Inversion Process Research Articles

Strategic small molecule engineering: Unleashing the full potential of Kevlar aramid membrane in organic solvent nanofiltration

Kevlar aramid fiber (KANF), renowned for its exceptional solvent resistance, holds immense potential in fabricating of solvent-resistant membranes. However, the well-ordered structure of its rigid polymeric chains, coupled with intense intermolecular forces, significantly impedes the transport of solvents. Here, we propose a methodology utilizing small molecule polyethylene glycol (PEG) to mediate an interlayer structural reconstruction of KANF membranes, thereby enhancing solvent permeation. PEG, functioning as a nanostructure regulator, effectively inhibits the diffusion of DMSO into non-solvents during the phase inversion process. This intervention results in the multi-directional polymerization of aramid nanofibers and the emergence of distinctive interconnected microporous structures between layers, which notably accelerates the transport speed of solvents within the membrane. Concurrently, preserving of the dense layer on the surface ensures superior separation performance for the KANF membranes. This research underscores the possibility of modulating the internal microstructure of KANF membranes and highlights the prospective utility of KANF-PEG membranes in the organic solvent nanofiltration field.

Mixed‐charge cellulose nanocrystal modified cellulose acetate membrane with endotoxin scavenging ability and antibacterial properties

AbstractBlending modification is used to improve the hemocompatibility of cellulose acetate (CA) dialysis membranes while endowing the CA membrane with endotoxin scavenging and antibacterial capabilities. First, polydopamine (PDA) and polyethylenimine (PEI) are used as negatively charged and positively charged moieties, respectively, together with cellulose nanocrystals (CNCs) to construct mixed charge CNCs (PEI‐PDA@CNCs). Then PEI‐PDA@CNCs is blended with the CA casting solution, and the modified CA dialysis membrane is prepared through a phase inversion process. Through biocompatibility, adsorption, antibacterial, and filtration experiments, various properties of PEI‐PDA@CNCs modified CA membrane (PDCA) are systematically tested. The results show that the PDCA membrane exhibited good blood compatibility and noncytotoxicity. At the same time, the PDCA membrane has antibacterial properties and excellent endotoxin adsorption capacity. Compared with the CA membrane, the clearance rates of PDCA membrane for Staphylococcus aureus and Escherichia coli reach 54.0% ± 1.5% and 52.9% ± 5.9% respectively. In the dynamic adsorption experiment, the adsorption capacity of PDCA membrane for endotoxin increases to 2322.1 ± 45.9 EU/g. The research results indicate that PEI‐PDA@CNC‐modified multifunctional CA membrane with endotoxin adsorption and antibacterial properties has potential application prospects in the fields of hemodialysis and blood purification.

Retrieving Seismic Source Characteristics Using Seismic and Infrasound Data: The 2020 ML 4.1 Kiruna Minequake, Sweden

AbstractA minequake of magnitude ML 4.1 occurred on 18 May 2020 early in the morning at the LKAB underground iron ore mine in Kiruna, Sweden. This is the largest mining‐induced earthquake in Scandinavia. It generated acoustic signals observed at three infrasound arrays at 9.3 (KRIS, Sweden), 155 (IS37, Norway), and 286 km (ARCI, Norway) distance. We perform full‐waveform focal mechanism inversion based on regional seismic data and local infrasound data. These independently highlight that this event was dominated by a shallow‐depth collapse in agreement with in‐mine seismic station data. However, regional infrasound data cannot inform the inversion process without an accurate model of atmospheric winds and temperatures. Yet, our numerical simulations demonstrate a potential of using local and regional infrasound data to constrain an event's focal mechanism and depth.

Distinct Neural Mechanisms Between Anesthesia Induction and Emergence: A Narrative Review.

Anesthesia induction and emergence are critical periods for perioperative safety in the clinic. Traditionally, the emergence from general anesthesia has been recognized as a simple inverse process of induction resulting from the elimination of general anesthetics from the central nervous system. However, accumulated evidence has indicated that anesthesia induction and emergence are not mirror-image processes because of the occurrence of hysteresis/neural inertia in both animals and humans. An increasing number of studies have highlighted the critical role of orexinergic neurons and their involved circuits in the selective regulation of emergence but not the induction of general anesthesia. Moreover, additional brain regions have also been implicated in distinct neural mechanisms for anesthesia induction and emergence, which extends the concept that anesthetic induction and emergence are not antiparallel processes. Here, we reviewed the current literature and summarized the evidence regarding the differential mechanism of neural modulation in anesthesia induction and emergence, which will facilitate the understanding of the underlying neural mechanism for emergence from general anesthesia.

Inversion of image-only intrinsic parameters for steel fibre concrete under combined rate-temperature conditions: An adaptively enhanced machine learning approach

Concrete not only bears quasi-static loads during the service of engineering structures, but also bears impact or explosion due to accidental accidents, so more and more attention has been paid to the study of concrete deformation characteristics and stress distribution. Obtaining the correct constitutive parameters is crucial for the study of the mechanical behavior of concrete, and the determination of constitutive parameters is essentially an inverse process, which is very challenging. In this paper, third-order Bessel curves are used to construct dynamic constitutive equations for steel-fibre concrete under rate-temperature union conditions, and to establish a database of the constitutive parameters corresponding to the factors influencing the mechanical behaviour of concrete. In order to select highly accurate and adaptive intelligent inversion models, Firstly, the black-winged kite optimisation algorithm (BKA) has been improved by improving the black-winged kite leader condition and integrating the optimal perturbation strategy of Morlet wavelet factor, which proves the superiority of the MBKA algorithm by comparing it with the BKA, Dung Beetle Optimisation Algorithm (DBO), Grey Wolf Optimisation Algorithm (GWO), and Harris Hawk Algorithm (HHO) in searching for the optimal results. Secondly, based on the database, the MBKA-LSSVR model, MBKA-LSSVR-Adaboost model, CNN-GRU model and CNN-LSTM model were built sequentially, respectively. The final results show that the MBKA-LSSVR-Adaboost model has the highest accuracy and the best performance for the parameter Pi (i = 0,1,2,3), and the inverted stress-strain curve proves that the proposed method is effective and accurate in determining the proposed constitutive parameters.

Geologically constrained geometry inversion and null-space navigation to explore alternative geological scenarios: a case study in the Western Pyrenees

SUMMARY Reducing the gap between geophysical inversion and geological interpretation can be achieved by integrating geological modelling into geophysical inversion. For this, we use a generalized, iterative level-set gravity inversion scheme in which geological units are deformed automatically. During the inversion process, a regularization term is defined using automated geological modelling to account for geological data and principles. This provides model-dependent geological constraints and encourages geological realism throughout inversion. To alleviate the dependence on the starting model and consider the possibility of features unseen by direct observations, an automated geophysical data-driven method is proposed to insert new rock units in the model. Uncertainty quantification is achieved through the null-space shuttle algorithm, which is used to generate a series of alternative models that are consistent with geophysical data. This methodology is applied to assess the uncertainties of a pre-existing 3-D crustal-scale geological model of the Western Pyrenean orogeny (France, Spain). The area is characterized by a positive gravity anomaly generally attributed to the presence of a shallow mantle body. The impact of variations in shape and density of key crustal and mantle features is investigated. Different scenarios are explored in 3-D space to produce a range of viable, relatively simple crustal-scale models of the area. This application demonstrates the capability and potential of this approach to evaluate alternative interpretations of geophysical data. The results show the plausibility of scenarios with a shorter subducted Iberian lower crust and a denser Axial Zone than in the pre-existing model.

High-resolution geophysical data unravel the post-Variscan structural history of the NW Cotentin inner shelf (Central English Channel)

The Cotentin Peninsula (CP) is one of the only area in Europe which contains records of a > 2.5 Ga-lasted geological history including three orogenic events (Archaean, Cadomian and Variscan) followed by a polyphase basin/inversion evolution during Meso-Cenozoic times. The CP area sensu lato is thus a suitable place for discussing how the structural configuration of the basement might have influenced the development of part of the southern shelf margin of the Central English Channel, even if sediments and post-Variscan tectonic records are limited at this place. This issue is addressed through an onshore/offshore structural approach combining newly-acquired high resolution bathymetric data and reflection seismic profiles, further constrained by lateral correlations onshore. The resulting Land-Sea Digital Elevation Model and corresponding geological map reveal a number of fault-bounded blocks involving a relatively thin package of Jurassic to Plio-Quaternary sequences, locally involved in slightly compressional deformations. These specific sedimentary and tectonic features typically characterize the southern shelf margin of the Central English Channel. They are discussed in terms of basin development and inversion processes in relation with basement structures and then integrated in the English Channel basin framework. Special attention is paid to three major structural features, i.e. the La Hague Offshore Fault, the La Hague Deep Fault network and the La Hague Deep, which emphasize, respectively, the role of structural inheritance and erosion/incision/deposition events during the post-Variscan tectono-sedimentary history of the southern elevated shoulder of the Central English Channel.

Antifouling Polyvinylidene Fluoride Membrane through Dopamine Self‐Polymerization Enhanced Surface Segregation toward Oil‐In‐Water Emulsions Separation

AbstractSurface segregation method, as an in situ method for simultaneous modification of membrane external surfaces and inner pore surfaces, has been more commonly employed to fabricate antifouling membranes. In this study, dopamine (DA) with self‐polymerization and bio‐adhesion ability is chosen as a surface segregation agent to fabricate antifouling polyvinylidene fluoride (PVDF) membrane for oil‐in‐water emulsions separation through synergistically regulating phase inversion, self‐polymerization of DA, and surface segregation of poly‐dopamine (PDA). During the phase inversion process, DA contacts with an alkaline coagulation bath to trigger self‐polymerization of DA, then the surface segregation of PDA proceeds spontaneously. The addition and self‐polymerization of DA can regulate the phase inversion process to acquire membranes with high porosity, as a result, the water permeance is increased from 134 to 538 L m−2 h−1 bar−1 with the oil rejection higher than 99.8%. Because the hydrophilic PDA layer on membrane and pore surfaces leads to a robust hydration layer, the membrane exhibits super‐oleophobicity underwater and excellent antifouling properties with water recovery ratio of more than 99.4%. This study may open a new route to preparing antifouling membranes by using small molecules as surface segregation agents.

1 × 4 nano-pixel power splitter designed using an electric profile correlation coefficient monitor method

The power splitter is one of the fundamental elements in a photonic IC. Among various power splitter structures, nano-pixel-based ones have attracted attention in recent years because of their flexible design capability. As there is no rigid design rule in nano-pixel layout, typically, inverse design algorithms are employed to realize the target function. In inverse design, general criteria are needed during the design process, and one typical criterion is the excess loss, however, there are no specific criteria for mode field evaluation. When designing a 1 × N power splitter, considering the power balance among the N output ports is crucial, therefore, we propose a correlation coefficient method to evaluate the output electric field profile. In this study, we adopted vector criteria including both an excess loss and correlation coefficient method during the inverse design process. As a result, the simulated results show all four 0th order modes and the output power to be 24.490%, 24.494%, 24.494%, and 24.490% with a low excess loss of 0.1 dB.

RedLionfish - fast Richardson-Lucy Deconvolution package for efficient point spread function suppression in volumetric data.

The experimental limitations with optics observed in many microscopy and astronomy instruments result in detrimental effects for the imaging of objects. This can be generally described mathematically as a convolution of the real object image with the point spread function that characterizes the optical system. The popular Richardson-Lucy (RL) deconvolution algorithm is widely used for the inverse process of restoring the data without these optical aberrations, often a critical step in data processing of experimental data. Here we present the versatile RedLionfish python package, that was written to make the RL deconvolution of volumetric (3D) data easier to run, very fast (by exploiting GPU computing capabilities) and with automatic handling of hardware limitations for large datasets. It can be used programmatically in Python/numpy using conda or PyPi package managers, or with a graphical user interface as a napari plugin.

Eddy Detection Inverted from Argo Profiles to Surface Altimetry

Abstract Argo floats are widely used to characterize vertical structures of ocean eddies, yet their capability to invert sea surface features of eddies, especially those overlooked by available altimeters, has not been explored. In this paper, we propose an “interior-to-surface” inversion algorithm to effectively expand the capacity of eddy detection by estimating altimeter-missed eddies’ surface attributes from their Argo-derived potential density anomaly profiles, given that the interior property and surface signature of eddies are highly correlated. An altimeter-calibrated machine learning ensemble is employed for the inversion training based on the joint altimeter–Argo eddy data and shows promising performance with mean absolute errors of 5.4 km, 0.5 cm, and 14.3 cm2 s−2 for eddy radius, amplitude, and kinetic energy, respectively. Then, the trained ensemble model is applied to independently invert the properties of eddies captured by an Argo-alone detection scheme, which yields high spatiotemporal consistency with their altimeter-captured counterparts. In particular, a portion of Argo-alone eddies is ∼25% smaller than altimeter-derived ones, indicating Argo’s unique capability of profiling weaker submesoscale eddies. Sea surface temperature and chlorophyll data are further applied to validate the reliability of eddies identified and characterized by the Argo-only algorithm. This new methodology effectively complements that of altimetry in eddy detection and can be expanded to estimate other physical/biochemical eddy variables from a variety of in situ observations. Significance Statement Despite thousands of eddies being routinely identified on a daily basis, it has been recognized that a substantial portion of eddies may still be missed due to inadequate sampling of altimeter constellations. Taking advantage of eddy’s correlation between surface and interior, a considerable number of eddies are discovered for the first time through an Argo-based eddy identification scheme. Here, we propose a new methodology to independently infer these recaptured eddies’ surface properties from their vertical signals through an “interior-to-surface” inversion process. The inferred eddy properties are verified by the spatiotemporal consistency with those derived from altimetry. Since Argo is capable of profiling smaller and weaker eddies, the proposed methodology significantly complements and expands that of altimetry in eddy observation.

Importance of Cosmic-Ray Propagation on Sub-GeV Dark Matter Constraints

We study sub-GeV dark matter (DM) particles that may annihilate or decay into Standard Model particles producing an exotic injection component in the Milky Way that leaves an imprint in both photon and cosmic-ray (CR) fluxes. Specifically, the DM particles may annihilate or decay into e + e −, μ + μ −, or π + π − and may radiate photons through their e ± products. The resulting e ± products can be directly observed in probes such as Voyager 1. Alternatively, the e ± products may produce bremsstrahlung radiation and upscatter the low-energy Galactic photon fields via the inverse Compton process, generating a broad emission from X-ray to γ-ray energies observable in experiments such as XMM-Newton. We find that we get a significant improvement in the DM annihilation and decay constraints from XMM-Newton (excluding thermally averaged cross sections of 10−31 cm3 s−1 ≲ 〈σ v〉 ≲ 10−26 cm3 s−1 and decay lifetimes of 1026 s ≲ τ ≲ 1028 s, respectively) by including best-fit CR propagation and diffusion parameters. This yields the strongest astrophysical constraints for this mass range of DM of 1 MeV to a few GeV and even surpasses cosmological bounds across a wide range of masses as well.

Geoelectric Modelling Based on Bessel Functions Integral and Damped Least-Square Inversion for Layered Earth Models

Apparent resistivity formulations of a geoelectric method for layered Earth have been obtained analytically in the Bessel functions integral. This formulation is obtained through the application of two boundary conditions. First, the current density is zero at the Earth's surface. Second, current density and electric potential are continuous at the boundary between the layers. Geoelectric modelling can be done using several model parameters through this formulation. The modelling results show that apparent resistivity formulations based on Bessel function integrals can simulate apparent resistivity curves for layered earth models. The inversion process uses the apparent resistivity formulation based on Bessel function integrals. In this study, the inversion process uses a dumped Least-squared inversion method. The first step begins by testing the inversion program using synthetic data. After that, the inversion program is used in field data. The inversion results using field data from geoelectric data in Mount Pandan, East Java, show that the program was well done, with a minimal error value of 1.24%.

Evaluating and validating 3-D simulated MASW and SPAC in situ tests in Argostoli, Greece

SUMMARY Geophysics and Geotechnical Engineering commonly use 1-D wave propagation analysis, simplifying complex scenarios by assuming flat and homogeneous soil layers, vertical seismic wave propagation and negligible pore water pressure effects (total stress analysis). These assumptions are commonly used in practice, providing the basis for applications like analysing site responses to earthquakes and characterizing soil properties through inversion processes. These processes involve various in situ tests to estimate the subsurface soil’s material profile, providing insights into its behaviour during seismic events. This study seeks to address the limitations inherent to 1-D analyses by using 3-D physics-based simulations to replicate in situ tests performed in the Argostoli basin, Greece. Active and passive source surveys are simulated, and their results are used to determine material properties at specific locations, using standard geophysical methods. Our findings underscore the potential of 3-D simulations to explore different scenarios, considering different survey configurations, source types and array sets.

Effect of MWCNTs surface functionalization on the characterization of PVA/MWCNTs nanocomposites

The present study aims to put forward the role of surface functionalization of multi-walled carbon nanotubes (MWCNTs) on the enhancement thermal and hydrophilicity properties of new nanocomposite based poly(vinyl alcohol)/surface functionalized MWCNTs (PVA/MWCNTs), prepared by a facile phase inversion process. In this study, the fabrication of PVA/MWCNTs nanocomposites is carried out using functionalized MWCNTs (f-MWCNTs) with different functional groups (–OH, –COOH, –NH2). The structural, morphological, thermal, hydrophilicity and physico-chemical properties of PVA/MWCNTs nanocomposites are characterized by XRD, FE-SEM, FT-IR, TGA and contact angle measurement. The FT-IR results confirm the formation of a hydrogen bond between MWCNTs and PVA chain. XRD analysis indicates an improvement in the crystallinity of the PVA/MWCNTs nanocomposite. TGA results reveal that the PVA/f-MWCNTs nanocomposites show higher thermal stability than pure PVA. It is revealed that PVA/MWCNTs nanocomposites based functionalized MWCNTs remarkably increase the degradation temperature, and thus enhancing the thermal properties. The highest weight loss (30.7 wt%) and degradation temperature (520 °C) values are obtained with PVA/f-MWCNTs(0.5 wt%). The contact angle measurement confirms that the hydrophobic properties of pure PVA became hydrophilic because of the functional groups of MWCNTs. The hydrophilicity of PVA/MWCNTs nanocomposites is increased with the increase in wt% of MWCNTs embedded in the nanocomposite.

Multiband Nonthermal Radiative Study of PeVatron Candidate Pulsar Wind Nebula HESS J1849-000

Pulsar wind nebula HESS J1849-000 is one of the sources that may emit PeV γ-ray photons based on the recent measurement by the Tibet Air Shower Array and the Large High Altitude Air Shower Observatory. We use a time-dependent model to investigate the nonthermal radiative properties of HESS J1849-000. Observed multiband data are produced well by relativistic leptons through synchrotron radiation and inverse Compton processes, and the particle transport and cooling processes are analyzed. Our results show that the particle adiabatic loss dominates over the synchrotron loss and inverse Compton losses, and the particle advection dominates over diffusion for the low-energy band. On the other hand, the particle synchrotron loss dominates over the adiabatic loss and inverse Compton losses, and the diffusion dominates over advection for the high-energy band. Furthermore, particle transport would be playing a significant role in the low-energy band, whereas the particle cooling processes may play a more important role in the high-energy band. The current diffusion coefficient 3.4 × 1026 cm2 s−1 at an electron energy of 1 TeV is derived, which implies a slow diffusion mechanism may occur within the nebula. More importantly, our model suggests that the particle's maximum energy is 3.6 PeV, which makes HESS J1849-000 a PeVatron candidate.

Waveform inversion with structural regularizing constraint based on gradient decomposition

Abstract Full waveform inversion (FWI) can simultaneously update low-to-medium wavenumber velocity components and high-wavenumber velocity components. However, if seismic data lack large-offset data and effective low-frequency components, FWI updates will be dominated by high-wavenumber velocity perturbation. Meanwhile, providing that the initial model is inaccurate, inversion will have the problem of local minima. In this study, FWI is developed with structural regularizing constraint based on gradient decomposition (RGDFWI). By correlating the separated forward wavefield and backward wavefield with specific propagating direction, FWI gradient is decomposed into tomography-mode gradient and migration-mode gradient. We propose an optimized strategy taking full advantage of the two modes of FWI gradient. On the one hand, we use tomography-mode gradient to enhance low-to-medium wavenumber updates. On the other hand, we use migration-mode gradient to apply structural regularizing constraint by estimating structure dip and adding sparsity constraint in Seislet domain. During the inversion process, high-wavenumber structural information constrains and guides low-wavenumber model updates. The results of two numerical tests, Marmousi model test and Overthrust model test, validate the optimized strategy, which can produce a better initial velocity model for FWI. The inversion finally generates a high-precision and high-resolution velocity model.

Water-Regulated Evolution of Inversion, Reinversion, and Amplification of Circularly Polarized Luminescence of Supramolecular Organogels Based on Glutamide-Cyanostilbene Amphiphile.

Water incorporated with supramolecular building blocks in organic solvents can play a key role in the circularly polarized luminescence (CPL) inversion and amplification of supramolecular assemblies. Herein, we demonstrate that fine-tuning the water content regulated the assembly structure evolution and made the circular dichroism and CPL sign of the system undergo intriguing inversion, reinversion, and amplification processes based on a unique and interesting glutamide-cyanostilbene system, as supported by morphology, spectroscopic observations, and time-dependent density functional theory calculation.

Acoustic full waveform inversion with elastic wave equation forward modeling

Full-waveform inversion (FWI) is a high-resolution velocity inversion method. Currently, acoustic full waveform inversion (AFWI) has achieved promising results in marine data inversion, but it still faces significant challenges in land data inversion. One of the reasons for the failure of AFWI in land data inversion is that the acoustic wave equation does not account for the elastic effects of seismic waves, such as surface waves and converted waves. This results in errors between the synthesized acoustic waveform and the observed elastic waveform, particularly in the amplitude and phase of the P-wave. To reduce the error caused by the elastic effect, we have improved the inversion process of AFWI. During the forward modeling stage, we replace the original acoustic wave equation with the elastic wave equation to simulate the wavefield. This allows us to obtain synthetic waveforms that incorporate elasticity, thereby reducing the corresponding error. When computing model gradients, we still base on the acoustic wave equation and only update the P-wave velocity model. This approach helps maintain a lower computational cost. We tested the method on the Marmousi model and field land data, and the results demonstrate that the method successfully reduces the error caused by the elastic effect, thereby improving the clarity of the inversion results.

Optimal step stress accelerated degradation tests with the bivariate inverse Gaussian process

AbstractStep‐stress accelerated degradation test (SSADT) has become a prevailing approach to lifetime assessment for highly reliable products. In practice, many products suffer from multiple degradation processes that significantly contribute to failures. In this paper, we investigate the optimal SSADT plans for products subject to two dependent degradation characteristics modeled by a bivariate inverse Gaussian process. The drift parameter of each process is assumed to be influenced by a common stress factor. A bivariate Birnbaum‐Saunders (BVBS)‐type distribution is employed to approximate the lifetime distribution and facilitate the derivation of the objective function. The optimal plans are prescribed under three common optimality criteria in the presence of constraints on test units and inspections. A revisited example of fatigue crack is then presented to demonstrate the proposed methods. Finally, the sensitivity of the SSADT plans is studied, and the results exhibit fair robustness of the optimal plans.