A Deep Collocation Method for the Bending Analysis of Kirchhoff Plate

In this paper,a deep collocation method(DCM)for thin plate bending problems is proposed.This method takes advantage of computational graphs and backpropagation algorithms involved in deep learning.Besides,the proposed DCM is based on a feedforward deep neural network(DNN)and differs from most previous applications of deep learning for mechanical problems.First,batches of randomly distributed collocation points are initially generated inside the domain and along the boundaries.A loss function is built with the aim that the governing partial differential equations(PDEs)of Kirchhoff plate bending problems,and the boundary/initial conditions are minimised at those collocation points.A combination of optimizers is adopted in the backpropagation process to minimize the loss function so as to obtain the optimal hyperparameters.In Kirchhoff plate bending problems,the C^1 continuity requirement poses significant difficulties in traditional mesh-based methods.This can be solved by the proposed DCM,which uses a deep neural network to approximate the continuous transversal deflection,and is proved to be suitable to the bending analysis of Kirchhoff plate of various geometries.

Recent Advances in Space-Deployable Structures in China

Deployable space structure technology is an approach used in building spacecraft,especially when realizing deployment and folding functions.Once in orbit,the structures are released from the fairing,deployed,and positioned.With the development of communication,remote-sensing,and navigation satellites,space-deployable structures have become cutting-edge research topics in space science and technology.This paper summarizes the current research status and development trend of spacedeployable structures in China,including large space mesh antennas,space solar arrays,and deployable structures and mechanisms for deep-space exploration.Critical technologies of space-deployable structures are addressed from the perspectives of deployable mechanisms,cable-membrane form-finding,dynamic analysis,reliable environmental adaptability analysis,and validation.Finally,future technology developments and trends are elucidated in the fields of mesh antennas,solar arrays,deployable mechanisms,and on-orbit adjustment,assembly,and construction.

Silicalite-1 zeolite encapsulated Fe nanocatalyst for Fenton-like degradation of methylene blue

Encapsulation of Fe nanoparticles in zeolite is a promising way to significantly improve the catalytic activity and stability of Fe-based catalysts during the degradation process of organic pollutants.Herein,Fe nanocatalysts were encapsulated into silicalite-1(S-1)zeolite by using a ligand-protected method(with dicyandiamide(DCD)as a organic ligand)under direct hydrothermal synthesis condition.High-resolution transmission electron microscopy(HRTEM)results confirmed the high dispersion of Fe nanocatalysts which were successfully encapsulated within the voids among the primary particles of the S-1 zeolite.The developed S-1 zeolite encapsulated Fe nanocatalyst(Fe@S-1)exhibited significantly improved catalytic activity and reusability in the catalytic degradation process of methylene blue(MB).Specifically,the developed Fe0.021@S-1 catalyst showed high catalytic degradation activity,giving a high MB degradation efficiency of 100%in 30 min,outperformed the conventional impregnated catalyst(Fe/S-1).Moreover,the Fe@S-1 catalyst afforded an outstanding stability,showing only ca.7.9%activity loss after five cycling tests,while the Fe/S-1 catalyst presented a significantly activity loss of 50.9%after only three cycles.Notably,the encapsulation strategy enabled a relatively lower Fe loading in the Fe@S-1 catalyst in comparison with that of the Fe/S-1 catalyst,i.e.,0.35%vs.0.81%(mass).Radical scavenging experiments along with electron spin resonance(ESR)measurements confirmed that the major role of
OH in the MB degradation process.Specifically,Fe@S-1 catalyst with high molar ratio of[Fe(DCD)]Cl3 is beneficial to form Fe complexes/nanoclusters in the voids(which has large pore size of 1–2 nm)among the primary particles of the zeolite,and thus improving the diffusion and accessibility of reactants to Fe active sites,and thus exhibiting a relatively higher degradation efficiency.This work demonstrates that zeolite-encapsulated Fe nanocatalysts present potential applications in the advanced oxidation of wastewater treatment.

Elevated thyroid stimulating hormone levels are associated with metabolic syndrome in a Chinese community-based population of euthyroid people aged 40 years and older

This study investigated whether high-normal thyrotropin（TSH） levels are associated with metabolic syndrome in euthyroid Chinese people≥40 years old.Clinical and metabolic factors were assessed in 2,356 subjects（40-77 years old） with TSH levels in the normal range（0.35-5.00 mU/L）.Using 2.50 mU/L as the cut-off point of TSH level within the normal range,we divided subjects into the high-TSH（2.50-5.00 mU/L;n= 1,064） and low-TSH（0.35-2.50mU/L;n= 1,292） group.The results showed that the mean levels of body mass index（BMI）,total cholesterol（TC）,low density lipoprotein cholesterol（LDL-C）,and fasting plasma glucose（FPG） were higher in the high-TSH group and TSH levels were significantly positively con-elated with BMI,LDL-C,TC,and FPG.The prevalence of central obesity,hypertriglyceridemia,low high density lipoprotein cholesterol（HDL-C）,and high FPG（〉5.60 mmol/L） was significantly higher in females and subjects with high-TSH levels.Metabolic syndrome was also more prevalent in the high-TSH group.People over the age of 40 years with high-normal TSH levels had a 1.2-fold increased risk of metabolic syndrome,compared with those with low-normal TSII levels,after adjusting for age and gender.In conclusion,high normal TSH is a risk factor for metabolic syndrome in people ≥40 years old.

Research on Fault Repair Method of All-Optical Network Based on SDN

All-optical network,as a new backbone network,is featured with high speed and large capacity transmission.It may be out of order due to various faults while providing high-performance transmission service,thus more effective fault repairing methods are required.A routing and wavelength assignment method based on SDN is designed and analyzed from the perspective of service function chaining in this paper.A multi-objective integer linear programming model based on impairment-aware and scheduling time is constructed by combining the unified control of control plane with the resource allocation mode of service function virtualization.Meanwhile,an improved Firefly Algorithm is adopted to solve the model for obtaining a better scheduling scheme,so as to the resources are allocated on-demand in a more flexible and efficient way,which effectively improved the self-recovery capability of the network.In the simulation experiments,Through the comparison between the method proposed and methods based on centralization and distribution,method proposed in the paper is superior to the compared ones in the indexes of survivability,blocking probability,link recovery time,and presents a better scheduling performance,makes the system has stronger ability of self-healing in the face of failure.

农商银行负债质量现状与管理建议

近年来,随着金融脱媒的不断加速和新兴金融业态的不断涌现,商业银行负债业务复杂程度不断上升,管理难度不断加大。为应对负债管理压力,部分地区银行出现违规揽储等乱象,造成潜在金融风险集聚。农商银行相较于其他银行抵抗风险能力弱,又是服务三农的重要力量,因此对于农商银行负债质量现状的分析就具备重要的现实意义。本研究对18家业绩较好的农商银行负债质量的五个维度进行了分析。结果发现,头部农商银行负债稳定性较好,但负债结构单一、主动负债能力不足、负债与资产匹配不合理且负债成本较高。最后提出优化负债质量管理的针对性建议,以期为全体农商银行建立可持续的负债管理模式提供指导。

Shape Memory Polymer Composite Booms with Applications in Reel-Type Solar Arrays

Solar arrays are the primary energy source for spacecraft.Although traditional rigid solar arrays improve power supply,the quality increases proportionally.Hence,it is difficult to satisfy the requirements of high-power and low-cost space applications.In this study,a shape-memory polymer composite(SMPC)boom was designed,fabricated,and characterized for flexible reel-type solar arrays.The SMPC boom was fabricated from a smart material,a shape-memory polymer composite,whose mechanical properties were tested.Additionally,a mathematical model of the bending stiffness of the SMPC boom was developed,and the bending and buckling behaviors of the boom were further analyzed using the ABAQUS software.An SMPC boom was fabricated to demonstrate its shape memory characteristics,and the driving force of the booms with varying geometric parameters was investigated.We also designed and manufactured a reel-type solar array based on an SMPC boom and verified its self-deployment capability.The results indicated that the SMPC boom can be used as a deployable unit to roll out flexible solar arrays.

Accurate time synchronization of power reference station based on BD3 system

A Beidou 3(BD3)system-based power reference station can provide high-precision time synchronization for power distribution systems by sending synchronization data packets to devices in a multi-hop routing fashion.However,optimizing route selection to reduce both time synchronization error and delay is a challenging problem.In this paper,we establish a software-defined network-enabled power reference station time synchronization framework based on BD3.Then,we formulate the joint problem to minimize cumulative synchronization error and delay through multi-hop route selection optimization.A back propagation(BP)neural network-improved intelligent time synchronization route selection algorithm named BP-RS is proposed to learn the optimal route selection,which uses a BP neural network to dynamically adjust the exploration factor to achieve rapid convergence.Simulation results show the superior performance of BP-RS in synchronization delay,synchronization error,and adaptability with changing routing topologies.

Development of homozygous tetraploid potato and whole genome doubling-induced the enrichment of H3K27ac and potentially enhanced resistance to cold-induced sweetening in tubers

Polyploid plants typically display advantages on some agronomically important traits over their diploid counterparts.Extensive studies have shown genetic,transcriptomic,and epigenetic dynamics upon polyploidization in multiple plant species.However,few studies have unveiled those alternations imposed only by ploidy level,without any interference from heterozygosity.Cultivated potato is highly heterozygous.Thus,in this study,we developed two homozygous autotetraploid lines and one homozygous diploid line in parallel from a homozygous diploid potato.We confirmed their ploidy levels using chloroplast counting and karyotyping.Oligo-FISH and genome re-sequencing validated that these potato lines are nearly homozygous.We investigated variations in phenotypes,transcription,and histone modifications between two ploidies.Both autotetraploid lines produced larger but fewer tubers than the diploid line.Interestingly,each autotetraploid line displayed ploidy-related differential expression for various genes.We also discovered a genomewide enrichment of H3K27ac in genic regions upon whole-genome doubling(WGD).However,such enrichment was not associated with the differential gene expression between two ploidies.The tetraploid lines may exhibit better resistance to cold-induced sweetening(CIS)than the diploid line in tubers,potentially regulated through the expression of CIS-related key genes,which seems to be associated with the levels of H3K4me3 in cold-stored tubers.These findings will help to understand the impacts of autotetraploidization on dynamics of phenotypes,transcription,and histone modifications,as well as on CIS-related genes in response to cold storage.

A Research on Road and Bridge Detection Based on Test Detection Technology

The existence of karst cave at the bottom of bored piles has a great impact on projects under construction and the surrounding buildings.Since bored piles require slurry wall protection,the current geophysical exploration method cannot effectively detect the karst cave at the bottom of the piles in the slurry.Combined with the characteristics of stress wave propagation,the sonar detection method is proposed.JL sonar detector can realize the transmission and acquisition of on-site sonar signals.This method makes full use of the mud conditions of bored cast-in-place piles,and the development of karst caves can be tracked and detected within 10 meters at the pile bottom during the drilling process.It has several advantages,including low cost,high speed,and high precision.This paper verifies the application of sonar detection technology in practical engineering through specific engineering cases.The research results put forward a new solution for cave exploration in karst areas,especially in liquid environment.

Technical Analysis of Subgrade and Pavement Construction in Settlement Section of Municipal Road and Bridge Engineering

The construction of municipal roads and bridges is an important foundation for the smooth traveling and transportation.However,if there a reduction in the subgrade and pavement part,the safety and the comfort of the driver will be seriously affected,therefore,reasonable measures should be taken on time to tackle the related issues.The significance of subgrade and pavement construction in the subsidence section,the key points of the construction,and the appropriate control measures that are should be taken in the actual construction,was discussed in this paper.Further,this paper analyzes the availability of the subgrade and pavement construction technology for the municipal roads and bridges,to provide a reference for engineers.

An efficient stiffness analysis model based on shear deformation theory for flexible skin shear variable-sweep wing

Fixed-wing aircraft cannot maintain optimal aerodynamic performance at different flight speeds. As a type of morphing aircraft, the shear variable-sweep wing(SVSW) can dramatically improve its aerodynamic performance by altering its shape to adapt to various flight conditions.In order to achieve smooth continuous shear deformation, SVSW's skin adopts a flexible composite skin design instead of traditional aluminum alloy materials. However, this also brings about the non-linear difficulty in stiffness modeling and calculation. In this research, a new SVSW design and efficient stiffness modeling method are proposed. Based on shear deformation theory, the flexible composite skin is equivalently modeled as diagonally arranged nonlinear springs, simulating the elastic force interaction between the skin and the mechanism. By shear loading tests of flexible composite skin, the accuracy of this flexible composite skin modeling method is verified. The SVSW stiffness model was established, and its accuracy was verified through static loading tests. The effects of root connection, sweep angles, and flexible composite skin on the SVSW stiffness are analyzed. Finally, considering three typical flight conditions of SVSW: low-speed flow(Ma = 0.3,Re = 5.82 × 10^(6)), transonic flow(Ma = 0.9, Re = 3.44 × 10^(6)), and supersonic flow(Ma = 3,Re = 7.51 × 10^(6)), the stiffness characteristics of SVSW under flight conditions were evaluated.The calculated results guide the application of SVSW.

Imbalanced rock burst assessment using variational autoencoder-enhanced gradient boosting algorithms and explainability

We conducted a study to evaluate the potential and robustness of gradient boosting algorithms in rock burst assessment,established a variational autoencoder(VAE)to address the imbalance rock burst dataset,and proposed a multilevel explainable artificial intelligence(XAI)tailored for tree-based ensemble learning.We collected 537 data from real-world rock burst records and selected four critical features contributing to rock burst occurrences.Initially,we employed data visualization to gain insight into the data’s structure and performed correlation analysis to explore the data distribution and feature relationships.Then,we set up a VAE model to generate samples for the minority class due to the imbalanced class distribution.In conjunction with the VAE,we compared and evaluated six state-of-theart ensemble models,including gradient boosting algorithms and the classical logistic regression model,for rock burst prediction.The results indicated that gradient boosting algorithms outperformed the classical single models,and the VAE-classifier outperformed the original classifier,with the VAE-NGBoost model yielding the most favorable results.Compared to other resampling methods combined with NGBoost for imbalanced datasets,such as synthetic minority oversampling technique(SMOTE),SMOTE-edited nearest neighbours(SMOTE-ENN),and SMOTE-tomek links(SMOTE-Tomek),the VAE-NGBoost model yielded the best performance.Finally,we developed a multilevel XAI model using feature sensitivity analysis,Tree Shapley Additive exPlanations(Tree SHAP),and Anchor to provide an in-depth exploration of the decision-making mechanics of VAE-NGBoost,further enhancing the accountability of treebased ensemble models in predicting rock burst occurrences.

Interpretable gradient boosting based ensemble learning and African vultures optimization algorithm optimization for estimating deflection induced by excavation

Intelligent construction has become an inevitable trend in the development of the construction industry.In the excavation project,using machine learning methods for early warning can improve construction efficiency and quality and reduce the chances of damage in the excavation process.An interpretable gradient boosting based ensemble learning framework enhanced by the African Vultures Optimization Algorithm(AVOA)was proposed and evaluated in estimating the diaphragm wall deflections induced by excavation.We investigated and compared the performance of machine learning models in predicting deflections induced by excavation based on a database generated by finite element simulations.First,we exploratively analyzed these data to discover the relationship between features.We used several state-of-the-art intelligent models based on gradient boosting and several simple models for model selection.The hyperparameters for all models in evaluation are optimized using AVOA,and then the optimized models are assembled into a unified framework for fairness assessment.The comprehensive evaluation results show that the AVOA-CatBoost built in this paper performs well(RMSE=1.84,MAE=1.18,R2=0.9993)and cross-validation(RMSE=2.65±1.54,MAE=1.17±0.23,R2=0.998±0.002).In the end,in order to improve the transparency and usefulness of the model,we constructed an interpretable model from both global and local perspectives.

Surrounding rock classification from onsite images with deep transfer learning based on EfficientNet

This paper proposes an accurate,efficient and explainable method for the classification of the surrounding rock based on a convolutional neural network(CNN).The state-of-the-art robust CNN model(EfficientNet)is applied to tunnel wall image recognition.Gaussian filtering,data augmentation and other data pre-processing techniques are used to improve the data quality and quantity.Combined with transfer learning,the generality,accuracy and efficiency of the deep learning(DL)model are further improved,and finally we achieve 89.96%accuracy.Compared with other state-of-the-art CNN architectures,such as ResNet and Inception-ResNet-V2(IRV2),the presented deep transfer learning model is more stable,accurate and efficient.To reveal the rock classification mechanism of the proposed model,Gradient-weight Class Activation Map(Grad-CAM)visualizations are integrated into the model to enable its explainability and accountability.The developed deep transfer learning model has been applied to support the tunneling of the Xingyi City Bypass in the high mountain area of Guizhou,China,with great results.

采用两步优化器的深度配点法与深度能量法求解薄板弯曲问题

随着计算机技术的进步以及机器学习算法的进一步发展,深度学习方法逐渐被广泛应用于各行各业中.论文发展并比较了适应于工程计算的深度配点法与深度能量法并应用于求解薄板弯曲问题.深度配点法采用物理信息驱动的深度神经网络,通过将物理信息(偏微分方程强形式)引入到损失函数中,最终将求解薄板弯曲问题简化为优化问题.深度能量法则是采用系统总势能驱动的神经网络.根据最小势能原理,在所有的可能位移场中,真实位移场的总势能取最小值,因此我们可以使用总势能构造损失函数,从而求解薄板弯曲问题.对于边界条件,通过罚函数法将有约束最优化问题转化为求解无约束最优化问题.深度配点法与深度能量法的适用性基于神经网络的通用近似定理.由于物理信息跟总势能的引入,增加了神经网络训练的困难,为了解决这个问题,我们发展了两步优化器方法.数值结果表明,深度配点法与深度能量法很适合求解薄板弯曲问题,并且程序实现简单,实现了真正意义上的"无网格法".

Gene Network Analysis and Functional Studies of Senescence-associated Genes Reveal Novel Regulators of Arabidopsis Leaf Senescence

Plant leaf senescence has been recognized as the last phase of plant development, a highly ordered process regulated by genes known as senescence associated genes （SAGs）. However, the function of most of SAGs in regulating leaf senescence as well as regulators of those functionally known SAGs are still unclear. We have previously developed a curated database of genes potentially associated with leaf senescence, the Leaf Senescence Database （LSD）. In this study, we built gene networks to identify common regulators of leaf senescence in Arabidopsis thaliana using promoting or delaying senescence genes in LSD. Our results demonstrated that plant hormones cytokinin, auxin, nitric oxide as well as small molecules, such as Ca2＋, delay leaf senescence. By contrast, ethylene, ABA, SA and JA as well as small molecules, such as oxygen, promote leaf senescence, altogether supporting the idea that phytohormones play a critical role in regulating leaf senescence. Functional analysis of candidate SAGs in LSD revealed that a WRKY transcription factor WRKY75 and a Cys2/His2-type transcription factor AZF2 are positive regulators of leaf senescence and loss-of-function of WRKY75 or AZF2 delayed leaf senescence. We also found that silencing of a protein phosphatase, AtMKP2, promoted early senescence. Collectively, LSD can serve as a comprehensive resource for systematic study of the molecular mechanism of leaf senescence as well as offer candidate genes for functional analyses.

DELLA proteins interact with FLC to repress flowering transition

Flowering is a highly orchestrated and extremely ct critical process in a plant＇s life cycle. Previous study has ademonstrated that SUPPRESSOR OF OVEREXPRESSION OF pCONSTANS 1（SOC1） and FLOWERING LOCUS T（FT） integrate m^-1 the gibberellic acid（GA） signaling pathway and vernalization higpathway in regulating flowering time, but detailed molecular Hmechanisms remain largely unclear. In GA signaling pathway,DELLA proteins are a group of master transcriptional regulators, while in vernalization pathway FLOWERING LOCUS C（FLC） is a core transcriptional repressor that down-regulates the expression of SOC1 and FT. Here, we report that DELLA proteins interact with FLC in vitro and in vivo, and the LHRI domains of DELLAs and the C-terminus of MADS domain of FLC are required for these interactions.Phenotypic and gene expression analysis showed that mutation of FLC reduces while over-expression of FLC enhances the GA response in the flowering process. Further,DELLA-FLC interactions promote the repression ability of FLC on its target genes. In summary, these findings report that the interaction between MADS box transcription factor FLC and GRAS domain regulator DELLAs may integrate various signaling inputs in flowering time control, and shed new light on the regulatory mechanism both for FLC and DELLAs in regulating gene expression.

The RALF1-FERONIA Complex Phosphorylates eIF4E1 to Promote Protein Synthesis and Polar Root Hair Growth

The molecular links between extracellular signals and the regulation of localized protein synthesis in plant cells are poorly understood.Here,we show that in Arabidopsis thaliana,the extracellular peptide RALF1 and its receptor,the FERONIA receptor kinase,promote root hair(RH)tip growth by modulating protein synthesis.We found that RALF1 promotes FERONIA-mediated phosphorylation of elF4E1,a eukaryotic translation initiation factor that plays a crucial role in the control of mRNA translation rate.Phosphorylated elF4E1 increases mRNA affinity and modulates mRNA translation and,thus,protein synthesis.The mRNAs targeted by the RALF1-FERONIA-elF4E1 module include ROP2 and RSL4,which are important regulators of RH cell polarity and growth.RALF1 and FERONIA are expressed in a polar manner in RHs,which facilitate elF4E1 polar丨ocalization and thus may control local f?OP2 translation.Moreover,we demonstrated that high-level accumulation of RSL4 exerts negative-feedback regulation of RALF1 expression by directly binding the RALF1 gene promoter,determining the final RH size.Our study reveals that the link between RALF1-FERONIA signaling and protein synthesis constitutes a novel component regulating cell expansion in these polar growing cells.

Quantitative and Functional Phosphoproteomic Analysis Reveals that Ethylene Regulates Water Transport via the C-Terminal Phosphorylation of Aquaporin PIP2;1 in Arabidopsis

Ethylene participates in the regulation of numerous cellular events and biological processes, including wa- ter loss, during leaf and flower petal wilting. The diverse ethylene responses may be regulated via dynamic interplays between protein phosphorylation/dephosphorylation and ubiquitin/26S proteasome-mediated protein degradation and protease cleavage. To address how ethylene alters protein phosphorylation through multi-furcated signaling pathways, we performed a lSN stable isotope labelling-based, differential, and quantitative phosphoproteomics study on air- and ethylene-treated ethylene-insensitive Arabidopsis double loss-of-function mutant ein3-1/eill-1. Among 535 non-redundant phosphopeptides identified, two and four phosphopeptides were up- and downregulated by ethylene, respectively. Ethylene- regulated phosphorylation of aquaporin PIP2;1 is positively correlated with the water flux rate and water loss in leaf. Genetic studies in combination with quantitative proteomics, immunoblot analysis, protoplast swelling/shrinking experiments, and leaf water loss assays on the transgenic plants expressing both the wild-type and S280A/S283A-mutated PIP2;1 in the both Col-O and ein3eill genetic backgrounds suggest that ethylene increases water transport rate in Arabidopsis cells by enhancing S280/S283 phosphorylation at the C terminus of PIP2;1. Unknown kinase and/or phosphatase activities may participate in the initial up- regulation independent of the cellular functions of EIN3/EIL1. This finding contributes to our understanding of ethylene-regulated leaf wilting that is commonly observed during post-harvest storage of plant organs.