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By the continuous development of aerospace, petroleum exploration, and other industrial fields, the fiber-optic acoustic sensor (FOAS) with high reliability is a desideration sensor, which can be used for noise monitoring in the extremely harsh environment. The FOAS based on the all-rigid Fabry–Perot resonator (FPR) relies on the new acoustic sensitive principle, where the change in the air refractive index is induced by sound waves and gets rid of the distortion caused by the mechanical characteristics of the acoustic sensor based on the movable parts. So, the FPR-based FOAS is very suitable for acoustic sensing in the harsh environment. In this paper, the reliability of this kind of FOASs is simulated and analyzed. The modal and anti-vibration simulation results of FPR with different sizes show that the FPR has a high natural frequency, and the external vibration environment does not affect the acoustic sensitivity of the FPR. The micro and small-batch all-rigid FPR can be manufactured by the optical contact. Moreover, the FPR can withstand the high temperature of 500°C that is verified by rapid heat treatment equipment. In order to improve the reliability of the FOAS, the metal packing shell is designed and fabricated. Moreover, the vibration and high-temperature tests of the packaged sensor are carried out. The two groups of tests show that the sensor can work normally under 10 g of acceleration vibration and 200°C high temperature, respectively. Therefore, the FOAS based on the FPR has high reliability and is very suitable for noise monitoring in the extreme harsh environment of various industrial fields. Furthermore, the research results of this paper will enhance the competitiveness and influence of the commercialized FOAS.

Introduction: In recent years, we witnessed increasing numbers of migrants worldwide owing to famine, poverty, regional conflicts, etc. Efforts by the United Nations and various organizations to help these migrants are hampered by rising anti-migrant sentiments and xenophobic rhetoric in many parts of the world. To arrive at win-win solutions that benefit both natives and migrants, we must discuss the migration problem objectively and scientifically. To do this, we must first resolve the paradox in our understanding of human migration (widely touted as good) vis-a-vis biological invasion (generally regarded as bad).Method: Suspecting that the two similar phenomena are more complex than we think, we reviewed and synthesized the disjoint literatures on human migration and biological invasion in recent times, and that on the human diaspora and human-aided dispersal of plants and animals in our pre-historic past. We then developed models of niche-niche interactions to simulate isolated ecosystems and communities, as well as those experiencing invasions from non-native populations.Results: In this paper, we simulated four invasion mechanisms on a star network: the direct introduction of a non-native population into existing periphery or core niches, or the non-native population first creating its own niche, which is thereafter attached to the periphery or core of the community. We found that periphery invasions can fail, i.e., the non-native population eventually disappears. When periphery invasion is successful, we found that there is little or no harm to the ecosystem or community. On the other hand, core invasion is always catastrophic, where the non-native population establishes itself at the expense of most or all of the native populations. For niche attachments, whether to the periphery or to the core, we found native and non-native populations coexisting in the end, sometimes with increased diversities.Discussion: Our results provide promising new insights and theoretical grounds for policymakers to discuss the ethics of immigration issues scientifically, and to ultimately discover win-win solutions for natives and migrants. The theoretical framework outlined in this paper can also be applied to the problem of introducing non-native biological species for economic gains, at acceptable ecological costs.

When analyzing the transmission characteristics of LEDs for long-distance lighting and communication applications, the light field is commonly assumed to be fully incoherent. However, in reality, the LED light source emits partially coherent light with a spatial coherence length on the order of microns. This paper is based on the generalized higher-order Lambert model of LEDs and aims to construct a Gaussian-Schell model for the LED beam (LED-GSM) on the near-field source plane, with a half-power angle of no more than 10o. Utilizing the cross-spectral density function transmission theory for partially coherent light, this paper provides the LED-GSM model’s spatial coherence length and beam radius at different distances and designs an experiment for measuring the spatial coherence length of LED beams. Experimental measurements of the spatial coherence length and beam spot size of LED beams at different distances are carried out using a Thorlabs LED528EHP light source. The experimental results match well with the theoretical simulations of the LED-GSM model, thus validating its effectiveness. Then, the proposed LED-GSM model is utilized to investigate the long-distance transmission characteristics of partially coherent narrow-beam LED light. Simulation results indicate that the spatial coherence length of the LED light field can reach tens to hundreds of millimeters over transmission distances of several kilometers. The beam radius is much smaller than that of the beam radius based on the fully incoherent model, and the beam intensity distribution also displays distinct differences.

In this paper, the fuzzy scattering problem with semicircular depressions on the boundary of a band-shaped elastic plate with steady SH guided wave incident is studied and an analytical solution is given. First, the SH guided wave is constructed by the guided wave expansion method, and then the scattered wave satisfying the free condition of the boundary stress of the strip domain is constructed by the cumulative mirror method. Finally, a definite solution equation is obtained based on the fact that the shear stress at the edge of the semi-circular recessed hole is zero. In this paper, the ambiguity of the number of waves and the width of the bands is taken into account. In order to avoid the irreversibility of interval algorithm and the difficulty of solving non-linear equations, the membership function of fuzzy quantity is segmented to make the membership degree and fuzzy quantity correspond respectively. A deterministic problem that translates into piecewise processing. Two numerical examples are given to examine the changes in fuzzy response of different numbers of fuzzy waves and fuzzy thicknesses to the dynamic stress concentration factor of the hoop at the collapse limit.

The fractional solitons have demonstrated many new phenomena, which cannot be explained by the traditional solitary wave theory. This paper studies some famous fractional wave equations including the fractional KdV–Burgers equation and the fractional approximate long water wave equation by a modified tanh-function method. The solving process is given in details, and new solitons can be rigorously explained by the obtained exact solutions. This paper offers a new window for studying fractional solitons.

In recent years, with the continuous enhancement of people’s fitness awareness, more and more people are doing anaerobic exercise training. Although anaerobic exercise training can improve physical fitness, people also have some problems in anaerobic exercise training due to the lack of necessary exercise training guidance. Therefore, in order to give full play to the role of anaerobic exercise training and enhance human body functions, this paper studies the effects of anaerobic exercise training and anaerobic exercise training on human body functions based on multiple linear regression analysis (MLR). This paper proposes an anaerobic exercise training model based on MLR, and conducts research experiments from seven aspects including exercise capacity, immunity, and cardiovascular function. The experimental results show that the MLR-based anaerobic exercise training mode can improve exercise capacity by 5.48%, immunity by 3.08%, and cardiovascular function by 4.31%.

Fault of rolling bearing signal is a common problem encountered in the production of life. Identifying the fault signal helps to locate the fault location and type quickly, react to the fault in time, and reduce the losses caused by the failure in production. In order to accurately identify the fault signal, this paper presents a triple feature extraction and classification method based on multi-scale dispersion entropy (MDE) and multi-scale permutation entropy (MPE), extracts the features of the signal of rolling bearing when it is working, and uses the classification algorithm to determine whether there is a fault in the bearing and the type of fault. Scale 2 of MDE is combined with scale 1 and scale 2 of MPE as the three features required for the experiment. As a comparison of recognition results, multi-scale entropy (MSE)is introduced. Ten scales of the three entropy are calculated, and all combinations of three feature extraction are obtained. K nearest neighbor algorithm is used for three feature recognition. The result shows that the combination recognition rate proposed in this paper reaches 96.2%, which is the best among all combinations.

Beamforming technology with spherical microphone arrays (SMAs) is often applied for localizing and identifying noise sources in airplane cabins, automobiles, and submarines. The performance of a SMA signal processing algorithm depends on its physical characteristics, especially the array aperture. The array aperture limits the frequency range of its application, and the small aperture leads to weak performance at low frequencies. In this paper, a large-aperture virtual SMA is obtained through the virtual SMA extrapolation method. Because the radius of the virtual SMA is larger than that of the actual SMA, an approximate low-frequency signal can be obtained, which may improve the localization effect of the low-frequency noise source of the SMA. Firstly, the paper introduces the extrapolation method of SMA, and through the discussion of several typical parameters such as envelope parameters, SMA aperture and signal-to-noise ratio (SNR), the application scope and conditions of SMA extrapolation method are given. In addition, this paper introduces compressed sensing technology (CS) into the calculation process of virtual SMA extrapolation to improve the accuracy of virtual SMA element data. The generalized inverse beamforming (GIB) algorithm is then used to locate and identify noise sources and verify the benefits of the virtual SMA. Simulation and experimental results show that the virtual SMA can locate and identify noise sources with high spatial resolution in the low frequency range.

The burial depth of Penglai gas field reservoir in the Sichuan Basin of China exceeds 7,000 m, and the reservoir temperature is 160°C. Penglai gas field belongs to the fractured reservoir, and there are many natural fractures distributed in the reservoir. Natural fractures are not only the storage place of natural gas, but also the transportation channel of natural gas. Gas wells mainly increase natural gas production through acid fracturing. In the early stage, Penglai Gas Field mainly used gelled acid fracturing technology to create an artificial fracture in the reservoir by injecting a large amount of acid fluid. However, the stimulation range of gelled acid fracturing is very small. After acid fracturing, gas wells can only produce 120,000 cubic meters of natural gas per day. To obtain higher natural gas production, this paper proposes a multi-stage temporary acid fracturing technology that can greatly improve the effect of acid fracturing. The temporary plugging agent for acid fracturing has been developed to meet the high-temperature requirements of the Penglai gas field. Based on the simulation of fracture propagation, the feasibility of acid fracturing expansion of natural fractures in the Penglai Gas Field is clarified. Fiber and granular temporary plugging agents that meet the plugging strength greater than 20 MPa are selected by using the dynamic temporary plugging instrument. MultiFracS software is used to optimize the multi-stage temporary acid fracturing process parameters. The research results in this paper have been applied to wells PS101, PS102, and PS103. After fracturing, compared with the gelling acid fracturing, the natural gas production has increased by more than three times, and the multi-stage temporary plugging acid fracturing has achieved a very good stimulation effect.

In this paper, nonlinear electrostatic structures on the ion time scale in plasma consisting of two populations of electrons (cold and hot), positrons, and warm adiabatic ions are investigated. The multiple scale method is used to derive the modified Korteweg–de Vries equation (mKdVE). The Jacobi elliptic function expansion method (JEFEM) is employed to find some exact analytical solutions such as periodic, solitonic, and shock solutions. It is shown that the variation in the plasma parameters of interest, for our model, allows the existence of solitary and periodic structures and no shocks. It is also shown that the most important plasma parameters for the plasma model under consideration are positron concentration, α, and the percentage of cold and hot electrons, represented by the parameters μ and ν, respectively. Additionally, the qualitative behavior of the mKdVE is studied using dynamical system theory. The topological structure of the solution is discussed in the phase plane. In this work, the phase plane analysis, which is restricted to the discrete values of the parameter, is extended to the continuous range of the parameter using a bifurcation diagram. Bifurcation diagrams are drawn to forecast the behavior of the solution for specifically chosen essential plasma parameters. The analytical solution and the qualitative behavior of the solution presented in this paper are shown to be compatible with each other. The results presented here are general and can be gainfully employed to study a variety of nonlinear waves in space, laboratory plasmas, and astrophysical plasmas.

Based on the Vector Autoregressive Model (VAR), this paper constructs a contagion complex network of global stock market returns, and uses the Quantile-on-Quantile Regression (QQR) to explore the impact of global geopolitical risks on the connectedness of global stock markets. By applying the risk contagion analysis framework, we depict risk contagion and correlation between financial markets in different countries. We also identify the risk contagion characteristics of international financial markets. This paper innovatively introduces the quantile-on-quantile regression method to the study of geopolitical risk. Through the quantile-on-quantile approach, we find that there is an asymmetric relationship between geopolitical risk and the global stock market correlation network. Our conclusions provide some suggestions for policy makers and relevant investors on how to deal with the current high global geopolitical risks. They also provide ideas on how to effectively hedge such risks during asset allocation and policy formulation.

Convolution neural network (CNN)is widely used in hyperspectral image (HSI) classification. However, the network architecture of CNNs is usually designed manually, which requires careful fine-tuning. Recently, many technologies for neural architecture search (NAS) have been proposed to automatically design networks, further improving the accuracy of HSI classification to a new level. This paper proposes a circular kernel convolution-β-decay regulation NAS-confident learning rate (CK-βNAS-CLR) framework to automatically design the neural network structure for HSI classification. First, this paper constructs a hybrid search space with 12 kinds of operation, which considers the difference between enhanced circular kernel convolution and square kernel convolution in feature acquisition, so as to improve the sensitivity of the network to hyperspectral information features. Then, the β-decay regulation scheme is introduced to enhance the robustness of differential architecture search (DARTS) and reduce the discretization differences in architecture search. Finally, we combined the confidence learning rate strategy to alleviate the problem of performance collapse. The experimental results on public HSI datasets (Indian Pines, Pavia University) show that the proposed NAS method achieves impressive classification performance and effectively improves classification accuracy.

With the increasing economic and strategic significance of the global navigation satellite systems (GNSS), interference events also occur frequently. Interference monitoring technologies aim to monitor the interference that may affect the regular operation of the GNSS. Interference monitoring technologies can be divided into three parts: interference detection and recognition, interference source direction finding, and interference source location and tracking. Interference detection aims to determine whether interference exists. This paper introduces the classification of interference and the corresponding detection methods. The purpose of interference recognition is to recognize and classify interference. It is often combined with pattern recognition and machine learning algorithms. Interference source direction finding aims to estimate the direction of the interference signal. There are three kinds of methods: amplitude, phase, and spatial spectrum estimation. Interference source location aims to estimate the position of the interference signal. It is usually based on the received signal strength (RSS), time difference of arrival (TDOA), frequency difference of arrival (FDOA), angle of arrival (AOA) or direction of arrival (DOA). Interference source tracking aims to track moving interference sources, and it is generally based on Kalman filter theory. This paper summarizes the interference monitoring technologies and their latest progress. Finally, prospects for interference monitoring technologies are offered.

With the improvement of people's material living standards, more and more people start to pay attention to health issues. This paper takes the health field as the main research object, and discusses the current development and status quo of the health field. Through literature review, it is found that the current health field mainly focuses on the single monitoring of a certain organ or body function, and there are limitations in systematic health monitoring research, and most of the research stays at the stage of human body monitoring. Therefore, this paper intends to design a sports health monitoring and management system based on artificial intelligence. The system is mainly divided into a body temperature monitoring module, a blood pressure monitoring module and an exercise monitoring module, through which the user's health data is monitored. In order to ensure the practicability of the system, this paper selects three common life states in daily life for experimental testing, namely exercise state, rest state and sick state. The experimental test results show that each monitoring module can operate correctly and normally under three different states. The lowest temperature was 36.5° and the highest temperature was 37.1° under the exercise state. The lowest blood pressure is 70 in the resting state, and the highest blood pressure is 80. In the sick state, the maximum value of motor threshold is 0.2, the minimum value is 0.1, and the threshold difference is 0.1. Each module reads and backs up relevant data, and sends it to the platform for intelligent analysis. The platform will analyze and compare the data of different modules at the same time, judge the health status of the user at that time, choose whether to issue a health alert for the user, and finally complete the entire system process of the health monitoring management system. This proves that the sports health monitoring management system based on artificial intelligence algorithm designed in this paper is effective and feasible.

A large number of heliophysicists from across career levels, institution types, and job titles came together to support a poster at Heliophysics 2050 and the position papers for the 2024 Heliophysics decadal survey titled “Cultivating a Culture of Inclusivity in Heliophysics,” “The Importance of Policies: It’s not just a pipeline problem,” and “Mentorship within Heliophysics.” While writing these position papers, the number of people who privately shared disturbing stories and experiences of bullying and harassment was shocking. The number of people who privately expressed how burned out they were was staggering. The number of people who privately spoke about how they considered leaving the field for their and their family’s health was astounding. And for as much good there is in our community, it is still a toxic environment for many. If we fail to do something now, our field will continue to suffer. While acknowledging the ongoing growth that we as individuals must work toward, we call on our colleagues to join us in working on organizational, group, and personal levels toward a truly inclusive culture, for the wellbeing of our colleagues and the success of our field. This work includes policies, processes, and commitments to promote: accountability for bad actors; financial security through removing the constant anxiety about funding; prioritization of mental health and community through removing constant deadlines and constant last-minute requests; a collaborative culture rather than a hyper-competitive one; and a community where people can thrive as whole persons and do not have to give up a healthy or well-rounded life to succeed.

Shack-Hartmann wavefront sensor (SHWFS) has been widely used in adaptive optics (AO) systems to detect phase distortion characteristics. In laser communication, target detection, vision optics and other application fields, the performance of SHWFS is affected by bright skylight and scattered light, which restricted the working ability of the AO system severely. Therefore, this paper proposes a new polarized SHWFS (p-SHWFS) based on the principle of polarization imaging, which utilize the difference of state of polarization (SoP) between signal and stray light to improve the image contrast. The p-SHWFS can be composed simply by a micro-lens array and a linear polarization camera. The camera uses four directional polarizing filters at 0°, 135°, 45° and 90° on every four pixels. Thus, the degree of linear polarization (DoLP) and angle of linear polarization (AoLP) for the incident wavefront can be analyzed, and the signal-to-background ratio (SBR) can be improved in some certain depending on the difference of SoP. In this paper, we introduce the basic principle of the p-SHWFS and validate the feasibility and accuracy improvement by numerical simulation and practical experiments. The experimental results show that the p-SHWFS can improve obviously the measurement accuracy under strong stray light when the difference of SoP exists. That may give us some initial reference to reduce the influence of stray light in laser communication, target detection, vision optics and other application fields.

There is abundant ship information in ship-radiated noise, which is helpful for ship target recognition, classification and tracking. However, owing to the increasing complexity of the marine environment, it makes difficult to extract S-RN features. Dispersion entropy has been proven to be an excellent method to extract the features of S-RN by analyzing the complexity of S-RN, and has been widely used in feature extraction of S-RN. This paper summarizes the research progress of DE in the feature extraction of S-RN in recent years, and provides a comprehensive reference for researchers related to this topic. First, DE and its improved algorithm are described. Then the traditional and DE-based S-RN feature extraction methods are summarized, and the application of DE in S-RN feature extraction methods is concluded from two aspects: methods that apply DE algorithms only and methods that combine DE with mode decomposition algorithms. Finally, the research prospects of DE and the summary of this paper are given.

We describe how the prompt fission neutron spectrum (PFNS) was determined for the Manhattan Project at Los Alamos. Early work before World War II at American and British universities is described, together with theoretical work by Feather at Cambridge and Bethe at Los Alamos. As the Manhattan Project was being planned in 1942, two experiments on natural uranium were commissioned that proved to be influential: 1) An integral experiment at Chicago by Christy and Manley that accurately determined the average PFNS spectrum energy, 2.2 ± 0.2 MeV; 2) Bloch and Staub’s Stanford cyclotron measurement of the PFNS spectrum, which obtained an average energy of 1.70 ± 0.34 MeV. These two papers, previously unavailable outside of Los Alamos, are reproduced in the Supplementary Appendix. From these data, at the beginning of the project in 1943 Serber estimated an average 235U PFNS energy of 2 MeV, and indeed this agrees with today’s best estimate. The challenges facing the scientists involved both the availability of only very small samples of enriched uranium and plutonium targets, and fast neutron detection technologies. During the project, 235U and 239Pu PFNS were measured by Nicodemus and Staub. These also proved to be quite accurate and gave an average spectrum energy of 2 MeV for 235U. [This is not reproduced in the Appendix because it was published after the war in Physical Review 89, 1288 (1953)]. New methods were developed to enable more accurate measurements, and this paper describes how the PFNS was determined surprisingly well by 1945. We end by describing the post-war measurements in the 50s, including the PFNS data used by Ford and Wheeler in their simulations in 1951, the Bonner 1952 data, the seminal 1952 Watt paper with a new empirical parametrization of the PFNS, and the accurate PFNS measurement undertaken at Los Alamos by Cranberg et al. in 1956. We compare the measurements with our best understanding today as embodied in the Evaluated Nuclear Data File ENDF/B-VIII.0. Some images from historical documents in our Los Alamos National Security Research Center (NSRC) archives are shown.

In this paper, a heterogeneous intersection formula, a method of fusion of coordinates, and an error allocation method are introduced in order to improve the target coordinate measurement accuracy of the intersection measurement of the theodolite. Additionally, the angle measurement accuracy of the theodolite is divided into horizontal and vertical components for discussion, and the coordinate measurement accuracy of the theodolite obtained by this method is compared and analyzed. This paper first introduces the formula for coplanar intersection, then suggests the formula for fusing theodolite coordinates and error, and then verifies the accuracy of the formula through experimentation. Finally, it simulates the goniometric accuracy with the normal distribution error using MATLAB and derives the coordinate measurement accuracy using this method. The simulation results demonstrate the viability of the error distribution approach and fusion formula used for data processing in this paper.

The reliability of the immersed tunnel element joint is the key to determine whether the immersed tunnel can operate safely. At present, the immersed tunnel monitoring mostly pays attention to the joint opening and closing amount and neglects the differential deformation of the joint. Based on the immersed tunnel of Hong Kong-Zhuhai-Macao Bridge, combined with the operating environment and structural characteristics of the immersed tunnel, this paper introduces a close-range photogrammetry method to monitor the differential deformation of the immersed tunnel element joint. Through theoretical analysis, software and hardware development, laboratory test and field test, the paper puts forward puts forward a comprehensive multi-parameter evaluation and screening algorithm of boundary fitting ellipse based on fitting rate, ellipticity and area difference and a micro-displacement correction algorithm for camera based on three-dimensional calibration object, and develops an automatic monitoring system equipment for differential deformation of immersed tunnel element joint. Upon tests in tunnels, the monitoring equipment is proven in automatic monitoring on differential deformation of immersed tunnel element joints. This equipment has been successfully applied to the E31~E32 element joint of Hong Kong-Zhuhai-Macao Bridge immersed tunnel, which verifies the effectiveness of the equipment from the perspective of practical engineering application.

Introduction: Distributed wideband jamming (interference) is commonly used in navigation countermeasure. Due to the limited volume of GNSS (Global Navigation Satellite System) array antenna receiver, the number of interferences usually exceeds the number of array elements. At present, the anti-jamming capability and mechanism of Global Navigation Satellite System array antenna against distributed sup-DOF (Degree of Freedom) interference have not been fully studied.Methods and innovation: To solve this problem, this paper analyzes the characteristics of GNSS System array antenna against sup-Degree of Freedom interference by formula derivation and simulation. Firstly, the definition of sup-Degree of Freedom interference of Global Navigation Satellite System array antenna is proposed from the perspective of spatial anti-jamming; Secondly, the directional characteristics of Global Navigation Satellite System array antenna for sup-Degree of Freedom interference suppression are analyzed.Results: The results show that the performance of sup-Degree of Freedom interference suppression is sensitive to the direction and distribution of interference. On the one hand, the residual interference power varies from interference direction and distribution, while the minimum value of which is zero and the maximum value is the sum of interference power. On the other hand, the suppression performance of UCA (Uniform Circular Array) and central Uniform Circular Array is periodic along azimuth. If the number of elements on the circumference is M (M ≥ 3), the period of the suppression performance is 4π/M/3+(−1M+1.Discussion: The conclusion of this paper show the upper and lower bounds of sup-Degree of Freedom interference suppression performance and the variation rule in azimuth, which can be used in the fields such as interference deployment, anti-jamming performance evaluation and anti-jamming algorithm development.

In order to alleviate the privacy issue of traditional smart grids, some researchers have proposed a power metering system based on a federated learning framework, which jointly trains the model by exchanging gradients between multiple data owners instead of raw data. However, recent research shows that the federated learning framework still has privacy and security issues. Secondly, since the server does not have direct access to all parties data sets and training process, malicious attackers may conduct poisoning attacks. This is a new security threat in federated learning - poisoning attack. However, solving the two problems at the same time seems to be contradictory because privacy protection requires the inseparability of the training gradients of all parties, and security requires the server to be able to identify the poisoned client. To solve the above issues, this paper proposes an intrusion detection method based on federated learning client-side security in AMI networks, which uses CKKS to protect model parameters. In addition, to resist the poisoning attack in federated learning, the model trained by the data processing center and the model trained by each client are firstly calculated for the direction similarity, and the similarity value is scaled as the adaptive weight of the aggregation model. Then, the size of each client model update is normalized to be the same size as the data processing center model update. Finally, the normalized updates and adaptive weights are weighted averaged to form a global model update. The research results show that the method in this paper can effectively resist inference attacks and poisoning attacks. In the AMI network, the intrusion detection method based on federated learning can maintain a good detection performance.

The equipment in railway station is complicated and diverse, and the health status assessment and prediction of equipment is crucial to the safe and stable operation of stations. Graph Neural Networks (GNNs) effectively combine graph data with deep learning technology, which has stronger data and knowledge representation capability and can efficiently handle some non-Euclidean spatial data problems with irregular station equipment associated network structure. Based on this, this paper takes the automatic gate machine and X-ray security checker as an example and proposes a health status assessment and prediction scheme for railway passenger station equipment based on Graph Long Short-Term Memory (G-LSTM) neural network. This paper first analyzes the main factors affecting the health status of passenger station equipment, as well as the correlation between the equipment. Then, the initial graph network structure of the passenger station equipment is constructed, and the G-LSTM model is used to evaluate and predict the health status of the passenger station equipment. Finally, this paper takes the automatic gate machine and X-ray security checker of a high-speed railway station in Beijing as an example to verify the proposed method. The experimental results show that all evaluation metrics perform well, indicating that the G-LSTM model has high accuracy in assessing and predicting the health status of automatic gate machine and X-ray security checker. This paper realizes the health status assessment and prediction of railway passenger station equipment, which can provide some reference for the Prognostics and Health Management (PHM) of equipment in railway stations.

In this paper, a hybrid Mach-Zehnder optical modulator is proposed based on silicon nitride/organic polymer waveguides, which is expected to break through the performance bottleneck of the silicon-based optical modulator by exploiting the low-loss optical transmission property of silicon nitride waveguides and the excellent modulation performance of organic polymers. For reduction of the optical loss and ease of photonic packaging, perfectly vertical silicon nitride bidirectional grating couplers are utilized for both input/output optical coupling and power splitting/combining. Thus, a Mach-Zehnder interferometer can be constructed with a back-to-back configuration of such grating couplers. With grating apodization, the coupler can achieve a simulated coupling efficiency of 70%. To bridge the silicon nitride waveguides and the polymer waveguides, a longitudinal adiabatic mode-spot converter with a transmission efficiency of 99.2% was designed. In this paper, high-β donor-π bridge-accepter molecule YLD-124 combined with HD-BB-OH as the host polymer is utilized for a design example. The polymer waveguides with inverted ridge structure can be realized through the processes of silica cladding etching, spin coating or microfluidic trench filling of polymer. Following this design, we numerically demonstrate a hybrid silicon nitride-polymer Mach-Zehnder modulator with modulation efficiency of 1.57 Vcm and Electric-Optical bandwidth of 174 GHz. The total insertion loss is less than 5.74 dB, including two grating coupler losses of about 3.08 dB.

In transient high-speed scenes such as chemical explosions, magnetic compression, electric explosion, and laser-driven flyer, the target object can accelerate from 0 to tens of km/s in a few nanoseconds. The time-stretched photon Doppler velocimetry uses the time-stretched interferometry to downscale the frequency of the Doppler shift signal in the optical domain, which breaks through the bandwidth limitations of photoelectric detectors and electrical digital to analog converters. A quasi-continuous time-stretched photon Doppler velocimetry (QT-PDV) is proposed in this paper, for the measurement of microsecond high-speed movement events. On the principle of hardware optical path, the velocity signal of the target object is encoded on multiple stretched chirp pulses, avoiding sampling interruptions and trigger condition limitations; in the signal demodulation methods, the error compensation algorithm is used to compensate for the frequency shift signal, which reduces the system error caused by the displacement and increases the effective recording time. This paper adopts the high-power nanosecond laser to drive the metal film to produce a high-speed target, where beat frequency was downscaled to 2.2 GHz from 4.4 GHz.

Heisenberg guessed, after he established the matrix quantum mechanics, that the non-commutativity of the matrices of position and momentum implied that the position and momentum of a particle could not be precisely simultaneously determined. He consequently conjectured that time and energy should also have a similar relationship. Soon after, Robertson derived an inequality concerning the space coordinate and momentum, which was thought to be the mathematical expression of the uncertainty relation guessed by Heisenberg. Since then, people have tried various devices to prove the correctness of these two relations. However, no one conducted a careful analysis of Heisenberg’s primary paper. In this work, we point out some serious problems in Heisenberg’s paper and the literature talking about the uncertainty relationships: the physical concepts involved in the uncertainty relations are not clear; one physical concept had more than one explanation, i.e., switching concepts; there has never been measurement experiment to support the relations. The conclusions are that the so-called coordinate–momentum uncertainty relation has never been related to actual measurement and there does not exist a time–energy uncertainty relation.

This paper reviews the discovery of the optical soliton and historical attempts of its applications in ultra-high-speed communications. It also reveals various episodes that took place in the course of its discovery and in subsequent developments in the form of a memoir. The paper is expected to stimulate young scientists for their future activities and contributions.

There is much discrepancy in the literature concerning the possibility of a superconductor expelling gravito-electromagnetic fields just as it expels electromagnetic fields in the Meissner effect. Contradicting results are found in at least 18 papers written collectively by more than 20 authors and published over the course of more than 55 years (from 1966 to the present year of 2022). The primary purpose of this paper is to carefully explain the reason for the discrepancies, and provide a single conclusive treatment which may bring coherence to the subject. The analysis begins with a covariant Lagrangian for spinless charged particles (Cooper pairs) in the presence of electromagnetic fields in curved space-time. It is known that such a Lagrangian can lead to a vanishing Hamiltonian. Alternatively, it is shown that using a “space + time” Lagrangian leads to an associated Hamiltonian with a canonical momentum and minimal coupling rule. Discrepancies between Hamiltonians obtained by various authors are resolved. The canonical momentum leads to a modified form of the London equations and London gauge that includes the effects of gravity. A key result is that the gravito-magnetic field is expelled from a superconductor with a penetration depth on the order of the London penetration depth only when an appropriate magnetic field is also present. The gravitational flux quantum (fluxoid) in the body of a superconductor, and the quantized supercurrent in a superconducting ring, are also derived. Lastly, the case of a superconducting ring in the presence of a charged rotating mass cylinder is used as an example of applying the formalism developed.

Event extraction in the field of public opinion aims to extract important event arguments and their corresponding roles from the moment-to-moment generated opinion reports. Most of the existing research methods divide the task into three subtasks: event trigger extraction, event type detection, and event argument extraction. Despite the remarkable achievements of the event argument extraction paradigm combining part-of-speech (POS) and event trigger features, the performance of POS features in combinatorial event argument extraction tasks is struggling due to its inherent semantic diversity in Chinese. In addition, previous research work ignored the deep semantic interaction between event trigger and text. To address the aforementioned problems, this paper proposes an opinion event extraction model (NN-EE) combining NSP and NER, which alleviates the lack of performance of combinatorial event argument extraction by introducing NER technology. Meanwhile, the event trigger features are incorporated into the NSP mechanism of the pre-trained language model BERT to prompt the model to learn the deep semantic interaction between the event trigger and original text. The results of the self-constructed food opinion report dataset (FD-OR) in this paper show that the NN-EE model achieves optimal performance.

With the increase of point cloud scale, the time required by traditional ICP-related point cloud registration methods increases dramatically, which cannot meet the registration requirements of large-scale point clouds. In this paper, a fast registration technique for large scale point clouds based on virtual viewpoint image generation is studied. Firstly, the projection image of color point cloud is generated by virtual viewpoint. Then, the feature is extracted based on ORB and the rotation and translation matrix is calculated. The experimental results show that the registration time of the proposed method is about 1s when the size of the point cloud is from 300,000 to 2 million, which is improved by 17–258 times compared with the traditional ICP registration method, and the registration error is reduced by 80% from ICP 5.0 to 1.0. This paper provides a new idea and method for large-scale color point cloud registration.

In this invited paper, a novel water chemical oxygen demand (COD) detection method based on laser spectroscopy is proposed, and the COD value is obtained according to the intensity ratio of laser Fluorescence-Raman signal produced by laser incident into water. Based on the laser Fluorescence-Raman ratio (LFRR) method, we design a portable water quality measurement system. In which, a 405 nm semiconductor laser is used as the light source. The laser is coupled into the delivering port of Y-type fiber and then transmitted into water. The generated Mie scattered light, water Raman light and corresponding fluorescence are received and transmitted into spectrometer through the detecting port of Y-type fiber, and the COD value can be obtained by analyzing the LFRR of water spectra. The mixed solution of sodium humate and glucose is used as the COD standard solution to calibrate the designed system. The experiment results show that the optimal volume ratio of the two solutions is 1:29. When the COD of standard solutions is in the 1–12 mg/L concentration range, a good linear relationship can be found between the COD value and LFRR value with a correlation coefficient of 0.974. In addition, the COD of natural water samples are measured with LFRR method, the results of which are consistent with COD values obtained by rapid digestion spectrophotometry. Meanwhile, experimental results prove that the COD detection method proposed in this paper has the advantages of high sensitivity, high precision, high detection speed and simplicity, which can be widely used in various water areas for real-time COD monitoring.

As a new type of reflective display technology with paper-like display performance, electrowetting display (EWD) can realize ultra-low power consumption, wide viewing angle and fast response speed. In order to apply the EWD to the large-size display field, an extensible driving model for multiple grayscales colorful EWDs was proposed in this paper. The proposed driving model consisted of a grayscale model, a colorful display model and an extensible driving model. With the grayscale model and the colorful display model, the driving waveform of the colorful grayscale display was designed based on limited output voltage levels of a general-purpose graphic driver chip. And then, the extensible driving model was used to realize the large-size display large-scale display based on a matrix of small-size EWD panels. In addition, an experimental platform, which was composed of the display panel and the driving board with a data interface, was designed based on the proposed models. Experimental results showed that it could realize an 18-bit colorful dynamic display on the extended display matrix with a resolution of 48*16. It was indicated that the display matrix could be used for multiple grayscales and colorful dynamic displays by applying the proposed driving models. The research has brought about a way of enlarging the size of the EWD, which is conducive to broadening the scope of application of EWDs.

Electronic paper display has received increasing attention due to its outstanding properties of wide viewing angle, bistable state and lower energy consumption. Among various electronic paper display technologies, electrowetting e-paper (EWD) is the most promising as it can achieve full-color display by using stacked layers or RGB color filter. However, the EWD is faced with several challenges, including poor color brightness, low contrast ratio and small color gamut. To improve the performance of the EWD, we proposed a new configuration of EWD consisting of three independent PCLC reflection films based on the cholesteric liquid crystal materials. We designed and experimentally fabricated three types of reflection films, and then added the PCLC films to the tri-layered EWD device. We experimentally characterized the reflectivity and color gamut of the sample in the dark room. It is found that the experimental results and simulation results match with each other. It is demonstrated that with the PCLC films, the reflectivity is improved by 20%, while the color gamut is improved by 80%, which is sufficient for the daily display demand of E-paper. The proposed EWD device containing PCLC reflection films provide a new strategy to improve the brightness and color gamut of current EWD device, and is promising for realizing the full-color E-paper display.

In this paper we discuss and explain the phenomenon of synchronization in lightly supported mechanical systems. The investigations are focused on the models of self–excited pendula hanged on the horizontally oscillating beam, which is lightly connected with the external support. Our results are based on the Centre-of-Mass (CoM) Theorem, which can be applied to the considered systems and allows to analytically confirm the observed behaviours. We present typical dynamical solutions, including periodic and quasiperiodic oscillations, within which the oscillators synchronize. The possible synchronous configurations are analyzed and examined, depending on the number of the pendula creating the system, their parameters and the initial conditions. We discuss bifurcations between different types of solutions, determining the regions and the conditions supporting the synchronization. Our investigations exhibit, that with the increase of the size of the network, the number of co–existing attractors also increases, leading to possible multistability and new types of behaviours (e.g., the traveling phase one). The results obtained numerically match with the analytical ones obtained from the CoM Theorem, which explains the existence of particular types of dynamical configurations. The study presented in this paper involves classical lightly supported pendula systems and due to their basic character, one can expect to observe similar behaviours in other types of mechanical models.

One of the essential features of capital markets as an adaptive complex network is their collective behavior. In this paper, we have analyzed the collective behavior of banking sectors of four stock markets, which are composed of emerging and mature ones. By plotting the dendrograms and heat maps of the correlation matrices, it is found that the mature markets are more similar to each other. By applying the method of Random matrix theory(RMT), one of the important complexity notions, and its tools: participation ratio(PR) and relative participation ratio(RPR), it is obvious that mature markets have a lower degree of collective behavior than the emerging ones. By perturbing the correlation matrix of these markets, it is found that the mature markets are more vulnerable. It means that emerging markets that have lower cross-correlations are less vulnerable to perturbations. The findings of this paper are useful for policymakers of these countries to concentrate on the market structures and their behaviors.

The construction of large-scale integrated photonic circuit cannot be separated from the important role played by silicon-based optoelectronic devices. As a basic and important link in on-chip photon propagation, beam splitting is of great significance for the efficient utilization of sources and the compact integration of optoelectronic devices. It is widely used in power splitting, polarization separation, wavelength division multiplexing and other scenarios. This paper reviews the on-chip beam splitting methods in recent years, which are mainly divided into the following categories: y-branch, multimode interference coupling, directional coupling, and inverse design. This paper introduces their research status, including optimization design methods, functions and applications in large-scale quantum chips and optoelectronic hybrid integration, looking forward to providing a reference for the further research of beam splitting methods and the wide application of beam splitters in the frontier field in the future.

Aiming at the application requirements of spectral imaging technology in satellite remote sensing, biomedical diagnosis, marine detection and rescue, agricultural and forestry monitoring and classification, military camouflage identification, etc., this paper uses 532 and 650 nm lasers as light sources, and uses multi-spectral intensity correlation imaging equipment—snapshot spectroscopic cameras based on ghost imaging via sparsity constraints (GISC) enable precise identification of targets. In this paper, the principle of snapshot GISC spectral imaging is expounded, and the experimental research work of GISC spectral imaging target recognition technology based on active laser illumination is carried out. The experimental results show that using a 532 nm laser as the light source to illuminate the target object can accurately identify the green target letter “I”; using a 650 nm laser as the light source to illuminate the target object can accurately identify the red target letter “Q”. And gives spectral imaging results of the color target “QIT” acquired by the GISC spectroscopic camera through a single exposure at the wavelength range from 446 to 698nm, with both pseudo-color map and color fusion map. In order to further illustrate the feasibility of the experiment, the spectral distribution of the reconstructed image is analyzed, which has important practical significance and engineering value.

This paper introduces a compact magnetic state-selection cesium atomic clock called LIP Cs-3000 and analyses its characteristics. The test results reveal that the ranges of the line width, peak-to-valley ratio and signal-to-noise ratio of Ramsey pattern are 340–410 Hz, 2–13 and 2,000–8,000 respectively. The corresponding distributions of these parameters are derived by using statistical methods. According to these results, some suggestions are put forward for the further development of the clock. It is also pointed out that the most important factor affecting the accuracy of LIP Cs-3000 atomic clock is the uncertainty of cavity phase shift. In addition, the method to estimate the lifetime of a clock has been proposed. In the end, the paper gives some environmental adaptability designs of the clock, which enable the clock to be used in complex environments.

As an important branch of non-destructive testing, laser ultrasonic testing has attracted increasing attention in the field of material testing because of its instantaneity, non-contact and wide adaptability. Based on the finite element method, the process of laser-excited ultrasonic signal is numerically simulated, and the influence of angled cracks on the ultrasonic signal is analyzed. In this paper, the effects of the time function, pulse width, and spot radius of a Gaussian light source are analyzed through the transient field. The different modes of the ultrasonic signal are used to fit the crack’s angle, depth, and width to complete the characteristic analysis of the surface angled crack. The results show that the displacement peak-valley difference of the direct Rayleigh wave is negatively correlated with the crack angle. The displacement extremes of the transmitted Rayleigh wave boundary are negatively correlated with crack depth and width, while the transmitted Rayleigh wave is positively correlated. This paper presents a method for the quantitative analysis of surface-angled cracks and provides a theoretical basis for further experimental verification.

In recent years, many researchers have leveraged various memristors to design many novel memristive chaotic systems with complex dynamics. Compared with other chaotic systems, applying these memristive chaotic systems to image encryption is expected to solve some key problems in this field. Therefore, exploiting a recently reported memristive chaotic system, this paper proposes a novel image encryption scheme based on the memristive chaotic system and combining bidirectional bit-level cyclic shift and dynamic DNA-level diffusion (IES-M-BD). First, a discrete memristive chaotic map is employed to generate chaotic sequences. Then, the plaintext image is shifted circularly on bit-level according to chaotic sequences and the hash value of the plaintext image. After that, the shifted matrix is recombined on the bit plane and encoded dynamically by DNA encoding rules. Next, dynamic DNA-level diffusion and DNA-level permutation are carried out in two rounds. Finally, the encrypted image is obtained after dynamic DNA decoding. Simulation tests and performance analyses are also carried out in this paper. The simulation results and the security analyses demonstrate that this encryption scheme has a high security level and can resist various attacks.

The luminescent solar concentrator (LSC) as energy harvesting window is an emerging technology in the realm of building integrated photovoltaics. Using recent advancement for assessing the balance between transmitted color quality and potential electricity generation, this paper optimizes theoretical luminophore absorption spectra for the highest power generation possible. The power conversion efficiencies (PCE) are based on coupling of the LSC waveguide to a highly efficient crystalline silicon solar cell. A non-convex optimisation algorithm maximizing absorption is used with constraints for color quality parameters: average visible transmission (AVT) and color rendering index (CRI). An optimal luminophore has been defined using a continuous absorption function with a cut-off and limited absorption in the visible spectrum. Two types of constraints are set: 1) 55% < AVT < 100% and 2) 55% < AVT < 100% and 70 < CRI < 100. The first constraint will ensure sufficient visible light and the second ensures appropriate color rendering. Ray-trace validated results show high power conversion efficiencies ranging from 9.53% to 14.3% for (AVT = 90%, CRI = 98) and (AVT = 55%), respectively. Future studies can use these results to benchmark (tandem) LSCs for specific lighting requirements. Furthermore, the flexibility of the proposed method allows for the adaptation to constraints not used in this paper.

Raman spectroscopy is widely used in many fields with the advantages of simultaneous species detection and molecular fingerprint characteristics, but the low detection sensitivity limits its further development, especially for highly scattering or turbid mediums. In this consideration, a new method called quartz tube enhanced Raman scattering spectroscopy was proposed for the first time in this paper. A quartz tube was inserted into the powder sample to improve the coupling of light into the medium and increase the interaction volume of the laser with the sample (“volume-excitation”), multiple scattering of the light within the turbid medium resulted in an increased Raman signal. In this paper, the effect of different sizes of quartz tubes on the sensitivity enhancement was studied. The results show that the enhancement factor of the signal intensity was nearly 5.37 (the Raman signal of HCO3−) compared to traditional Raman spectroscopy technology. Furthermore, the method was successfully applied to improve the Raman signal intensity of the mixed sample (1:5, m (PO43−):m (HCO3−)) and detect the baking soda powder buried under a 6 mm thick layer of potassium dihydrogen phosphate powder. The results show that the technology will open a new way for the quantitative analysis and detection of powder samples.

For over half a century, high-energy particle accelerators have been a major enabling technology for particle and nuclear physics research as well as sources of X-rays for photon science research in material science, chemistry and biology. Particle accelerators for energy and intensity Frontier research in particle and nuclear physics continuously push the accelerator community to invent ways to increase the energy and improve the performance of accelerators, reduce their cost, and make them more power efficient. The accelerator community has demonstrated imagination and creativity in developing a plethora of future accelerator ideas and proposals. The technical maturity of the proposed facilities ranges from shovel-ready to those that are still largely conceptual. At this time, over 100 contributed papers have been submitted to the Accelerator Frontier of the US particle physics decadal community planning exercise known as Snowmass’2021. These papers cover a broad spectrum of topics: beam physics and accelerator education, accelerators for neutrinos, colliders for Electroweak/Higgs studies and multi-TeV energies, accelerators for Physics Beyond Colliders and rare processes, advanced accelerator concepts, and accelerator technology for Radio Frequency cavities (RF), magnets, targets and sources. This paper provides an overview of the present state of accelerators for particle physics and gives a brief description of some of the major facilities that have been proposed, their perceived advantages and some of the remaining challenges.

This paper presents an analytical framework for the physical environment of cities using fractal theory. The strength of the approach lies in its simplicity and precision. The equations presented in this article comprise: the number of occupied sites in an area; the population and the length of roads of a city; its fractal dimension; its number of average and maximum levels (floors per building); the average density of population and roads; what are the limits to growth as well as an analysis on some of the city’s scaling laws. These equations describe to a high level of precision the real values measured in the system of the United Kingdom, for every city above 5,000 people, which amounts to a sample size of 1,031 cities. This work will allow further research into the nature of cities, since it enables the creation of synthetic cities, and further analytical derivations that can arise from these building blocks. The paper shows as well how the same set of equations can be used to characterise the internal distribution of cities from the perspective of its growth as a possible example of an application of the framework.

The majority of scholars believe that Shor’s algorithm is a unique and powerful quantum algorithm for RSA cryptanalysis, so current postquantum cryptography research has largely considered only the potential threats of Shor’s algorithm. This paper verifies the feasibility of deciphering RSA public key cryptography based on D-Wave, which is the second most effective RSA attack method after Shor’s algorithm. This paper proposes the influence of different column methods on the final integer factorization, puts forward a new dimension reduction formula, simplifies the integer factorization model based on quantum annealing, simulates it with the qbsolv quantum computing software environment provided by D-Wave, and factors the integer 1630729 (an 11-bit prime factor multiplied by an 11-bit prime factor). The research results show that choosing an appropriate number of columns and column width in the binary integer factorization multiplication table is very important for studying the optimization ability of the quantum annealing algorithm. In fact, Science, Nature, IEEE Spectrum, and the National Academies of Sciences (NAS) are consistent in asserting that the practical application of general-purpose quantum computers is far in the future. Therefore, although D-Wave computers were initially mainly purchased by Lockheed Martin, Google, etc., for purposes such as image processing, machine learning, combinatorial optimization, and software verification, post quantum cryptography research should further consider the potential of the D-Wave quantum computer in deciphering RSA cryptosystems in the future, and a discussion of this potential is one of the contributions of this paper.

This paper presents the development of a laboratory scale apparatus and first experimental results on the characterization of fingering patterns of immiscible fluids in a porous rock (Fontainebleau sandstone), using three dimensional full-field measurements from x-ray tomography. The few existing studies that have extended experimental investigation of immiscible fluid flow from 2D to 3D have been primarily interested in the pore scale or performed on idealized porous media. While the heterogeneities inherent to natural rocks are known to play an important role on subsurface fluid flow regimes, a limited number of studies have approached the problem of characterizing the time resolved 3D multiphase flow in these material, at the mesoscale. The series of experiments reported in this paper has been performed at a low viscosity ratio, water invasion into oil as the defending fluid, and different capillary numbers (1.8 orders of magnitude). The results illustrate the qualitative transition in the flow regime, from capillary fingering to viscous fingering. While a full quantitative characterization of geometrical features of fluid fingers will require further technical refinements, a qualitative understanding can be already gathered from the results presented herein.

Papers in the literature dealing with the Ethernet network characterize packet delay variation (PDV) as a long-range dependence (LRD) process. The fractional Gaussian noise (fGn) or the generalized fractional Gaussian noise (gfGn) belong to the LRD process. The IEEE1588v2 is a two-way delay (TWD) protocol that uses the messages from the Forward (Master to Slave) and the Reverse (Slave to Master) paths. Suppose we have a significant difference between the PDV variances of the Forward and the Reverse paths. Thus, if we can use only the path with the lowest PDV variance (namely, only the one-way delay (OWD) technique), we might get a better clock skew performance from the mean square error (MSE) point of view compared with the traditional TWD method. This paper proposes two OWD clock skew estimators, one for the Forward path and one for the Reverse path applicable for the white-Gaussian, fGn and gfGn environment. Those OWD estimators do not depend on the unknown asymmetry between the fixed delays in the Forward and Reverse paths and nor on the clock offset between the Master and Slave. We also supply two closed-form approximated expressions for the MSE related to our new proposed OWD clock skew estimators. In addition, we supply some conditions, summarized in a table, guiding us whether we should use the OWD clock skew estimator for the Forward path or for the Reverse path, or just use the TWD algorithm. Simulation results confirm that our new proposed OWD clock skew estimators achieve better clock skew performances from the MSE point of view, compared with the TWD clock skew estimator recently proposed by the same authors and compared with two literature known OWD methods (the maximum likelihood and Kalman clock skew estimators).

Tunable Diode Laser Absorption Spectroscopy (TDLAS), a trace gas sensing technology based on infrared absorption spectroscopy, has been developed rapidly in the past few decades. The advantages of low cost and easy miniaturization could be applied in real-time monitoring. As an important factor, the detection sensitivity of TDLAS has been improved by a variety of methods. In this review paper, the important advances in TDLAS detection sensitivity are discussed, including the selection of absorption lines, the improvement of diode lasers, the design of effective optical paths, data demodulation, and the suppression of background interference. For gases with high application values, such as CH4, CO2, and NO, we summarize the detection sensitivity that the existing TDLAS system has been achieved, combined with the above-improved process. However, considering the principle of infrared absorption, the increase in detection sensitivity could reach an ultra-limit. Therefore, the hypothesis of the sensitivity limit of TDLAS is proposed at the end of the paper, through the quantization analysis.

The critical damage value of rock is an important parameter of stability analysis when engineering rock mass. Based on the previous single test method, this paper, combined with the deformation characteristics of rock residual phase under different stress paths, proposed a single specimen repeated loading method to measure the critical damage value of rock based on different damage variables. The paper also proposed to modify the critical damage value based on residual constitutive energy and to improve the definition of damage variables based on constitutive energy dissipation. According to the microstructure characteristics of the rock sample, the mechanism of the single specimen method to determine the critical value of rock sample damage is revealed. The results show that: 1) Comparing the results of triaxial failure test of rock under different stress paths and single specimen repeated loading test, the residual strength of rock sample is mainly controlled by the confining pressure of loading, which is not an obvious relationship with initial confining pressure and stress path; 2) The number of repeated compressions has little effect on the internal structure, particle flatness, and particle surface smoothness of their specimens, which is reflected at the macroscopic level that the residual strength of sandstone tends to achieve a stable value; and 3) The corrected critical damage value based on residual strain energy is closer to the theoretical value. Test methods in this paper can provide useful references for determination of critical damage value.

This paper aims to analyze the impact of COVID-19 on the sustainability of the banking sector and the fintech sector. In China, where banks’ revenue mainly comes from branches, we collect relevant data manually and use the OLS model for empirical analysis. The results show that as the COVID-19 infection rate increases, the number of bank branches decreases significantly, which threatens the banking sector’s sustainability. The fintech sector acts as a competitor to the banking sector. With the increase of COVID-19 infection rate, the public pays more attention to fintech, promoting the development of the fintech sector. Moreover, the impact of COVID-19 on these two sectors will diminish over time. In addition, this paper finds that COVID-19 further weakens the number of bank branches during the epidemic through the mediating effect of fintech. The findings of this paper help to assess the sustainability of the different financial sectors during the epidemic, which is essential for financial stability.