The Impact of the Digital Economy on Rural Residents’Working Hours:Mechanisms and Empirical Evidence

The rapid development of the digital economy has provided a new impetus for rural residents to extend their working hours.Based on the data collected by the China Labor-force Dynamics Survey(CLDS)in 2014,2016,and 2018,this paper measured the development level of the digital economy in China from the perspectives of internet development and digital financial inclusion,and tested the mechanisms of how the digital economy affected rural residents’working hours.The results showed that the digital economy extended rural residents’working hours by expanding information channels and enhancing human capital,and this mechanism was affected by heterogeneity in rural residents’educational background,age,and social capital.Building on these findings,this paper holds that to increase rural residents’income by extending their working hours and achieving common prosperity for all,it is necessary to expand the opportunities for rural residents to participate in skills training and promote their accumulation of human capital.

Unraveling the Fundamental Mechanism of Interface Conductive Network Influence on the Fast‑Charging Performance of SiO‑Based Anode for Lithium‑Ion Batteries

Progress in the fast charging of high-capacity silicon monoxide(SiO)-based anode is currently hindered by insufficient conductivity and notable volume expansion.The construction of an interface conductive network effectively addresses the aforementioned problems;however,the impact of its quality on lithium-ion transfer and structure durability is yet to be explored.Herein,the influence of an interface conductive network on ionic transport and mechanical stability under fast charging is explored for the first time.2D modeling simulation and Cryo-transmission electron microscopy precisely reveal the mitigation of interface polarization owing to a higher fraction of conductive inorganic species formation in bilayer solid electrolyte interphase is mainly responsible for a linear decrease in ionic diffusion energy barrier.Furthermore,atomic force microscopy and Raman shift exhibit substantial stress dissipation generated by a complete conductive network,which is critical to the linear reduction of electrode residual stress.This study provides insights into the rational design of optimized interface SiO-based anodes with reinforced fast-charging performance.

The action mechanism of the work done by the electric field force on moving charges to stimulate the emergence of carrier generation/recombination in a PN junction

It is discovered that the product of the current and the electric field in a PN junction should be regarded as the rate of work(power)done by the electric field force on moving charges(hole current and electron current),which was previously misinterpreted as solely a Joule heating effect.We clarify that it is exactly the work done by the electric field force on the moving charges to stimulate the emergence of non-equilibrium carriers,which triggers the novel physical phenomena.As regards to Joule heat,we point out that it should be calculated from Ohm’s law,rather than simply from the product of the current and the electric field.Based on this understanding,we conduct thorough discussion on the role of the electric field force in the process of carrier recombination and carrier generation.The thermal effects of carrier recombination and carrier generation followed are incorporated into the thermal equation of energy.The present study shows that the exothermic effect of carrier recombination leads to a temperature rise at the PN interface,while the endothermic effect of carrier generation causes a temperature reduction at the interface.These two opposite effects cause opposite heat flow directions in the PN junction under forward and backward bias voltages,highlighting the significance of managing device heating phenomena in design considerations.Therefore,this study possesses referential significance for the design and tuning on the performance of piezotronic devices.

A Deformable Network with Attention Mechanism for Retinal Vessel Segmentation

The intensive application of deep learning in medical image processing has facilitated the advancement of automatic retinal vessel segmentation research.To overcome the limitation that traditional U-shaped vessel segmentation networks fail to extract features in fundus image sufficiently,we propose a novel network(DSeU-net)based on deformable convolution and squeeze excitation residual module.The deformable convolution is utilized to dynamically adjust the receptive field for the feature extraction of retinal vessel.And the squeeze excitation residual module is used to scale the weights of the low-level features so that the network learns the complex relationships of the different feature layers efficiently.We validate the DSeU-net on three public retinal vessel segmentation datasets including DRIVE,CHASEDB1,and STARE,and the experimental results demonstrate the satisfactory segmentation performance of the network.

Quantum generative adversarial networks based on a readout error mitigation method with fault tolerant mechanism

Readout errors caused by measurement noise are a significant source of errors in quantum circuits,which severely affect the output results and are an urgent problem to be solved in noisy-intermediate scale quantum(NISQ)computing.In this paper,we use the bit-flip averaging(BFA)method to mitigate frequent readout errors in quantum generative adversarial networks(QGAN)for image generation,which simplifies the response matrix structure by averaging the qubits for each random bit-flip in advance,successfully solving problems with high cost of measurement for traditional error mitigation methods.Our experiments were simulated in Qiskit using the handwritten digit image recognition dataset under the BFA-based method,the Kullback-Leibler(KL)divergence of the generated images converges to 0.04,0.05,and 0.1 for readout error probabilities of p=0.01,p=0.05,and p=0.1,respectively.Additionally,by evaluating the fidelity of the quantum states representing the images,we observe average fidelity values of 0.97,0.96,and 0.95 for the three readout error probabilities,respectively.These results demonstrate the robustness of the model in mitigating readout errors and provide a highly fault tolerant mechanism for image generation models.

A Tabletop Nano-CT Image Noise Reduction Network Based on 3-Dimensional Axial Attention Mechanism

Nano-computed tomography(Nano-CT)is an emerging,high-resolution imaging technique.However,due to their low-light properties,tabletop Nano-CT has to be scanned under long exposure conditions,which the scanning process is time-consuming.For 3D reconstruction data,this paper proposed a lightweight 3D noise reduction method for desktop-level Nano-CT called AAD-ResNet(Axial Attention DeNoise ResNet).The network is framed by theU-net structure.The encoder and decoder are incorporated with the proposed 3D axial attention mechanism and residual dense block.Each layer of the residual dense block can directly access the features of the previous layer,which reduces the redundancy of parameters and improves the efficiency of network training.The 3D axial attention mechanism enhances the correlation between 3D information in the training process and captures the long-distance dependence.It can improve the noise reduction effect and avoid the loss of image structure details.Experimental results show that the network can effectively improve the image quality of a 0.1-s exposure scan to a level close to a 3-s exposure,significantly shortening the sample scanning time.

Study on the Mechanism of Action of Glyasperin A in the Treatment of Atherosclerosis Based on Network Pharmacology and Molecular Docking

[Objectives] This study was conducted to investigate the mechanism of action of glyasperin A in the treatment of atherosclerosis using a network pharmacology approach. [Methods] Targets related to atherosclerosis were searched in GeneCards database. An active ingredient-disease-target network was constructed by Cytoscape 3.7.1. A target protein interaction network was constructed by String database. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the DAVID database. [Results] Glyasperin A acted on 36 atherosclerosis-related targets, and the biofunctional and pathway enrichment analyses showed that it was mainly involved in response to xenobiotic stimulus, drug transport across blood-brain barrier, lipid oxidation, barrier, and lipid oxidation, etc. The results showed that glyasperin A acted on 36 atherosclerosis-related targets. The biofunctional and pathway enrichment analyses showed that it was mainly involved in response to xenobiotic stimulus, drug transport across blood-brain barrier, lipid oxidation, positive regulation of protein localization to nucleus, and hepoxilin biosynthetic process, and it played an anti-fatigue role through signal pathways such as serotonergic synapse, efferocytosis, arachidonic acid metabolism, chemical carcinogenesis-receptor activation and platelet activation. [Conclusions] Glyasperin A has multi-target and multi-pathway effects in the treatment of atherosclerosis. This study provides reference for further research on glyasperin A in the treatment of atherosclerosis.

Preparation of Ephedra houttuynia Granule and Its Therapeutic Mechanism of Anti-Mycoplasma gallisepticum Infection Based on Network Pharmacology

The use of Chinese herbal medicines can replace antibiotics that cause drug-resistance problems,which are currently necessary for disease control.In this paper,a traditional Chinese medicine compound named Ephedra houttuynia granule for the treatment of Mycoplasma galliscepticum(MG)infection was prepared.Furthermore,its action mechanism was explored through network pharmacology.The optimal extraction and granulation processes of the compound were determined by high performance liquid chromatography(HPLC)method and L9 orthogonal test,and in the treatment experiment,Ephedra houttuynia granule showed a significant therapeutic effect on MG infection.In the study of network pharmacology,the results showed that the core targets of Ephedra houttuynia granule against MG infection were vascular endothelial growth factor(VEGFA),fos proto-oncogene(FOS),prepro-coagulation factor II(F2),etc.,the gene ontology/kyoto encyclopedia of genes and genomes(GO/KEGG)analysis results indicated that the signaling pathways of neuroactive ligand receptor interaction,cAMP,IL-17,T cell receptor,and tumor necrosis factor(TNF)might involve in anti-MG infection.In conclusion,this study would provide a new idea for elucidating the action mechanism of other diseases in veterinary clinic,which had a certain guiding significance.

Exploring the molecular mechanism of Baoyuan decoction in the treatment of lung cancer based on network pharmacology and molecular docking

Background:Baoyuan decoction is used clinically as an adjuvant treatment for lung cancer.However,the underlying mechanism remains unclear.Therefore,this study aimed to explore the mechanism of action of Baoyuan decoction in lung cancer treatment using network pharmacology and molecular docking technology.Methods:The Traditional Chinese Medicines Systems Pharmacology Database and Analysis Platform and SwissTargetPrediction databases were used to screen the active ingredients of Baoyuan decoction and their relevant targets.Lung cancer-related targets were obtained from the GeneCards,Online Mendelian Inheritance in Man,and DrugBank databases.Protein-protein interaction network of the common targets was constructed using the STRING database and analyzed using Cytoscape software 3.10.1.Furthermore,Gene Ontology enrichment,Kyoto Encyclopedia of Genes and Genomes pathway analyses and visualization of common genes were performed using the R software.Finally,molecular docking of the selected key ingredients and targets was performed,and the results were verified using AutoDock Vina software.Results:We identified 142 potential active ingredients,3624 potential lung cancer-related targets,and 341 common drug targets.A total of 72 core targets were identified,of which AKT1,TP53,interleukin-6,epithelial growth factor receptor,and signal transducer and activator of transcription 3 were key.A total of 4116 items were obtained via Gene Ontology enrichment analyses.Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed 189 related signaling pathways,including the PI3K-Akt,AGE-RAGE signaling pathways in diabetic complications,FOXO,and TH signaling pathways,which are involved in cell proliferation,autophagy,metastasis,invasion,radiation resistance,and chemotherapy resistance in the lung cancer microenvironment.The molecular docking results suggested that the key ingredients had a strong affinity for key targets.Conclusion:This study demonstrates that Baoyuan decoction plays a key therapeutic role in a complex manner involving multiple ingredients,targets,and pathways in lung cancer.Our findings are anticipated to provide new ideas for follow-up experimental research and clinical application.

Hybrid model for BOF oxygen blowing time prediction based on oxygen balance mechanism and deep neural network

The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.

New Rural Community Construction or Retention Development:A Comparative Analysis of Rural Settlement Transition Mechanism in Plain Agriculture Area of China Based on Actor Network Theory

It is an important way to realize rural revitalization and sustainable development to guide rural settlement transition(RST)in an appropriate way.This paper uses actor network theory(ANT)to construct a theoretical framework for the study of RST.Taking two typical villages with different transition paths in rural areas of North China Plain as examples,this paper reveals the mechanism of RST and makes a comparative analysis.The results show that:1)after identifying problems and obligatory passage point,key actors recruit heterogeneous actors into the actor network by entrusting them with common interests,and realize RST under the system operation.2)Rural settlements under different transition paths have similarities in the problems to be solved,collective actions and policy factors,but there are differences in the transition process,mechanism and effect.The actor network and mechanism of RST through the path of new rural community construction are more complex and the transition effect is more thorough.In contrast,the degree of RST of retention development path is limited if there is no resource and location advantage.3)Based on the applicable conditions of different paths,this paper designs a logical framework of‘Situation-Structure-Behavior-Result’to scientifically guide the identification of RST paths under the background of rural revitalization.

Exploring the mechanism of active ingredients of Smilacis Glabrae Rhizoma in treating migraine headache through network pharmacology and animal experiments

Background:To explore the potential mechanism of action of the active ingredients of Smilacis Glabrae Rhizoma(SGR)in the treatment of migraine using network pharmacology and in vivo experiments.Methods:Through the search of Traditional Chinese Medicines Systems Pharmacology Database and Analysis Platform,Genecards,Drugbank and other databases,we obtained active ingredients,targets of SGR and related disease targets of migraine,and took the intersection for protein-protein interactions analysis.After constructing the network diagram,network topology analysis was performed to derive the core targets and key active ingredients,and Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed.Finally,molecular docking was performed and validated by in vivo experiments.In vivo experiments,18 male BALB/c mice were selected,and the SGR group was fed with SGR drinking tablet concentrate,and nitroglycerin injection was used to construct a mouse model of migraine.Enzyme-linked immunosorbent assay test was used to detect the levels of TNF-α,IL-1β,IL-6,and AKT1 in plasma.Results:The results showed that the core targets of SGR for the treatment of migraine were TNF-α,IL-1β,IL-6,and AKT1.These core targets and key active ingredients had better binding ability.Compared with the blank group,the number of head scratching in the model group increased.Compared with the model group,there was a significant reduction of the number of head scratching in the SGR group.In comparison with the blank group,the protein level in the plasma in the model group was markedly higher.Compared with the model group,the protein level in the SGR group was significantly lower.Conclusion:SGR has the characteristics of improving migraine based on multi-targets,multi-components and multi-pathways,and the mechanism of action may be related to the inhibition of the release of inflammatory factors,neuron protection,and interference with apoptosis and other processes.

Based on network pharmacology,molecular docking and experimental validation to reveal the potential molecular mechanism of quercetin for the treatment of diarrheal irritable bowel syndrome

Objective:To explore the potential mechanism of action of quercetin in the treatment of diarrhea irritable bowel syndrome(IBS-D).Methods:The potential targets of quercetin were obtained from the TCMSP,SwissTar-getPrediction,and BATMAN-TCM databases.The targets of IBS-D were obtained by searching the GeneCards database with"diarrhea irritable bowel syndrome"as the keyword,and the targets of quercetin and IBS-D were intersected.The PPI network was constructed by Cytoscape 3.7.1 software.The intersected targets were imported into the DAVID database for GO functional analysis and KEGG pathway enrichment analysis.The binding ability of quercetin to the core targets was observed using molecular docking.Based on this,we established an IBS-D rat model,administered quercetin for intervention,and experimentally validated the network pharmacology prediction results by HE staining and ELISA assay.Results:Network pharmacology analysis showed that TP53,TNF-α,AKT1,VEGF-A,IL-6 factors and MAPK,PI3K-Akt signaling pathway as the core targets and pathways of quercetin for the treatment of IBS-D.The results of animal experiments revealed that quercetin could inhibit the secretion of TP53,TNF-α,AKT1,VEGF-A,IL-1βand IL-6,reduce the inflammatory response and improve IBS-D.Conclusion:Quercetin could protect colon tissue by regulating the expression of TP53,TNF-α,AKT1,VEGF-A,IL-1βand IL-6,thereby treating IBS-D.

Multiscale Characteristics and Connection Mechanisms of Attraction Networks:A Trajectory Data Mining Approach Leveraging Geotagged Data

Urban tourism is considered a complex system,and multiscale exploration of the organizational patterns of attraction networks has become a topical issue in urban tourism,so exploring the multiscale characteristics and connection mechanisms of attraction networks is important for understanding the linkages between attractions and even the future destination planning.This paper uses geotagging data to compare the links between attractions in Beijing,China during four different periods:the pre-Olympic period(2004–2007),the Olympic Games and subsequent‘heat period’(2008–2013),the post-Olympic period(2014–2019),and the COVID-19(Corona Virus Disease 2019)pandemic period(2020–2021).The aim is to better understand the evolution and patterns of attraction networks at different scales in Beijing and to provide insights for tourism planning in the destination.The results show that the macro,meso-,and microscales network characteristics of attraction networks have inherent logical relationships that can explain the commonalities and differences in the development process of tourism networks.The macroscale attraction network degree Matthew effect is significant in the four different periods and exhibits a morphological monocentric structure,suggesting that new entrants are more likely to be associated with attractions that already have high value.The mesoscale links attractions according to the common purpose of tourists,and the results of the community segmentation of the attraction networks in the four different periods suggest that the functional polycentric structure describes their clustering effect,and the weak links between clusters result from attractions bound by incomplete information and distance,and the functional polycentric structure with a generally more efficient network of clusters.The pattern structure at the microscale reveals the topological transformation relationship of the regional collaboration pattern,and the attraction network structure in the four different periods has a very similar importance profile structure suggesting that the attraction network has the same construction rules and evolution mechanism,which aids in understanding the attraction network pattern at both macro and micro scales.Important approaches and practical implications for planners and managers are presented.

Integrated data mining and network pharmacology to discover a novel traditional Chinese medicine prescription against diabetic retinopathy and reveal its mechanism

Background:Diabetic retinopathy(DR)is currently the leading cause of blindness in elderly individuals with diabetes.Traditional Chinese medicine(TCM)prescriptions have shown remarkable effectiveness for treating DR.This study aimed to screen a novel TCM prescription against DR from patents and elucidate its medication rule and molecular mechanism using data mining,network pharmacology,molecular docking and molecular dynamics(MD)simulation.Method:TCM prescriptions for treating DR was collected from patents and a novel TCM prescription was identified using data mining.Subsequently,the mechanism of the novel TCM prescription against DR was explored by constructing a network of core TCMs-core active ingredients-core targets-core pathways.Finally,molecular docking and MD simulation were employed to validate the findings from network pharmacology.Result:The TCMs of the collected prescriptions primarily possessed bitter and cold properties with heat-clearing and supplementing effects,attributed to the liver,lung and kidney channels.Notably,a novel TCM prescription for treating DR was identified,composed of Lycii Fructus,Chrysanthemi Flos,Astragali Radix and Angelicae Sinensis Radix.Twenty core active ingredients and ten core targets of the novel TCM prescription for treating DR were screened.Moreover,the novel TCM prescription played a crucial role for treating DR by inhibiting inflammatory response,oxidative stress,retinal pigment epithelium cell apoptosis and retinal neovascularization through various pathways,such as the AGE-RAGE signaling pathway in diabetic complications and the MAPK signaling pathway.Finally,molecular docking and MD simulation demonstrated that almost all core active ingredients exhibited satisfactory binding energies to core targets.Conclusions:This study identified a novel TCM prescription and unveiled its multi-component,multi-target and multi-pathway characteristics for treating DR.These findings provide a scientific basis and novel insights into the development of drugs for DR prevention and treatment.

Study on the mechanism of SND in the treatment of anxiety disorders based on network pharmacology, molecular docking and experiment validation

Background:Sini decoction(SND)is a classic traditional Chinese medicine(TCM)formulation that can be used to treat anxiety-related disorders,but the active substance and underlying molecular mechanism of its anxiolytic effects are unknown.In this study,network pharmacology,molecular docking research and experimental verification methods were used to preliminarily explore the bioactive compounds and potential target mechanisms of SND anxiolytic.Methods:The active components and corresponding targets of SND were collected by TCMSP.GeneCards,OMIM,PharmGkb,TTD and Drugbank were used to search for the targets of anxiety disorders.The core target of SND in the treatment of anxiety was screened by PPI.R language was used to analyze the intersection targets of SND in the treatment of anxiety disorders by GO and KEGG enrichment analysis.AutoDock Vina was used for molecular docking,and Discovery Studio was used for visual conformation analysis after docking.The anti-anxiety effect and molecular mechanism of SND were studied by in vivo experiment.Results:Based on network pharmacological analysis,we obtained 112 active ingredients and 350 effective targets related to anxiety from SND.In PPI analysis,26 targets such as STAT3,MAPK3,MAPK1,MAPK14,SRC,HSP90AA1,TP53 and PIK3CA were identified as core targets.GO and KEGG analysis showed that the anxiolytic mechanism of SND may be related to the neuroactive ligand-receptor interaction pathway and inflammatory pathway.Molecular docking showed that quercetin,naringenin,licochalcone A had high affinity with JAK2,MAPK14 and MAPK3.Animal experiments have shown that SND reverses the upregulation of GluN2B(NMDAR)and GluA1(AMPAR)proteins,and SND improves anxiety disorders by regulating glutamate transmitter levels,which may be related to neuroactive ligand-receptor interaction pathways,particularly glutamate receptors.Conclusion:This study shows that SND can improve FS-induced behavioral changes in mice and can modulate hippocampal synapse-associated protein defects,partially reversing glutamate receptor expression through the neuroactive ligand-receptor interaction pathway,and further improved anxiety disorders.At the same time,combined with network pharmacology and molecular docking,the key components,core targets and related pathways of SND are discussed,which shows that the active components of SND play an effective role in anxiety through multi-targets and multi-pathways,which provides a reference for the material basis and mechanism of SND.

Exploring the mechanism of action of herb pair Pinellia Ternata-Magnolia Officinalis in the treatment of liver cancer based on network pharmacology and molecular docking

Background:Explore the anti-tumor mechanism of herb pair Pinellia ternate-Magnolia officinalis(BX-HP)in liver cancer through network pharmacology using molecular docking methods.Method:The active ingredients and corresponding targets of the herb pair Pinellia ternate-Magnolia officinalis were obtained from the HERB database.The relevant targets for liver cancer were obtained from GeneCards,DisGeNET,TTD,and Drugbank databases.Obtain common targets between herb pair Pinellia ternate-Magnolia officinalis and liver cancer through the Bioinformatics platform,establish a PPI network diagram using STRING software,and perform GO functional enrichment and KEGG pathway enrichment analysis on the DAVID platform.AutoDockTools 1.5.7 software and molecular dynamics simulation analysis are used to evaluate the binding of components to target proteins.HERB database,SwissTargetPrediction database,SwissADME database,UniProt database,GeneCards database,TTD database,DRUGBANK database,DisGeNET database,String,DAVID.Bioinformatics platform,PDB database,PubChem and TCMSP database.Result:A total of 22 active ingredients with a Probability>0.1 targets in Magnolia officinalis were screened,26 active ingredients with a Probability>0.1 targets in Pinellia ternata,ten vital active ingredients,corresponding to 979 and 803 targets with a Probability>0.1 targets,2536 liver cancer-related targets,and 279 targets in the herb pair Pinellia ternata-Magnolia officinalis.The GO functional enrichment analysis resulted in 1297 entries,namely 971 biological process entries,118 cell localization entries,and 208 molecular function entries.Three signaling pathways were annotated through the KEGG pathway.Based on molecular docking,ten vital active ingredients and five target proteins were validated to exhibit an excellent binding affinity.The above data indicates that combining the herb pair Pinellia ternata-Magnolia officinalis may treat liver cancer through specific targets and signaling pathways.Conclusion:Herb pair Pinellia ternata-Magnolia officinalis has a synergistic effect on treating liver cancer through multicomponent,multitarget,and multi-pathway approaches.This study provides a sufficient theoretical basis for subsequent research.

Configuration Synthesis and Lightweight Networking of Deployable Mechanism Based on a Novel Pyramid Module

Deployable mechanism with preferable deployable performance,strong expansibility,and lightweight has attracted much attention because of their potential in aerospace.A basic deployable pyramid unit with good deployability and expandability is proposed to construct a sizeable deployable mechanism.Firstly,the basic unit folding principle and expansion method is proposed.The configuration synthesis method of adding constraint chains of spatial closed-loop mechanism is used to synthesize the basic unit.Then,the degree of freedom of the basic unit is analyzed using the screw theory and the link dismantling method.Next,the three-dimensional models of the pyramid unit,expansion unit,and array unit are established,and the folding motion simulation analysis is carried out.Based on the number of components,weight reduction rate,and deployable rate,the performance characteristics of the three types of mechanisms are described in detail.Finally,prototypes of the pyramid unit,combination unit,and expansion unit are developed to verify further the correctness of the configuration synthesis based on the pyramid.The proposed deployable mechanism provides aference for the design and application of antennas with a large aperture,high deployable rate,and lightweight.It has a good application prospect in the aerospace field.

The underlying mechanism of variety–water–nitrogen–stubble damage interactions on yield formation in ratoon rice with low stubble height under mechanized harvesting

Agronomic measures are the key to promote the sustainable development of ratoon rice by reducing the damage from mechanical crushing to the residual stubble of the main crop, thereby mitigating the impact on axillary bud sprouting and yield formation in ratoon rice. This study used widely recommended conventional rice Jiafuzhan and hybrid rice Yongyou 2640 as the test materials to conduct a four-factor block design field experiment in a greenhouse of the experimental farm of Fujian Agricultural and Forestry University, China from 2018 to 2019.The treatments included fertilization and no fertilization, alternate wetting and drying irrigation and continuous water flooding irrigation, and plots with and without artificial crushing damage on the rice stubble. At the same time, a 13C stable isotope in-situ detection technology was used to fertilize the pot experiment. The results showed significant interactions among varieties, water management, nitrogen application and stubble status.Relative to the long-term water flooding treatment, the treatment with sequential application of nitrogen fertilizer coupled with moderate field drought for root-vigor and tiller promotion before and after harvesting of the main crop, significantly improved the effective tillers from low position nodes. This in turn increased the effective panicles per plant and grains per panicle by reducing the influence of artificial crushing damage on rice stubble and achieving a high yield of the regenerated rice. Furthermore, the partitioning of 13C assimilates to the residual stubble and its axillary buds were significantly improved at the mature stage of the main crop, while the translocation rate to roots and rhizosphere soil was reduced at the later growth stage of ratooning season rice. This was triggered by the metabolism of hormones and polyamines at the stem base regulated by the interaction of water and fertilizer at this time. We therefore suggest that to achieve a high yield of ratoon rice with low stubble height under mechanized harvesting, the timely application of nitrogen fertilizer is fundamental,coupled with moderate field drying for root-vigor preservation and tiller promotion before and after the mechanical harvesting of the main crop.

Regeneration of the heart:f rom molecular mechanisms to clinical therapeutics

Heart injury such as myocardial infarction leads to cardiomyocyte loss,fibrotic tissue deposition,and scar formation.These changes reduce cardiac contractility,resulting in heart failure,which causes a huge public health burden.Military personnel,compared with civilians,is exposed to more stress,a risk factor for heart diseases,making cardiovascular health management and treatment innovation an important topic for military medicine.So far,medical intervention can slow down cardiovascular disease progression,but not yet induce heart regeneration.In the past decades,studies have focused on mechanisms underlying the regenerative capability of the heart and applicable approaches to reverse heart injury.Insights have emerged from studies in animal models and early clinical trials.Clinical interventions show the potential to reduce scar formation and enhance cardiomyocyte proliferation that counteracts the pathogenesis of heart disease.In this review,we discuss the signaling events controlling the regeneration of heart tissue and summarize current therapeutic approaches to promote heart regeneration after injury.