Rock mass quality prediction on tunnel faces with incomplete multi-source dataset via tree-augmented naive Bayesian network

Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.

Trusted artificial intelligence for environmental assessments: An explainable high-precision model with multi-source big data

Environmental assessments are critical for ensuring the sustainable development of human civilization.The integration of artificial intelligence(AI)in these assessments has shown great promise,yet the"black box"nature of AI models often undermines trust due to the lack of transparency in their decision-making processes,even when these models demonstrate high accuracy.To address this challenge,we evaluated the performance of a transformer model against other AI approaches,utilizing extensive multivariate and spatiotemporal environmental datasets encompassing both natural and anthropogenic indicators.We further explored the application of saliency maps as a novel explainability tool in multi-source AI-driven environmental assessments,enabling the identification of individual indicators'contributions to the model's predictions.We find that the transformer model outperforms others,achieving an accuracy of about 98%and an area under the receiver operating characteristic curve(AUC)of 0.891.Regionally,the environmental assessment values are predominantly classified as level II or III in the central and southwestern study areas,level IV in the northern region,and level V in the western region.Through explainability analysis,we identify that water hardness,total dissolved solids,and arsenic concentrations are the most influential indicators in the model.Our AI-driven environmental assessment model is accurate and explainable,offering actionable insights for targeted environmental management.Furthermore,this study advances the application of AI in environmental science by presenting a robust,explainable model that bridges the gap between machine learning and environmental governance,enhancing both understanding and trust in AI-assisted environmental assessments.

Tuning Excitation Transport in a Dissipative Rydberg Ring

We demonstrate the flexible tunability of excitation transport in Rydberg atoms,under the interplay of controlled dissipation and interaction-induced synthetic flux.Considering a minimum four-site setup,i.e.,a triangular configuration with an additional output site,we study the transport of a single excitation.

Twin-Capture Rydberg State Excitation Enhanced with Few-Cycle Laser Pulses

Quantum excitation is usually regarded as a transient process occurring instantaneously,leaving the underlying physics shrouded in mystery.Recent research shows that Rydberg-state excitation with ultrashort laser pulses can be investigated and manipulated with state-of-the-art few-cycle pulses.We theoretically find that the efficiency of Rydberg state excitation can be enhanced with a short laser pulse and modulated by varying the laser intensities.We also uncover new facets of the excitation dynamics,including the launching of an electron wave packet through strong-field ionization,the re-entry of the electron into the atomic potential and the crucial step where the electron makes a U-turn,resulting in twin captures into Rydberg orbitals.By tuning the laser intensity,we show that the excitation of the Rydberg state can be coherently controlled on a sub-optical-cycle timescale.Our work paves the way toward ultrafast control and coherent manipulation of Rydberg states,thus benefiting Rydberg-state-based quantum technology.

Low-Energy Spin Excitations in Detwinned FeSe

Antiferromagnetic spin fluctuation is regarded as the leading driving force for electron pairing in high-Tc superconductors.In iron-based superconductors,spin excitations at low energy range,especially the spin-resonance mode at ER~5kBTc,are important for understanding the superconductivity.Here,we use inelastic neutron scattering(INS)to investigate the symmetry and in-plane wave-vector dependence of low-energy spin excitations in uniaxial-strain detwinned Fe Se.The low-energy spin excitations(E<10 meV)appear mainly at Q=(±1,0)in the superconducting state(T9K)and the nematic state(T90 K),confirming the constant C_(2) rotational symmetry and ruling out the C_(4) mode at E≈3 meV reported in a prior INS study.Moreover,our results reveal an isotropic spin resonance in the superconducting state,which is consistent with the s±wave pairing symmetry.At slightly higher energy,low-energy spin excitations become highly anisotropic.The full width at half maximum of spin excitations is elongated along the transverse direction.The Q-space isotropic spin resonance and highly anisotropic low-energy spin excitations could arise from dyz intra-orbital selective Fermi surface nesting between the hole pocket aroundΓpoint and the electron pockets centered at MX point.

A multi-source information fusion layer counting method for penetration fuze based on TCN-LSTM

When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ferromagnetic materials,thereby posing challenges in accurately determining the number of layers.To address this issue,this research proposes a layer counting method for penetration fuze that incorporates multi-source information fusion,utilizing both the temporal convolutional network(TCN)and the long short-term memory(LSTM)recurrent network.By leveraging the strengths of these two network structures,the method extracts temporal and high-dimensional features from the multi-source physical field during the penetration process,establishing a relationship between the multi-source physical field and the distance between the fuze and the target plate.A simulation model is developed to simulate the overload and magnetic field of a projectile penetrating multiple layers of target plates,capturing the multi-source physical field signals and their patterns during the penetration process.The analysis reveals that the proposed multi-source fusion layer counting method reduces errors by 60% and 50% compared to single overload layer counting and single magnetic anomaly signal layer counting,respectively.The model's predictive performance is evaluated under various operating conditions,including different ratios of added noise to random sample positions,penetration speeds,and spacing between target plates.The maximum errors in fuze penetration time predicted by the three modes are 0.08 ms,0.12 ms,and 0.16 ms,respectively,confirming the robustness of the proposed model.Moreover,the model's predictions indicate that the fitting degree for large interlayer spacings is superior to that for small interlayer spacings due to the influence of stress waves.

Low-energy inelastic electron scattering from carbon monoxide:Excitation and de-excitation of the X^(1)Σ^(+),a^(3)Π,a'^(3)∑^(+),A^(1)Π,d^(3)Δ,e^(3)∑^(-),I^(1)∑^(-)and D^(1)Δelectronic states

Cross-sections for electronic excitation and de-excitation among the ground state and lowest-lying seven electronic excited states of carbon monoxide(CO)by low-energy electron impact are computed using the R-matrix method.The excitation cross-sections from the ground state to the electronic states a^(3)Π,a'^(3)Σ^(+)+and A^(1)Πagree with previous experimental and theoretical results.In addition,the cross-sections for the I^(1)Σ^(+)-and D^(1)Δstates of CO,which will cascade to CO a'^(3)Σ^(+)+and A^(1)Πstates,are calculated.Furthermore,in contrast to the typical increase in electronic excitation cross-sections with collision energy,the de-excitation cross-sections show a negative trend with increasing energy.

Mapping the antiparallel aligned domain rotation by microwave excitation

The evolution process of magnetic domains in response to external fields is crucial for the modern understanding and application of spintronics.In this study,we investigated the domain rotation in stripe domain films of varying thicknesses by examining their response to microwave excitation in four different orientations.The resonance spectra indicate that the rotation field of stripe domain film under an applied magnetic field approaches the field where the resonance mode of sample changes.The saturation field of the stripe domain film corresponds to the field where the resonance mode disappears when measured in the stripe direction parallel to the microwave magnetic field.The results are reproducible and consistent with micromagnetic simulations,providing additional approaches and techniques for comprehending the microscopic mechanisms of magnetic domains and characterizing their rotation.

Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things

The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.

Excitation and ionization of OCS molecules in strong UV and NIR laser fields

Rydberg state excitation(RSE) is a highly non-linear physical phenomenon that is induced by the ionization of atoms or molecules in strong femtosecond laser fields. Here we observe that both parent and fragments(S, C, OC) of the triatomic molecule carbonyl sulfide(OCS) can survive strong 800 nm or 400 nm laser fields in high Rydberg states. The dependence of parent and fragment RSE yields on laser intensity and ellipticity is investigated in both laser fields, and the results are compared with those for strong-field ionization. Distinctly different tendencies for laser intensity and ellipticity are observed for fragment RSE compared with the corresponding ions. The mechanisms of RSE and strong-field ionization of OCS molecules in different laser fields are discussed based on the experimental results. Our study sheds some light on the strong-field excitation and ionization of molecules irradiated by femtosecond NIR and UV laser fields.

A new method for deriving broad-band polar motion geodetic excitations

While the geodetic excitationχ(t)of polar motion p(t)is essential to improve our understanding of global mass redistributions and relative motions with respect to the terrestrial frame,the widely adopted method to deriveχ(t)from p(t)has biases in both amplitude and phase responses.This study has developed a new simple but more accurate method based on the combination of the frequency-and time-domain Liouville's equation(FTLE).The FTLE method has been validated not only with 6-h sampled synthetic excitation series but also with daily and 6-h sampled polar motion measurements as well asχ(t)produced by the interactive webpage tool of the International Earth Rotation and Reference Systems Service(IERS).Numerical comparisons demonstrate thatχ(t)derived from the FTLE method has superior performances in both the time and frequency domains with respect to that obtained from the widely adopted method or the IERS webpage tool,provided that the input p(t)series has a length around or more than 25 years,which presents no practical limitations since the necessary polar motion data are readily available.The FTLE code is provided in the form of Mat Lab function.

Vibration attenuation performance of wind turbine tower using a prestressed tuned mass damper under seismic excitation

With the rapid development of large megawatt wind turbines,the operation environment of wind turbine towers(WTTs)has become increasingly complex.In particular,seismic excitation can create a resonance response and cause excessive vibration of the WTT.To investigate the vibration attenuation performance of the WTT under seismic excitations,a novel passive vibration control device,called a prestressed tuned mass damper(PS-TMD),is presented in this study.First,a mathematical model is established based on structural dynamics under seismic excitation.Then,the mathematical analytical expression of the dynamic coefficient is deduced,and the parameter design method is obtained by system tuning optimization.Next,based on a theoretical analysis and parameter design,the numerical results showed that the PS-TMD was able to effectively mitigate the resonance under the harmonic basal acceleration.Finally,the time-history analysis method is used to verify the effectiveness of the traditional pendulum tuned mass damper(PTMD)and the novel PS-TMD device,and the results indicate that the vibration attenuation performance of the PS-TMD is better than the PTMD.In addition,the PS-TMD avoids the nonlinear effect due to the large oscillation angle,and has the potential to dissipate hysteretic energy under seismic excitation.

Core level excitation spectra of La and Mn ions in LaMnO3

Manganese-based perovskite is popular for research on ferromagnetic materials,and its spectroscopic studies are essential for understanding its electronic structure,dielectric,electrical,and magnetic properties.In this paper,the M-edge spectra of La ions and the M-edge,L-edge,and K-edge spectra of Mn ions in LaMnO3 are calculated by considering both the free-ion multiplet calculation and the crystal field effects.We analyze spectral shapes,identify peak origins,and estimate the oxidation states of La and Mn ions in LaMnO3 theoretically.It is concluded that La ions in LaMnO3 predominantly exist in the trivalent state,while Mn ions exist primarily in the trivalent state with a minor presence of tetravalent ions.Furthermore,the calculated spectra are in better conformity with the experimental spectra when the proportion of Mn3+is 90%and Mn4+is 10%.This article enhances our comprehension of the oxidation states of La and Mn within the crystal and also provides a valuable guidance for spectroscopic investigations of other manganates.

Runout prediction of potential landslides based on the multi-source data collaboration analysis on historical cases

Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.

A Web-Based Approach for the Efficient Management of Massive Multi-source 3D Models

Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development of real-scene 3D applications in China.In this paper,we address this challenge by reorganizing spatial and temporal information into a 3D geospatial grid.It introduces the Global 3D Geocoding System(G_(3)DGS),leveraging neighborhood similarity and uniqueness for efficient storage,retrieval,updating,and scheduling of these models.A combination of G_(3)DGS and non-relational databases is implemented,enhancing data storage scalability and flexibility.Additionally,a model detail management scheduling strategy(TLOD)based on G_(3)DGS and an importance factor T is designed.Compared with mainstream commercial and open-source platforms,this method significantly enhances the loadable capacity of massive multi-source real-scene 3D models in the Web environment by 33%,improves browsing efficiency by 48%,and accelerates invocation speed by 40%.

Auto-parametric resonance of a continuous-beam-bridge model under two-point periodic excitation:an experimental investigation and stability analysis

The auto-parametric resonance of a continuous-beam bridge model subjected to a two-point periodic excitation is experimentally and numerically investigated in this study.An auto-parametric resonance experiment of the test model is conducted to observe and measure the auto-parametric resonance of a continuous beam under a two-point excitation on columns.The parametric vibration equation is established for the test model using the finite-element method.The auto-parametric resonance stability of the structure is analyzed by using Newmark's method and the energy-growth exponent method.The effects of the phase difference of the two-point excitation on the stability boundaries of auto-parametric resonance are studied for the test model.Compared with the experiment,the numerical instability predictions of auto-parametric resonance are consistent with the test phenomena,and the numerical stability boundaries of auto-parametric resonance agree with the experimental ones.For a continuous beam bridge,when the ratio of multipoint excitation frequency(applied to the columns)to natural frequency of the continuous girder is approximately equal to 2,the continuous beam may undergo a strong auto-parametric resonance.Combined with the present experiment and analysis,a hypothesis of Volgograd Bridge's serpentine vibration is discussed.

Measured dynamic load distribution within the in situ axlebox bearing of high-speed trains under polygonal wheel–rail excitation

The dynamic load distribution within in-service axlebox bearings of high-speed trains is crucial for the fatigue reliability assessment and forward design of axlebox bearings. This paper presents an in situ measurement of the dynamic load distribution in the four rows of two axlebox bearings on a bogie wheelset of a high-speed train under polygonal wheel–rail excitation. The measurement employed an improved strain-based method to measure the dynamic radial load distribution of roller bearings. The four rows of two axlebox bearings on a wheelset exhibited different ranges of loaded zones and different means of distributed loads. Besides, the mean value and standard deviation of measured roller–raceway contact loads showed non-monotonic variations with the frequency of wheel–rail excitation. The fatigue life of the four bearing rows under polygonal wheel–rail excitation was quantitatively predicted by compiling the measured roller–raceway contact load spectra of the most loaded position and considering the load spectra as input.

Electron capture and excitation in intermediate-energy He^(2+)–H(1s,2s)collisions

The semiclassical non-perturbative atomic orbital close-coupling approach has been employed to study the electron capture and excitation processes in He^(2+)-H(1s)and He^(2+)-H(2s)collision systems.In order to ensure the accuracy of our calculated cross sections,a large number of high excited states and pseudostates are included in the expansion basis sets which are centered on the target and projectile,respectively.The total and partial charge transfer and excitation cross sections are obtained for a wide-energy domain ranging from 1 keV/amu to 200 keV/amu.The present calculations are also compared with the results from other theoretical methods.These cross section data are useful for the investigation of astrophysics and laboratory plasma.

Designing an Experimental Device for Swinging Excitation Spray Cooling

In this paper,we introduce the design principle of the oscillating excited spray cooling experimental device.We then designed an oscillating excited spray cooling experimental device.By using the device,the swaying motion can be realized through the control system,and the motion of the droplet under different vibration frequencies can be observed.By measuring the liquid flow rate and pressure,the changes in liquid flow rate,pressure,and temperature with time under different vibration frequencies were studied.The trajectory of the droplet and the temperature distribution of the droplet under different vibration frequencies could be observed.The device has a simple structure,is easy to control,and can achieve continuous observation of the spray cooling process.

Multi-Source Data Privacy Protection Method Based on Homomorphic Encryption and Blockchain

Multi-Source data plays an important role in the evolution of media convergence.Its fusion processing enables the further mining of data and utilization of data value and broadens the path for the sharing and dissemination of media data.However,it also faces serious problems in terms of protecting user and data privacy.Many privacy protectionmethods have been proposed to solve the problemof privacy leakage during the process of data sharing,but they suffer fromtwo flaws:1)the lack of algorithmic frameworks for specific scenarios such as dynamic datasets in the media domain;2)the inability to solve the problem of the high computational complexity of ciphertext in multi-source data privacy protection,resulting in long encryption and decryption times.In this paper,we propose a multi-source data privacy protection method based on homomorphic encryption and blockchain technology,which solves the privacy protection problem ofmulti-source heterogeneous data in the dissemination ofmedia and reduces ciphertext processing time.We deployed the proposedmethod on theHyperledger platformfor testing and compared it with the privacy protection schemes based on k-anonymity and differential privacy.The experimental results showthat the key generation,encryption,and decryption times of the proposedmethod are lower than those in data privacy protection methods based on k-anonymity technology and differential privacy technology.This significantly reduces the processing time ofmulti-source data,which gives it potential for use in many applications.