reducing agent, byproduct of the reaction, controlling AgNPs size and stability. Investigation of the samples using UV–visible spectroscopy (UV–vis), Inductively coupled plasma optical emission spectroscopy (ICP), transmission electron microscope (TEM), Fourier transform infrared spectroscopy (FTIR), x-ray diffraction (XRD), x-ray photoelectron spectroscopy (XPS) and Thermogravimetric analysis (TG) revealed that AgNPs successfully formed under controlling the size and stability. Across all ratios except using only PL as an electrolyte, the results revealed the occurrence [chitosan/pullulan] Ag+ complex band at around 250 nm and a localized peak at 420 nm attributed to the SPR of AgNPs. TEM confirmed AgNPs formation with decreasing in size and increasing in concentration as a function of increasing CS content. Findings obtained by quantifying the concentration of silver using ICP whereas the concentration of CS is raised, the concentration of silver liberated increases. Zeta potential revealed that AgNPs have a positive surface charge maximized with increasing CS content. Furthermore, stability against aging for 2 months at 4 °C revealed that the addition of PL to CS matrix works on increasing the stability of AgNPs against aging.
Green-mediated sol-gel fabrication of CuO/ZnO nanoparticles from orange peel extract for environmental remediation: insights from x-ray diffraction analysis using various models
Authors: Ali Dilawar , Muneer Iqra , Pirzada Muntaha , Ejaz Tanzeela , Yasmeen Farhat , Bashir Farooq , Hanif Muhammad , Aziz Muhammad Hammad , Wahab Rizwan
Published: December 2024

This study introduces an eco-friendly and simple approach for synthesizing zinc oxide (ZnO), copper oxide (CuO), and ZnO-CuO composite nanoparticles using orange peel extract, minimizing the use of harmful chemicals while enhancing their antibacterial and photocatalytic properties. The nanoparticles were annealed at 400 °C for 2 h in the air. Characterization was conducted using x-ray Diffraction (XRD), Dynamic Light Scattering, Fourier Transform Infrared Spectroscopy (FTIR), and UV-visible Spectroscopy. XRD revealed that ZnO and CuO nanoparticles crystallized in hexagonal wurtzite and monoclinic structures, respectively, with crystallite size and lattice strain analyzed through Williamson–Hall, Size-Strain Plot, Halder-Wagner, and Wagner-Aqua methods. FTIR spectra confirmed the presence of Zn-O and CuO bonds, verifying successful synthesis. The optical bandgaps measured were 3.07 eV for ZnO, 2.702 eV for CuO, and 1.842 eV for the ZnO-CuO nanocomposite. Antimicrobial efficacy, assessed via the disc diffusion method, showed the ZnO-CuO composite exhibited enhanced antibacterial activity against both gram-positive and gram-negative strains compared to individual ZnO and CuO. Photocatalytic experiments demonstrated that under sunlight, the ZnO-CuO nanocomposite achieved 78% degradation of 10 ppm methylene blue within 90 min, outperforming individual ZnO (55%) and CuO (38%). These results highlight the ZnO-CuO composite’s potential for effective dye degradation and environmental remediation applications.
Electromagnetic shielding enhancement in cement composites: a comparative study of mechanically and thermally recycled carbon fibers
Authors: Öztürk Murat
Published: December 2024

The recycling of carbon fibers that have reached the end of their service life and their reintegration into new applications hold significant importance from an environmental and sustainable perspective. In this study, the aim is to enhance the electromagnetic wave shielding properties of cement-based composites by incorporating mechanically and thermally recycled and ball-milled carbon fibers at volumetric ratios of 1%, 2%, and 3%. Electromagnetic tests are conducted in the X-band frequency range (8–12.5 GHz), commonly preferred for microwave applications. The obtained results demonstrate an improvement in the SE
A
(absorption loss )and SE
T
(total power loss) values of the composite with the use of recycled fibers. This improvement is particularly more pronounced in composites containing thermally recycled fibers. The enhanced performance is attributed to the electrical conductivity imparted by carbon fibers. At a frequency of 11.9 GHz, the SE
T
value increased from 8.5 dB for the control sample to 9.2 dB for composites with 3% mechanically recycled fibers and up to 19 dB for composites with 3% thermally recycled fibers. These findings indicate that using recycled carbon fibers enhances the electromagnetic wave shielding properties, with thermal recycling contributing more significantly to this enhancement.
Exploring Milky Way rotation curves with Gaia DR3: a comparison between ΛCDM, MOND, and general relativistic approaches
Authors: Beordo William , Crosta Mariateresa , Lattanzi Mario Gilberto
Published: December 2024

With the release of Gaia DR3, we extend the comparison between dynamical models for the Milky Way rotation curve initiated in the previous work. Utilising astrometric and spectro-photometric data for 719143 young disc stars within |z| < 1 kpc and up to R ≃ 19 kpc, we investigate the accuracy of MOND and ΛCDM frameworks in addition to previously studied models, such as the classical one with a Navarro-Frenk-White dark matter halo and a general relativistic model. We find that all models, including MOND and ΛCDM, are statistically equivalent in representing the observed rotational velocities. However, ΛCDM, characterized by an Einasto density profile and cosmological constraints on its parameters, assigns more dark matter than the model featuring a Navarro-Frenk-White profile, with the virial mass estimated at 1.5–2.5 × 1012 M⊙ — a value significantly higher than recent literature estimates. Beyond 10–15 kpc, non-Newtonian/non-baryonic contributions to the rotation curve are found to become dominant for all models consistently. Our results suggest the need for further exploration into the role of General Relativity, dark matter, and alternative theories of gravitational dynamics in shaping Milky Way's rotation curve.
Research on high-power MRS power supply based on ZVS
Authors: Zhao Y , Sun KZ , Shang XL
Published: December 2024

Magnetic resonance sounding is currently the only type of trenchless detection method for groundwater exploration, offering advantages such as comprehensive information acquisition, unique interpretation, and quantifiable results. The main challenge faced by magnetic resonance sounding in actual detection processes is the complex electromagnetic noise interference in the environment, making it difficult to ensure a high signal-to-noise ratio for water detection. The signal detected by the instrument can be stacked multiple times, which increases the signal-to-noise ratio by √ n times. Therefore, the collected signal can be stacked multiple times through repeated measurements. However, the power supply system of previous nuclear magnetic resonance water detectors used the LCC resonance mode, which presents issues such as low power, fewer signal acquisition times per unit time, and difficult heat dissipation. This article proposes a nuclear magnetic resonance power supply system based on Zero Voltage Switching (ZVS), which adopts constant resonance technology to reduce switching loss and shorten the time required for the power supply to charge the energy storage capacitor. This approach increases the number of measurements per unit time, thereby improving the signal-to-noise ratio.
Landslide microseismic observation with nodal seismometers and Distributed Acoustic Sensing
Authors: Liao Xiaolong , Wang Baoshan
Published: December 2024

On February 22, 2023, a large-scale landslide involving 10 million cubic meters of material occurred at the Xinjing Coal Mine in Inner Mongolia, China, resulting in significant casualties and property damage. To investigate the secondary effects of this landslide, microseismic activity was monitored one week after the event using Distributed Acoustic Sensing (DAS) and nodal seismometers. The instruments successfully recorded microearthquakes, which were then located using double-difference earthquake location techniques. The analysis revealed that the microseismic activity was concentrated near the underground goaf, correlating with the primary cause of the landslide — an excessively steep slope in the surface coal mine. This suggests that the landslide remains in an unstable state.
Research on precise detection of landfill based on high density resistivity method
Authors: Yuankun  , Hongchao Lu , Yinsheng Yao , Chenxing
Published: December 2024

Aiming at the technical problems of accurate detection of landfill sites, this paper first establishes two-dimensional and three-dimensional anomaly identification models based on the resistivity of surrounding rock at the actual boundary of landfill sites, analyzes the abnormal response characteristics of landfill sites, and obtains the electrical distribution law. After that, the 3D high density resistivity method was used to measure the landfill site, the electrical distribution law of the rock in the area was used to interpret the data, and the drilling verification was used to successfully realize the accurate detection of the landfill site.
Design and Offshore Testing of the Nodal Deep Sea Seismic–Electromagnetic Joint Acquisition System
Authors: Yao Yongchao , He Zhanxiang , Ying Zhiqi , Zhao Yunsheng
Published: December 2024

This paper presents the design, development, and offshore validation of OBSEM, a pioneering marine seismic-electromagnetic joint acquisition system aimed at enhancing comprehensive underwater observation capabilities. The system integrates the functionalities of ocean bottom seismometers (OBS) and ocean bottom electro-magnetometers (OBEM), enabling synchronous collection of seismic and electromagnetic signals. Detailed are the structural components, including sensors, data acquisition unit, power supply, clock synchronization system, and signal conditioning techniques employed to augment the signal-to-noise ratio of low-frequency electromagnetic signals. Noteworthy is the clock synchronization methodology employing a hybrid GPS and atomic clock configuration for precise temporal alignment. Furthermore, an automatic leveling system is engineered to maintain the seismometer’s horizontal orientation, crucial for ensuring data fidelity. The integration of seismic and electromagnetic data offers a significant advancement in marine geophysical surveys, promising heightened exploration efficacy and inversion accuracy. Offshore trials conducted in the South China Sea affirm the efficacy of OBSEM, with future endeavors aimed at deep-sea validation.
Analysis of the performance of frequency-Bessel transformation surface wave tomography method in geotechnical engineering investigation
Authors: Chai Haibin , Han Sixu , Luo Qiang , Shao Kui , Wen Yonghui , Yang Zhentao , Gao Yuqiu
Published: December 2024

The frequency-bessel transform surface wave tomography method has emerged as a novel method for surface wave imaging during the past few years. This technique facilitates imaging large-scale crust-mantle structures and enables shallow engineering exploration. Compared to conventional methods like SPAC, it markedly enhances the quality of the surface wave dispersion curve, particularly in higher mode, enhancing the reliability of inversion. Its active and passive source data processing integration is particularly noteworthy, significantly broadening surface wave methods’ application scope. Our research reviews the performance of this technique in addressing common geological issues encountered in geotechnical engineering investigation, such as bedrock surface detection, cover layer detection, karst detection, and permafrost layer detection. Moreover, it recommends this innovative technique’s widespread adoption and further advancement.
Three dimensional inversion of mise-a-la-masse-based electric data using U-Net convolutional neural network
Authors: Meng Yuhang , Li Jinghe , He Zhanxiang , Zhang Yujie
Published: December 2024

Nonlinear inversion algorithms are away ill-pose for the limited and special data measurement, such as mise-a-la-masse-based electric method and borehole to surface electromagnetic method. It is natural to develop new inversion algorithms without calculating the the Jacobian matrix and its inverse matrix, especially for three dimensional inversion. Basing on U-Net fully convolutional neural network, a three dimensional inversion of mise-a-la-masse-based electric data is proposed in this paper. The random rotated spheroids are used to synthesize diverse geological models. A typical U-Net learning network is constructed with incorporating the Dice coefficient and the input data feedback to the trained network. Synthetic datasets testing validates the effectiveness of this proposed algorithm for mise-a-la-masse-based electric data.
Two-dimensional deep learning magnetotelluric inversion
Authors: Liu W , Wang H , Guo T , Yan MS , Xi ZZ
Published: December 2024

Deep learning (DL) inversion methods have showcased promising applications in solving geophysical inverse problems. In this work, we develop a DL model (SwinTUNet) to enable accurate reconstruction of the nonlinear mapping between the network inputs and outputs and achieve two-dimensional (2-D) magnetotelluric (MT) inversion. SwinTUNet is built by employing the strong Swin Transformer as the backbone network and adopting the UNet architecture. Moreover, to create a training dataset that aligns with practical MT inverse problems and ensuring effective applications, we design and generate a set of random synthetic resistivity models with gradual-varying resistivity values. Inversion examples demonstrate that the proposed SwinTUNet inversion method holds a great promise in promoting the applicability of DL inversion methods in realistic MT prospecting scenarios.
Online evaluation method of current transformer operation error based on differential noise filtering and current carrying classification
Authors: Qi Chengfei , Wang Yachao , Zhang Yuning , Wang Yaoyu , Zhang Ru , Bi Chaoran , Yi Shuxian , Zhang Xiwei , Liu Yan
Published: December 2024

A current transformer is an important equipment for detection and protection in power systems. Its stability is poor in long-term operation. In this paper, an online evaluation method of current transformer operation error based on differential noise filtering and current carrying classification is proposed. The stability and classification of the current secondary side data are carried out by using the differential noise filtering-current carrying classification method. The principal component analysis (PCA) method is used to analyze and model the processed measurement data, and the evaluation standard quantity Q is obtained. By comparing the real-time evaluation statistics and standard quantities, the real-time evaluation of the current transformer measurement error is completed. Comparative experiments show that the measurement error of 0.2 level current transformer can be accurately evaluated by using the method proposed in this paper.
Power tower bolt looseness detection method based on phase-sensitive optical time domain reflection technology
Authors: Xu Qiang , Ji Hang , Si Wenrong , He Bing , Zhao Yingying
Published: December 2024

Due to the vibration threat during the operation of equipment, the bolt structure of the power tower will be loose, which seriously threatens the safety of power operation and maintenance. An innovative method utilizing the principle of phase-sensitive optical time domain reflection has been designed to effectively detect the loosening of bolts on power towers in response to the aforementioned issues. Phase-sensitive optical time-domain reflection technology is introduced to capture subtle vibration signals caused by bolt loosening. The detection principle is constructed to adjust the components of the static magnetic field in different directions so that the electromagnetic ultrasonic transducer can receive transverse guided waves and longitudinal guided waves. An in-depth analysis was conducted on the operational mechanism of phase-sensitive optical time-domain reflection technology. According to this principle, the ultrasonic wave emitted by an electromagnetic ultrasonic transducer propagates along a certain path, and the guided wave velocity is calculated. Thus, the realization process of bolt looseness detection in a power tower is constructed. The experimental results show that the loosening rate of bolts is effectively reduced after the application of this method, which greatly promotes overall safety. The root mean square error of this method is smaller, and the detection effect is the best.
A knowledge graph-based method for intelligent risk assessment of power grid
Authors: Zhang Jun , Zhang Chen , Han Xinyang , Liu Xiaohan , Zhu Xiaoping , Chen Lifei , Jin Xiaoling
Published: December 2024

With the advancement of science and technology, the material resources that support people’s lives are becoming increasingly abundant, leading to increasingly complex accidents in the electricity system caused by factors such as Natech. Currently, a superficial security check problem exists in analyzing potential hazards in China. Moreover, the evaluation work becomes superficial, resulting in inaccurate identification results and making it difficult to ensure the long-term safety and stability of the power system. Based on these issues, this paper proposes a power system safety assessment method based on a standardized digital knowledge graph (KG). In this method, firstly, through research on standardized digital transformation theory, a triplet dataset based on event accidents is established to support knowledge graph construction; secondly, through knowledge graph construction, hazard analysis and evaluation of the power system are achieved.
Health monitoring method of power supply chain based on R-tree dynamic index algorithm
Authors: Cui Lichong , Chu Huayu , Su Lei , Fu Yanyang , Wang Qi , Li Zihan
Published: December 2024

In order to discover and manage the risks in the supply chain in time, the entire supply chain is clearly defined, and a health monitoring method for the power grid material supply chain based on the R-tree dynamic index algorithm is constructed. The overall internal supply chain operation structure of the power company is analyzed. The speed histogram is used to divide the speed field corresponding to the index algorithm in order to measure the node speed domain accurately. The rectangular bounding box of the root node is calculated. The internal health data of the power supply chain is identified. The fuzzy clustering operation is used. The original sample size is obtained. The algorithm data is clustered under the action of the index matrix. Bad data is identified in the supply chain. The overlap threshold and the intra-class compact threshold are initialized. The R-tree dynamic index of the optimal clustering is obtained. Quantity output results are generated, and unhealthy data in the material supply chain is classified. The identification and monitoring of unhealthy data in the supply chain are realized. Experiments show that the proposed method can efficiently monitor the risk factors existing in the material supply chain, and the monitoring of supply chain health risks is consistent with the actual occurrence value, the error is small, the method is feasible and effective, and the robustness is good.