The lunar surface and its deep layers contain abundant resources and valuable information resources,the exploration and exploitation of which are important for the sustainable development of the human economy and soci...The lunar surface and its deep layers contain abundant resources and valuable information resources,the exploration and exploitation of which are important for the sustainable development of the human economy and society.Technological exploration and research in the field of deep space science,especially lunar-based exploration,is a scientific strategy that has been pursued in China and worldwide.Drilling and sampling are key to accurate exploration of the desirable characteristics of deep lunar resources.In this study,an in-situ condition preserved coring(ICP-Coring)and analysis system,which can be used to test drilling tools and develop effective sampling strategies,was designed.The key features of the system include:(1)capability to replicate the extreme temperature fluctuations of the lunar environment(-185 to 200℃)with intelligent temperature control;(2)ability to maintain a vacuum environment at a scale of 10^(-3) Pa,both under unloaded conditions within Ф580 mm×1000 mm test chamber,and under loaded conditions using Ф400 mm×800 mm lunar rock simulant;(3)application of axial pressures up to 4 MPa and confining pressures up to 3.5 MPa;(4)sample rotation at any angle with a maximum sampling length of 800 mm;and(5)multiple modes of rotary-percussive drilling,controlled by penetration speed and weight on bit(WOB).Experimental studies on the drilling characteristics in the lunar rock simulant-loaded state under different drill bit-percussive-vacuum environment configurations were conducted.The results show that the outgassing rate of the lunar soil simulant is greater than that of the lunar rock simulant and that a low-temperature environment contributes to a reduced vacuum of the lunar-based simulated environment.The rotary-percussive drilling method effectively shortens the sampling time.With increasing sampling depth,the temperature rise of the drilling tools tends to rapidly increase,followed by slow growth or steady fluctuations.The temperature rise energy accumulation of the drill bits under vacuum is more significant than that under atmospheric pressure,approximately 1.47 times higher.The real-time monitored drilling pressure,penetration speed and rotary torque during drilling serve as parameters for discriminating the drilling status.The results of this research can provide a scientific basis for returning samples from lunar rock in extreme lunar-based environments.展开更多
An improved understanding of biodiversity-productivity relationships(BPRs)along environmental gradients is crucial for effective ecosystem management and biodiversity conservation.The stress-gradient hypothesis sugges...An improved understanding of biodiversity-productivity relationships(BPRs)along environmental gradients is crucial for effective ecosystem management and biodiversity conservation.The stress-gradient hypothesis suggests that BPRs are stronger in stressful environments compared to more favorable conditions.However,there is limited knowledge regarding the variation of BPRs along elevational gradients and their generality across different landscapes.To study how BPRs change with elevation,we harnessed inventory data on 6,431 trees from152 plots surveyed twice in eight to ten year intervals in mountain forests of temperate Europe and subtropical Asia.We quantified the relationship between aboveground productivity and different biodiversity measures,including taxonomic,functional,and phylogenetic diversity.To elucidate the processes underlying BPRs,we studied the variation of different functional traits along elevation across landscapes.We found no general pattern of BPRs across landscapes and elevations.Relationships were neutral for all biodiversity measures in temperate forests,and negative for taxonomic and functional diversity in subtropical forests.BPRs were largely congruent between taxonomic,functional and phylogenetic diversity.We found only weak support for the stress-gradient hypothesis,with BPRs turning from negative to positive(effect not significant)close to the tree line in subtropical forests.In temperate forests,however,elevation patterns were strongly modulated by species identity effects as influenced by specific traits.The effect of traits such as community-weighted mean of maximum plant height and wood density on productivity was congruent across landscapes.Our study highlights the context-dependence of BPRs across elevation gradients and landscapes.Species traits are key modulating factors of BPRs and should be considered more explicitly in studies of the functional role of biodiversity.Furthermore,our findings highlight that potential trade-offs between conserving biodiversity and fostering ecosystem productivity exist,which require more attention in policy and management.展开更多
Rapid and accurate acquisition of soil organic matter(SOM)information in cultivated land is important for sustainable agricultural development and carbon balance management.This study proposed a novel approach to pred...Rapid and accurate acquisition of soil organic matter(SOM)information in cultivated land is important for sustainable agricultural development and carbon balance management.This study proposed a novel approach to predict SOM with high accuracy using multiyear synthetic remote sensing variables on a monthly scale.We obtained 12 monthly synthetic Sentinel-2 images covering the study area from 2016 to 2021 through the Google Earth Engine(GEE)platform,and reflectance bands and vegetation indices were extracted from these composite images.Then the random forest(RF),support vector machine(SVM)and gradient boosting regression tree(GBRT)models were tested to investigate the difference in SOM prediction accuracy under different combinations of monthly synthetic variables.Results showed that firstly,all monthly synthetic spectral bands of Sentinel-2 showed a significant correlation with SOM(P<0.05)for the months of January,March,April,October,and November.Secondly,in terms of single-monthly composite variables,the prediction accuracy was relatively poor,with the highest R^(2)value of 0.36 being observed in January.When monthly synthetic environmental variables were grouped in accordance with the four quarters of the year,the first quarter and the fourth quarter showed good performance,and any combination of three quarters was similar in estimation accuracy.The overall best performance was observed when all monthly synthetic variables were incorporated into the models.Thirdly,among the three models compared,the RF model was consistently more accurate than the SVM and GBRT models,achieving an R^(2)value of 0.56.Except for band 12 in December,the importance of the remaining bands did not exhibit significant differences.This research offers a new attempt to map SOM with high accuracy and fine spatial resolution based on monthly synthetic Sentinel-2 images.展开更多
This study investigates the relationship between the persistence and the zonal scale of atmospheric dipolar modes(DMs). Results from the daily data of ERA5 and the long-term output of an idealized atmospheric model sh...This study investigates the relationship between the persistence and the zonal scale of atmospheric dipolar modes(DMs). Results from the daily data of ERA5 and the long-term output of an idealized atmospheric model show that the atmospheric DMs with a broader(narrower) zonal scale dipolar structure possess a longer(shorter) persistence. A detailed vorticity budget analysis indicates that the persistence of a hemispheric-scale DM(1/1 DM) and a regional or sectoral DM(1/8 DM) in the model both largely rely on the persistence of the nonlinear eddy forcing. Linear terms can indirectly reduce the persistence of the anomalous nonlinear eddy forcing in a 1/8 DM by modifying the baroclinicity via the arousal of anomalous vertical motions. Therefore, the atmospheric DMs with a broader(narrower) zonal scale possess a longer(shorter) persistence because the effects of the linear terms are less(more) pronounced when the atmospheric DMs have better(worse) zonal symmetry. Further analyses show that the positive eddy feedback effect is weak or even absent in a 1/8DM and the high-frequency eddy forcing acts more like a concomitant phenomenon rather than a leading driving factor for a 1/8 DM. Thus, the hemispheric-scale DM and the regional or sectoral DMs are different, not only in their persistence but also in their dynamics.展开更多
The damage of rock joints or fractures upon shear includes the surface damage occurring at the contact asperities and the damage beneath the shear surface within the host rock.The latter is commonly known as off-fault...The damage of rock joints or fractures upon shear includes the surface damage occurring at the contact asperities and the damage beneath the shear surface within the host rock.The latter is commonly known as off-fault damage and has been much less investigated than the surface damage.The main contribution of this study is to compare the results of direct shear tests conducted on saw-cut planar joints and tension-induced rough granite joints under normal stresses ranging from 1 MPa to 50 MPa.The shear-induced off-fault damages are quantified and compared with the optical microscope observation.Our results clearly show that the planar joints slip stably under all the normal stresses except under 50 MPa,where some local fractures and regular stick-slip occur towards the end of the test.Both post-peak stress drop and stick-slip occur for all the rough joints.The residual shear strength envelopes for the rough joints and the peak shear strength envelope for the planar joints almost overlap.The root mean square(RMS)of asperity height for the rough joints decreases while it increases for the planar joint after shear,and a larger normal stress usually leads to a more significant decrease or increase in RMS.Besides,the extent of off-fault damage(or damage zone)increases with normal stress for both planar and rough joints,and it is restricted to a very thin layer with limited micro-cracks beneath the planar joint surface.In comparison,the thickness of the damage zone for the rough joints is about an order of magnitude larger than that of the planar joints,and the coalesced micro-cracks are generally inclined to the shear direction with acute angles.The findings obtained in this study contribute to a better understanding on the frictional behavior and damage characteristics of rock joints or fractures with different roughness.展开更多
Multi-modal fusion technology gradually become a fundamental task in many fields,such as autonomous driving,smart healthcare,sentiment analysis,and human-computer interaction.It is rapidly becoming the dominant resear...Multi-modal fusion technology gradually become a fundamental task in many fields,such as autonomous driving,smart healthcare,sentiment analysis,and human-computer interaction.It is rapidly becoming the dominant research due to its powerful perception and judgment capabilities.Under complex scenes,multi-modal fusion technology utilizes the complementary characteristics of multiple data streams to fuse different data types and achieve more accurate predictions.However,achieving outstanding performance is challenging because of equipment performance limitations,missing information,and data noise.This paper comprehensively reviews existing methods based onmulti-modal fusion techniques and completes a detailed and in-depth analysis.According to the data fusion stage,multi-modal fusion has four primary methods:early fusion,deep fusion,late fusion,and hybrid fusion.The paper surveys the three majormulti-modal fusion technologies that can significantly enhance the effect of data fusion and further explore the applications of multi-modal fusion technology in various fields.Finally,it discusses the challenges and explores potential research opportunities.Multi-modal tasks still need intensive study because of data heterogeneity and quality.Preserving complementary information and eliminating redundant information between modalities is critical in multi-modal technology.Invalid data fusion methods may introduce extra noise and lead to worse results.This paper provides a comprehensive and detailed summary in response to these challenges.展开更多
Utilizing single atom sites doping into metal oxides to modulate their intrinsic active sites,achieving precise selectivity control in complex organic reactions,is a highly desirable yet challenging endeavor.Meanwhile...Utilizing single atom sites doping into metal oxides to modulate their intrinsic active sites,achieving precise selectivity control in complex organic reactions,is a highly desirable yet challenging endeavor.Meanwhile,identifying the active site also represents a significant obstacle,primarily due to the intricate electronic environment of single atom site doped metal oxide.Herein,a single atom Cu doped TiO_(2)catalyst(Cu_(1)-TiO_(2)) is prepared via a simple“colloid-acid treatment”strategy,which switches aniline oxidation selectivity of TiO_(2) from azoxybenzene to nitrosobenzene,without using additives or changing solvent,while other metal or nonmetal doped TiO_(2) did not possess.Comprehensive mechanistic investigations and DFT calculations unveil that Ti-O active site is responsible for triggering the aniline to form a new PhNOH intermediate,two PhNOH condense to azoxybenzene over TiO_(2) catalyst.As for Cu_(1)-TiO_(2),the charge-specific distribution between the isolated Cu and TiO_(2) generates unique Cu_(1)-O-Ti hybridization structure with nine catalytic active sites,eight of them make PhNOH take place spontaneous dissociation to produce nitrosobenzene.This work not only unveils a new mechanistic pathway featuring the PhNOH intermediate in aniline oxidation for the first time but also presents a novel approach for constructing single-atom doped metal oxides and exploring their intricate active sites.展开更多
A significant demand rises for energy-efficient deep neural networks to support power-limited embedding devices with successful deep learning applications in IoT and edge computing fields.An accurate energy prediction...A significant demand rises for energy-efficient deep neural networks to support power-limited embedding devices with successful deep learning applications in IoT and edge computing fields.An accurate energy prediction approach is critical to provide measurement and lead optimization direction.However,the current energy prediction approaches lack accuracy and generalization ability due to the lack of research on the neural network structure and the excessive reliance on customized training dataset.This paper presents a novel energy prediction model,NeurstrucEnergy.NeurstrucEnergy treats neural networks as directed graphs and applies a bi-directional graph neural network training on a randomly generated dataset to extract structural features for energy prediction.NeurstrucEnergy has advantages over linear approaches because the bi-directional graph neural network collects structural features from each layer's parents and children.Experimental results show that NeurstrucEnergy establishes state-of-the-art results with mean absolute percentage error of 2.60%.We also evaluate NeurstrucEnergy in a randomly generated dataset,achieving the mean absolute percentage error of 4.83%over 10 typical convolutional neural networks in recent years and 7 efficient convolutional neural networks created by neural architecture search.Our code is available at https://github.com/NEUSoftGreenAI/NeurstrucEnergy.git.展开更多
Sodium dentrite formed by uneven plating/stripping can reduce the utilization of active sodium with poor cyclic stability and,more importantly,cause internal short circuit and lead to thermal runaway and fire.Therefor...Sodium dentrite formed by uneven plating/stripping can reduce the utilization of active sodium with poor cyclic stability and,more importantly,cause internal short circuit and lead to thermal runaway and fire.Therefore,sodium dendrites and their related problems seriously hinder the practical application of sodium metal batteries(SMBs).Herein,a design concept for the incorporation of metal-organic framework(MOF)in polymer matrix(polyvinylidene fluoride-hexafluoropropylene)is practiced to prepare a novel gel polymer electrolyte(PH@MOF polymer-based electrolyte[GPE])and thus to achieve high-performance SMBs.The addition of the MOF particles can not only reduce the movement hindrance of polymer chains to promote the transfer of Na^(+)but also anchor anions by virtue of their negative charge to reduce polarization during electrochemical reaction.A stable cycling performance with tiny overpotential for over 800 h at a current density of 5 mA cm^(-2)with areal capacity of 5 mA h cm^(-2)is achieved by symmetric cells based on the resulted GPE while the Na_(3)V_(2)O_(2)(PO_(4))_(2)F@rGO(NVOPF)|PH@MOF|Nacell also displays impressive specific cycling capacity(113.3 mA h g^(-1)at 1 C)and rate capability with considerable capacity retention.展开更多
Most existing star-galaxy classifiers depend on the reduced information from catalogs,necessitating careful data processing and feature extraction.In this study,we employ a supervised machine learning method(GoogLeNet...Most existing star-galaxy classifiers depend on the reduced information from catalogs,necessitating careful data processing and feature extraction.In this study,we employ a supervised machine learning method(GoogLeNet)to automatically classify stars and galaxies in the COSMOS field.Unlike traditional machine learning methods,we introduce several preprocessing techniques,including noise reduction and the unwrapping of denoised images in polar coordinates,applied to our carefully selected samples of stars and galaxies.By dividing the selected samples into training and validation sets in an 8:2 ratio,we evaluate the performance of the GoogLeNet model in distinguishing between stars and galaxies.The results indicate that the GoogLeNet model is highly effective,achieving accuracies of 99.6% and 99.9% for stars and galaxies,respectively.Furthermore,by comparing the results with and without preprocessing,we find that preprocessing can significantly improve classification accuracy(by approximately 2.0% to 6.0%)when the images are rotated.In preparation for the future launch of the China Space Station Telescope(CSST),we also evaluate the performance of the GoogLeNet model on the CSST simulation data.These results demonstrate a high level of accuracy(approximately 99.8%),indicating that this model can be effectively utilized for future observations with the CSST.展开更多
BACKGROUND Research on gastrointestinal mucosal adenocarcinoma(GMA)is limited and controversial,and there is no reference tool for predicting postoperative survival.AIM To investigate the prognosis of GMA and develop ...BACKGROUND Research on gastrointestinal mucosal adenocarcinoma(GMA)is limited and controversial,and there is no reference tool for predicting postoperative survival.AIM To investigate the prognosis of GMA and develop predictive model.METHODS From the Surveillance,Epidemiology,and End Results database,we collected clinical information on patients with GMA.After random sampling,the patients were divided into the discovery(70%of the total,for model training),validation(20%,for model evaluation),and completely blind test cohorts(10%,for further model evaluation).The main assessment metric was the area under the receiver operating characteristic curve(AUC).All collected clinical features were used for Cox proportional hazard regression analysis to determine factors influencing GMA’s prognosis.RESULTS This model had an AUC of 0.7433[95% confidence intervals(95%CI):0.7424-0.7442]in the discovery cohort,0.7244(GMA:0.7234-0.7254)in the validation cohort,and 0.7388(95%CI:0.7378-0.7398)in the test cohort.We packaged it into Windows software for doctors’use and uploaded it.Mucinous gastric adenocarcinoma had the worst prognosis,and these were protective factors of GMA:Regional nodes examined[hazard ratio(HR):0.98,95%CI:0.97-0.98,P<0.001]and chemotherapy(HR:0.62,95%CI:0.58-0.66,P<0.001).CONCLUSION The deep learning-based tool developed can accurately predict the overall survival of patients with GMA postoperatively.Combining surgery,chemotherapy,and adequate lymph node dissection during surgery can improve patient outcomes.展开更多
Background The neurophysiological differences in cortical plasticity and cholinergic system function due to ageing and their correlation with cognitive function remain poorly understood.Aims To reveal the differences ...Background The neurophysiological differences in cortical plasticity and cholinergic system function due to ageing and their correlation with cognitive function remain poorly understood.Aims To reveal the differences in long-term potentiation(LTP)-like plasticity and short-latency afferent inhibition(SAl)between older and younger individuals,alongside their correlation with cognitive function using transcranial magnetic stimulation(TMS).Methods The cross-sectional study involved 31 younger adults aged 18-30 and 46 older adults aged 60-80.All participants underwent comprehensive cognitive assessments and a neurophysiological evaluation based on TMS.Cognitive function assessments included evaluations of global cognitive function,language,memory and executive function.The neurophysiological assessment included LTP-like plasticity and SAl.Results The findings of this study revealed a decline in LTP among the older adults compared with the younger adults(wald χ^(2)=3.98,p=0.046).Subgroup analysis further demonstrated a significant reduction in SAl level among individuals aged 70-80 years in comparison to both the younger adults(SAI(N20)):(t=-3.37,p=0.018);SAl(N20+4):(t=-3.13,p=0.038)and those aged 60-70(SAl(N20)):(t=3.26,p=0.025);SAl(N20+4):(t=-3.69,p=0.006).Conversely,there was no notable difference in SAl level between those aged 60-70 years and the younger group.Furthermore,after employing the Bonferroni correction,the correlation analysis revealed that only the positive correlation between LTP-like plasticity and language function(r=0.61,p<0.001)in the younger group remained statistically significant.Conclusions During the normal ageing process,a decline in synaptic plasticity may precede cholinergic system dysfunction.In individuals over 60 years of age,there is a reduction in LTP-like plasticity,while a decline in cholinergic system function is observed in those over 70.Thus,the cholinergic system may play a vital role in preventing cognitive decline during normal ageing.In younger individuals,LTP-like plasticity might represent a potential neurophysiological marker for language function.展开更多
BACKGROUND Stroke frequently results in oropharyngeal dysfunction(OD),leading to difficulties in swallowing and eating,as well as triggering negative emotions,malnutrition,and aspiration pneumonia,which can be detrime...BACKGROUND Stroke frequently results in oropharyngeal dysfunction(OD),leading to difficulties in swallowing and eating,as well as triggering negative emotions,malnutrition,and aspiration pneumonia,which can be detrimental to patients.However,routine nursing interventions often fail to address these issues adequately.Systemic and psychological interventions can improve dysphagia symptoms,relieve negative emotions,and improve quality of life.However,there are few clinical reports of systemic interventions combined with psychological interventions for stroke patients with OD.AIM To explore the effects of combining systemic and psychological interventions in stroke patients with OD.METHODS This retrospective study included 90 stroke patients with OD,admitted to the Second Affiliated Hospital of Qiqihar Medical College(January 2022–December 2023),who were divided into two groups:regular and coalition.Swallowing function grading(using a water swallow test),swallowing function[using the standardized swallowing assessment(SSA)],negative emotions[using the selfrating anxiety scale(SAS)and self-rating depression scale(SDS)],and quality of life(SWAL-QOL)were compared between groups before and after the intervention;aspiration pneumonia incidence was recorded.RESULTS Post-intervention,the coalition group had a greater number of patients with grade 1 swallowing function compared to the regular group,while the number of patients with grade 5 swallowing function was lower than that in the regular group(P<0.05).Post-intervention,the SSA,SAS,and SDS scores of both groups decreased,with a more significant decrease observed in the coalition group(P<0.05).Additionally,the total SWAL-QOL score in both groups increased,with a more significant increase observed in the coalition group(P<0.05).During the intervention period,the total incidence of aspiration and aspiration pneumonia in the coalition group was lower than that in the control group(4.44%vs 20.00%;P<0.05).CONCLUSION Systemic intervention combined with psychological intervention can improve dysphagia symptoms,alleviate negative emotions,enhance quality of life,and reduce the incidence of aspiration pneumonia in patients with OD.展开更多
BACKGROUND Stroke has become one of the most serious life-threatening diseases due to its high morbidity,disability,recurrence and mortality rates.AIM To explore the intervention effect of multi-disciplinary treatment...BACKGROUND Stroke has become one of the most serious life-threatening diseases due to its high morbidity,disability,recurrence and mortality rates.AIM To explore the intervention effect of multi-disciplinary treatment(MDT)extended nursing model on negative emotions and quality of life of young patients with post-stroke.METHODS A total of 60 young stroke patients who were hospitalized in the neurology department of our hospital from January 2020 to December 2021 were selected and randomly divided into a control group and an experimental group,with 30 patients in each group.The control group used the conventional care model and the experimental group used the MDT extended nursing model.After the inhospital and 3-mo post-discharge interventions,the differences in negative emotions and quality of life scores between the two groups were evaluated and analyzed at the time of admission,at the time of discharge and after discharge,respectively.RESULTS There are no statistically significant differences in the negative emotions scores between the two groups at admission,while there are statistically significant differences in the negative emotions scores within each group at admission and discharge,at discharge and post-discharge,and at discharge and post-discharge.In addition,the negative emotions scores were all statistically significant at discharge and after discharge when compared between the two groups.There was no statistically significant difference in quality of life scores at the time of admission between the two groups,and the difference between quality of life scores at the time of admission and discharge,at the time of discharge and post-discharge,and at the time of admission and post-discharge for each group of patients was statistically significant.CONCLUSION The MDT extended nursing mode can improve the negative emotion of patients and improve their quality of life.Therefore,it can be applied in future clinical practice and is worthy of promotion.展开更多
Grain weight and grain number are important yield component traits in wheat and identification of underlying genetic loci is helpful for improving yield.Here,we identified eight stable quantitative trait loci(QTL)for ...Grain weight and grain number are important yield component traits in wheat and identification of underlying genetic loci is helpful for improving yield.Here,we identified eight stable quantitative trait loci(QTL)for yield component traits,including five loci for thousand grain weight(TGW)and three for grain number per spike(GNS)in a recombinant inbred line population derived from cross Yangxiaomai/Zhongyou 9507 across four environments.Since grain size is a major determinant of grain weight,we also mapped QTL for grain length(GL)and grain width(GW).QTGW.caas-2D,QTGW.caas-3B,QTGW.caas-5A and QTGW.caas-7A.2 for TGW co-located with those for grain size.QTGW.caas-2D also had a consistent genetic position with QGNS.caas-2D,suggesting that the pleiotropic locus is a modulator of trade-off effect between TGW and GNS.Sequencing and linkage mapping showed that TaGL3-5A and WAPO-A1 were candidate genes of QTGW.caas-5A and QTGW.caas-7A.2,respectively.We developed Kompetitive allele specific PCR(KASP)markers linked with the stable QTL for yield component traits and validated their genetic effects in a diverse panel of wheat cultivars from the Huang-Huai River Valley region.KASP-based genotyping analysis further revealed that the superior alleles of all stable QTL for TGW but not GNS were subject to positive selection,indicating that yield improvement in the region largely depends on increased TGW.Comparative analyses with previous studies showed that most of the QTL could be detected in different genetic backgrounds,and QTGW.caas-7A.1 is likely a new QTL.These findings provide not only valuable genetic information for yield improvement but also useful tools for marker-assisted selection.展开更多
Mobile-edge computing(MEC)is a promising technology for the fifth-generation(5G)and sixth-generation(6G)architectures,which provides resourceful computing capabilities for Internet of Things(IoT)devices,such as virtua...Mobile-edge computing(MEC)is a promising technology for the fifth-generation(5G)and sixth-generation(6G)architectures,which provides resourceful computing capabilities for Internet of Things(IoT)devices,such as virtual reality,mobile devices,and smart cities.In general,these IoT applications always bring higher energy consumption than traditional applications,which are usually energy-constrained.To provide persistent energy,many references have studied the offloading problem to save energy consumption.However,the dynamic environment dramatically increases the optimization difficulty of the offloading decision.In this paper,we aim to minimize the energy consumption of the entireMECsystemunder the latency constraint by fully considering the dynamic environment.UnderMarkov games,we propose amulti-agent deep reinforcement learning approach based on the bi-level actorcritic learning structure to jointly optimize the offloading decision and resource allocation,which can solve the combinatorial optimization problem using an asymmetric method and compute the Stackelberg equilibrium as a better convergence point than Nash equilibrium in terms of Pareto superiority.Our method can better adapt to a dynamic environment during the data transmission than the single-agent strategy and can effectively tackle the coordination problem in the multi-agent environment.The simulation results show that the proposed method could decrease the total computational overhead by 17.8%compared to the actor-critic-based method and reduce the total computational overhead by 31.3%,36.5%,and 44.7%compared with randomoffloading,all local execution,and all offloading execution,respectively.展开更多
基金supported by the National Natural Science Foundation of China(Nos.52225403,U2013603,52434004,and 52404365)the Program for Guangdong Introducing Innovative and Entrepreneurial Teams(No.2019ZT08G315)+2 种基金the Shenzhen National Science Fund for Distinguished Young Scholars(No.RCJC20210706091948015)the National Key Research and Development Program of China(2023YFF0615404)the Scientific Instrument Developing Project of Shenzhen University。
文摘The lunar surface and its deep layers contain abundant resources and valuable information resources,the exploration and exploitation of which are important for the sustainable development of the human economy and society.Technological exploration and research in the field of deep space science,especially lunar-based exploration,is a scientific strategy that has been pursued in China and worldwide.Drilling and sampling are key to accurate exploration of the desirable characteristics of deep lunar resources.In this study,an in-situ condition preserved coring(ICP-Coring)and analysis system,which can be used to test drilling tools and develop effective sampling strategies,was designed.The key features of the system include:(1)capability to replicate the extreme temperature fluctuations of the lunar environment(-185 to 200℃)with intelligent temperature control;(2)ability to maintain a vacuum environment at a scale of 10^(-3) Pa,both under unloaded conditions within Ф580 mm×1000 mm test chamber,and under loaded conditions using Ф400 mm×800 mm lunar rock simulant;(3)application of axial pressures up to 4 MPa and confining pressures up to 3.5 MPa;(4)sample rotation at any angle with a maximum sampling length of 800 mm;and(5)multiple modes of rotary-percussive drilling,controlled by penetration speed and weight on bit(WOB).Experimental studies on the drilling characteristics in the lunar rock simulant-loaded state under different drill bit-percussive-vacuum environment configurations were conducted.The results show that the outgassing rate of the lunar soil simulant is greater than that of the lunar rock simulant and that a low-temperature environment contributes to a reduced vacuum of the lunar-based simulated environment.The rotary-percussive drilling method effectively shortens the sampling time.With increasing sampling depth,the temperature rise of the drilling tools tends to rapidly increase,followed by slow growth or steady fluctuations.The temperature rise energy accumulation of the drill bits under vacuum is more significant than that under atmospheric pressure,approximately 1.47 times higher.The real-time monitored drilling pressure,penetration speed and rotary torque during drilling serve as parameters for discriminating the drilling status.The results of this research can provide a scientific basis for returning samples from lunar rock in extreme lunar-based environments.
基金supported by the Sino-German Postdoc Scholarship Program of the China Scholarship Council(CSC)the German Academic Exchange Service(DAAD)+4 种基金supported in part by the National Natural Science Foundation of China(Nos.32071541,41971071)the Ministry of Science and Technology of China(Nos.2021FY100200,2021FY100702,2023YFF0805802)the Youth Innovation Promotion Association,CAS(No.2021392)the International Partnership Program,CAS(No.151853KYSB20190027)the“Climate Change Research Initiative of the Bavarian National Parks”funded by the Bavarian State Ministry of the Environment and Consumer Protection.
文摘An improved understanding of biodiversity-productivity relationships(BPRs)along environmental gradients is crucial for effective ecosystem management and biodiversity conservation.The stress-gradient hypothesis suggests that BPRs are stronger in stressful environments compared to more favorable conditions.However,there is limited knowledge regarding the variation of BPRs along elevational gradients and their generality across different landscapes.To study how BPRs change with elevation,we harnessed inventory data on 6,431 trees from152 plots surveyed twice in eight to ten year intervals in mountain forests of temperate Europe and subtropical Asia.We quantified the relationship between aboveground productivity and different biodiversity measures,including taxonomic,functional,and phylogenetic diversity.To elucidate the processes underlying BPRs,we studied the variation of different functional traits along elevation across landscapes.We found no general pattern of BPRs across landscapes and elevations.Relationships were neutral for all biodiversity measures in temperate forests,and negative for taxonomic and functional diversity in subtropical forests.BPRs were largely congruent between taxonomic,functional and phylogenetic diversity.We found only weak support for the stress-gradient hypothesis,with BPRs turning from negative to positive(effect not significant)close to the tree line in subtropical forests.In temperate forests,however,elevation patterns were strongly modulated by species identity effects as influenced by specific traits.The effect of traits such as community-weighted mean of maximum plant height and wood density on productivity was congruent across landscapes.Our study highlights the context-dependence of BPRs across elevation gradients and landscapes.Species traits are key modulating factors of BPRs and should be considered more explicitly in studies of the functional role of biodiversity.Furthermore,our findings highlight that potential trade-offs between conserving biodiversity and fostering ecosystem productivity exist,which require more attention in policy and management.
基金National Key Research and Development Program of China(2022YFB3903302 and 2021YFC1809104)。
文摘Rapid and accurate acquisition of soil organic matter(SOM)information in cultivated land is important for sustainable agricultural development and carbon balance management.This study proposed a novel approach to predict SOM with high accuracy using multiyear synthetic remote sensing variables on a monthly scale.We obtained 12 monthly synthetic Sentinel-2 images covering the study area from 2016 to 2021 through the Google Earth Engine(GEE)platform,and reflectance bands and vegetation indices were extracted from these composite images.Then the random forest(RF),support vector machine(SVM)and gradient boosting regression tree(GBRT)models were tested to investigate the difference in SOM prediction accuracy under different combinations of monthly synthetic variables.Results showed that firstly,all monthly synthetic spectral bands of Sentinel-2 showed a significant correlation with SOM(P<0.05)for the months of January,March,April,October,and November.Secondly,in terms of single-monthly composite variables,the prediction accuracy was relatively poor,with the highest R^(2)value of 0.36 being observed in January.When monthly synthetic environmental variables were grouped in accordance with the four quarters of the year,the first quarter and the fourth quarter showed good performance,and any combination of three quarters was similar in estimation accuracy.The overall best performance was observed when all monthly synthetic variables were incorporated into the models.Thirdly,among the three models compared,the RF model was consistently more accurate than the SVM and GBRT models,achieving an R^(2)value of 0.56.Except for band 12 in December,the importance of the remaining bands did not exhibit significant differences.This research offers a new attempt to map SOM with high accuracy and fine spatial resolution based on monthly synthetic Sentinel-2 images.
基金supported by the National Key Research and Development Program of China (mechanism for disaster-causing Northeast cold vortex and key technologies for its forecast, Grant No.2023YFC3007700)。
文摘This study investigates the relationship between the persistence and the zonal scale of atmospheric dipolar modes(DMs). Results from the daily data of ERA5 and the long-term output of an idealized atmospheric model show that the atmospheric DMs with a broader(narrower) zonal scale dipolar structure possess a longer(shorter) persistence. A detailed vorticity budget analysis indicates that the persistence of a hemispheric-scale DM(1/1 DM) and a regional or sectoral DM(1/8 DM) in the model both largely rely on the persistence of the nonlinear eddy forcing. Linear terms can indirectly reduce the persistence of the anomalous nonlinear eddy forcing in a 1/8 DM by modifying the baroclinicity via the arousal of anomalous vertical motions. Therefore, the atmospheric DMs with a broader(narrower) zonal scale possess a longer(shorter) persistence because the effects of the linear terms are less(more) pronounced when the atmospheric DMs have better(worse) zonal symmetry. Further analyses show that the positive eddy feedback effect is weak or even absent in a 1/8DM and the high-frequency eddy forcing acts more like a concomitant phenomenon rather than a leading driving factor for a 1/8 DM. Thus, the hemispheric-scale DM and the regional or sectoral DMs are different, not only in their persistence but also in their dynamics.
基金financial support from Taishan Scholars Program(Grant No.2019KJG002)National Natural Science Foundation of China(Grant Nos.42272329 and 52279116).
文摘The damage of rock joints or fractures upon shear includes the surface damage occurring at the contact asperities and the damage beneath the shear surface within the host rock.The latter is commonly known as off-fault damage and has been much less investigated than the surface damage.The main contribution of this study is to compare the results of direct shear tests conducted on saw-cut planar joints and tension-induced rough granite joints under normal stresses ranging from 1 MPa to 50 MPa.The shear-induced off-fault damages are quantified and compared with the optical microscope observation.Our results clearly show that the planar joints slip stably under all the normal stresses except under 50 MPa,where some local fractures and regular stick-slip occur towards the end of the test.Both post-peak stress drop and stick-slip occur for all the rough joints.The residual shear strength envelopes for the rough joints and the peak shear strength envelope for the planar joints almost overlap.The root mean square(RMS)of asperity height for the rough joints decreases while it increases for the planar joint after shear,and a larger normal stress usually leads to a more significant decrease or increase in RMS.Besides,the extent of off-fault damage(or damage zone)increases with normal stress for both planar and rough joints,and it is restricted to a very thin layer with limited micro-cracks beneath the planar joint surface.In comparison,the thickness of the damage zone for the rough joints is about an order of magnitude larger than that of the planar joints,and the coalesced micro-cracks are generally inclined to the shear direction with acute angles.The findings obtained in this study contribute to a better understanding on the frictional behavior and damage characteristics of rock joints or fractures with different roughness.
基金supported by the Natural Science Foundation of Liaoning Province(Grant No.2023-MSBA-070)the National Natural Science Foundation of China(Grant No.62302086).
文摘Multi-modal fusion technology gradually become a fundamental task in many fields,such as autonomous driving,smart healthcare,sentiment analysis,and human-computer interaction.It is rapidly becoming the dominant research due to its powerful perception and judgment capabilities.Under complex scenes,multi-modal fusion technology utilizes the complementary characteristics of multiple data streams to fuse different data types and achieve more accurate predictions.However,achieving outstanding performance is challenging because of equipment performance limitations,missing information,and data noise.This paper comprehensively reviews existing methods based onmulti-modal fusion techniques and completes a detailed and in-depth analysis.According to the data fusion stage,multi-modal fusion has four primary methods:early fusion,deep fusion,late fusion,and hybrid fusion.The paper surveys the three majormulti-modal fusion technologies that can significantly enhance the effect of data fusion and further explore the applications of multi-modal fusion technology in various fields.Finally,it discusses the challenges and explores potential research opportunities.Multi-modal tasks still need intensive study because of data heterogeneity and quality.Preserving complementary information and eliminating redundant information between modalities is critical in multi-modal technology.Invalid data fusion methods may introduce extra noise and lead to worse results.This paper provides a comprehensive and detailed summary in response to these challenges.
文摘Utilizing single atom sites doping into metal oxides to modulate their intrinsic active sites,achieving precise selectivity control in complex organic reactions,is a highly desirable yet challenging endeavor.Meanwhile,identifying the active site also represents a significant obstacle,primarily due to the intricate electronic environment of single atom site doped metal oxide.Herein,a single atom Cu doped TiO_(2)catalyst(Cu_(1)-TiO_(2)) is prepared via a simple“colloid-acid treatment”strategy,which switches aniline oxidation selectivity of TiO_(2) from azoxybenzene to nitrosobenzene,without using additives or changing solvent,while other metal or nonmetal doped TiO_(2) did not possess.Comprehensive mechanistic investigations and DFT calculations unveil that Ti-O active site is responsible for triggering the aniline to form a new PhNOH intermediate,two PhNOH condense to azoxybenzene over TiO_(2) catalyst.As for Cu_(1)-TiO_(2),the charge-specific distribution between the isolated Cu and TiO_(2) generates unique Cu_(1)-O-Ti hybridization structure with nine catalytic active sites,eight of them make PhNOH take place spontaneous dissociation to produce nitrosobenzene.This work not only unveils a new mechanistic pathway featuring the PhNOH intermediate in aniline oxidation for the first time but also presents a novel approach for constructing single-atom doped metal oxides and exploring their intricate active sites.
基金supported by the Natural Science Foundation of Liaoning Province(2020-BS-054)the Fundamental Research Funds for the Central Universities(N2017005)the National Natural Science Foundation of China(62162050).
文摘A significant demand rises for energy-efficient deep neural networks to support power-limited embedding devices with successful deep learning applications in IoT and edge computing fields.An accurate energy prediction approach is critical to provide measurement and lead optimization direction.However,the current energy prediction approaches lack accuracy and generalization ability due to the lack of research on the neural network structure and the excessive reliance on customized training dataset.This paper presents a novel energy prediction model,NeurstrucEnergy.NeurstrucEnergy treats neural networks as directed graphs and applies a bi-directional graph neural network training on a randomly generated dataset to extract structural features for energy prediction.NeurstrucEnergy has advantages over linear approaches because the bi-directional graph neural network collects structural features from each layer's parents and children.Experimental results show that NeurstrucEnergy establishes state-of-the-art results with mean absolute percentage error of 2.60%.We also evaluate NeurstrucEnergy in a randomly generated dataset,achieving the mean absolute percentage error of 4.83%over 10 typical convolutional neural networks in recent years and 7 efficient convolutional neural networks created by neural architecture search.Our code is available at https://github.com/NEUSoftGreenAI/NeurstrucEnergy.git.
基金financially supported by National Natural Science Foundation of China(Grans Nos.22179109 and 22005315)Fundamental Research Funds for the Central Universities(SWU120080)Chongqing Key Laboratory of Materials Surface&Interface Science(Project No.KFJJ2002)
文摘Sodium dentrite formed by uneven plating/stripping can reduce the utilization of active sodium with poor cyclic stability and,more importantly,cause internal short circuit and lead to thermal runaway and fire.Therefore,sodium dendrites and their related problems seriously hinder the practical application of sodium metal batteries(SMBs).Herein,a design concept for the incorporation of metal-organic framework(MOF)in polymer matrix(polyvinylidene fluoride-hexafluoropropylene)is practiced to prepare a novel gel polymer electrolyte(PH@MOF polymer-based electrolyte[GPE])and thus to achieve high-performance SMBs.The addition of the MOF particles can not only reduce the movement hindrance of polymer chains to promote the transfer of Na^(+)but also anchor anions by virtue of their negative charge to reduce polarization during electrochemical reaction.A stable cycling performance with tiny overpotential for over 800 h at a current density of 5 mA cm^(-2)with areal capacity of 5 mA h cm^(-2)is achieved by symmetric cells based on the resulted GPE while the Na_(3)V_(2)O_(2)(PO_(4))_(2)F@rGO(NVOPF)|PH@MOF|Nacell also displays impressive specific cycling capacity(113.3 mA h g^(-1)at 1 C)and rate capability with considerable capacity retention.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(grant No.XDB41000000)the National Natural Science Foundation of China(NSFC,Grant Nos.12233008 and 11973038)+2 种基金the China Manned Space Project(No.CMS-CSST-2021-A07)the Cyrus Chun Ying Tang Foundationsthe support from Hong Kong Innovation and Technology Fund through the Research Talent Hub program(GSP028)。
文摘Most existing star-galaxy classifiers depend on the reduced information from catalogs,necessitating careful data processing and feature extraction.In this study,we employ a supervised machine learning method(GoogLeNet)to automatically classify stars and galaxies in the COSMOS field.Unlike traditional machine learning methods,we introduce several preprocessing techniques,including noise reduction and the unwrapping of denoised images in polar coordinates,applied to our carefully selected samples of stars and galaxies.By dividing the selected samples into training and validation sets in an 8:2 ratio,we evaluate the performance of the GoogLeNet model in distinguishing between stars and galaxies.The results indicate that the GoogLeNet model is highly effective,achieving accuracies of 99.6% and 99.9% for stars and galaxies,respectively.Furthermore,by comparing the results with and without preprocessing,we find that preprocessing can significantly improve classification accuracy(by approximately 2.0% to 6.0%)when the images are rotated.In preparation for the future launch of the China Space Station Telescope(CSST),we also evaluate the performance of the GoogLeNet model on the CSST simulation data.These results demonstrate a high level of accuracy(approximately 99.8%),indicating that this model can be effectively utilized for future observations with the CSST.
文摘BACKGROUND Research on gastrointestinal mucosal adenocarcinoma(GMA)is limited and controversial,and there is no reference tool for predicting postoperative survival.AIM To investigate the prognosis of GMA and develop predictive model.METHODS From the Surveillance,Epidemiology,and End Results database,we collected clinical information on patients with GMA.After random sampling,the patients were divided into the discovery(70%of the total,for model training),validation(20%,for model evaluation),and completely blind test cohorts(10%,for further model evaluation).The main assessment metric was the area under the receiver operating characteristic curve(AUC).All collected clinical features were used for Cox proportional hazard regression analysis to determine factors influencing GMA’s prognosis.RESULTS This model had an AUC of 0.7433[95% confidence intervals(95%CI):0.7424-0.7442]in the discovery cohort,0.7244(GMA:0.7234-0.7254)in the validation cohort,and 0.7388(95%CI:0.7378-0.7398)in the test cohort.We packaged it into Windows software for doctors’use and uploaded it.Mucinous gastric adenocarcinoma had the worst prognosis,and these were protective factors of GMA:Regional nodes examined[hazard ratio(HR):0.98,95%CI:0.97-0.98,P<0.001]and chemotherapy(HR:0.62,95%CI:0.58-0.66,P<0.001).CONCLUSION The deep learning-based tool developed can accurately predict the overall survival of patients with GMA postoperatively.Combining surgery,chemotherapy,and adequate lymph node dissection during surgery can improve patient outcomes.
基金the National Key Research and Development Program of China(2022YFC2009700)the National Science Foundation of China(82372582)+1 种基金the Medical Applications Basic Research Project of Suzhou Science and Technology Bureau(SKY2023033)the Wujiang District Science,Education,Health and Promotion Project(WWK202021).
文摘Background The neurophysiological differences in cortical plasticity and cholinergic system function due to ageing and their correlation with cognitive function remain poorly understood.Aims To reveal the differences in long-term potentiation(LTP)-like plasticity and short-latency afferent inhibition(SAl)between older and younger individuals,alongside their correlation with cognitive function using transcranial magnetic stimulation(TMS).Methods The cross-sectional study involved 31 younger adults aged 18-30 and 46 older adults aged 60-80.All participants underwent comprehensive cognitive assessments and a neurophysiological evaluation based on TMS.Cognitive function assessments included evaluations of global cognitive function,language,memory and executive function.The neurophysiological assessment included LTP-like plasticity and SAl.Results The findings of this study revealed a decline in LTP among the older adults compared with the younger adults(wald χ^(2)=3.98,p=0.046).Subgroup analysis further demonstrated a significant reduction in SAl level among individuals aged 70-80 years in comparison to both the younger adults(SAI(N20)):(t=-3.37,p=0.018);SAl(N20+4):(t=-3.13,p=0.038)and those aged 60-70(SAl(N20)):(t=3.26,p=0.025);SAl(N20+4):(t=-3.69,p=0.006).Conversely,there was no notable difference in SAl level between those aged 60-70 years and the younger group.Furthermore,after employing the Bonferroni correction,the correlation analysis revealed that only the positive correlation between LTP-like plasticity and language function(r=0.61,p<0.001)in the younger group remained statistically significant.Conclusions During the normal ageing process,a decline in synaptic plasticity may precede cholinergic system dysfunction.In individuals over 60 years of age,there is a reduction in LTP-like plasticity,while a decline in cholinergic system function is observed in those over 70.Thus,the cholinergic system may play a vital role in preventing cognitive decline during normal ageing.In younger individuals,LTP-like plasticity might represent a potential neurophysiological marker for language function.
基金Supported by Qiqihar City Science and Technology Plan Joint Guidance Project,No.LSFGG-2022085.
文摘BACKGROUND Stroke frequently results in oropharyngeal dysfunction(OD),leading to difficulties in swallowing and eating,as well as triggering negative emotions,malnutrition,and aspiration pneumonia,which can be detrimental to patients.However,routine nursing interventions often fail to address these issues adequately.Systemic and psychological interventions can improve dysphagia symptoms,relieve negative emotions,and improve quality of life.However,there are few clinical reports of systemic interventions combined with psychological interventions for stroke patients with OD.AIM To explore the effects of combining systemic and psychological interventions in stroke patients with OD.METHODS This retrospective study included 90 stroke patients with OD,admitted to the Second Affiliated Hospital of Qiqihar Medical College(January 2022–December 2023),who were divided into two groups:regular and coalition.Swallowing function grading(using a water swallow test),swallowing function[using the standardized swallowing assessment(SSA)],negative emotions[using the selfrating anxiety scale(SAS)and self-rating depression scale(SDS)],and quality of life(SWAL-QOL)were compared between groups before and after the intervention;aspiration pneumonia incidence was recorded.RESULTS Post-intervention,the coalition group had a greater number of patients with grade 1 swallowing function compared to the regular group,while the number of patients with grade 5 swallowing function was lower than that in the regular group(P<0.05).Post-intervention,the SSA,SAS,and SDS scores of both groups decreased,with a more significant decrease observed in the coalition group(P<0.05).Additionally,the total SWAL-QOL score in both groups increased,with a more significant increase observed in the coalition group(P<0.05).During the intervention period,the total incidence of aspiration and aspiration pneumonia in the coalition group was lower than that in the control group(4.44%vs 20.00%;P<0.05).CONCLUSION Systemic intervention combined with psychological intervention can improve dysphagia symptoms,alleviate negative emotions,enhance quality of life,and reduce the incidence of aspiration pneumonia in patients with OD.
基金Supported by the Joint Guidance Project of Qiqihar Science and Technology Plan in 2020,No.LHYD-202054。
文摘BACKGROUND Stroke has become one of the most serious life-threatening diseases due to its high morbidity,disability,recurrence and mortality rates.AIM To explore the intervention effect of multi-disciplinary treatment(MDT)extended nursing model on negative emotions and quality of life of young patients with post-stroke.METHODS A total of 60 young stroke patients who were hospitalized in the neurology department of our hospital from January 2020 to December 2021 were selected and randomly divided into a control group and an experimental group,with 30 patients in each group.The control group used the conventional care model and the experimental group used the MDT extended nursing model.After the inhospital and 3-mo post-discharge interventions,the differences in negative emotions and quality of life scores between the two groups were evaluated and analyzed at the time of admission,at the time of discharge and after discharge,respectively.RESULTS There are no statistically significant differences in the negative emotions scores between the two groups at admission,while there are statistically significant differences in the negative emotions scores within each group at admission and discharge,at discharge and post-discharge,and at discharge and post-discharge.In addition,the negative emotions scores were all statistically significant at discharge and after discharge when compared between the two groups.There was no statistically significant difference in quality of life scores at the time of admission between the two groups,and the difference between quality of life scores at the time of admission and discharge,at the time of discharge and post-discharge,and at the time of admission and post-discharge for each group of patients was statistically significant.CONCLUSION The MDT extended nursing mode can improve the negative emotion of patients and improve their quality of life.Therefore,it can be applied in future clinical practice and is worthy of promotion.
基金supported by financial support from the National Key Research and Development Program of China(2021YFF1200200)the National Natural Science Foundation of China(22161132008)+2 种基金the Natural Science Foundation of Shanghai,China(19520714100 and 19ZR1475800)the Starry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study(SNZJU-SIAS-006)the Natural Science Foundation of Zhejiang Province(LQ21C050001)。
基金funded by the National Natural Science Foundation of China(91935304 and 32272182)Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences.
文摘Grain weight and grain number are important yield component traits in wheat and identification of underlying genetic loci is helpful for improving yield.Here,we identified eight stable quantitative trait loci(QTL)for yield component traits,including five loci for thousand grain weight(TGW)and three for grain number per spike(GNS)in a recombinant inbred line population derived from cross Yangxiaomai/Zhongyou 9507 across four environments.Since grain size is a major determinant of grain weight,we also mapped QTL for grain length(GL)and grain width(GW).QTGW.caas-2D,QTGW.caas-3B,QTGW.caas-5A and QTGW.caas-7A.2 for TGW co-located with those for grain size.QTGW.caas-2D also had a consistent genetic position with QGNS.caas-2D,suggesting that the pleiotropic locus is a modulator of trade-off effect between TGW and GNS.Sequencing and linkage mapping showed that TaGL3-5A and WAPO-A1 were candidate genes of QTGW.caas-5A and QTGW.caas-7A.2,respectively.We developed Kompetitive allele specific PCR(KASP)markers linked with the stable QTL for yield component traits and validated their genetic effects in a diverse panel of wheat cultivars from the Huang-Huai River Valley region.KASP-based genotyping analysis further revealed that the superior alleles of all stable QTL for TGW but not GNS were subject to positive selection,indicating that yield improvement in the region largely depends on increased TGW.Comparative analyses with previous studies showed that most of the QTL could be detected in different genetic backgrounds,and QTGW.caas-7A.1 is likely a new QTL.These findings provide not only valuable genetic information for yield improvement but also useful tools for marker-assisted selection.
基金supported by the National Natural Science Foundation of China(62162050)the Fundamental Research Funds for the Central Universities(No.N2217002)the Natural Science Foundation of Liaoning ProvincialDepartment of Science and Technology(No.2022-KF-11-04).
文摘Mobile-edge computing(MEC)is a promising technology for the fifth-generation(5G)and sixth-generation(6G)architectures,which provides resourceful computing capabilities for Internet of Things(IoT)devices,such as virtual reality,mobile devices,and smart cities.In general,these IoT applications always bring higher energy consumption than traditional applications,which are usually energy-constrained.To provide persistent energy,many references have studied the offloading problem to save energy consumption.However,the dynamic environment dramatically increases the optimization difficulty of the offloading decision.In this paper,we aim to minimize the energy consumption of the entireMECsystemunder the latency constraint by fully considering the dynamic environment.UnderMarkov games,we propose amulti-agent deep reinforcement learning approach based on the bi-level actorcritic learning structure to jointly optimize the offloading decision and resource allocation,which can solve the combinatorial optimization problem using an asymmetric method and compute the Stackelberg equilibrium as a better convergence point than Nash equilibrium in terms of Pareto superiority.Our method can better adapt to a dynamic environment during the data transmission than the single-agent strategy and can effectively tackle the coordination problem in the multi-agent environment.The simulation results show that the proposed method could decrease the total computational overhead by 17.8%compared to the actor-critic-based method and reduce the total computational overhead by 31.3%,36.5%,and 44.7%compared with randomoffloading,all local execution,and all offloading execution,respectively.
