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).

Design and optimization of a greener sinomenine hydrochloride preparation process considering variations among different batches of the medicinal herb

The current methods used to industrially produce sinomenine hydrochloride involve several issues,including high solvent toxicity,long process flow,and low atomic utilization efficiency,and the greenness scores of the processes are below 65 points.To solve these problems,a new process using anisole as the extractant was proposed.Anisole exhibits high selectivity for sinomenine and can be connected to the subsequent water-washing steps.After alkalization of the medicinal material,heating extraction,water washing,and acidification crystallization were carried out.The process was modeled and optimized.The design space was constructed.The recommended operating ranges for the critical process parameters were 3.0–4.0 h for alkalization time,60.0–80.0℃ for extraction temperature,2.0–3.0(volume ratio)for washing solution amount,and 2.0–2.4 mol·L^(-1) for hydrochloric acid concentration.The new process shows good robustness because different batches of medicinal materials did not greatly impact crystal purity or sinomenine transfer rate.The sinomenine transfer rate was about 20%higher than that of industrial processes.The greenness score increased to 90 points since the novel process proposed in this research solves the problems of long process flow,high solvent toxicity,and poor atomic economy,better aligning with the concept of green chemistry.

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.

Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

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.

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.

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.

A review on plasma-based CO_(2) utilization:process considerations in the development of sustainable chemical production

Plasma-based processes,particularly in carbon capture and utilization,hold great potential for addressing environmental challenges and advancing a circular carbon economy.While significant progress has been made in understanding plasma-induced reactions,plasma-catalyst interactions,and reactor development to enhance energy efficiency and conversion,there remains a notable gap in research concerning overall process development.This review emphasizes the critical need for considerations at the process level,including integration and intensification,to facilitate the industrialization of plasma technology for chemical production.Discussions centered on the development of plasma-based processes are made with a primary focus on CO_(2) conversion,offering insights to guide future work for the transition of the technology from laboratory scale to industrial applications.Identification of current research gaps,especially in upscaling and integrating plasma reactors with other process units,is the key to addressing critical issues.The review further delves into relevant research in process evaluation and assessment,providing methodological insights and highlighting key factors for comprehensive economic and sustainability analyses.Additionally,recent advancements in novel plasma systems are reviewed,presenting unique advantages and innovative concepts that could reshape the future of process development.This review provides essential information for navigating the path forward,ensuring a comprehensive understanding of challenges and opportunities in the development of plasma-based CCU process.

Modeling and analysis of air combustion and steam regeneration in methanol to olefins processes

Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However,the catalyst deactivation is an inevitable feature in MTO processes,and regeneration,therefore,is one of the key steps in industrial MTO processes.Traditionally the MTO catalyst is regenerated by removing the deposited coke via air combustion,which unavoidably transforms coke into carbon dioxide and reduces the carbon utilization efficiency.Recent study shows that the coke species over MTO catalyst can be regenerated via steam,which can promote the light olefins yield as the deactivated coke species can be essentially transferred to industrially useful synthesis gas,is a promising pathway for further MTO processes development.In this work,we modelled and analyzed these two MTO regeneration methods in terms of carbon utilization efficiency and technology economics.As shown,the steam regeneration could achieve a carbon utilization efficiency of 84.31%,compared to 74.74%for air combustion regeneration.The MTO processes using steam regeneration can essentially achieve the near-zero carbon emission.In addition,light olefins production of the MTO processes using steam regeneration is 12.81%higher than that using air combustion regeneration.In this regard,steam regeneration could be considered as a potential yet promising regeneration method for further MTO processes,showing not only great environmental benefits but also competitive economic performance.

Process synthesis for the separation of coal-to-ethanol products

The coal-to-ethanol process,as the clean coal utilization,faces challenges from the energy-intensive distillation that separates multi-component effluents for pure ethanol.Referring to at least eight columns,the synthesis of the ethanol distillation system is impracticable for exhaustive comparison and difficult for conventional superstructure-based optimization as rigorous models are used.This work adopts a superstructure-based framework,which combines the strategy that adaptively selects branches of the state-equipment network and the parallel stochastic algorithm for process synthesis.High-performance computing significantly reduces time consumption,and the adaptive strategy substantially lowers the complexity of the superstructure model.Moreover,parallel computing,elite search,population redistribution,and retention strategies for irrelevant parameters are used to improve the optimization efficiency further.The optimization terminates after 3000 generations,providing a flowsheet solution that applies two non-sharp splitting options in its distillation sequence.As a result,the 59-dimension superstructure-based optimization was solved efficiently via a differential evolution algorithm,and a high-quality solution with a 28.34%lower total annual cost than the benchmark was obtained.Meanwhile,the solution of the superstructure-based optimization is comparable to that obtained by optimizing a single specific configuration one by one.It indicates that the superstructure-based optimization that combines the adaptive strategy can be a promising approach to handling the process synthesis of large-scale and complex chemical processes.

Optical PAM-4/PAM-8 generation via dual-Raman process in Rydberg atoms

A scheme of optical four-level pulse amplitude modulation(PAM-4) is proposed based on dual-Raman process in Rydberg atoms. A probe field counter-propagates with a dual-Raman field which drives the ground and the excited states transition, respectively, and the Rydberg transition is driven by a microwave(MW) field. A gain peak appears in the probe transmission and is sensitive to the MW field strength. Optical PAM-4 can be achieved by encoding an MW signal and decoding the magnitude of a probe signal. Simulation results show that the differential nonlinearity and the integral nonlinearity of the proposed scheme can be reduced by 5 times and 6 times, respectively, compared with the counterparts of previous scheme, and the ratio of level separation mismatch is close to the ideal value 1. Moreover, the scheme is extended to optical PAM-8 signal, which may further improve the spectral efficiency.

SIL1 improves cognitive impairment in APP23/PS45 mice by regulating amyloid precursor protein processing and Aβ generation

SIL1,an endoplasmic reticulum(ER)-resident protein,is reported to play a protective role in Alzheimer’s disease(AD).However,the effect of SIL1 on amyloid precursor protein(APP)processing remains unclear.In this study,the role of SIL1 in APP processing was explored both in vitro and in vivo.In the in vitro experiment,SIL1 was either overexpressed or knocked down in cells stably expressing the human Swedish mutant APP695.In the in vivo experiment,AAV-SIL1-EGFP or AAV-EGFP was microinjected into APP23/PS45 mice and their wild-type littermates.Western blotting(WB),immunohistochemistry,RNA sequencing(RNA-seq),and behavioral experiments were performed to evaluate the relevant parameters.Results indicated that SIL1 expression decreased in APP23/PS45 mice.Overexpression of SIL1 significantly decreased the protein levels of APP,presenilin-1(PS1),and C-terminal fragments(CTFs)of APP in vivo and in vitro.Conversely,knockdown of SIL1 increased the protein levels of APP,β-site APP cleavage enzyme 1(BACE1),PS1,and CTFs,as well as APP mRNA expression in 2EB2 cells.Furthermore,SIL1 overexpression reduced the number of senile plaques in APP23/PS45 mice.Importantly,Y-maze and Morris Water maze tests demonstrated that SIL1 overexpression improved cognitive impairment in APP23/PS45 mice.These findings indicate that SIL1 improves cognitive impairment in APP23/PS45 mice by inhibiting APP amyloidogenic processing and suggest that SIL1 is a potential therapeutic target for AD by modulating APP processing.

Numerical Study of the Efficiency of Multi-Layer Membrane Filtration in Desalination Processes

Multi-layer membrane filtration is a widely used technology for separating and purifying different components ofa liquid mixture. This technique involves passing the liquid mixture through a series of membranes with decreasing pore sizes, which allows for the separation of different components according to their molecular size. Thisstudy investigates the filtration process of a fluid through a two-dimensional porous medium designed forseawater desalination. The focus is on understanding the impact of various parameters such as the coefficientof friction, velocity, and the number of layers on filtration efficiency. The results reveal that the number of layersplays a crucial role in desalination, with an increase in layers leading to enhanced filtration quality, following apower law relationship. The study explores the influence of the coefficient of friction on filtration performance,emphasizing its significant effect on the number of particles filtered over time. Additionally, the role of the initialvelocity in filtration efficiency is examined, showing distinct effects at both high and low velocities. Biofouling isidentified as a factor influencing filtration, with an initial increase in filtered particles followed by a decline due toparticle accumulation in pores.

Process Optimization of Cu-en/AP Composite Microspheres Preparation by Electrostatic Spray Method Based on ANSYS Simulation

To investigate the process optimizationof Cu-en/AP composite microspheres preparation via electrostatic spraying,and to reveal the effects of droplet properties and flow rate variations on the experimental results during the electrostatic spraying process,the prepared process parameters of Cu-en/AP composite microspheres by electrostatic spray method under the orthogonal experimental design simulated by ANSYS(Fluent).The influence of flow rate,solvent ratio,and solid mass on the experimental results is examined using a controlled variable method.The results indicate that under the conditions of a flow rate of 2.67×10^(-3)kg/s an acetone-to-deionized water ratio of 1.5∶1.0,and a solid mass of 200 mg,the theoretical particle size of the composite microspheres can reach e nanoscale.Droplet trajectories in the electric field remain stable without significant deviation.The simulation results show that particle diameter decreases with increasing flow rate,with the trend leveling off around a flow rate of 1×10^(-3)kg/s.As the solvent ratio increases(with higher acetone content),particle diameter initially decreases,reaching a minimum around a ratio of 1.5∶1.0 before gradually increasing.Increasing the solid mass also reduces the particle diameter,with a linear increase in diameter observed at around 220 mg.Cu-en/AP composite microspheres with nanoscale dimensions were confirmed under these conditions by the final SEM images.

BAR:a branch-alternation-resorting algorithm for locality exploration in graph processing

Unstructured and irregular graph data causes strong randomness and poor locality of data accesses in graph processing.This paper optimizes the depth-branch-resorting algorithm(DBR),and proposes a branch-alternation-resorting algorithm(BAR).In order to make the algorithm run in parallel and improve the efficiency of algorithm operation,the BAR algorithm is mapped onto the reconfigurable array processor(APR-16)to achieve vertex reordering,effectively improving the locality of graph data.This paper validates the BAR algorithm on the GraphBIG framework,by utilizing the reordered dataset with BAR on breadth-first search(BFS),single source shortest paht(SSSP)and betweenness centrality(BC)algorithms for traversal.The results show that compared with DBR and Corder algorithms,BAR can reduce execution time by up to 33.00%,and 51.00%seperatively.In terms of data movement,the BAR algorithm has a maximum reduction of 39.00%compared with the DBR algorithm and 29.66%compared with Corder algorithm.In terms of computational complexity,the BAR algorithm has a maximum reduction of 32.56%compared with DBR algorithm and53.05%compared with Corder algorithm.

The Frontiers and Future Landscape of Research and Education on Value Rationality in Contemporary China

The importance of conducting in-depth research and education on value rationality in the new era is increasingly recognized.Therefore,it is essential to systematically grasp the themes,frontiers,and trends of research in this field,organizing the knowledge system to provide references for future studies.This necessitates clarifying the research achievements of scholars from different disciplines and institutions.Using the CiteSpace visualization analysis method,we can analyze,summarize,and synthesize research networks,hotspots,and knowledge structures,thereby forming a direction for advancing research.Through literature review methods and knowledge graph software analysis,it is believed that value rationality and instrumental rationality represent the rational attitudes individuals adopt when contemplating issues and putting them into practice.They are merely methods and should not be subjected to excessive value judgments.The relationship between value rationality and instrumental rationality is a focal point of societal concern,involving complex interdisciplinary issues with significant theoretical value and practical implications.In the future,the academic community needs to strengthen research collaboration,enhance the expansion of value rationality in various social practice fields,and conduct empirical studies to build consensus for the construction of Chinese society.

Preparation Process and Quality Standard of Rougan Huaxian Ointment

[Objectives] To establish the preparation process and quality standard of Rougan Huaxian ointment.[Methods] The L 9(3 4) orthogonal test was employed to optimize the preparation process by considering the multiplication of water addition, extraction time, and extraction frequency as influencing factors. The dry paste yield was utilized as the evaluation criterion, in conjunction with the actual production conditions. Thin layer chromatography was employed to identify Radix Astragali, Lycii Fructus, Herba Dendrobii, and Rhizoma Polygoni Cuspidati. Ethanol served as the solvent for the determination of ethanol-soluble extractives using the cold immersion method.[Results] The preparation process was conducted as follows: the specified quantity of medicinal materials was combined with water for extraction purposes, performed in two separate stages. In each stage, eight times the amount of water was added. The first extraction lasted for 1.5 h, while the second extraction was completed in 1.0 h. The resulting liquid was then concentrated into a thick paste with a relative density ranging from 1.25 to 1.30 at a temperature of 60 ℃. The thin-layer chromatography analysis of Radix Astragali, Lycii Fructus, Herba Dendrobii, and Rhizoma Polygoni Cuspidati demonstrated distinct spots, effective separation, and the absence of interference from negative samples. Additionally, the ethanol-soluble extractives yielded a minimum of 8.0% in terms of dry weight.[Conclusions] The preparation process for Rougan Huaxian ointment is both stable and feasible. Furthermore, the quality standards established for this preparation are unique and reproducible, thereby facilitating effective quality control.

Prediction and optimization of flue pressure in sintering process based on SHAP

Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.

An Unprecedented Efficiency with Approaching 21%Enabled by Additive‑Assisted Layer‑by‑Layer Processing in Organic Solar Cells

Recently published in Joule,Feng Liu and colleagues from Shanghai Jiaotong University reported a record-breaking 20.8%power conversion efficiency in organic solar cells(OSCs)with an interpenetrating fibril network active layer morphology,featuring a bulk p-in structure and proper vertical segregation achieved through additive-assisted layer-by-layer deposition.This optimized hierarchical gradient fibrillar morphology and optical management synergistically facilitates exciton diffusion,reduces recombination losses,and enhances light capture capability.This approach not only offers a solution to achieving high-efficiency devices but also demonstrates the potential for commercial applications of OSCs.

Exploration and Practice of Nitrogen Addition Process for LF Refining Ladle Bottom Blowing Nitrogen Steel Liquid

This article discusses and analyzes the law of nitrogen increase in liquid steel and the main factors affect-ing the nitrogen increasing of molten steel,through the way of adding nitrogen to molten steel by bottom blowing nitrogen gas in LF refining process.It is considered that the main factors affecting the nitrogen increasing instability of molten steel are the initial temperature of LF refining,nitrogen relative element,surface active elements[O]and[S]of steel liquid,and bottom blowing rate of ladle.The large-scale production practice shows that T[O]not more than 50×10-6 and[S]is not more than 0.020 in LF refining at the initial temperature of not less than 1570.The liquid steel nitrogen enrichment test is carried out by ladle bottom blowing nitrogen gas after 20 min of refining,the flow rate is set as(6.0~7.0)NL/min per ton,and it is turned to 2 NL/min at 6 min before the end of refining,the nitrogen increasing rate of liquid steel is basically stable at(5~6)×10-6 per minute.