颈椎前路Hybrid手术和颈椎后路单开门椎管扩大成形术治疗多节段脊髓型颈椎病临床疗效分析

目的:分析颈椎前路Hybrid手术和颈椎后路单开门椎管扩大成形术(EODL)治疗多节段脊髓型颈椎病的疗效,探讨多节段脊髓型颈椎病患者手术方式的选择。方法:对2017年7月—2020年7月在首都医科大学附属北京中医医院手术治疗的70例多节段脊髓型颈椎病患者进行回顾性分析,根据手术方式不同,分为前路组35例和后路组35例,前路组患者行Hybrid手术[颈椎前路椎间盘切除融合术(ACDF)联合人工颈椎间盘置换术(ACDR)],后路组患者行EODL。记录2组患者住院时间、手术时间、术中出血量和术后引流量,通过日本骨科协会(JOA)评分、JOA改善率、颈椎残障功能指数(NDI)、疼痛视觉模拟评分(VAS)和术后满意度评分进行疗效评价,统计2组患者术后并发症发生情况。结果:与后路组比较,前路组患者术中出血量、术后引流量、住院时间和手术时间均明显减少(P<0.01),术前各项评分差异无统计学意义(P>0.05)。末次随访时,与后路组比较,前路组患者JOA评分和JOA改善率明显升高(P<0.01),NDI评分和VAS评分明显降低(P<0.01)。与术前比较,末次随访时2组患者JOA评分明显升高(P<0.01),NDI和VAS评分均明显降低(P<0.01)。按术后满意度评分评价,2组患者术后满意度均较高。2组患者术后并发症发生率比较差异无统计学意义(P>0.05)。结论:颈椎前路Hybrid手术和EODL在治疗多节段脊髓型颈椎病方面均取得了较为满意的疗效。Hybrid手术具有出血量少和手术时间短等优点,临床上应根据患者实际情况选择最适宜的术式。

Activation Redistribution Based Hybrid Asymmetric Quantization Method of Neural Networks

The demand for adopting neural networks in resource-constrained embedded devices is continuously increasing.Quantization is one of the most promising solutions to reduce computational cost and memory storage on embedded devices.In order to reduce the complexity and overhead of deploying neural networks on Integeronly hardware,most current quantization methods use a symmetric quantization mapping strategy to quantize a floating-point neural network into an integer network.However,although symmetric quantization has the advantage of easier implementation,it is sub-optimal for cases where the range could be skewed and not symmetric.This often comes at the cost of lower accuracy.This paper proposed an activation redistribution-based hybrid asymmetric quantizationmethod for neural networks.The proposedmethod takes data distribution into consideration and can resolve the contradiction between the quantization accuracy and the ease of implementation,balance the trade-off between clipping range and quantization resolution,and thus improve the accuracy of the quantized neural network.The experimental results indicate that the accuracy of the proposed method is 2.02%and 5.52%higher than the traditional symmetric quantization method for classification and detection tasks,respectively.The proposed method paves the way for computationally intensive neural network models to be deployed on devices with limited computing resources.Codes will be available on https://github.com/ycjcy/Hybrid-Asymmetric-Quantization.

MicroRNA-502-3p regulates GABAergic synapse function in hippocampal neurons

Gamma-aminobutyric acid(GABA)ergic neurons,the most abundant inhibitory neurons in the human brain,have been found to be reduced in many neurological disorders,including Alzheimer's disease and Alzheimer's disease-related dementia.Our previous study identified the upregulation of microRNA-502-3p(miR-502-3p)and downregulation of GABA type A receptor subunitα-1 in Alzheimer's disease synapses.This study investigated a new molecular relationship between miR-502-3p and GABAergic synapse function.In vitro studies were perfo rmed using the mouse hippocampal neuronal cell line HT22 and miR-502-3p agomiRs and antagomiRs.In silico analysis identified multiple binding sites of miR-502-3p at GABA type A receptor subunitα-1 mRNA.Luciferase assay confirmed that miR-502-3p targets the GABA type A receptor subunitα-1 gene and suppresses the luciferase activity.Furthermore,quantitative reve rse transcription-polymerase chain reaction,miRNA in situ hybridization,immunoblotting,and immunostaining analysis confirmed that overexpression of miR-502-3p reduced the GABA type A receptor subunitα-1 level,while suppression of miR-502-3p increased the level of GABA type A receptor subunitα-1 protein.Notably,as a result of the overexpression of miR-502-3p,cell viability was found to be reduced,and the population of necrotic cells was found to be increased.The whole cell patch-clamp analysis of human-GABA receptor A-α1/β3/γ2L human embryonic kidney(HEK)recombinant cell line also showed that overexpression of miR-502-3p reduced the GABA current and overall GABA function,suggesting a negative correlation between miR-502-3p levels and GABAergic synapse function.Additionally,the levels of proteins associated with Alzheimer s disease were high with miR-502-3p overexpression and reduced with miR-502-3p suppression.The present study provides insight into the molecular mechanism of regulation of GABAergic synapses by miR-502-3p.We propose that micro-RNA,in particular miR-502-3p,could be a potential therapeutic to rget to modulate GABAergic synapse function in neurological disorders,including Alzheimer's disease and Alzheimer's diseaserelated dementia.

The Extended Hybrid Carrier-Based Multiple Access Technology for High Mobility Scenarios

The hybrid carrier(HC)system rooted in the carrier fusion concept is gradually garnering attention.In this paper,we study the extended hybrid carrier(EHC)multiple access scheme to ensure reliable wireless communication.By employing the EHC modulation,a power layered multiplexing framework is realized,which exhibits enhanced interference suppression capability owing to the more uniform energy distribution design.The implementation method and advantage mechanism are explicated respectively for the uplink and downlink,and the performance analysis under varying channel conditions is provided.In addition,considering the connectivity demand,we explore the non-orthogonal multiple access(NOMA)method of the EHC system and develop the EHC sparse code multiple access scheme.The proposed scheme melds the energy spread superiority of EHC with the access capacity of NOMA,facilitating superior support for massive connectivity in high mobility environments.Simulation results have verified the feasibility and advantages of the proposed scheme.Compared with existing HC multiple access schemes,the proposed scheme exhibits robust bit error rate performance and can better guarantee multiple access performance in complex scenarios of nextgeneration communications.

复杂建设环境下基于Hybrid A^(*)算法的铁路平面线形绿色优化设计

随着“双碳经济下绿色铁路”理念的兴起,将“绿色生态”融入到铁路平面线路优化已成为近年来的研究热点。本文以铁路建设成本与生态破坏成本的协同优化为目标,引入并改进了一种自动驾驶导航算法(Hybrid A^(*)算法),以适应复杂的铁路设计问题,同时考虑最小曲线半径、最大曲线半径、最短曲线长度、最短夹直线长度、缓和曲线长度等铁路线形约束。研究结果表明:(1)改进后算法以离散网格方式整合外部环境因素,实现渐进式全局探索,获取接近全局最优的铁路线路设计结果;(2)该方法在复杂外部环境约束下,无需预设水平交点位置和数量,可自动生成符合线路-环境耦合约束的优化平面线路方案。

Production traits and fertility of reciprocal hybrids between Argopecten irradians irradians and A.i.concentricus

The two bay scallop subspecies,Argopecten irradians irradians(NN)and A.i.concentricus(SS),are fast growing and major cultured bivalves in China.However,their relatively small sizes and decreasing production traits caused by long-term inbreeding have been major concerns to the industry in the last two decades.Hybridization between the two bay scallop subspecies may provide a new approach to breed a new variety with superior production traits for the industry.For this end,in this study,we hybridized the two bay scallop subspecies in order to obtain a new strain that incorporates the genes of both subspecies.No significant difference was found in fertilization rate,hatching rate and metamorphosis rate between the purebred and crossbred cohorts(NN♀×SS♂,denoted as NS;SS♀×NN♂,denoted as SN).Both mating strategy(intra-vs.inter-population crosses)and egg origin had significant effects on growth and survival at the larval stage.Heterosis was observed in the crossbred and was more pronounced in older stages.Genetic diversity of the reciprocal hybrids,especially that of SN,was increased compared with the purebred cohorts.Almost all hybrids were completely fertile and able to reproduce by selffertilization or by backcrossing with either parent.Apparently,male sterile individuals whose gonads were fully occupied by the ovary part at mature stage were found in the hybrids for the first time.The hybrids,especially SN,may provide precious germplasm resources for the production of ternary hybrids with the Peruvian scallop,A.purpuratus.

MXene-based hybrid materials for electrochemical and photoelectrochemical H_(2) generation

The conversion of solar energy to produce clean hydrogen fuel through water splitting is an emerging strategy for efficiently storing solar energy in the form of solar fuel.This aligns with the increasing global demand for the development of an ideal energy alternative to fossil fuels that does not emit greenhouse gases.Electrochemical(EC) and photoelectrochemical(PEC) water splitting technologies have garnered significant attention worldwide for advanced hydrogen solar fuel production in recent decades.To achieve sustainable green H_(2) production,it is essential to create efficient catalyst materials that are low-cost and can replace expensive noble metal-based catalysts.These characteristics make them an ideal catalyst material for the process.Two-dimensional MXenes with M_(n+1)X_(n) structure have been identified as a promising option for EC and PEC water splitting due to their superior hydrophilicity,metal-like conductivity,large surface area,and adjustable surface chemistry.Here,we present a summary of recent advancements in the synthesis and performance enhancement methods for MXene hybrid materials in hydrogen production through EC and PEC water splitting.Furthermore,we examine the challenges and insights associated with the rational design of MXene-based hybrid materials to facilitate efficient water splitting for sustainable solar fuel production.

Origin and evolution of a new tetraploid mangrove species in an intertidal zone

Polyploidy is a major factor in the evolution of plants,yet we know little about the origin and evolution of polyploidy in intertidal species.This study aimed to identify the evolutionary transitions in three truemangrove species of the genus Acanthus distributed in the Indo-West Pacific region.For this purpose,we took an integrative approach that combined data on morphology,cytology,climatic niche,phylogeny,and biogeography of 493 samples from 42 geographic sites.Our results show that the Acanthus ilicifolius lineage distributed east of the Thai-Malay Peninsula possesses a tetraploid karyotype,which is morphologically distinct from that of the lineage on the west side.The haplotype networks and phylogenetic trees for the chloroplast genome and eight nuclear genes reveal that the tetraploid species has two sub-genomes,one each from A.ilicifolius and A.ebracteatus,the paternal and maternal parents,respectively.Population structure analysis also supports the hybrid speciation history of the new tetraploid species.The two sub-genomes of the tetraploid species diverged from their diploid progenitors during the Pleistocene.Environmental niche models revealed that the tetraploid species not only occupied the near-entire niche space of the diploids,but also expanded into novel environments.Our findings suggest that A.ilicifolius species distributed on the east side of the Thai-Malay Peninsula should be regarded as a new species,A.tetraploideus,which originated from hybridization between A.ilicifolius and A.ebracteatus,followed by chromosome doubling.This is the first report of a true-mangrove allopolyploid species that can reproduce sexually and clonally reproduction,which explains the long-term adaptive potential of the species.

Recent progress of hybrid cathode interface layer for organic solar cells

Organic solar cells(OSCs)have gained conspicuous progress during the past few decades due to the development of materials and upgrading of the device structure.The power conversion efficiency(PCE)of the single-junction device had surpassed 19%.The cathode interface layer(CIL),by optimizing the connection between the active layer and the cathode electrode,has become a momentous part to strengthen the performances of the OSCs.Simultaneously,CIL is also indispensable to illustrating the working mechanism of OSCs and enhancing the stability of the OSCs.In this essay,hybrid CILs in OSCs have been summarized.Firstly,the advancement and operating mechanism of OSCs,and the effects and relevant design rules of CIL are briefly concluded;secondly,the significant influence of CIL on enhancing the stability and PCE of OSCs is presented;thirdly,the characteristics of organic hybrid CIL and organic-inorganic hybrid CIL are introduced.Finally,the conclusion and outlook of CIL are summarized.

Deep genome skimming reveals the hybrid origin of Pseudosasa gracilis (Poaceae: Bambusoideae)

Pseudosasa gracilis(Poaceae:Bambusoideae)is a temperate woody bamboo species endemic to Southcentral China with a narrow distribution.Previous phylogenetic studies revealed an unexpected,isolated phylogenetic position of Ps.gracilis.Here we conducted phylogenomic analysis by sampling populations of Ps.gracilis and its sympatric species Ps.nanunica and Sinosasa polytricha reflecting different genomic signals,by deep genome skimming.Integrating molecular evidence from chloroplast genes and genome-wide SNPs,we deciphered the phylogenetic relationships of Ps.gracilis.Both plastid and nuclear data indicate that Ps.gracilis is more closely related to Sinosasa,which is discordant with the taxonomic treatment.To further explore this molecular-morphological conflict,we screened 411“perfect-copy”syntenic genes to reconstruct phylogenies using both the concatenation and coalescent methods.We observed extensive discordance between gene trees and the putative species tree.A significant hybridization event was detected based on 411 genes from the D subgenome,showing Ps.gracilis was a hybrid descendant between Sinosasa longiligulata and Ps.nanunica,with 63.56%and 36.44%inheritance probabilities of each parent.Moreover,introgression events were detected in the C subgenome between Ps.gracilis and S.polytricha in the same distribution region.Our findings suggest that sympatric hybridization and introgression play a crucial role in the origin of Ps.gracilis.By providing an empirical example of bamboo of hybrid origin using comprehensive analyses based on genomic data from different inheritance systems and morphological characters,our study represents a step forward in understanding of reticulate evolution of bamboos.

Transcriptomic and metabolomic analysis provides insights into lignin biosynthesis and accumulation and differences in lodging resistance in hybrid wheat

The use of hybrid wheat is one way to improve the yield in the future.However,greater plant heights increase lodging risk to some extent.In this study,two hybrid combinations with differences in lodging resistance were used to analyze the stem-related traits during the filling stage,and to investigate the mechanism of the difference in lodging resistance by analyzing lignin synthesis of the basal second internode(BSI).The stem-related traits such as the breaking strength,stem pole substantial degree(SPSD),and rind penetration strength(RPS),as well as the lignin content of the lodging-resistant combination(LRC),were significantly higher than those of the lodgingsensitive combination(LSC).The phenylpropanoid biosynthesis pathway was significantly and simultaneously enriched according to the transcriptomics and metabolomics analysis at the later filling stage.A total of 35 critical regulatory genes involved in the phenylpropanoid pathway were identified.Moreover,42%of the identified genes were significantly and differentially expressed at the later grain-filling stage between the two combinations,among which more than 80%were strongly up-regulated at that stage in the LRC compared with LSC.On the contrary,the LRC displayed lower contents of lignin intermediate metabolites than the LSC.These results suggested that the key to the lodging resistance formation of LRC is largely the higher lignin synthesis at the later grain-filling stage.Finally,breeding strategies for synergistically improving plant height and lodging resistance of hybrid wheat were put forward by comparing the LRC with the conventional wheat applied in large areas.

Hybrid Skin-Topological Effect Induced by Eight-Site Cells and Arbitrary Adjustment of the Localization of Topological Edge States

Hybrid skin-topological effect(HSTE)in non-Hermitian systems exhibits both the skin effect and topological protection,offering a novel mechanism for localization of topological edge states(TESs)in electrons,circuits,and photons.However,it remains unclear whether the HSTE can be realized in quasicrystals.

Efficient removal of U(VI) from wastewater by a sponge-like 3D porous architecture with hybrid electrospun nanofibers

Removal of uranium(VI)from nuclear wastewater is urgent due to the global nuclear energy exploitation.This study synthesized novel sponge-like 3D porous materials for enhanced uranium adsorption by combining electrospinning and fibrous freeze-shaping techniques.The materials possessed an organic-inorganic hybrid architecture based on the electrospun fibers of polyacrylonitrile(PAN)and SiO_(2).As a sup-porting material,the surface of fibrous SiO_(2) could be further functionalized by cyano groups via(3-cyanopropyl)triethoxysilane.All the cyano groups were turned into amidoxime(AO)groups to obtain a amidoxime-functionalized sponge(PAO/SiO_(2)-AO)through the subsequent ami-doximation process.The proposed sponge exhibited enhanced uranium adsorption performance with a high removal capacity of 367.12 mg/g,a large adsorption coefficient of 4.0×10^(4)mL/g,and a high removal efficiency of 97.59%.The UO_(2)^(2+)adsorption kinetics perfectly conformed to the pseudo-second-order reaction.The sorbent also exhibited an excellent selectivity for UO_(2)^(2+) with other interfering metal ions.2023 Hohai University.Production and hosting by Elsevier B.V.

Degradation and biocompatibility of one-step electrodeposited magnesium thioctic acid/magnesium hydroxide hybrid coatings on ZE21B alloys for cardiovascular stents

Constructing a functional hybrid coating appears to be a promising strategy for addressing the poor corrosion resistance and insufficient endothelialization of Mg-based stents.Nevertheless,the steps for preparing composite coatings are usually complicated and time-consuming.Herein,a novel composite coating,composed of bioactive magnesium thioctic acid(MTA)layer formed by deposition and corrosion-resistant magnesium hydroxide(Mg(OH)_(2))layer grown in situ,is simply fabricated on ZE21B alloys via one-step electrodeposition.Scanning electron microscopy(SEM)shows that the electrodeposited coating has a compact and uniform structure.And the high adhesion of the MTA/Mg(OH)_(2)hybrid coating is also confirmed by the micro-scratch test.Electrochemical test,scanning kelvin probe(SKP),and hydrogen evolution measurement indicate that the hybrid coating effectively reduces the degradation rate of Mg substrates.Haemocompatibility experiment and cell culture trial detect that the composite coating is of fine biocompatibility.Finally,the preparation mechanism of MTA/Mg(OH)_(2)hybrid coatings is discussed and proposed.This coating shows a great potential application for cardiovascular stents.

Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

Accurate soil moisture(SM)prediction is critical for understanding hydrological processes.Physics-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface processes.In addition to PB models,deep learning(DL)models have been widely used in SM predictions recently.However,few pure DL models have notably high success rates due to lacking physical information.Thus,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM predictions.To this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM predictions.The performances of the proposed hybrid models were investigated and compared with two existing hybrid models.The results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid models.Moreover,the ensemble model performed best among all hybrid models at all forecast time scales and different soil conditions.It is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day predictions.These findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

Cryptic diversity and rampant hybridization in annual gentians on the Qinghai-Tibet Plateau revealed by population genomic analysis

Understanding the evolutionary and ecological processes involved in population differentiation and speciation provides critical insights into biodiversity formation. In this study, we employed 29,865 single nucleotide polymorphisms(SNPs) and complete plastomes to examine genomic divergence and hybridization in Gentiana aristata, which is endemic to the Qinghai-Tibet Plateau(QTP) region. Genetic clustering revealed that G. aristata is characterized by geographic genetic structures with five clusters(West, East, Central, South and North). The West cluster has a specific morphological character(i.e., blue corolla) and higher values of FSTcompared to the remaining clusters, likely the result of the geological barrier formed by the Yangtze River. The West cluster diverged from the other clusters in the Early Pliocene;these remaining clusters diverged from one another in the Early Quaternary. Phylogenetic reconstructions based on SNPs and plastid data revealed substantial cyto-nuclear conflicts. Genetic clustering and D-statistics demonstrated rampant hybridization between the Central and North clusters,along the Bayankala Mountains, which form the geological barrier between the Central and North clusters. Species distribution modeling demonstrated the range of G. aristata expanded since the Last Interglacial period. Our findings provide genetic and morphological evidence of cryptic diversity in G. aristata, and identified rampant hybridization between genetic clusters along a geological barrier.These findings suggest that geological barriers and climatic fluctuations have an important role in triggering diversification as well as hybridization, indicating that cryptic diversity and hybridization are essential factors in biodiversity formation within the QTP region.

Study of hybrid nanofluid flow in a stationary cone-disk system with temperature-dependent fluid properties

Cone-disk systems find frequent use such as conical diffusers,medical devices,various rheometric,and viscosimetry applications.In this study,we investigate the three-dimensional flow of a water-based Ag-Mg O hybrid nanofluid in a static cone-disk system while considering temperature-dependent fluid properties.How the variable fluid properties affect the dynamics and heat transfer features is studied by Reynolds's linearized model for variable viscosity and Chiam's model for variable thermal conductivity.The single-phase nanofluid model is utilized to describe convective heat transfer in hybrid nanofluids,incorporating the experimental data.This model is developed as a coupled system of convective-diffusion equations,encompassing the conservation of momentum and the conservation of thermal energy,in conjunction with an incompressibility condition.A self-similar model is developed by the Lie-group scaling transformations,and the subsequent self-similar equations are then solved numerically.The influence of variable fluid parameters on both swirling and non-swirling flow cases is analyzed.Additionally,the Nusselt number for the disk surface is calculated.It is found that an increase in the temperature-dependent viscosity parameter enhances heat transfer characteristics in the static cone-disk system,while the thermal conductivity parameter has the opposite effect.

Coupling of Adhesion and Anti‑Freezing Properties in Hydrogel Electrolytes for Low‑Temperature Aqueous‑Based Hybrid Capacitors

Solid-state zinc-ion capacitors are emerging as promising candidates for large-scale energy storage owing to improved safety,mechanical and thermal stability and easy-to-direct stacking.Hydrogel electrolytes are appealing solid-state electrolytes because of eco-friendliness,high conductivity and intrinsic flexibility.However,the electrolyte/electrode interfacial contact and anti-freezing properties of current hydrogel electrolytes are still challenging for practical applications of zinc-ion capacitors.Here,we report a class of hydrogel electrolytes that couple high interfacial adhesion and anti-freezing performance.The synergy of tough hydrogel matrix and chemical anchorage enables a well-adhered interface between hydrogel electrolyte and electrode.Meanwhile,the cooperative solvation of ZnCl2 and LiCl hybrid salts renders the hydrogel electrolyte high ionic conductivity and mechanical elasticity simultaneously at low temperatures.More significantly,the Zn||carbon nanotubes hybrid capacitor based on this hydrogel electrolyte exhibits low-temperature capacitive performance,delivering high-energy density of 39 Wh kg^(-1)at-60°C with capacity retention of 98.7%over 10,000 cycles.With the benefits of the well-adhered electrolyte/electrode interface and the anti-freezing hydrogel electrolyte,the Zn/Li hybrid capacitor is able to accommodate dynamic deformations and function well under 1000 tension cycles even at-60°C.This work provides a powerful strategy for enabling stable operation of low-temperature zinc-ion capacitors.

Scale-space effect and scale hybridization in image intelligent recognition of geological discontinuities on rock slopes

Geological discontinuity(GD)plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses.Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data.Inspired by recent advances in computer vision,deep learning(DL)models have been widely utilized for image-based fracture identification.The multi-scale characteristics,image resolution and annotation quality of images will cause a scale-space effect(SSE)that makes features indistinguishable from noise,directly affecting the accuracy.However,this effect has not received adequate attention.Herein,we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques.Next,we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio(PSNR)and structural similarity(SSIM).Combining these metrics with the scale-space theory,we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition.It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models.In light of these observations,we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation.The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD.It also facilitates the objective understanding,description and analysis of the rock behavior and stability of slopes from the perspective of image data.

Hybrid modeling for carbon monoxide gas-phase catalytic coupling to synthesize dimethyl oxalate process

Ethylene glycol(EG)plays a pivotal role as a primary raw material in the polyester industry,and the syngas-to-EG route has become a significant technical route in production.The carbon monoxide(CO)gas-phase catalytic coupling to synthesize dimethyl oxalate(DMO)is a crucial process in the syngas-to-EG route,whereby the composition of the reactor outlet exerts influence on the ultimate quality of the EG product and the energy consumption during the subsequent separation process.However,measuring product quality in real time or establishing accurate dynamic mechanism models is challenging.To effectively model the DMO synthesis process,this study proposes a hybrid modeling strategy that integrates process mechanisms and data-driven approaches.The CO gas-phase catalytic coupling mechanism model is developed based on intrinsic kinetics and material balance,while a long short-term memory(LSTM)neural network is employed to predict the macroscopic reaction rate by leveraging temporal relationships derived from archived measurements.The proposed model is trained semi-supervised to accommodate limited-label data scenarios,leveraging historical data.By integrating these predictions with the mechanism model,the hybrid modeling approach provides reliable and interpretable forecasts of mass fractions.Empirical investigations unequivocally validate the superiority of the proposed hybrid modeling approach over conventional data-driven models(DDMs)and other hybrid modeling techniques.