bluuebunny/crossref_metadata_2025 huggingface dataset:
A transformer cascaded model for defect detection of sewer pipes based on confusion matrix
Authors: Yu Zifeng , Li Xianfeng , Sun Lianpeng
Published: August 2024

Urban sewerage systems are critical to urban infrastructure. However, they are often subject to defects that threaten their operational reliability and efficiency. Some different types of sewer defects often have similar features. Recently, a number of deep learning models have emerged to automatically identify sewer failures, but these models often fail to accurately distinguish between them. In this paper, we propose a cascaded model to address this problem. Our work is based on the confusion matrix, which is obtained from a baseline model. With the confusion matrix, we can group confusable defects for better processing. We then design a Transformer cascaded model consisting of two steps. The first step performs coarse-grained defect detection to predict either a specific type of defect, or a group of confusable defects. In the later case, we perform a fine-grained defect detection to further distinguish the specific type of defect with the sub-model specifically trained for that group. The experimental results show that this cascaded model achieves a significant performance improvement by improving the mean average precision from 0.767 to 0.818 with our sewer object detection dataset. This method paves the way for accurate detection of defects in sewer systems.
DFMC SBAS service performance analysis of multi-GNSS based on BDS-3 in different regions
Authors: Wang Ziwei , Wang Le , Xie Wei , Huang Guanwen , Yang Weicong , Tian Yaozhao
Published: August 2024

The dual-frequency multi-constellation satellite-based augmentation system (DFMC SBAS) plays a crucial role in many fields, such as civil aviation and other safety-critical applications. To analyze the performance of the third generation of the BeiDou navigation satellite system (BDS-3) dual-frequency SBAS services in global major regions and the enhancement of navigation service performance by multi-Global Navigation Satellite System DFMC SBAS, four schemes are designed to conduct experiments using user end positioning in China (CHN), Europe (EUR), and Australia (AUS), and the results are analyzed under Approach with Vertical guidance I (APV-I) and Category I Precision Approach (CAT-I). In terms of the number of enhanced satellites, user range error, positioning accuracy, and DFMC SBAS service integrity, the results show that the positioning performances of the BDS-3 DFMC SBAS in the horizontal and vertical directions are 0.60 and 1.12 m for the CHN region, 0.87 and 1.39 m for the EUR region, and 0.64 and 1.11 m for the AUS region. In the CHN and AUS regions, the horizontal and vertical accuracies are comparable and better than those in the EUR region. Under the APV-I performance index, except for stations at the edge of the service range in the CHN and AUS regions, the availability and continuity of all stations were 100% and over 99% in the EUR region. The BDS-3 + Galileo + GPS DFMC SBAS service can significantly improve the positioning accuracy compared to a single constellation. Under the APV-I performance index, the availability and continuity of all stations in the three regions reached 100%, which also satisfied the minimum requirement of CAT-I service availability (99%).
Remaining useful life prediction of rolling bearings based on time convolutional network and transformer in parallel
Authors: Tang Youfu , Liu Ruifeng , Li Chunhui , Lei Na
Published: August 2024

Remaining useful life prediction (RUL) is crucial for maintaining the reliability and safety of industrial equipment. Recently, the Transformer has been widely used due to its ability to effectively extract global feature information in rolling bearing RUL prediction. However, the Transformer is weak in acquiring local feature information and cannot extract temporal features from the degradation process. Conversely, a temporal convolutional network (TCN) can effectively extract local features but is weak in global feature extraction. Therefore, to address the above problems, this paper proposes a prediction method based on the parallel combination of TCN and Transformer. The method first extracts the time domain, frequency domain, and time-frequency domain features from the original vibration signals. After screening through the evaluation indices, the features are fused using K-means clustering and principal component analysis (PCA) to construct health indicators (HI) that characterize the degradation of rolling bearings. Then, a TCN-Transformer parallel network model is constructed to extract both local and global features, and a feed-forward neural network (FNN) is used for the prediction of RUL. Finally, experimental validation is carried out on the PHM2012 bearing dataset, and the results show that the method achieves higher RUL prediction accuracy compared to other methods.
Classification and detection of noise in IoT based MQ gas sensors using artificial neural network
Authors: Dutta Nimisha , Mazumdar Rajdeep
Published: August 2024

IoT-based Metal Oxide Semiconductor (MOS) gas sensors have potential applications in health, industrial, and agriculture sectors. MQ gas sensors are easy to use, have a large detection range, high sensitivity, and efficiency, and can be interfaced with Arduino for effective use. However, like other any other sensors, the MQ gas sensors are also not able to escape the effect of noise that affects the sensitivity and selectivity causing the unwanted wrong classification and identification of gases, etc finally leading to a wrong justification of results and data. Hence, the study of noise and its removal is very crucial for greater accuracy in its analysis. The main aim of our work is to check whether one can classify different types of noises or noisy signals accurately using even simple ANNs so that after testing the different filtration techniques for the signals we can obtain an independent system specifically for the MQ gas sensors, that can classify as well as filter the noisy signals based on the category to which they are classified. The best and most effective noise filtration method is then obtained. During the study Narrow Neural Network model and Medium Neural Network demonstrated high accuracy in validation and testing, with ROC curves indicating their efficiency and effectiveness.
Temporal convolutional network with soft threshold and contractile self-attention mechanism for remaining useful life prediction of rolling bearings
Authors: Ma Hao , Wang Jinrui , Han Baokun , Zhang Zongzhen , Bao Huaiqian
Published: August 2024

Remaining useful life (RUL) prediction is an effective approach to prevent system failures and reduce maintenance expenditures. Due to the wide receptive field and the avoidance of future information leakage, the temporal convolutional network (TCN) is widely applied for RUL estimation of bearings. However, the predictive performance of TCN is limited by the loss of degradation features and the breakdown of continuity in timing information. To overcome the above defects, a hybrid temporal convolutional network with soft threshold and contractile self-attention mechanism (HTCN-SC) is proposed. Firstly, the adaptive threshold is determined by the contraction self-attention mechanism with higher interpretability, which captures the contribution of different features to the estimation of RUL. Then, the soft threshold is employed to activate the degraded features. On the one hand, the degeneracy features endowed by the dilated causal convolution with obvious negative values are fully preserved. On the other hand, the noise components that are given low weights are completely suppressed compared to the original TCN. Finally, parallel branch composed of one-dimensional convolutional networks are used to supplement the continuity of time series. Degradation signals from different working conditions and bearings are employed to verify the performance of the HTCN-SC. The results indicate that HTCN-SC with accurate RUL estimation and generalization ability is an effective tool for rolling bearing health monitoring.
Real Time Measurement of Electron Temperature using Coupled Center Tapped Emissive and Langmuir Probe (CCTELP)
Authors: Sanyasi Amulya Kumar , Awasthi Lalit M , Srivastava Pankaj Kumar , Adhikari Ayan , Sugandhi Ritesh
Published: August 2024

Conventional electrostatic probes are commonly used for measuring the plasma parameters like plasma density, electron temperature, plasma potential and floating potential respectively in a laboratory plasma to unveil physical processes of relevance to magnetosphere and fusion plasmas. With such probes, real-time measurement of electron temperature and its fluctuating AC component becomes very difficult. These measurements are significant as they directly give the measure of energy flux and hence can be utilized in estimating the turbulence-induced energy loss in any plasma system, especially useful for electron temperature gradient plasmas. Although Triple Langmuir Probe (TLP) diagnostics provide information on real-time measurement of electron temperature, this involves many complications. These complications of TLP are suitably overcome by the proposed diagnostic, which makes use of a combination of a closely separated centre tap emissive probe (CTEP) and Langmuir probe (LP) installed on a single probe head. The coupled centre-tapped emissive and Langmuir probe (CCTELP) provides direct measurement of electron temperature (T_e) and its fluctuations (T ̃_e). The design of the proposed diagnostic is very simple and it is almost free of rigorous control electronics and post-data analysis otherwise needed to estimate the electron temperature. These features make this diagnostic an additional and simple candidate for real-time measurement of electron temperature and its fluctuation. The paper will highlight details on this novel diagnostics, called CCTELP for the measurement in Maxwellian plasmas.
Automated body measurement of beef cattle based on keypoint detection and local point cloud clustering
Authors: Yang Lisha , Jiang Tao , Gui Xiaofei , Duan Qingling
Published: August 2024

Body size parameters of beef cattle are crucial for assessing growth status and breeding value. In actual farming environments, the various postures of beef cattle and complex backgrounds can affect the accuracy and stability of non-contact body measurement methods. Therefore, this paper proposes a novel method called the cattle body measurement method (CBMM), which combines keypoint detection with local point cloud clustering. First, a keypoint detection model based on YOLOv8-SimBiFPN is constructed. This model enhances the feature extraction and fusion capabilities of YOLOv8-pose by introducing SimAM and BiFPN into the backbone and neck networks, respectively, and realizes 2D keypoint detection for beef cattle in various postures. Second, a 3D keypoint-locating algorithm based on Density-based spatial clustering of applications with noise (DBSCAN) is proposed. This algorithm utilizes 2D keypoints, depth maps and camera parameters to generate local point clouds, which are then clustered using DBSCAN to segment cattle body point clouds, thereby relocating the 3D keypoints based on their positional features. Finally, body size parameters are calculated based on the 3D keypoints and distance formulae. In our experiment, the mean average precision (mAP@0.5) of YOLOv8-SimBiFPN reached 99.1% on an Angus beef cattle keypoint detection dataset. The mean absolute percentage errors for measuring beef cattle withers height, hip height, body depth, body length, and oblique body length using the CBMM were 4.37%, 4.96%, 6.47%, 4.84%, and 4.14%, respectively. In summary, our method can achieve non-contact body measurement for beef cattle in a free-moving state with high accuracy and stability.
A novel approach on calibration of a laser line sensor’s position in the machine coordinate system
Authors: Mei Ning , Li Du , Zhen Xiaotong , Pan Jianzhou , Zhao Zhengcai
Published: August 2024

On-machine measurement facilitates real-time monitoring and feedback of the machining status of parts, thereby preventing secondary positioning errors in the offline measurement of parts. Calibrating spatial position of the measuring sensor is crucial for ensuring the accuracy of on-machine measurements. This paper introduces a novel approach to on-machine calibration of line laser displacement sensors, based on the fitted sphere-center method and iterative position in both height and width directions along the line laser. By constructing a transformation matrix and measuring multiple sets of data to determine the unknowns in the matrix, the spatial position of the laser displacement sensor can be calibrated. The results showed that the polar deviation of the standard ball radius was 0.006 73 mm, confirming the feasibility and accuracy of the method.
Modified Universal Kriging-based clearance error optimization for orthogonal robot
Authors: Liu Wei , Zhang Qi , Xu Chunjie , Wan Yidong
Published: August 2024

Aiming at the problem that the clearance error of the traditional tire laser engraving robot is too high, and thus the resulting positioning accuracy cannot meet the accuracy requirements needed for engraving at this stage, this paper takes the homemade orthogonal robot as the object of research, and researches the optimization method of the positioning error of the orthogonal robot based on the modified Kriging. In this paper, we use spinor theory to construct a robot clearance error model, establish an objective function with orthogonal robot clearance error as the optimization objective, and use a particle swarm algorithm to modify Universal Kriging (MUK) to optimize the positioning error. The optimization method is simulated and analyzed, and MUK is selected for comparison with other optimization methods. The simulation results show that 52% relative reduces the number of iterations of the MUK to the UK model, 79% relative to the particle swarm optimization, and 81% relative to the ordinary kriging model, which makes the algorithm better applicable in comparison. At the same time, a tire laser engraving orthogonal robot experimental platform was built for physical verification experiments, and the experimental results show that the maximum error before and after the optimization of the integrated error of orthogonal robot positioning accuracy has been reduced by 89.91%; the average positioning error has been reduced by 86.90%; and the root-mean-square error has been reduced by 83.01%, which further proves the practicability of the proposed method.
Nijenhuis geometry IV: conservation laws, symmetries and integration of certain non-diagonalisable systems of hydrodynamic type in quadratures
Authors: Bolsinov Alexey V , Konyaev Andrey Yu , Matveev Vladimir S
Published: August 2024

The paper contains two lines of results: the first one is a study of symmetries and conservation laws ofgl-regular Nijenhuis operators. We prove the splitting theorem for symmetries and conservation laws of Nijenhuis operators, show that the space of symmetries of agl-regular Nijenhuis operator forms a commutative algebra with respect to (pointwise) matrix multiplication. Moreover, all the elements of this algebra are strong symmetries of each other. We establish a natural relationship between symmetries and conservation laws of agl-regular Nijenhuis operator and systems of the first and second companion coordinates. Moreover, we show that the space of conservation laws is naturally related to the space of symmetries in the sense that any conservation laws can be obtained from a single conservation law by multiplication with an appropriate symmetry. In particular, we provide an explicit description of all symmetries and conservation laws forgl-regular operators at algebraically generic points. The second line of results contains an application of the theoretical part to a certain system of partial differential equations of hydrodynamic type, which was previously studied by different authors, but mainly in the diagonalisable case. We show that this system is integrable in quadratures, i.e. its solutions can be found for almost all initial curves by integrating closed 1-forms and solving some systems of functional equations. The system is not diagonalisable in general, and construction and integration of such systems is an actively studied and explicitly stated problem in the literature.
Online MR-guided proton and ion beam radiotherapy: investigation of image quality
Authors: Paul K , Dorsch S , Elter A , Beyer C , Naumann J , Hansmann T , Feldmeier E , Haberer T , Karger C P , Debus J , Klüter S
Published: August 2024

Objective. Magnetic resonance (MR) images free of artefacts are of pivotal importance for MR-guided ion radiotherapy. This study investigates MR image quality for simultaneous irradiation in an experimental setup using phantom imaging as well as in-vivo imaging. Observed artefacts are described within the study and their cause is investigated with the goal to find conclusions and solutions for potential future hybrid devices. Approach. An open MR scanner with a field strength of 0.25 T has been installed in front of an ion beamline. Simultaneous magnetic resonance imaging and irradiation using raster scanning were performed to analyze image quality in dedicated phantoms. Magnetic field measurements were performed to assist the explanation of observed artifacts. In addition, in-vivo images were acquired by operating the magnets for beam scanning without transporting a beam. Main Results. The additional frequency component within the isocenter caused by the fringe field of the horizontal beam scanning magnet correlates with the amplitude and frequency of the scanning magnet steering and can cause ghosting artifacts in the images. These are amplified with high currents and fast operating of the scanning magnet. Applying a real-time capable pulse sequence in-vivo revealed no ghosting artifacts despite a continuously changing current pattern and a clinical treatment plan activation scheme, suggesting that the use of fast imaging is beneficial for the aim of creating high quality in-beam MR images. This result suggests, that the influence of the scanning magnets on the MR acquisition might be of negligible importance and does not need further measures like extensive magnetic shielding of the scanning magnets. Significance. Our study delimited artefacts observed in MR images acquired during simultaneous raster scanning ion beam irradiation. The application of a fast pulse sequence showed no image artefacts and holds the potential that online MR imaging in future hybrid devices might be feasible.
Semi-supervised lung adenocarcinoma histopathology image classification based on multi-teacher knowledge distillation
Authors: Wang Qixuan , Zhang Yanjun , Lu Jun , Li Congsheng , Zhang Yungang
Published: August 2024

Objective. In this study, we propose a semi-supervised learning (SSL) scheme using a patch-based deep learning (DL) framework to tackle the challenge of high-precision classification of seven lung tumor growth patterns, despite having a small amount of labeled data in whole slide images (WSIs). This scheme aims to enhance generalization ability with limited data and reduce dependence on large amounts of labeled data. It effectively addresses the common challenge of high demand for labeled data in medical image analysis. Approach. To address these challenges, the study employs a SSL approach enhanced by a dynamic confidence threshold mechanism. This mechanism adjusts based on the quantity and quality of pseudo labels generated. This dynamic thresholding mechanism helps avoid the imbalance of pseudo-label categories and the low number of pseudo-labels that may result from a higher fixed threshold. Furthermore, the research introduces a multi-teacher knowledge distillation (MTKD) technique. This technique adaptively weights predictions from multiple teacher models to transfer reliable knowledge and safeguard student models from low-quality teacher predictions. Main results. The framework underwent rigorous training and evaluation using a dataset of 150 WSIs, each representing one of the seven growth patterns. The experimental results demonstrate that the framework is highly accurate in classifying lung tumor growth patterns in histopathology images. Notably, the performance of the framework is comparable to that of fully supervised models and human pathologists. In addition, the framework’s evaluation metrics on a publicly available dataset are higher than those of previous studies, indicating good generalizability. Significance. This research demonstrates that a SSL approach can achieve results comparable to fully supervised models and expert pathologists, thus opening new possibilities for efficient and cost-effective medical images analysis. The implementation of dynamic confidence thresholding and MTKD techniques represents a significant advancement in applying DL to complex medical image analysis tasks. This advancement could lead to faster and more accurate diagnoses, ultimately improving patient outcomes and fostering the overall progress of healthcare technology.
Non-contrasted computed tomography (NCCT) based chronic thromboembolic pulmonary hypertension (CTEPH) automatic diagnosis using cascaded network with multiple instance learning
Authors: Zhao Mayang , Song Liming , Zhu Jiarui , Zhou Ta , Zhang Yuanpeng , Chen Shu-Cheng , Li Haojiang , Cao Di , Jiang Yi-Quan , Ho Waiyin , Cai Jing , Ren Ge
Published: August 2024

Objective. The diagnosis of chronic thromboembolic pulmonary hypertension (CTEPH) is challenging due to nonspecific early symptoms, complex diagnostic processes, and small lesion sizes. This study aims to develop an automatic diagnosis method for CTEPH using non-contrasted computed tomography (NCCT) scans, enabling automated diagnosis without precise lesion annotation. Approach. A novel cascade network (CN) with multiple instance learning (CNMIL) framework was developed to improve the diagnosis of CTEPH. This method uses a CN architecture combining two Resnet-18 CNN networks to progressively distinguish between normal and CTEPH cases. Multiple instance learning (MIL) is employed to treat each 3D CT case as a ‘bag’ of image slices, using attention scoring to identify the most important slices. An attention module helps the model focus on diagnostically relevant regions within each slice. The dataset comprised NCCT scans from 300 subjects, including 117 males and 183 females, with an average age of 52.5 ± 20.9 years, consisting of 132 normal cases and 168 cases of lung diseases, including 88 cases of CTEPH. The CNMIL framework was evaluated using sensitivity, specificity, and the area under the curve (AUC) metrics, and compared with common 3D supervised classification networks and existing CTEPH automatic diagnosis networks. Main results. The CNMIL framework demonstrated high diagnostic performance, achieving an AUC of 0.807, accuracy of 0.833, sensitivity of 0.795, and specificity of 0.849 in distinguishing CTEPH cases. Ablation studies revealed that integrating MIL and the CN significantly enhanced performance, with the model achieving an AUC of 0.978 and perfect sensitivity (1.000) in normal classification. Comparisons with other 3D network architectures confirmed that the integrated model outperformed others, achieving the highest AUC of 0.8419. Significance. The CNMIL network requires no additional scans or annotations, relying solely on NCCT. This approach can improve timely and accurate CTEPH detection, resulting in better patient outcomes.
A nonlinear structural pulse-like seismic response prediction method based on pulse-like identification and decomposition learning
Authors: Liu Bo , Xu Qiang , Chen Jianyun , Wang Yin , Chen Jiansheng , Zhang Tianran
Published: August 2024

Accurate and fast prediction of structural response under seismic action is important for structural performance assessment, however, existing deep learning-based prediction methods do not consider the effect of pulse characteristics of near-fault pulse-like ground motions on structural response. To address the above issues, a new method based on wavelet decomposition and attention mechanism-enhanced decomposition learning, i.e. WD–AttDL, is proposed in this study to predict structural response under pulse-like ground motions. This method innovatively combines a WD-based velocity pulse-identification method with decomposition learning, where decomposed pulses and high-frequency features are used as inputs to the neural-network model, thus simplifying the identification of pulse features for the model. The decomposition learning model integrates several types of neural network components such as convolutional neural network feature extraction submodule, long short-term memory neural network temporal learning submodule and self-attention mechanism submodule. In order to verify the accuracy and validity of the proposed methodology, three sets of case studies were carried out, including elasto-plastic time-history analyses of planar reinforced concrete (RC) frame structures, a three-dimensional RC frame structure, and two types of masonry seismic isolation structures. Compared with existing structural seismic response models, WD–AttDL synergistically integrates the advantages of different modules and thus offers a higher prediction accuracy. In particular, it reduces the peak error of the predicted response, which is important for the evaluation of structural performance. In addition, WD–AttDL has a great potential for application in fast vulnerability and reliability analysis of pulse-like earthquakes in nonlinear structures.
On the time-dependent sliding contact behavior of three-phase polymer matrix smart composites
Authors: Hu Chi , Shen Huoming , Wang Yuxing , Zhang Guoyong , Liu Juan , Zhang Xin
Published: August 2024

Three-phase smart composites consisting of magnetostrictive and piezoelectric reinforcements embedded with a polymer matrix can achieve specific multifunctional properties in response to external stimuli, which are well-suited for the application of sensors, actuators, and electronic devices. The materials exhibit complex behaviors characterized by electro-magneto-viscoelasticity coupling during the contact of these smart structures. This paper proposes a novel hybrid element method for numerically analyzing the frictionless sliding contact problem stemming from the viscoelastic behavior and multiphase interactions of polymer matrix smart composites. The study aims to fully investigate the effects of material properties, sliding velocities, and action time on the contact behavior of materials via the integration of the conjugate gradient method with the discrete convolution-fast Fourier transform algorithm. The analytical viscoelastic frequency response functions are derived by substituting elastic solutions with the time-dependent relaxation modulus. Numerical results show that three-phase polymer matrix smart composites exhibit lower contact pressure and higher surface electric/magnetic potential than three-phase magneto-electro-elastic composites. Sliding velocity and action time strongly influence the distribution of pressure/stress and electric/magnetic potential.
Shear wave velocity in a functionally graded piezoelectric semiconductor plate clamped on a rigid base
Authors: Shukla Shreya , Sahu Sanjeev A
Published: August 2024

This paper investigates the propagation of horizontally polarized shear waves in a piezoelectric semiconductor (PSC) layered structure. The modal consists of a pre-stressed PSC thin plate atop an elastic dielectric half-space joined perfectly at the interface. It is postulated that the material parameters and initial stress exhibit an exponential variation exclusively along the depth. The velocity equation of the considered wave is analytically obtained based on the traction-free boundary conditions. Numerical examples have been employed to examine the influences of several parameters, including semiconducting properties, material gradient index, initial stresses, external biasing electric field, and PSC film thickness, on the characteristics of the wave. Graphs have been generated to visualize the dependency of wave velocity and attenuation on these factors. The wave’s velocity and damping properties are significantly influenced by the thickness and steady state carrier density of the PSC plate. Besides yielding critical results, current findings are instrumental in designing high-frequency SAW devices.
Modes, bounds, and synthesis of optimal electromagnetic scatterers
Authors: Gustafsson Mats
Published: August 2024

This paper presents an optimal synthesis of material distributions in obstacles for maximal extinction, scattering, or absorption. The material synthesis is based on an explicit construction utilizing the current distribution derived from physical bounds excited from the far-field. The bounds are expressed in radiation modes for materials restricted by their resistivity and characteristic modes for materials restricted by the contrast. The results are valid for arbitrary shapes, and analytical expressions are provided for spherical shapes.
Efficient approach for generating vortex sources with arbitrary orbital angular momentum in acoustic experiments
Authors: Hao Zhanlei , Li Songsong , Xu Yadong , Zhu Shan , Chen Huanyang
Published: August 2024

In theoretical research framework of acoustics or optics, how to provide stable and efficient experimental vortex sources with arbitrary orbital angular momentum (OAM) (especially with larger OAM) is a highly challenging research topic. Here, we propose and demonstrate the general principle of two different methods to generate vortex sources with arbitrary OAM, based on the point-sources array and acoustic metamaterials, respectively. Specifically, the general synthetic law is summarized from the analytical perspective behind generating two-dimensional vortex waves using different point sources with different phases, and the design flexibility of acoustic metamaterials is also utilized to provide an ideal solution for generating vortex sources with larger OAM. Besides, we qualitatively and quantitatively determine the OAM of generated vortex waves through simple formulas, and briefly discuss the applicability and stability of two different methods with complementary advantages. The principles of vortex sources generation revealed in this work provide direct theoretical support for the experimental exploration of interactions between multiphysics fields and complex media, with potential applications in vortex fields manipulation and OAM detection.
Effects of Nd-doping on crystal phase, structure and photocatalytic performance of TiO2 powders prepared by sol-gel method
Authors: Si Yuqi , Mamat Mamatrishat , Baikeli Yiliyasi , Feng Guangwen
Published: August 2024

In this work, 0.3–2 mol% neodymium (Nd) doped titanium dioxide (TiO2) powder was prepared by sol–gel method. The XRD showed that the anatase phase occur for the Nd doped TiO2 powders, and the Nd doping suppressed the original rutile phase for the pure TiO2 powder. SEM and TEM revealed that Nd doping reduced the tendency of severe aggregation and increased the specific surface area compare with pure TiO2 powder, and the Gibbs free energy difference did not reach the critical value of the phase transition driving force, while the adjustment of the Ti-O bond length caused by the addition of Nd3+ impeded the transformation of TiO2 to rutile phase. The photocatalytic activity test results for Methylene blue show that the 0.5 mol% Nd doped TiO2 had the best photocatalytic activity with the degradation efficiency of 96.2%.
Coupled awareness-epidemic spreading with the consideration of self-isolation behavior
Authors: Xian Jiajun , Wang Teng , Zhang Wei , Chen Kunwei , Meng Nan , Sun Jiawen , Yang Dan , Liu Ming , Ye Jinlin , Wang Wei
Published: August 2024

Epidemic transmission and the associated awareness diffusion are fundamentally interactive. There has been a burgeoning interest in exploring the coupled epidemic-awareness dynamic. However, current research predominantly focuses on self-protection behavior stimulated by awareness, paying less attention to self-isolation behavior. Given the constraints of government-mandated quarantine measures, spontaneous self-isolation actions assume greater significance in the long-term response to epidemics. In response, we propose a coupled awareness-epidemic spreading model with the consideration of self-isolation behavior and subsequently employ a Micro Markov Chain Approach to analyze the model. Extensive experiments show that self-isolation behavior can effectively raise the epidemic threshold and reduce the final outbreak scale. Notably, in multiplex networks with positive inter-layer correlation, the inhibitory effect is the greatest. Moreover, there exists a metacritical point, only when the awareness diffusion probability exceeds the critical value of this point, the epidemic threshold will increase with the increase of awareness diffusion probability. In addition, the growth of the average degree of the virtual-contact layer can reduce the value of this metacritical point. This research emphasizes the significant role of self-isolation behavior in curbing epidemic transmission, providing valuable perspectives for epidemic prevention through the interplay of awareness and epidemic spreading.
Ion temperature gradient modes modulational stability with kappa-distribution
Authors: Aziz K , Mahmood A , Saqib K , Abbas A
Published: August 2024

We investigated the modulational stability and instability of the ion temperature gradient (ITG) mode in electron-ion plasma. Ions are dynamic species, whereas electrons follow a Kappa distribution. We used the reduction perturbation approach to determine the linear dispersion relation for the fluid under consideration. The nonlinear Schrodinger equation describes nonlinear features such as nonlinear modulational stability or instability in the ITG mode. The product of dissipation and nonlinear coefficients, known as LM, contains both modulational stability and instability in the ion temperature gradient mode. Theoretical results are expanded numerically, showing the influence of various plasma parameters on modulational stability and instability, particularly the superthermality coefficient κ

e
. The current observations may be extended to space and laboratory plasma for modification.
Noether symmetries, conservation laws and geometric properties of the Banados-Teitelboim-Zanelli black hole metric
Authors: Bakhshandeh-Chamazkoti Rohollah
Published: August 2024

This study provides a comprehensive analysis of the Banados-Teitelboim-Zanelli (BTZ) black hole, a significant solution in three-dimensional gravity. We begin with a detailed exploration of the BTZ black hole metric, highlighting its derivation and physical properties, such as its horizon structure and thermodynamic characteristics. The thermodynamics of BTZ black holes, including temperature, entropy, and free energy, are analyzed to understand their stability and behavior. A central focus of this work is the application of Noether symmetry principles to the BTZ black hole. We systematically compute the Noether symmetries of the BTZ metric and discuss their physical implications, including their role in conservation laws and stability analysis. This includes an examination of perturbations and their impact on the stability of the black hole, as well as a detailed geodesic analysis that leverages Noether symmetries to simplify the study of particle motion in this spacetime. Additionally, we investigate the first integrals associated with the BTZ black hole metric, elucidating their significance for the dynamics and conservation laws within this framework. The geometric analysis is further expanded through the Cartan structure equations, providing insight into the intrinsic geometric properties of the BTZ black hole and associated curvature tensors. Overall, this work integrates thermodynamic, symmetric, and geometric analyses to offer a unified understanding of the BTZ black hole’s structure and behavior, contributing to the broader field of black hole physics in lower-dimensional spacetimes.
Solution of one-dimensional Kondo lattice model, ground state calculation
Authors: Karnaukhov Igor N
Published: August 2024

The ground state of the Kondo chain is calculated taking into account the formation of local singlet states of electrons and moments. Singlets are entangled local states of electrons and moments arranged chaotically and varying in time. Two-particle scattering matrix of electrons forming singlets is calculated using the Bethe Ansatz. It is shown that electrons do not hybridize with local moments, and a lattice with a double cell is not formed. In the Kondo insulator a charge gap is calculated for an arbitrary value of the exchange integral. In the case of strong interaction the gap is determined by the single-particle energy of the singlet, for weak interaction—by correlations (the gap is proportional to the square of the exchange integral).
Cylindrical Blume-Capel Nanotube with core/shell structure: compensation temperature and hysteresis loops
Authors: El Kihel K , Salama M , Hachem N , El Bouziani M
Published: August 2024

The critical, compensation and hysteresis behaviors of the Blume-Capel model with mixed spins

S

k

S

=
±
2
,
±
1
,
0

and

σ

i

C

=
±
3

/

2
,
±
1

/

2

, on a cylindrical nanotube with core–shell structure were studied using the mean-field approximation based on the Gibbs-Bogoliubov inequality. The effects of the single-ion anisotropies and the exchange coupling on phase diagrams, magnetizations and hysteresis loops were investigated. The first-order and second-order phase transitions and critical end-point were found, therefore, the system does not give any tricritical point. Furthermore, the model’s results anticipate the presence of the compensation phenomena and multi-cycle hysteresis behaviors.
Puzzle of the cornell potential on the heavy and heavy-light meson spectra
Authors: A Alkathiri Ali , El-Sherif L S , Bakry A M , Ismail Atef , Allosh M
Published: August 2024

We computed the eigenvalues and eigenfunctions via the Cornell potential, approximately, using Numerov approach. The experimental data for the quantum states 3
S
1 were utilized to fit the mass spectra. Results were compared with observed data and the results obtained from other potential functions in the existing literature for the heavy (

c

c
¯

,

b

b
¯

and

b

c
¯

) as well as heavy-light (B, Bs, D and Ds) meson states. The yielded meson spectra based on this potential are matching well with the available experimental data.
Investigation on the optical properties of group-III nitride materials based on fully-connected neural network
Authors: Li Yi , Ge Mei , Wang Meiyu , Deng Honghai , Guo Xinglong , Zhu Youhua
Published: August 2024

In order to accurately simulate the optical properties of nitride optoelectronic devices, such as the reflection spectrum of distributed Bragg reflectors (DRBs), the optical constant is generally considered an important parameter. In this work, the fully-connected neural network is adopted to predict the real and imaginary parts of ordinary dielectric function (DF) of III-nitrides across the full composition range and wide spectral range. The input parameters include Al-component, Ga-component, In-component, and photon energy. The predicted dielectric constant is basically consistent with the results calculated by the analytical model reported in the literature. Then, the band gaps of 6 eV, 3.4 eV and 0.73 eV for AlN, GaN, and InN were determined by using the Tauc formula. The fitted bowing parameters are 0.94 eV, 4.3 eV, and 1.6 eV for AlGaN, InAlN, and InGaN alloys, respectively. Finally, using the predicted dielectric constant, the calculated reflection spectrum of the DBR structures is in agreement with the experimental results in the literature.
Effect of temperature on braking performance of the comb-type disc magnetorheological brake
Authors: Zhu Xinyue , Yang Xiaolong , Cao Zhiqiang
Published: August 2024

To investigate the effect of internal temperature variation of the comb-type disc magnetorheological brake on braking performance, firstly we simulate the temperature field analysis of magnetorheological brake by using the finite element method, and verify the reasonableness of the simulation using experiments. Secondly, the temperature variation of comb magnetorheological brakes during intermittent 5 min braking and continuous braking and the effect of temperature on the braking torque were investigated experimentally. The experimental results show that as the number of braking increases, the maximum temperature inside the brake increases until saturation, while the braking torque decreases. This research helps to enhance the realization of braking stability over the effective operating temperature range.
Investigating novel Mo2X3S (X = Se, Te) materials: probing the influence of chalcogen substitution on electronic, optical, and thermoelectric properties
Authors: Mohamed Abdelhay Salah , Gul Banat , Salman Khan Muhammad , Ahmad Hijaz , Awang Mohd Khalid , Abbas Faheem
Published: August 2024

The excellent thermal performance and adjustable optoelectronic characteristics distinguish the ternary semiconductors. Using the state-of-the-art density functional theory, the optoelectronic, and thermoelectric characteristics of new Mo2X3S (X = Se, Te) ternary chalcogenides are studied. The predicted band gap values with TB-mBJ for Mo2Se3S and Mo2Te3S materials were 1.41 eV and 2.10 eV, respectively. For their possible employment in optoelectronic applications, the components of the complex dielectric function and the vital optical characteristics were calculated and studied. For an increase in the band gap and with the replacement of Se to Te, the peaks in ε
1(ω) shifted to higher energies. Mo2Se3S and Mo2Te3S both show stronger absorption in the UV and visible ranges. Based on the observed peaks in the reflection spectrum, they may used as ultraviolet-reflecting materials with good efficacy. Both Mo2Se3S and Mo2Te3S have positive Seebeck coefficient values, they exhibit p-type conduction. The Mo2Te3S material displays a maximum Seebeck coefficient at about 500 K compared to Mo2Se3S, which leads to a maximum ZT.
Constraining the hadronic properties of star-forming galaxies above 1 GeV with 15-years Fermi-LAT data
Authors: Ambrosone A. , Chianese M. , Marinelli A.
Published: August 2024

Star-forming and starburst galaxies (SFGs and SBGs) are considered to be powerful emitters of non-thermal γ-rays and neutrinos, due to their intense phases of star-formation activity, which should confine high-energy Cosmic-Rays (CRs) inside their environments. On this regard, the Fermi-LAT collaboration has found a correlation between the γ-ray and infrared luminosities for a sample of local sources. Yet, the physics behind these non-thermal emission is still under debate. We provide novel constraints on the tight relation between γ-rays and star formation rate (SFR) exploiting 15 years of public Fermi-LAT data. Thus, we probe the calorimetric fraction Fcal of high-energy protons in SFGs and SBGs, namely, the fraction of high-energy protons actually producing high-energy γ-rays and neutrinos. Further, we extrapolate this information to their diffuse γ-ray and neutrino emissions constraining their contribution to the extra-galactic gamma-ray background (EGB) and the diffuse neutrino flux. Using the publicly-available fermitools, we analyse 15.3 years of γ-ray between 1-1000 GeV data for 70 sources, 56 of which were not previously detected. We relate this emission to a theoretical model for SBGs in order to constrain Fcal for each source and then study its correlation with the star formation rate of the sources. Firstly, we find at 4σ level an indication of γ-ray emission for other two SBGs, namely M 83 and NGC 1365. By contrast, we find that, even with the new description of background, the significance for the γ-ray emission of M 33 (initially reported as discovered) still stands at ~ 4σ (as already reported by previous works).
Along with previous findings, the flux of each detected source is consistent with a ~ E
-2.3/2.4 spectrum, compatible with the injected CR flux inferred in the Milky-Way. We also notice that the correlation between Fcal and the SFR is in accordance with the expected scaling relation for CR escape dominated by advection. We remark that undiscovered sources strongly constrain Fcal at 95% CL, providing fundamental information when we interpret the results as common properties of SFGs and SBGs. Finally, we find that these sources might contribute (12 ± 3)% to the EGB, while the corresponding diffuse neutrino flux strongly depends on the spectral index distribution along the source class.
Shadows, rings and optical appearance of a magnetically charged regular black hole illuminated by various accretion disks
Authors: Zare Soroush , Nieto Luis M. , Feng Xing-Hui , Dong Shi-Hai , Hassanabadi Hassan
Published: August 2024

The Event Horizon Telescope (EHT) imaging of the supermassive black holes at the centers
of Messier 87 galaxy (M87) and the Milky Way galaxy (Sgr A) marks a significant step in observing
the photon rings and central brightness depression that define the optical appearance of black
holes with an accretion disk scenario. Inspired by this, we take into account a static and
spherically symmetric magnetically charged regular black hole (MCRBH) metric characterized by its
mass and an additional parameter q, which arises from the coupling of Einstein gravity and
nonlinear electrodynamics (NLED) in the weak field approximation. This parameterized model
offers a robust foundation for testing the coupling of Einstein gravity and NLED in the
weak-field approximation, using the EHT observational results. In this study, we investigate the
geodesic motion of particles around the solution, followed by a discussion of its fundamental
geometrical characteristics such as scalar invariants. Using null geodesics, we examine how the
model parameter influences the behavior of the photon sphere radius and the associated shadow
silhouette. We seek constraints on q by applying the EHT results for supermassive black holes
M87* and Sgr A*. Furthermore, it is observed that the geodesics of time-like particles are
susceptible to variations in q, which can have an impact on the traits of the innermost stable
circular orbit and the marginally bounded orbit. Our primary objective is to probe how the free
parameter q affects various aspects of the accretion disk surrounding the MCRBH using the
thin-disk approximation. Next, we discuss the physical characteristics of the thin accretion
disk as well as the observed shadows and rings of the MCRBH, along with its luminosity, across
various accretion models. Ultimately, variations in accretion models and the parameter q yield
distinct shadow images and optical appearances of the MCRBH.
Cosmic purity lost: perturbative and resummed late-time inflationary decoherence
Authors: Burgess C.P. , Colas Thomas , Holman R. , Kaplanek Greg , Vennin Vincent
Published: August 2024

We compute the rate with which unobserved fields decohere other fields to which they couple, both in flat space and in de Sitter space, for spectator scalar fields prepared in their standard adiabatic vacuum. The process is very efficient in de Sitter space once the modes in question pass outside the Hubble scale, displaying the tell-tale phenomenon of secular growth that indicates the breakdown of perturbative methods on a time scale parameterically long compared with the Hubble time. We show how to match the perturbative evolution valid at early times onto a late-time Lindblad evolution whose domain of validity extends to much later times, thereby allowing a reliable resummation of the perturbative result beyond the perturbative regime. Super-Hubble modes turn out to be dominantly decohered by unobserved modes that are themselves also super-Hubble. If applied to curvature perturbations during inflation our observations here could close a potential loophole in recent calculations of the late-time purity of the observable primordial fluctuations.