Simulation of dilatancy-controlled gas migration processes in saturated bentonite using a coupled multiphase flow and elastoplastic H2 M model

Dilatancy-controlled gas flow in preferential pathways plays a key role in the safety analysis of radioactive waste repositories.This is particularly the case for bentonite,an often-preferred barrier material.Gas flow in preferential pathways is characterized by localization and spontaneous behavior,which is challenging to simulate in numerical models due to strong hydro-mechanical coupling.To analyze a laboratory experiment in the framework of the DECOVALEX-2023 project,this study introduced a new approach of combining continuous modelling methods with spatial material properties derived from material heterogeneities and experimental observations.The proposed model utilized hydro-mechanical spatial distributions,namely Young’s modulus and gas entry pressure,and elastoplasticity combined with a linear swelling model.A conceptual strain-dependent permeability approach simulated dilatancycontrolled gas flow based on hydro-mechanical coupling.To test the effectiveness of the presented approach,a gas injection test in a compacted,saturated bentonite sample was simulated using the opensource code OpenGeoSys 5.8 and compared with experimental observations.The presented methodology is capable of simulating localized gas flow in preferential pathways.The spatial distributions of Young’s modulus and gas entry pressure affect the swelling pressure,relative permeability and,in combination with the strain-dependent permeability model,also the intrinsic permeability.

Effect of bubble morphology and behavior on power consumption in non-Newtonian fluids’aeration process

Due to a prolonged operation time and low mass transfer efficiency, the primary challenge in the aeration process of non-Newtonian fluids is the high energy consumption, which is closely related to the form and rate of impeller, ventilation, rheological properties and bubble morphology in the reactor. In this perspective, through optimal computational fluid dynamics models and experiments, the relationship between power consumption, volumetric mass transfer rate(kLa) and initial bubble size(d0) was constructed to establish an efficient operation mode for the aeration process of non-Newtonian fluids. It was found that reducing the d0could significantly increase the oxygen mass transfer rate, resulting in an obvious decrease in the ventilation volume and impeller speed. When d0was regulated within 2-5 mm,an optimal kLa could be achieved, and 21% of power consumption could be saved, compared to the case of bubbles with a diameter of 10 mm.

Migratory mode transition of astrocyte progenitors in the cerebral cortex: an intrinsic or extrinsic cell process?

The cerebral cortex is comprised of properly localized cell types that exert their specific functions.In the developing brain,cells migrate from the germinal region to their functional locations(Silva et al.,2019;Cossart and Garel,2022).For example,neocortical excitatory neurons are generated in the cerebral ventricular and subventricular zones,move to the developing cortical plate via radial migration,and reside in a radial array of six neuronal layers(Oishi and Nakajima,2018).On the other hand,cortical interneurons are mainly generated in ganglionic eminences,migrate tangentially across the cerebral cortex,and reach their final destinations in the cortex(Lim et al.,2018).The failure of neuronal migration leads to defects in cortical layer formation.While the mechanisms of neuronal distribution have been well examined,how astrocytes are diffusely distributed in the cortex is still unclear.Astrocytes are glial cells in the cerebral cortex with several functions,including metabolic support and synapse formation(Abbott et al.,2006;Bosworth and Allen,2017;Allen and Lyons,2018).For example,astrocytes establish synaptic connectivity in the developing brain while they contact numerous synapses and maintain optimal neuronal activity in the adult brain.In the developing brain,astrocytes are primarily generated from radial glia after the neurogenic period.While a certain type of astrocyte called fibrous astrocytes populates the white matter,protoplasmic astrocytes migrate to the cortical plate during neural network formation.

The roles of macrophage migration inhibitory factor in retinal diseases

Macrophage migration inhibitory factor(MIF),a multifunctional cytokine,is secreted by various cells and participates in inflammatory reactions,including innate and adaptive immunity.There are some evidences that MIF is involved in many vitreoretinal diseases.For example,MIF can exacerbate many types of uveitis;measurements of MIF levels can be used to monitor the effectiveness of uveitis treatment.MIF also alleviates trauma-induced and glaucoma-induced optic nerve damage.Furthermore,MIF is critical for retinal/choroidal neovascularization,especially complex neovascularization.MIF exacerbates retinal degeneration;thus,anti-MIF therapy may help to mitigate retinal degeneration.MIF protects uveal melanoma from attacks by natural killer cells.The mechanism underlying the effects of MIF in these diseases has been demonstrated:it binds to cluster of differentiation 74,inhibits the c-Jun N-terminal kinase pathway,and triggers mitogen-activated protein kinases,extracellular signal-regulated kinase-1/2,and the phosphoinositide-3-kinase/Akt pathway.MIF also upregulates Toll-like receptor 4 and activates the nuclear factor kappa-B signaling pathway.This review focuses on the structure and function of MIF and its receptors,including the effects of MIF on uveal inflammation,retinal degeneration,optic neuropathy,retinal/choroidal neovascularization,and uveal melanoma.

Reinforcement Learning in Process Industries:Review and Perspective

This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.

Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

The Impact of Hula Project (1993-2018) on Nutrient Migrations

During the 1950s the Hula wetlands and old lake were drained and the land converted utilization to agriculture and ecotourism. As a result of the drainage, the Peat Soil was exposed to atmospheric oxygen. The geochemical environment was modified from reductive to oxidative and the Nitrogen in it was converted from Ammonium to Nitrate. Intensive migration of Nitrate from the Hula Valley induced a national concern of water quality deterioration in the lake which was dissipated when Nitrogen deficiency was developed in Lake Kinneret. Forty years after drainage the ecosystem structure was renovated (Hula Project, HP) aimed at agricultural management and nutrient migration reduction. The paper examines through evaluation of the ecological data record (1993-2018) the impact of hydrological changes, attributed to the HP implementation on nutrient dynamics within surface waters in the Hula Valley. It is suggested that soil moisture elevation by irrigation in summer reduced Phosphorus and enhanced Nitrate concentrations.

GIPC1 promotes tumor growth and migration in gastric cancer via activating PDGFR/PI3K/AKT signaling

The high mortality rate associated with gastric cancer(GC)has resulted in an urgent need to identify novel therapeutic targets for GC.This study aimed to investigate whether GAIP interacting protein,C terminus 1(GIPC1)represents a therapeutic target and its regulating mechanism in GC.GIPC1 expression was elevated in GC tissues,liver metastasis tissues,and lymph node metastases.GIPC1 knockdown or GIPC1 blocking peptide blocked the platelet-derived growth factor receptor(PDGFR)/PI3K/AKT signaling pathway,and inhibited the proliferation and migration of GC cells.Conversely,GIPC1 overexpression markedly activated the PDGFR/PI3K/AKT signaling pathway,and promoted GC cell proliferation and migration.Furthermore,platelet-derived growth factor subunit BB(PDGF-BB)cytokines and the AKT inhibitor attenuated the effect of differential GIPC1 expression.Moreover,GIPC1 silencing decreased tumor growth and migration in BALB/c nude mice,while GIPC1 overexpression had contrasting effects.Taken together,our findings suggest that GIPC1 functions as an oncogene in GC and plays a central role in regulating cell proliferation and migration via the PDGFR/PI3K/AKT signaling pathway.

NADARAYA-WATSON ESTIMATORS FOR REFLECTED STOCHASTIC PROCESSES

We study the Nadaraya-Watson estimators for the drift function of two-sided reflected stochastic differential equations.The estimates,based on either the continuously observed process or the discretely observed process,are considered.Under certain conditions,we prove the strong consistency and the asymptotic normality of the two estimators.Our method is also suitable for one-sided reflected stochastic differential equations.Simulation results demonstrate that the performance of our estimator is superior to that of the estimator proposed by Cholaquidis et al.(Stat Sin,2021,31:29-51).Several real data sets of the currency exchange rate are used to illustrate our proposed methodology.

Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have been proposed,most of them can only address part of the practical difficulties.An oscillation is heuristically defined as a visually apparent periodic variation.However,manual visual inspection is labor-intensive and prone to missed detection.Convolutional neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction capabilities.In this work,an exploration of the typical CNN models for visual oscillation detection is performed.Specifically,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation detection.The feasibility and validity of this framework are verified utilizing extensive numerical and industrial cases.Compared with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and mean-nonstationarity.In addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

Operational optimization of copper flotation process based on the weighted Gaussian process regression and index-oriented adaptive differential evolution algorithm

Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.

Dendritic spine degeneration:a primary mechanism in the aging process

Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).

Multimodal Data-Driven Reinforcement Learning for Operational Decision-Making in Industrial Processes

Dear Editor, This letter proposes a multimodal data-driven reinforcement learning-based method for operational decision-making in industrial processes. Due to the frequent fluctuations of feedstock properties and operating conditions in the industrial processes, existing data-driven methods cannot effectively adjust the operational variables. In addition, multimodal data such as images, audio.

Phase-stable wide-bandgap perovskites enabled by suppressed ion migration

Wide-bandgap(>1.7 eV)perovskites suffer from severe light-induced phase segregation due to high bromine content,causing irreversible damage to devices stability.However,the strategies of suppressing photoinduced phase segregation and related mechanisms have not been fully disclosed.Here,we report a new passivation agent 4-aminotetrahydrothiopyran hydrochloride(4-ATpHCl)with multifunctional groups for the interface treatment of a 1.77-eV wide-bandgap perovskite film.4-ATpH^(+)impeded halogen ion migration by anchoring on the perovskite surface,leading to the inhibition of phase segregation and thus the passivation of defects,which is ascribed to the interaction of 4-ATpH^(+)with perovskite and the formation of low-dimensional perovskites.Finally,the champion device achieved an efficiency of 19.32%with an open-circuit voltage(V_(OC))of 1.314 V and a fill factor of 83.32%.Moreover,4-ATpHCl modified device exhibited significant improved stability as compared with control one.The target device maintained 80%of its initial efficiency after 519 h of maximum power output(MPP)tracking under 1 sun illumination,however,the control device showed a rapid decrease in efficiency after 267 h.Finally,an efficiency of 27.38%of the champion 4-terminal all-perovskite tandem solar cell was achieved by mechanically stacking this wide-bandgap top subcell with a 1.25-eV low-bandgap perovskite bottom subcell.

Migration Networks Pattern of China’s Floating Population from the Perspective of Complex Network

Since China’s reform and opening-up,the growing disparity between urban and rural areas and regions has led to massive migration.With China’s Rural Revitalization Strategy and the industrial transfer from the eastern coastal areas to the inland,the migration direction and pattern of the floating population have undergone certain changes.Using the 2017 China Migrants Dynamic Survey(CMDS),excluding Hong Kong,Macao,and Taiwan regions of China,organized by China’s National Health Commission,the relationship matrix of the floating population is constructed according to the inflow place of the interviewees and their outflow place(the location of the registered residence)in the questionnaire survey.We then apply the complex network model to analyze the migration direction and network pattern of China’s floating population from the city scale.The migration network shows an obvious hierarchical agglomeration.The first-,second-,third-and fourth-tier distribution cities are municipalities directly under the central government,provincial capital cities,major cities in the central and western regions and ordinary cities in all provinces,respectively.The migration trend is from the central and western regions to the eastern coastal areas.The migration network has‘small world’characteristics,forming nine communities.It shows that most node cities in the same community are closely linked and geographically close,indicating that the migration network of floating population is still affected by geographical proximity.Narrowing the urban-rural and regional differences will promote the rational distribution this population.It is necessary to strengthen the reform of the registered residence system,so that the floating population can enjoy urban public services comparable to other populations,and allow migrants to live and work in peace.

Application of Gaussian Beam Summation Migration in Reflected In-seam Wave Imaging

The geological conditions for coal mining in China are complex,with various structural issues such as faults and collapsed columns seriously compromising the safety of coal mine production.In-seam wave exploration is an effective technique for acquiring detailed information on geological structures in coal seam working faces.However,the existing reflected in-seam wave imaging technique can no longer meet the exploration precision requirements,making it imperative to develop a new reflected in-seam wave imaging technique.This study applies the Gaussian beam summation(GBS)migration method to imaging coal seams'reflected in-seam wave data.Firstly,with regard to the characteristics of the reflected in-seam wave data,methods such as wavefield removal and enveloped superposition are employed for the corresponding wavefield separation,wave train compression and other processing of reflected in-seam waves.Thereafter,imaging is performed using the GBS migration technique.The feasibility and effectiveness of the proposed method for reflected in-seam wave imaging are validated by conducting GBS migration tests on 3D coal-seam fault models with different dip angles and throws.By applying the method to reflected in-seam wave data for an actual coal seam working face,accurate imaging of a fault structure is obtained,thereby validating its practicality.

Volumetric lattice Boltzmann method for pore-scale mass diffusionadvection process in geopolymer porous structures

Porous materials present significant advantages for absorbing radioactive isotopes in nuclear waste streams.To improve absorption efficiency in nuclear waste treatment,a thorough understanding of the diffusion-advection process within porous structures is essential for material design.In this study,we present advancements in the volumetric lattice Boltzmann method(VLBM)for modeling and simulating pore-scale diffusion-advection of radioactive isotopes within geopolymer porous structures.These structures are created using the phase field method(PFM)to precisely control pore architectures.In our VLBM approach,we introduce a concentration field of an isotope seamlessly coupled with the velocity field and solve it by the time evolution of its particle population function.To address the computational intensity inherent in the coupled lattice Boltzmann equations for velocity and concentration fields,we implement graphics processing unit(GPU)parallelization.Validation of the developed model involves examining the flow and diffusion fields in porous structures.Remarkably,good agreement is observed for both the velocity field from VLBM and multiphysics object-oriented simulation environment(MOOSE),and the concentration field from VLBM and the finite difference method(FDM).Furthermore,we investigate the effects of background flow,species diffusivity,and porosity on the diffusion-advection behavior by varying the background flow velocity,diffusion coefficient,and pore volume fraction,respectively.Notably,all three parameters exert an influence on the diffusion-advection process.Increased background flow and diffusivity markedly accelerate the process due to increased advection intensity and enhanced diffusion capability,respectively.Conversely,increasing the porosity has a less significant effect,causing a slight slowdown of the diffusion-advection process due to the expanded pore volume.This comprehensive parametric study provides valuable insights into the kinetics of isotope uptake in porous structures,facilitating the development of porous materials for nuclear waste treatment applications.

Runx2 regulates peripheral nerve regeneration to promote Schwann cell migration and re-myelination

Runx2 is a major regulator of osteoblast differentiation and function;however,the role of Runx2 in peripheral nerve repair is unclea r.Here,we analyzed Runx2expression following injury and found that it was specifically up-regulated in Schwann cells.Furthermore,using Schwann cell-specific Runx2 knocko ut mice,we studied peripheral nerve development and regeneration and found that multiple steps in the regeneration process following sciatic nerve injury were Runx2-dependent.Changes observed in Runx2 knoc kout mice include increased prolife ration of Schwann cells,impaired Schwann cell migration and axonal regrowth,reduced re-myelination of axo ns,and a block in macrophage clearance in the late stage of regeneration.Taken together,our findings indicate that Runx2 is a key regulator of Schwann cell plasticity,and therefore peripheral nerve repair.Thus,our study shows that Runx2 plays a major role in Schwann cell migration,re-myelination,and peripheral nerve functional recovery following injury.

LFM Radar Source Passive Localization Algorithm Based on Range Migration

Traditional single-satellite passive localization algorithms are influenced by frequency and angle measurement accuracies,resulting in error estimation of emitter position on the order of kilometers.Subsequently,a single-satellite localization algorithm based on passive synthetic aper-ture(PSA)was introduced,enabling high-precision positioning.However,its estimation of azimuth and range distance is considerably affected by the residual frequency offset(RFO)of uncoopera-tive system transceivers.Furthermore,it requires data containing a satellite flying over the radia-tion source for RFO search.After estimating the RFO,an accurate estimation of azimuth and range distance can be carried out,which is difficult to achieve in practical situations.An LFM radar source passive localization algorithm based on range migration is proposed to address the dif-ficulty in estimating frequency offset.The algorithm first provides a rough estimate of the pulse repetition time(PRT).It processes intercepted signals through range compression,range interpola-tion,and polynomial fitting to obtain range migration observations.Subsequently,it uses the changing information of range migration and an accurate PRT to formulate a system of nonlinear equations,obtaining the emitter position and a more accurate PRT through a two-step localization algorithm.Frequency offset only induces a fixed offset in range migration,which does not affect the changing information.This algorithm can also achieve high-precision localization in squint scenar-ios.Finally,the effectiveness of this algorithm is verified through simulations.

Correlation of Microbiological Stability with Redox Processes in White Wines

In this paper, the authors analyzed the correlation between the microbiological stability of white wines and the content of sulfur dioxide, which influences the main redox processes that take place in the technological stages of the wine. The consecutive, parallel and spontaneous development of several redox processes and their impact on the quality, microbiological and crystalline stability of white wines were examined. The reduction of additive and subtractive technological interventions, of the amounts of adjuvants (sulphurous anhydride) is essential for the production of organic wines.