bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single inertial neuron with forced bipolar pulse: chaotic dynamics, circuit implementation, and color image encryption
Authors: Zhao Shuang , Chuah Joon Huang , Khairuddin Anis Salwa Mohd , Chen Chengjie 
Published: December 2024

Abstract
The bipolar pulse current can effectively mimic the external time-varying stimulus of neurons, and its effect of neuronal dynamics has rarely been reported. To this end, this paper reports the effects of bipolar pulses on a two-dimensional single inertial neuron model, showcasing the chaotic dynamics of hidden attractors and coexisting symmetric attractors, which is of significant importance for understanding the complex behaviors of neuron dynamics under time-varying external stimuli and its application. Firstly, the mathematical model of the single intertial neuron model with forced bipolar pulse is presented, and then the equilibrium states behaving as unstable saddle point (USP), stable node-focus (SNF), and stable node point (SNP) are analyzed. Additionally, by using multiple dynamical methods including bifurcation plots, basins of attraction, and phase plots, complex dynamics of interesting bifurcation behaviors and coexisting attractors are revealed, which are induced by the forced bipolar pulse current as well as initial values, both. In addition, such effets are well valideted via a simple multiplerless electronic neuron circuit. The implementation circuit of presented model is constructed on the analog level and executed using PSIM circuit platform. The measurement results verified the double-scroll chaotic attractors and the coexisting period/chaos behaviors. Finally, the chaotic sequences of the model are applied to color image encryption for the benefit of requirements on modern security field. The encryption effectiveness is demonstrated through various evaluation indexes, including histogram analysis, information entropy, correlation coefficient, plaintext sensitivity, and resistance to noise attacks.
First-principles study of robust half-metallic ferromagnetism and electronic structure of the Heusler compounds Co2-xCrxMnGe
Authors: Dey Sarkar Mainak , Ghosh Sulagna , Sanyal Dirtha , Jana Debnarayan 
Published: December 2024

Abstract
Half-metallic ferromagnets (HMFs) are among the most promising materials in the field of spintronics because of their distinct band structures, which consist of two characteristic subbands, one with semiconductor-like behaviour and the other with metallic features. Using density functional theory-based calculations, we have carried out in-depth studies to predict the effects of Co replacement by Cr on electronic structure as well as the magnetic properties of Co2-xCrxMnGe with 0 ≤ x ≤ 1. The results demonstrate that the alloys are stable in the ferromagnetic phase with half-metallic nature. The origin of ferromagnetism can be explained by Ruderman-Kittel-Kasuya-Yosida (RKKY), like exchange interaction. Due to their high Curie temperatures, which increase linearly with the total magnetic moment, all alloys are suitable for applications at and above room temperature. Besides, the electronic properties have revealed a transition from half-metallic to semi-metallic character for higher doping concentration (x = 0.75, x = 1.0). The calculated total magnetic moments, however, decrease with increasing doping concentration, consistent with the Slater-Pauling rule. The observed high value of spin polarisation of all the studied compounds suggests their futuristic roadmaps for possible spintronics applications beyond room temperature.
Stream ciphers for digital image transactions by learning quantum true random numbers
Authors: Bao Zhenjie , Wan Changsheng , Phoha Vir Virander , Hu Yichen , Zhang Juan , Xu Wenda , Chen Haitao 
Published: December 2024

Abstract
The digital economy drives a surge in online digital image transactions, increasing the risk of data breaches due to extensive image file transmission. Stream ciphers, known for their efficiency compared to block ciphers, have emerged as a preferred choice for encrypting images in such transactions to safeguard transmitted data. Nevertheless, traditional stream cipher algorithms face diverse security threats. To address this challenge, efforts have been devoted to generating stream ciphers by generative adversarial networks (GANs) transforming input style into random patterns. Regrettably, these ciphers face issues in key sensitivity, randomness, and style transformation failures. Quantum true random numbers offer a potential solution but are costly to deploy. To handle this dilemma, we design stream ciphers relied on a neural network random number generator (RNG) using quantum true random numbers for training least squares GANs. Specifically, two fully-connected layers are incorporated into the RNG, avoiding the defects of style transformation in existing GANs-based stream ciphers. Besides, a random number calculation formula is employed to ensure that each decimal place output by the generator contributes to the computation of the random numbers. By doing so, the randomness of GANs is enhanced and the deployment of costly quantum devices is avoided. Experiments reveal that the information entropy of our generated images reaches to 7.9991, the adjacent pixel correlation coefficient of the ciphertext attains -0.0015, the Number of Pixel Change Rate and Unified Average Changing Intensity achieve 99.62% and 33.52%, respectively. These results demonstrate that the designed RNG facilitates randomness, whilst having secure properties applied in stream ciphers.
High-performance dual-core photonic crystal fiber polarization beam splitter based on gold-titania composite film coating
Authors: Liu Yundong , Wang Yujun , Liu Hualin , Shi Nianfeng , Li Yingying , Meng Xiaojian 
Published: December 2024

Abstract
A novel gold-titania composite film-coated dual-core photonic crystal fiber polarization beam splitter (GT-DC-PCF PBS) is proposed for the first time. The titania film and gold film are sequentially deposited on the inner wall of the central air hole to improve the polarization splitting performance and enhance the adsorption strength between the gold film and the optical fiber. Based on the mode coupling theory and surface plasmon resonance effect, the transmission characteristics of x-polarization (X-pol) and y-polarization (Y-pol) odd and even modes in the near-infrared band are analyzed by finite element method. Meanwhile, the variation of coupling length and coupling length ratio for X-pol and Y-pol light under different PCF structural parameters at the wavelength of 1550 nm are also studied to optimize the performance of PBS. The results show that at the 1550 nm communication window, the extinction ratio of the PBS is up to −175.82 dB for the polarization splitting length of 2.76 mm, with an operating bandwidth of 179 nm and a maximum insertion loss of 0.23 dB. This paper aims to propose a novel design method to improve the performance of DC-PCF PBS, which has profound guiding significance for the development of high-performance PBS.
Application of nanocrystalline spinel MFe2O4, (M=Co and Cu) in waste water treatment
Authors: G R Vasudha , Rai M Vaishali , Venugopal Deepa Mugudthi , Varija Raghu Shamprasad , Narayana Yerol 
Published: December 2024

Abstract
Transition metal spinel ferrites MFe2O4 (M=Cu and Co) were successfully synthesized following the co-precipitation method and their structural, optical, photocatalytic, antimicrobial and toxicity properties were studied. The characterization of the title compounds has been carried out using XRD, SEM, EDS, FT-IR and UV–vis DRS spectroscopy. The XRD studies confirmed a cubic spinel structure with the Fd-3m space group, and CuFe2O4 and CoFe2O4 exist in the nanocrystalline size of 20 nm and 16 nm, respectively. The SEM images revealed the agglomerated nature of the ferrite nanoparticles, and the EDAX spectrum confirmed the samples elemental compositions and purity. The FT-IR spectra indicated the presence of metal-oxygen stretching bands. The ferrite samples demonstrated photocatalytic activity in the visible region, as assessed by methylene blue (MB) degradation in an aqueous solution under visible irradiation. After 105 min, CuFe2O4 and CoFe2O4 catalysts exhibited 72% and 56% degradation for the MB solution. Through broth dilution, MFe2O4 (M=Cu and Co) nanoparticles were evaluated for their antimicrobial activity using S. aureus and E. coli, a gram-positive and gram-negative bacterium, respectively. Studies indicated that CoFe2O4 nanoparticles exhibit better antibacterial activity when compared to CuFe2O4. However, the antifungal activity study indicated that CuFe2O4 nanoparticles exhibit better antifungal activity when compared to CoFe2O4 nanoparticles. The toxicity of the nanomaterials was tested by mixing MFe2O4 (M=Cu and Co) with normal fly food and administering it orally to Drosophila melanogaster. The results indicated that the functionalized CuFe2O4 nanoparticles are less toxic to living organisms. Hence, optimized nanocrystalline spinel has the potential to degrade dyes from polluted water and act as an antimicrobial agent by rupturing pathogen cells. They have potential applications in both environmental safety and biomedicine.
Constraints on the primordial black hole abundance through scalar-induced gravitational waves from Advanced LIGO and Virgo's first three observing runs
Authors: Jiang Yang , Yuan Chen , Li Chong-Zhi , Huang Qing-Guo 
Published: December 2024

Abstract
As a promising dark matter candidate, primordial black holes (PBHs) lighter than
∼ 10-18
M
⊙ are supposed to have evaporated by today through Hawking radiation. This
scenario is challenged by the memory burden effect, which suggests that the evaporation of black
holes may slow down significantly after they have emitted about half of their initial mass. We
explore the astrophysical implications of the memory burden effect on the PBH abundance by today
and the possibility for PBHs lighter than ∼ 10-18
M
⊙ to persist as dark matter. Our
analysis utilizes current LIGO-Virgo-KAGRA data to constrain the primordial power spectrum and
infer the PBH abundance. We find a null detection of scalar-induced gravitational waves that
accompanied the formation of the PBHs. Then we find that PBHs are ruled out within the mass range
∼ [10-24,10-19]M
⊙. Furthermore, we expect that next-generation gravitational
wave detectors, such as the Einstein Telescope and the Cosmic Explorer, will provide even more
stringent constraints. Our results indicate that future detectors can reach sensitivities that
could rule out PBH as dark matter within ∼ [10-29
M
⊙,10-16
M
⊙] in the null
detection of scalar-induced gravitational waves.
Preparing Al2O3/TiO2 nano-multilayers on the surface of FeAl/Al2O3 coating as tritium permeation barrier
Authors: Guo Enkai , He Yifu , Zhong Fen , Fu Bowen , Wang Kun , Cai Guangxu , Jiang Changzhong , Ren Feng 
Published: December 2024

Abstract
Preparing tritium permeation barrier (TPB) coating on the surface of structural materials can effectively alleviate tritium permeation in fusion reactor system. However, due to the existence of inevitable certain number of defects in TPB, there is still a gap between the commonly prepared TPB coatings and the requirements proposed by fusion reactors. In this work, composite coatings with Al2O3/TiO2 nano-multilayers (NMLs) covering on the surface of FeAl/Al2O3 coating were prepared as TPB. The FeAl/Al2O3 TPB coating on the surface of 316L stainless steel was prepared by electrochemical deposition of Al, aluminization and in-situ oxidation. Due to the aggregation of Cr, there are micro sized defects in the Al2O3 layer. The presence of defects seriously reduces its hydrogen isotopes permeation resistance. The atomic layer deposition was then adopted to prepare Al2O3/TiO2 NMLs with period thickness of 15, 7.5 and 3 nm on the surface of Al2O3 layer, which not only cover the defects, but also utilize interfaces to suppress hydrogen isotopes permeation. The composite coating sample with the period thickness of 3 nm showed great enhancement of two orders of magnitude in deuterium permeation resistance property compared to the original FeAl/Al2O3 TPB coating at 500 °C, and the permeation reduction factor reaches a high value of 5 × 105, which far above the requirements of future fusion reactors.
Sensor fault estimation based on double model adaptive method for dynamic Point-the-bit rotary steerable systems
Authors: Shao Mingzhu , Geng Yanfeng , Wang Weiliang , Huang Shuaishuai 
Published: December 2024

Abstract
The dynamic point-the-bit rotary steerable system (DPRSS) is utilized to accomplish superior control of the drilling trajectory in oil and gas operations. However, sensor faults may undermine the reliability of DPRSS. This study focuses on the estimation of sensor faults in DPRSS. First, the DPRSS is modelled as a linear system subjected to drilling disturbances. The model integrates the rotational speed of the drill collar within its system state equations and incorporates prior knowledge about the stabilized platform. Afterward, the Double Model Adaptive Estimation (DMAE) algorithm is employed to estimate the system state, the unknown inputs, and sensor faults. Lastly, simulations and experimental results are presented to demonstrate the efficacy of the DMAE method in estimating sensor faults.
Application of cuttings natural gamma spectroscopy logging technology in well A-1
Authors: Bing Lei , Yu Yi , Zang Fali , Zhang Xinghua 
Published: December 2024

Abstract
The H-1 well revealed significant disparities between the Paleozoic strata in the Northern Jiangsu Basin and the anticipated stratigraphy prior to drilling, posing substantial challenges to the swift determination of stratigraphic ages at the site. Geological logging can obtain very limited data, such as rock color and lithology, and falls short of achieving precise lithologic identification and detailed stratification; while the X-ray diffraction logging(XRD) can initially analyze mineral content, it is unable to delineate the classification of clay mineral species.Cuttings natural gamma spectroscopy logging can precisely analyze the gamma-ray energy spectrum produced by the decay of radioactive isotopes within the formation, primarily comprising potassium, thorium, and uranium.The concentrations of Uranium (U), Thorium (Th), and Potassium (K) in rocks are intimately associate with the lithology, the extent of organic matter content, and the sedimentary environment . This technology facilitates the quantitative assessment of potassium, thorium, and uranium content within the formation. Its application has proven to be crucial for accurately identifying lithologies, conducting detailed stratigraphic comparisons, performing in-depth sedimentary environment analyses, and evaluating organic matter content.The cuttings natural gamma spectroscopy data of H-1 well shows good correlation with the natural gamma logging data, which can meet the requirements of accurate lithology identification; the rocks of different strata in the analytical map can meet the requirements of fine stratum division; the correlation coefficient between U element content and Total Organic Carbon (TOC) content is up to 0.974, which is feasible to calculate the TOC with U element content; finally, the deposition environment analysis based on natural gamma spectral recording confirmed by the analysis of trace elements.
Application of nuclear magnetic resonance core logging technology in oil and gas exploration of deep/ultra deep low porosity and low permeability reservoirs
Authors: Wang Xin , Ji Jianfei , Yin Sai 
Published: December 2024

Abstract
In order to improve the efficiency of deep/ultra deep oil and gas exploration decision-making and release production capacity, and to address the difficulties in implementing the physical and fluid properties of complex deep/ultra deep reservoirs, nuclear magnetic resonance logging technology is used to establish a permeability calculation method and a glutenite reservoir pore structure evaluation method so that the liquid production capacity of the reservoir is classified. Combing nuclear magnetic resonance logging with gas logging technology, an comprehensive hydrocarbon evaluation index SI is established to evaluate complex fluid properties. The results show that: (1) The permeability calculated by T2gm using nuclear magnetic resonance logging spectra is highly consistent with laboratory measurement results. (2) By combining the nuclear magnetic porosity and permeability of the test layer with the pore structure parameters calculated by nuclear magnetic, a classification standard for low porosity and low permeability glutenite reservoirs can be established, which can provide a preliminary evaluation of the reservoir’s liquid production capacity. (3) The comprehensive evaluation chart of nuclear magnetic resonance logging combining with gas logging can effectively distinguish oil layers, gas layers, and water layers, thereby distinguishing complex fluid properties. This research achievement is of great value for implementing the physical and fluid properties of deep/ultra deep complex reservoirs in Bohai Oilfield, and guiding efficient exploration and development operations.
Prediction of waxing degree in oil wells based on the frost optimizer algorithm
Authors: Wu Jiaqi , Yuan Chunhua , Li Xiangyu 
Published: December 2024

Abstract
Monitoring wax deposition in oil wells becomes increasingly difficult in the complex and extended downhole working conditions, where direct measurement is often impractical. Over time, wax buildup intensifies, affecting oil production and equipment functionality. The degree of wax deposition in oil wells is difficult to measure. This paper proposes a predictive strategy for rod pumping well operations. It integrates the Crested Porcupine Optimizer (CPO) optimization algorithm with Variational Mode Decomposition (VMD) decomposition, selecting suitable K and α values for the electrical power of oil wells. The Rime improves Long Short-Term Memory (RIME-LSTM) network forecasts each mode component, and the final prediction is obtained by summing these values. The method’s performance was validated using real power time series data from four wells over a specific period. The coefficient of determination (R²) and mean absolute percentage error (MAPE) evaluated the models, confirming effectiveness. Finally, a rating strategy for wax deposition predicts when to perform shutdown cleaning before severe accumulation occurs, thus protecting the oil pump and preventing low production rates. This article studies the prediction of downhole technology and wax deposition degree in oil wells, and proves its effectiveness through experiments.
Design of a downhole dynamic recorder based on flash memory
Authors: Sun Chengqin , Hu Yongjian , Sun Qi , Zhang Guanjie , Zhang Qimengsha , Xiao Meng 
Published: December 2024

Abstract
In response to the current demand for drilling cost reduction, efficiency improvement, and drilling safety in the drilling process, it is necessary to collect a large amount of real-time downhole measurement data to achieve real-time monitoring of wellbore pressure, drilling tool efficiency,and drilling speed.Nowadays,traditional while drilling measuring instruments have disadvantages such as small storage capacity, large volume, and easy loss of power due to power failure.Therefore, designing a downhole dynamic recorder based on NAND (Non-And) large capacity memory, using a small, low-power, and fast reading NAND flash memory, combined with a high-performance processor microcontroller, can achieve high-speed data access.Through calculating its theoretical storage value,removing the influence of bad blocks, the storage capacity can be increased by more than three times compared to before optimization. Data reading, writing, and erasing can be significantly improved too, and it has non volatility due to power failure. This product can record real-time data such as triaxial vibration, pressure, rotational speed, and stickiness during the drilling process, which helps to understand the situation of downhole drilling operations, optimize parameters, analyze wellbore instability and drilling tool failure, improve drilling efficiency, reduce well construction costs, and provide important reference basis for intelligent drilling operations.
Oil well fault diagnosis method based on markov transition field and convolutional neural network-long short-term memory
Authors: Zhang Shuai , Li Xiangyu , Yuan Chunhua 
Published: December 2024

Abstract
The analysis of electrical parameters and fault diagnosis in oil wells is crucial in the petroleum industry. Traditional methods often struggle to accurately capture the characteristics of time-series data, resulting in inadequate diagnostic precision. This study investigates a novel approach to improving feature extraction and fault diagnosis of electrical parameter data from oil wells. Specifically, the paper proposes encoding oil well electrical parameter data into two-dimensional images using the Markov Transition Field (MTF) technique to generate an oil well fault dataset. By incorporating the Squeeze-and-Excitation (SE) attention mechanism, the enhanced Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model demonstrates more efficient feature extraction capabilities in oil well fault classification. Experimental results show that this method achieves a fault diagnosis accuracy of 96.7%, significantly surpassing the traditional method’s 92.7%.This research provides an effective solution for improving the precision of fault diagnosis in pumping units, thereby enhancing the safety and economic efficiency of oil well operations.
Development a novel gas chromatography-mass spectrometry equipment for rapid offshore oil and gas logging
Authors: Hao Wei , Wang Huan , Shi Zhe 
Published: December 2024

Abstract
With the development of offshore oil and gas exploration, the exploration area and region are constantly expanding, and the demand for efficient and accurate response of drilling real-time oil and gas data is becoming increasingly urgent. In response to this demand, this paper introduces a new fast field oil and gas logging instrument based on gas chromatography-mass spectrometry technology, which increases the measurement speed of existing instruments by more than 2 times. Conventional gas phase logging methods can only measure light hydrocarbon components (C1-C5) data, but cannot measure heavy hydrocarbon components (C6-C8), which are the key data reflecting oil content. For this reason, the FLAIR gas chromatography-mass spectrometer developed by Schlumberger can detect gaseous and liquid alkanes within 90 seconds. However, during offshore drilling, this detection method is slow and cannot guarantee real-time detection, and data loss may occur in key formations. In response to the above problems, we have developed a fast field oil and gas logging instrument based on chromatography-mass spectrometry technology. The instrument creatively uses mass spectrometry real-time decomposition technology to complete the detection of C1-C8 components within 45 seconds, completely solving the problem of rapid on-site determination of C1-C8 multi-components, and the on-site experiment has the same accuracy as the FLAIR instrument. The instrument can significantly improve the speed and quality of on-site measurement data, thereby improving the production efficiency and decision-making ability of offshore drilling platforms. The instrument has a wide range of application potential and may even become an essential instrument for conventional oil and gas exploration in the future.