Inversion Process Research Articles

SN1987A constraints to BSM models with extra neutral bosons near the trapping regime: U(1)Lμ−Lτ model as an illustrative example

New physics beyond the Standard Model (BSM) with an extra neutral boson can be constrained from the observation of SN1987A, since productions of this neutral boson in a supernova (SN) could accelerate the SN cooling and potentially lead to a period of the neutrino burst incompatible with the observation. The constraint to the model is formulated by the condition LNB≤3×1052 erg/s according to Raffelt with LNB the luminosity of BSM neutral boson. Computing the above luminosity in the large coupling case, the so-called trapping regime, is nontrivial since the luminosity is a competition between the large production rate and the efficient absorption or decay rate of the neutral boson. We illustrate such a subtlety using U(1)Lμ−Lτ model as an example where the Z′ luminosity, LZ′, from the neutrinosphere is calculated. We calculate Z′ production, absorption, and decay rates through pair-coalescence, semi-Compton, loop-bremsstrahlung from proton-neutron scattering, and their inverse processes in a benchmark SN simulation with muons. We point out that, as the coupling constant gZ′ increases, LZ′ shall be approaching to a constant plateau value for a given mZ′ instead of monotonically decreasing down to zero as obtained in the previous literature. We demonstrate that this plateau phenomenon can be understood by physical arguments and justified by numerical calculations. With a different result on LZ′ from the previous one, we discuss impacts on the constraints to U(1)Lμ−Lτ parameter space by SN1987A. The implication of our result to the similar constraint on a generic BSM model with an extra neutral boson is also discussed. Published by the American Physical Society 2024

A Theoretical Study of Positively Curved Circulenes Embedded with Five-Membered Heterocycles: Structures and Inversions

Recently, polycyclic arenes with positive curvature have gained increasing significance in the field of material chemistry. This study specifically explores the inversion barriers of a series of positively curved circulenes by using five-membered heterocycles integrated into the backbone of primitive [5]circulenes and [6]circulenes. For hetero[5]circulenes, where one benzenoid ring is replaced by a heterocycle, the inversion barriers exhibit a strong correlation with the rotary angles of the heterocycles, and larger rotary angles result in lower inversion barriers. Additionally, the aromaticity of the circulene undergoes a significant reduction during the inversion process. As the number n of replaced rings increases, the inversion barriers can be adjusted, demonstrating an almost linear relationship with n. In the case of hetero[6]circulenes, molecules bearing heterocycles with small rotary angles also show positive curvatures. Furthermore, we examine the relationship between the radii of the fitted sphere for the circulenes and the inversion barriers, revealing an intriguing inverse proportionality between the fourth power of the radius and the inversion barrier. We anticipate that this research will offer a fresh perspective on studies related to positively curved polycyclic arenes.

Application of electromagnetic method to seaward slope: Case study from Saemangeum Seawall in South Korea

As dams and seawalls around the world age, there has been increasing attention towards the safety of these structures and monitoring of their condition using various geophysical methods. However, assessing seaward slopes, which are directly impacted by waves and tides and a seawater-filled riprap stone deposit structure, has been challenging due to the highly conductive environment and the difficulty in installing contact equipment. This study examines the feasibility of using electromagnetic (EM) surveys to monitor seawall slopes by analyzing and interpreting multi-frequency EM data measured over 2-year period along the seawall slope of the Saemangeum Seawall in South Korea, which is recognized as the world’s longest seawall. The repeatability of data measured at the same survey line over the 2-years substantiates the reliability of EM survey data. The field data are inverted using a 2.5-dimensional regularized Gauss–Newton method. EM responses calculated from the inverted resistivity model closely mirrors the field data. The inversion results consistently indicate the presence of an isolated conductive anomaly with seawater resistivity below the survey line on the seaward slope. This suggests scouring erosion by seawater and affirms the applicability of the EM surveys to seaward slope monitoring. Additionally, the EM responses are affected significantly by sea level changes during the survey; these variations are quantified in this study. Thus, our results demonstrate the effectiveness of the EM method in monitoring the seaward slope to assess the safety of seawalls and provides a comprehensive overview of the entire data analysis and inversion processes, as a valuable reference for those using EM technology in their work.#xD;

Numerical Modeling on Ocean-Bottom Seismograph P-Wave Receiver Function to Analyze Influences of Seawater and Sedimentary Layers

It is challenging to apply the receiver function method to teleseisms recorded by ocean-bottom seismographs (OBSs) due to a specific working environment that differs from land stations. Teleseismic incident waveforms reaching the area beneath stations are affected by multiple reflections generated by seawater and sediments and noise resulting from currents. Furthermore, inadequate coupling between OBSs and the seabed basement and the poor fidelity of OBSs reduce the signal-to-noise ratio (SNR) of seismograms, leading to the poor quality of extracted receiver functions or even the wrong deconvolution results. For instance, the poor results cause strong ambiguities regarding the Moho depth. This study uses numerical modeling to analyze the influences of multiple reflections generated by seawater and sediments on H-kappa stacking and the neighborhood algorithm. Numerical modeling shows that seawater multiple reflections are mixed with the coda waves of the direct P-wave and slightly impact the extracted receiver functions and can thus be ignored in subsequent inversion processing. However, synthetic seismograms have strong responses to the sediments. Compared to the waveforms of horizontal and vertical components, the sedimentary responses are too strong to identify the converted waves clearly. The extracted receiver functions correspond to the above influences, resulting in divergent results of H-kappa stacking (i.e., the Moho depth and crustal average VP/VS ratio are unstable and have great uncertainties). Fortunately, waveform inversion approaches (e.g., the neighborhood algorithm) are available and valid for obtaining the S-wave velocity structure of the crust–upper mantle beneath the station, with sediments varying in thickness and velocity.

Inverse Identification of Constituent Elastic Parameters of Ceramic Matrix Composites Based on Macro–Micro Combined Finite Element Model

Accurate material performance parameters are the prerequisite for conducting composite material structural analysis and design. However, the complex multiscale structure of ceramic matrix composites (CMCs) makes it extremely difficult to accurately obtain their mechanical performance parameters. To address this issue, a CMC micro-scale constituents (fiber bundles and matrix) elastic parameter inversion method was proposed based on the integration of macro–micro finite element models. This model was established based on the μCT scan data of a plain-woven CMC tensile specimen using the chemical vapor infiltration (CVI) process, which could reflect the real microstructure and surface morphology characteristics of the material. A BP neural network was used to predict the multiscale stiffness, considering the influence of the porous structure on the macroscopic stiffness of the material. The inversion process of the constituent elastic parameters was established using the trust-region algorithm combined with an improved error function. The inversion results showed that this method could accurately invert the CMC constituent elastic parameters with excellent robustness and anti-noise performance. Under four different degrees of deviation in the initial iteration conditions, the inversion error of all parameters was within 1%, and the maximum inversion error was only 2.16% under a 10% high noise level.

Hybrid optimization for DC resistivity imaging via intelligible-in-time logic and the interior point method.

Geophysical DC resistivity imaging is crucial in subsurface exploration, environmental studies, and resource assessment. However, traditional inversion techniques face challenges in accurately resolving complex subsurface features because of the inherent nonlinearities in geophysical data. To overcome these challenges, we propose a hybrid optimization approach that combines incomprehensible but intelligible-in-time (IbI) logic with the interior point method (IPM). The IbI logic framework leverages complexity and temporal intelligibility, allowing for a dynamic interpretation of subsurface phenomena. By integrating IbI with IPM, our approach benefits from global exploration and local refinement, leading to improved convergence speed and solution quality. The objective function formulated for the inversion process includes data misfit and model regularization terms, which promote accurate and smooth solutions. Our methodology involves the use of the IbI logic algorithm (ILA) for initial global search, which identifies promising regions in the search space. This is followed by the application of IPM for local optimization. This synergy between the two algorithms ensures robustness and efficiency in handling large datasets and complex geological models. We conducted tests using synthetic and real DC resistivity data to validate our approach. The synthetic test demonstrated the accurate reconstruction of subsurface anomalies, whereas the real data test successfully identified fault zones, which is consistent with previous studies. The hybrid optimization algorithm significantly improves the resolution of subsurface structures and enhances geophysical data inversion practices. It balances the exploration and refinement phases effectively, optimizing the computation time and ensuring precise model delineation.

The new insight of tectonic setting in Sunda–Banda transition zone using tomography seismic. Case study: 7.1 M deep earthquake 29 August 2023

Abstract The Sunda–Banda arc transition zone features the collision of the Indo-Australian oceanic plate and the Australian continent, resulting in intricate geological and geodynamic conditions. Tectonic activity in this region is shaped by the convergence of multiple major plates, including the Indo-Australian oceanic plate and the Eurasian plate. The crustal structure along the Sunda–Banda arc transition zone is complex and influenced by various factors such as subduction, continental collision, and volcanic activity. The tectonic complexity of the region in eastern Indonesia makes it an interesting area for study. In this research, International Seismological Centre-Engdahl-van der Hilst-Buland catalogue data from 1964 to 2020 were used, which include recorded information on 69.705 earthquake events from 1.185 recording stations and consist of 2.943.974 P phases. Resolution testing was performed using various velocity grids, and optimal results were obtained with a medium resolution of ∼100 km × 100 km × 80 km for the inversion process. The tomographic inversion analysis provided valuable insights into subsurface structures within Earth’s crust and mantle up to a depth of approximately 750 km. The occurrence of deep earthquakes in the study area has provided valuable insights into complex dynamics associated with subduction and plate tectonics. The results of the tomographic inversion analysis reveal that earthquakes are concentrated in areas with high-velocity anomalies, indicating intense tectonic activity near the subduction zone. This study offers the perspective on the structural complexities and earthquake origins in the Sunda–Banda arc transition zone following the 2023 Mw 7.1 Bali Sea earthquake, which occurred on August 29, 2023, at 02:55:32 UTC + 7, approximately 163 km northeast of Lombok, Indonesia. This earthquake was caused by slab pull activity from the Australian Plate and involved a combination of downward and oblique-normal movement. These characteristics indicate the convergence and interaction between tectonic plates in the subduction process occurring in the Bali Sea area. As a result, there have been frequent occurrences of various tectonic and volcanic activities including earthquakes of different magnitudes. These results highlight the significance of the high-velocity anomaly connected to this occurrence, offering valuable insights into seismic behaviour and tectonic phenomena in the region. The findings of this study indicate that the deep earthquakes in the Bali Sea may be induced by faulting due to the transformation of metastable olivine into denser spinel at significant depths, along with shear instability caused by phase transitions within Earth’s mantle layers. This theory proposes that stress-induced changes in phase can initiate shear instabilities and subsequently lead to deep earthquakes.

Three-Dimensional Subsurface Model of Luk-Ulo Melange Complex, Karangsambung, Indonesia: Insights from Gravity Modeling

The Luk-Ulo Melange Complex (LMC) is characterized by a chaotic assemblage of mixed rocks with a block-in-matrix fabric. The exposed blocks consist of various scattered rock types, trending in an ENE-WSW direction. In the case of Mt. Parang, the origin of the diabase remains uncertain, with ongoing debate as to whether it is associated with in situ volcanic activity or represents an exotic block within the melange deposit. Subsurface data obtained through geophysical investigation can aid in modeling the geometry of intrusive bodies using inverse modeling techniques. In this study, we conducted a gravity survey and performed 3D inverse modeling to investigate the subsurface beneath Karangsambung. A total of 818 gravity data points and 28 rock density measurements were integrated with existing geological data to construct an a priori 3D geological model. To ensure the results align with geological concepts, the 3D inversion utilized a stochastic approach, allowing for the incorporation of multiple geological constraints over fifty million iterative procedures. Ultimately, the inversion successfully reduced the misfit between observed and calculated data from 2.71 to 0.55 mGal. Based on the inverted 3D model, the diabase rock in Mt. Parang is identified as having an intrusive origin. The intrusion model exhibited minimal changes in density, volume, and shape during the inversion process. Additionally, the model suggests the presence of a solidified magma reservoir at a depth of approximately 3 km, potentially related to Dakah volcanism. The inverted model also reveals the block-in-matrix structure of the Luk-Ulo Melange Complex in the northern area.

SAMControl: Controlling Pose and Object for Image Editing with Soft Attention Mask

To achieve content-consistent results in text-conditioned image editing, existing methods typically employ a reconstruction branch to capture the source image details via diffusion inversion and a generation branch to synthesize the target image based on the given textual prompt and the masked source image details. However, accurately segmenting source details is challenging with the current fixed-threshold mask strategy. Additionally, the inadequacies in the inversion process can lead to insufficient retention of source details. In this paper, we propose a method called SAMControl ( S oft A ttention M ask) to adaptively control the pose and object details for image editing. SAMControl dynamically learns flexible attention masks for different images at various diffusion steps. Furthermore, in the reconstruction branch, we utilize a direct inversion technique to ensure the fidelity of source details within SAM. Extensive qualitative and quantitative results demonstrate the effectiveness of the proposed method.

Application of Combined Geoelectrical Techniques for Groundwater Exploration at Federal University Gusau, Zamfara and its Environ, Northwest Nigeria

Study’s Excerpt Integrated approach combining Electrical Resistivity Tomography (ERT), Natural Electric Field (NEF) method, and Vertical Electrical Sounding (VES) is used to delineate groundwater potential in the study area. The results revealed that the water bearing aquifers in the study area are fractured basement layers at varying depths between 15 and 105 meters. This research provided a robust framework for groundwater exploration in arid and geologically complex terrains. Full Abstract The area of study is currently facing an acute water shortage due to the dominant lithological framework that underlies the region and its fragile climate condition. As such, this study aimed at unearthing the groundwater potential of the area using a combined three geoelectrical techniques. Techniques such as Electrical Resistivity Tomography (ERT), Natural Electric Field (NEF) method, and Vertical Electrical Sounding (VES) were employed in the delineation of the groundwater potential of the area. Using an ABEM SAS-4000 Resistivity meter and a PQWT-TC150 water-detector equipment, respectively. Wennar array was employed for the conduct of ERT while Schlumberger configuration was used for VES data collection. The measured apparent resistivity value was inputted into RES2DIV software and subjected to an inversion process to generate the resistivity structural image of the subsurface. However, IP2WIN software was used for the VES data interpretation. The result of the ERT method revealed two to three geoelectrical resistivity layers: an overburdened layer of topsoil/laterite with resistivity values ranging from 6.86 Ωm to 1095 Ωm and thicknesses of 1-13 meters, a weathered/fractured basement layer, interpreted as the aquifer unit, with resistivity values between 28.7 Ωm and 345 Ωm, and thicknesses ranging from 6 - 30 meters; and a fresh/slightly fractured basement layer with resistivity values from 367 Ωm to 6899 Ωm. NEF method revealed the thickness and depth of the aquiferous layer across the six profile lines to range between 15-60m, 30-90m, 15-85m, 20-80m, 45-105m, and 20-40m respectively, with points on profile five (5) identified as the most promising site with regards to groundwater development. VES result identifies weathered and fractured layers as the major aquiferous units with resistivity values ranging from 9.965 Ωm to 9651 Ωm and 21.7 Ωm to 859 Ωm respectively with fracture thickness reaching up to 60m in some instances. The result goes in line with the outcome of both NRF and ERT techniques. The geological interference of this lithology on groundwater exploration reveals both the weathered overburden and fractured basement as aquiferous units in the study area. The study identified several promising aquiferous zones at depths ranging from 15 to 105 meters, with fractured basement layers serving as primary reservoirs for groundwater development.

Oscillation and hysteresis characteristics of high-speed duct during TBCC inlet mode transition under mildly throttled condition

This study aims to investigate the intricate dynamic characteristics of the high-speed duct during the over-under Turbine-Based Combined Cycle TBCC inlet mode transition process while operating in an off-design state under throttled conditions. A typical over-under TBCC inlet, designed for a working Mach number range of 0–6 with a transition Mach number of 3.5, is examined through experimental studies in a supersonic wind tunnel with a freestream Mach number of 2.9. The investigation focuses on the complex oscillatory flow and unique hysteresis observed in the mode transition process of the high-speed duct under the mildly throttled condition, utilizing high-speed Schlieren and dynamic pressure acquisition system. The findings reveal that the high-speed duct undergoes four distinct oscillation stages akin to those in a higher throttled state during the mode transition, albeit with smaller dominant frequency and energy. Moreover, an irregular alternating “big/little buzz” mode is observed in the early stage of the large oscillation stage. Notably, the mildly throttled state exhibits three intriguing hysteresis properties compared to the unthrottled and higher throttled states. Firstly, hysteresis is observed in the shock train motion stage in the duct before unstart, along with the corresponding inverse process. Subsequently, hysteresis is noted in the unstart and restart of the high-speed duct, with a smaller hysteresis interval than in the unthrottled state. Finally, the hysteresis characteristics of oscillation mode switching and the corresponding inverse process are explored. Based on the analysis, the first two hysteresis phenomena are associated with the formation and dissipation of the separation bubble. The significant adverse pressure gradient constrains the cross-sectional capacity of the channel, rendering the disappearance of the separation bubble more challenging. The hysteresis in oscillation mode switching is linked to not only the channel cross-sectional capacity but also the state of the incoming boundary layer.

Comparison of methods measuring electrical conductivity in coastal aquifers

Coastal aquifers, the transition zone between freshwater and saltwater, show large salinity contrasts in the subsurface. Salinity is a key parameter to understand coastal groundwater flow dynamics and consequently also geochemical and microbial processes. For mapping porewater salinity, a variety of methods exists, mainly using electrical conductivity as a proxy. We investigate methods including hydrological/geochemical (well sampling, fluid logger) as well as geophysical method (direct push, geoelectrics) utilising measurements near the high-water line of a high-energy beach at the North Sea island of Spiekeroog. We compare the methods, discuss their benefits and limitations and assess their spatial and temporal resolution. One key to enable a comparison is the estimation of formation factors transforming bulk conductivity measured by geophysical tools in to fluid conductivities obtained from direct measurements. We derive depth-dependent formation factors derived from time-series measurements of fluid loggers and a vertical electrode installation. Using these formation factors, the vertical electrode chain proves to provide reliable salinities at high spatial and temporal dimension. Direct-push profiling data provide the highest vertical resolution. However, a careful calibration is needed to allow for salinity quantification. On the other hand, electrical resistivity tomography (ERT) exhibits the lowest spatial resolution, but can image two-dimensional salinity distributions. We found ERT to fit very well to all other methods, but the data analysis should be aimed at salinities instead of bulk conductivities, i.e. including formation factors and temperature models into the inversion process.

Higher-order fractional equations and related time-changed pseudo-processes

We study Cauchy problems of fractional differential equations in both space and time variables by expressing the solution in terms of “stochastic composition” of the solutions to two simpler problems. These Cauchy sub-problems respectively concern the space and the time differential operator involved in the main equation. We provide some probabilistic and pseudo-probabilistic applications, where the solution can be interpreted as the pseudo-transition density of a time-changed pseudo-process. To extend our results to higher order time-fractional problems, we introduce stable pseudo-subordinators as well as their pseudo-inverses. Finally, we present our results in the case of more general differential operators and we interpret the results by means of a linear combination of pseudo-subordinators and their inverse processes.

Reimagining Spaces in Central and Eastern Europe or Memory Roulette: Legal, Political and Social Aspects

Abstract If one was to look for a single word to describe the historical experiences of Central and Eastern Europe (cee), roulette comes immediately to mind. Be that the fall of great empires of the region following World War i (wwi), the tragedy of World War ii (wwii), the Iron Curtain separating cee from the rest of the world, the fall of communism, the more recent illiberal ‘reckoning’ or the Russo-Ukrainian war, the region’s history is characterised by unpredictibility. Importantly, these moments of ground-breaking change affect not only the political sphere – although the regime shifts and border changes are often amongst the most noticeable – but also the national imaginaries, as the process of collective memory inversion takes place, and official narratives of the yesteryear are replaced by those currently in power. Law plays an important role in managing these modifications, in particular those most visible, relating to public spaces and cultural heritage. The purpose of this paper is to look holistically at the changes that took place in the public sphere in the region since the end of wwi, with a particular focus on the intersection of law, politics and social changes. In the first, theoretical part of the paper, the author explains the relationship between collective memory and public spaces, linking these concepts with the understanding of the field, violence, habitus, and crisis proposed by Bourdieu. The second part of the paper introduces the major moments of change in the recent cee history from the perspective of reimagination of public spaces, illustrating them on selected case studies: post-wwi fall of the empires and the destruction of the Alexander Nevsky Cathedral in Warsaw, the wwii atrocities and the erasure of shtetl culture, the times of communism and the construction of the People’s Palace in Bucharest, the post-1989 decommunisation and the (not always) meticulous removal of the communist monuments from Estonia, the arrival of illiberalism and the reimagining of museums in Hungary, and, ultiamtely, the Russo-Ukrainian war and the ensuing derussification of Ukraine. In the third, conclusive part of the paper, the author looks at the big picture, linking the theoretical with the case studies more generally and proposing to draw lessons from Central and Eastern European roulette, which may also be applicable to other spaces in permanent flux.

Robust polymer electrolytes with fast ion-transport nanochannels constructed by carbon dots for long lifespan Li metal batteries

As an anode material in energy storage systems, Li metal has exceptional merits, including high specific capacity, low density, and low redox potential. However, challenges such as lithium dendrites and unstable solid electrolyte interphase (SEI) hinder the practical application of lithium metal batteries (LMBs). Solid polymer electrolytes (SPEs), notably PVDF-HFP, are expected to overcome the above problems because of their mechanical merits and safe features, but their limited ion transportation behaviors result in insufficient ionic conductivity at room temperature. Herein, we invent an approach to prepare high performance electrolytes composed by porous PVDF-HFP and functionalized carbon dots (CDs). Such porous PVDF-HFP polymer membranes are created by a subtle phase inversion process, possessing a sponge-like structure, vertical lithium-ion transport channels and CDs decorated surfaces, thus able to uptake the liquid electrolyte (LE) to form gel polymer electrolytes (GPEs). The CDs fillers are produced in large scale with adjustable surface states, which can enhance Li salts disassociation to release free Li ions. As a result, the optimal conductivity of the as-prepared GPEs at room temperature is up to 8.7 mS cm−1 and the lithium transference number reaches 0.64. Our GPEs endow Li symmetric batteries with very stable SEI and long cycling life over 2200 h, and help realize high capacities and retention rates of the LMBs using LiFePO4(LFP) or LiCoO2(LCO) cathodes.

A physics knowledge-based surrogate model framework for time-dependent slope deformation: Considering water effect and sliding states

The surrogate model serves as an efficient simulation tool during the slope parameter inversion process. However, the creep constitutive model integrated with dynamic damage evolution poses challenges in development of the required surrogate model. In this study, a novel physics knowledge-based surrogate model framework is proposed. In this framework, a Transformer module is employed to capture strain-driven softening-hardening physical mechanisms. Positional encoding and self-attention are utilized to transform the constitutive parameters associated with shear strain, which are not directly time-related, into intermediate latent features for physical loss calculation. Next, a multi-layer stacked GRU (gated recurrent unit) network is built to provide input interfaces for time-dependent intermediate latent features, hydraulic boundary conditions, and water-rock interaction degradation equations, with static parameters introduced via external fully-connected layers. Finally, a combined loss function is constructed to facilitate the collaborative training of physical and data loss, introducing time-dependent weight adjustments to focus the surrogate model on accurate deformation predictions during critical phases. Based on the deformation of a reservoir bank landslide triggered by impoundment and subsequent restabilization, an elasto-viscoplastic constitutive model that considers water effect and sliding state dependencies is developed to validate the proposed surrogate model framework. The results indicate that the framework exhibits good performance in capturing physical mechanisms and predicting creep behavior, reducing errors by about 30 times compared to baseline models such as GRU and LSTM (long short-term memory), meeting the precision requirements for parameter inversion. Ablation experiments also confirmed the effectiveness of the framework. This framework can also serve as a reference for constructing other creep surrogate models that involve non-time-related across dimensions.

A Method for Predicting the Remaining Service Life of Finite Data Products Based on Gaussian Stochastic Processes

There is a problem of poor predictive performance when predicting the remaining service life of products. Therefore, this paper proposes a finite data product remaining service life prediction method based on Gaussian stochastic processes. Analyze the types of product failure and degradation under limited data, and determine the factors affecting the degradation performance of product life through constant stress accelerated degradation tests, step stress accelerated degradation tests, and sequential stress accelerated aging tests; using the Wiener process to analyze the performance degradation characteristics of products, setting product failure thresholds, defining the remaining life of the product based on the degradation process, and using equal interval partitioning methods to determine the product health index, and clarifying the product failure process under limited data; by calculating the mathematical expected value, the numerical characteristics of the remaining life of the product are defined. Variance and moments are used to determine the predicted second-order central moment and origin moment. Based on the monotonic increasing characteristics of the inverse Gaussian process, the probability distribution of the random variable of product failure is determined after the Gaussian process. Under limited data, the actual working time of the product and the degradation amount at the time scale are clarified, and a preset threshold is set for the degradation amount. Build a residual life prediction model for product degradation and output the prediction results. The experimental results show that this method can accurately predict the remaining service life of the product and has good predictive performance.

SwinInver: 3D data-driven seismic impedance inversion based on Swin Transformer and adversarial training

As deep learning becomes increasingly prevalent in seismic impedance inversion, 3D data-driven approaches have garnered substantial interest. However, two critical challenges persist. First, existing methodologies predominantly rely on Convolutional Neural Networks (CNNs), which, due to the inherent locality of convolutional operations, are inadequate in capturing the global context of seismic data. This limitation notably hinders their performance in inverting complex subsurface structures, such as salt bodies. Second, the current inversion frameworks are prone to overfitting, particularly when trained on limited seismic datasets. To address these challenges, we propose SwinInver, a novel backbone network that integrates the Swin Transformer as its fundamental unit, coupled with a high-resolution network design to facilitate comprehensive global modeling of intricate subsurface structures. Furthermore, we incorporate adversarial training to enhance the inversion process and effectively mitigate overfitting. Experimental evaluations demonstrate that SwinInver significantly surpasses conventional CNN-based approaches in both synthetic and field data scenarios, providing a more accurate and reliable framework for seismic impedance inversion.

Diffusion-model-based inverse problem processing for optically-measured sound field

This paper proposes a diffusion-model-based method for addressing inverse problems in optical sound-field imaging. Optical sound-field imaging, known for its high spatial resolution, measures sound by detecting small variations in the refractive index of air caused by sound but often suffers from unavoidable noise contamination. Therefore, we present a diffusion model-based approach for sound-field inverse problems, including denoising, noisy sound-field reconstruction and extrapolation. During inference, sound-field degradation is introduced into the inverse denoising process, with range-null space decomposition used as a solver to handle degradation, iteratively generating degraded sound-field information. Numerical experiments show that our method outperforms other deep-learning-based methods in denoising and reconstruction tasks, and obtains effective results in extrapolation task. The experimental results demonstrate the applicability of our model to the real world.

Construction of Asymmetric Filler Density Mixed-Matrix MOF Membranes via Liquid-Phase Ion Activation for Advanced Oxidation Processes.

Mixed-matrix membrane (MMM) reactors incorporating metal-organic framework (MOF) fillers have significant applications in fields such as separation, catalysis, and chiral resolution. However, the traditional method of directly mixing MOF fillers with polymers results in a symmetric structure where most of the MOF fillers are uniformly distributed across the membrane reactor's cross-section. During usage, this leads to a pronounced trade-off between flux and efficiency and the waste of the MOF, as the rich pore characteristics and active sites of MOFs are not fully utilized. In this study, we propose a liquid-phase ion activation strategy that enables the in situ formation of a uniform and densely packed MOF shell layer on the membrane surface during the phase inversion process of MMM fabrication. This asymmetric density distribution of the MOF-based MMM reactor selectively induces the generation of considerable nonradical 1O2 in the peroxomonosulfate (PMS) system, demonstrating superior catalytic degradation performance against antibiotics like TC and dye molecules (with a flux of 1880 L m-2 h-1 and a Kapp value of 648 min-1), as well as outstanding cycling stability and environmental tolerance. This discovery sheds light on the design and engineering of composite membrane materials and applications for advanced oxidation processes in water purification.