Some studies have confirmed the neuroprotective effect of remote ischemic conditioning against stroke. Although numerous animal researches have shown that the neuroprotective effect of remote ischemic conditioning may...Some studies have confirmed the neuroprotective effect of remote ischemic conditioning against stroke. Although numerous animal researches have shown that the neuroprotective effect of remote ischemic conditioning may be related to neuroinflammation, cellular immunity, apoptosis, and autophagy, the exact underlying molecular mechanisms are unclear. This review summarizes the current status of different types of remote ischemic conditioning methods in animal and clinical studies and analyzes their commonalities and differences in neuroprotective mechanisms and signaling pathways. Remote ischemic conditioning has emerged as a potential therapeutic approach for improving stroke-induced brain injury owing to its simplicity, non-invasiveness, safety, and patient tolerability. Different forms of remote ischemic conditioning exhibit distinct intervention patterns, timing, and application range. Mechanistically, remote ischemic conditioning can exert neuroprotective effects by activating the Notch1/phosphatidylinositol 3-kinase/Akt signaling pathway, improving cerebral perfusion, suppressing neuroinflammation, inhibiting cell apoptosis, activating autophagy, and promoting neural regeneration. While remote ischemic conditioning has shown potential in improving stroke outcomes, its full clinical translation has not yet been achieved.展开更多
Gassy soils are distributed in relatively shallow layers the Quaternary deposit in Hangzhou Bay area. The shallow gassy soils significantly affect the construction of underground projects. Proper characterization of s...Gassy soils are distributed in relatively shallow layers the Quaternary deposit in Hangzhou Bay area. The shallow gassy soils significantly affect the construction of underground projects. Proper characterization of spatial distribution of shallow gassy soils is indispensable prior to construction of underground projects in the area. Due to the costly conditions required in the site investigation for gassy soils, only a limited number of gas pressure data can be obtained in engineering practice, which leads to the uncertainty in characterizing spatial distribution of gassy soils. Determining the number of boreholes for investigating gassy soils and their corresponding locations is pivotal to reducing construction risk induced by gassy soils. However, this primarily relies on the engineering experience in the current site investigation practice. This study develops a probabilistic site investigation optimization method for planning investigation schemes (including the number and locations of boreholes) of gassy soils based on the conditional random field and Monte Carlo simulation. The proposed method aims to provide an optimal investigation scheme before the site investigation based on prior knowledge. Finally, the proposed approach is illustrated using a case study.展开更多
The study of the morphometric parameters of the three most abundant species in the lower course of the Kouilou River (Chrysichthys auratus, Liza falcipinnis and Pellonula vorax) was carried out. The standard length of...The study of the morphometric parameters of the three most abundant species in the lower course of the Kouilou River (Chrysichthys auratus, Liza falcipinnis and Pellonula vorax) was carried out. The standard length of Chrysichthys auratus varies between 43.57 and 210 mm, for an average of 96.70 ± 28.63 mm;the weight varies between 2.92 and 140.83 mg, an average of 73.03 ± 21.62 mg. The condition coefficient is equal to 4.42 ± 1.52. Liza falcipinnis has a standard length which varies between 59.9 mm and 158.08 mm for an average of 88.15 ± 29.74 mm;its weight varies between 4.77 and 76.21 mg, an average of 18.61 ± 11.82 mg. The condition coefficient is equal to 2.47 ± 1.57. Pellonula vorax has a standard length which varies between 60.33 mm and 117.72 mm;for an average of 80.48 ± 17.75 mm;the weight varies between 3.61 and 25.17 mg, an average of 9.03 ± 3.61 mg. The condition coefficient is equal to 2.17 ± 0.57. These three species have a minor allometric growth.展开更多
We used observed concentrations of air pollutants,reanalyzed meteorological parameters,and results from the Goddard Earth Observing System Chemical Transport Model to examine the relationships between concentrations o...We used observed concentrations of air pollutants,reanalyzed meteorological parameters,and results from the Goddard Earth Observing System Chemical Transport Model to examine the relationships between concentrations of maximum daily 8-h average ozone(MDA8 O_(3)),PM_(2.5)(particulate matter with diameter of 2.5μm or less),and PM_(2.5)components and 2-m temperature(T2)or relative humidity(RH),as well as the effectiveness of precursor emission reductions on the control of O_(3) and PM_(2.5) in Beijing–Tianjin–Hebei(BTH)under different summertime temperature and humidity conditions.Both observed(simulated)MDA8 O_(3) and PM_(2.5) concentrations increased as T2 went up,with linear trends of 4.8(3.2)ppb℃^(−1) and 1.9(1.5)μg m^(−3)℃^(−1),respectively.Model results showed that the decreases in MDA8 O_(3) from precursor emission reductions were more sensitive to T2 than to RH.Reducing a larger proportion of volatile organic compound(VOC)emissions at higher T2 was more effective for the control of summertime O_(3) in BTH.For the control of summertime PM_(2.5) in BTH,reducing nitrogen oxides(NOx)combined with a small proportion of VOCs was the best measure.The magnitude of reduction in PM_(2.5) from reducing precursor emissions was more sensitive to RH than to T2,with the best efficiency at high RH.Results from this study are helpful for formulating effective policies to tackle O_(3) and PM_(2.5) pollution in BTH.展开更多
Federated learning(FL)is a distributed machine learning paradigm for edge cloud computing.FL can facilitate data-driven decision-making in tactical scenarios,effectively addressing both data volume and infrastructure ...Federated learning(FL)is a distributed machine learning paradigm for edge cloud computing.FL can facilitate data-driven decision-making in tactical scenarios,effectively addressing both data volume and infrastructure challenges in edge environments.However,the diversity of clients in edge cloud computing presents significant challenges for FL.Personalized federated learning(pFL)received considerable attention in recent years.One example of pFL involves exploiting the global and local information in the local model.Current pFL algorithms experience limitations such as slow convergence speed,catastrophic forgetting,and poor performance in complex tasks,which still have significant shortcomings compared to the centralized learning.To achieve high pFL performance,we propose FedCLCC:Federated Contrastive Learning and Conditional Computing.The core of FedCLCC is the use of contrastive learning and conditional computing.Contrastive learning determines the feature representation similarity to adjust the local model.Conditional computing separates the global and local information and feeds it to their corresponding heads for global and local handling.Our comprehensive experiments demonstrate that FedCLCC outperforms other state-of-the-art FL algorithms.展开更多
The impacts of lateral boundary conditions(LBCs)provided by numerical models and data-driven networks on convective-scale ensemble forecasts are investigated in this study.Four experiments are conducted on the Hangzho...The impacts of lateral boundary conditions(LBCs)provided by numerical models and data-driven networks on convective-scale ensemble forecasts are investigated in this study.Four experiments are conducted on the Hangzhou RDP(19th Hangzhou Asian Games Research Development Project on Convective-scale Ensemble Prediction and Application)testbed,with the LBCs respectively sourced from National Centers for Environmental Prediction(NCEP)Global Forecast System(GFS)forecasts with 33 vertical levels(Exp_GFS),Pangu forecasts with 13 vertical levels(Exp_Pangu),Fuxi forecasts with 13 vertical levels(Exp_Fuxi),and NCEP GFS forecasts with the vertical levels reduced to 13(the same as those of Exp_Pangu and Exp_Fuxi)(Exp_GFSRDV).In general,Exp_Pangu performs comparably to Exp_GFS,while Exp_Fuxi shows slightly inferior performance compared to Exp_Pangu,possibly due to its less accurate large-scale predictions.Therefore,the ability of using data-driven networks to efficiently provide LBCs for convective-scale ensemble forecasts has been demonstrated.Moreover,Exp_GFSRDV has the worst convective-scale forecasts among the four experiments,which indicates the potential improvement of using data-driven networks for LBCs by increasing the vertical levels of the networks.However,the ensemble spread of the four experiments barely increases with lead time.Thus,each experiment has insufficient ensemble spread to present realistic forecast uncertainties,which will be investigated in a future study.展开更多
Although time-dependent deformation of geomaterials underpins slope-failure prediction models,the influence of strain rate on shearing strength and deformation behavior of loess remains unclear.The consolidated undrai...Although time-dependent deformation of geomaterials underpins slope-failure prediction models,the influence of strain rate on shearing strength and deformation behavior of loess remains unclear.The consolidated undrained(CU)and drained(CD)triaxial testing elucidated the impact of strain rate(0.005–0.3 mm/min)on strength envelopes,deformation moduli,pore pressures,and dilatancy characteristics of unsaturated and quasi-saturated loess.Under drained conditions with a controlled matric suction of 50 kPa,increasing strain rates from 0.005 mm/min to 0.011 mm/min induced decreases in failure deviatoric stress(qf),initial deformation modulus(Ei),and cohesion(c),while friction angles remained unaffected.Specimens displayed initial contractive volumetric strains transitioning to dilation across varying confining pressures.Higher rates diminished contractive volumetric strains and drainage volumes,indicating reduced densification and strength in the shear zone.Under undrained conditions,both unsaturated and quasi-saturated(pore pressure coefficient B=0.75)loess exhibited deteriorating mechanical properties with increasing rates from 0.03 mm/min to 0.3 mm/min.For unsaturated loess,reduced contractive volumetric strains at higher rates manifested relatively looser structures in the pre-peak stress phase.The strength decrement in quasi-saturated loess arose from elevated excess porewater pressures diminishing effective stresses.Negative porewater pressures emerged in quasi-saturated loess at lower confining pressures and strain rates.Compared to previous studies,the qf and Ei exhibited rate sensitivity below threshold values before attaining minima with marginal subsequent influence.The underlying mechanism mirrors the transition from creep to accelerated deformation phase of landslides.展开更多
In cold regions,rock structures will be weakened by freeze-thaw cycles under various water immersion conditions.Determining how water immersion conditions impact rock deterioration under freeze-thaw cycles is critical...In cold regions,rock structures will be weakened by freeze-thaw cycles under various water immersion conditions.Determining how water immersion conditions impact rock deterioration under freeze-thaw cycles is critical to assess accurately the frost resistance of engineered rock.In this paper,freeze-thaw cycles(temperature range of-20℃-20℃)were performed on the sandstones in different water immersion conditions(fully,partially and non-immersed in water).Then,computed tomography(CT)tests were conducted on the sandstones when the freeze-thaw number reached 0,5,10,15,20 and 30.Next,the effects of water immersion conditions on the microstructure deterioration of sandstone under freezethaw cycles were evaluated using CT spatial imaging,porosity and damage factor.Finally,focusing on the partially immersed condition,the immersion volume rate was defined to understand the effects of immersion degree on the freeze-thaw damage of sandstone and to propose a damage model considering the freeze-thaw number and immersion degree.The results show that with increasing freeze-thaw number,the porosities and damage factors under fully and partially immersed conditions increase continuously,while those under non-immersed condition first increase and then remain approximately constant.The most severe freeze-thaw damage occurs in fully immersed condition,followed by partially immersed condition and finally non-immersed condition.Interestingly,the freeze-thaw number and the immersion volume rate both impact the microstructure deterioration of the partially immersed sandstone.For the same freeze-thaw number,the damage factor increases approximately linearly with increasing immersion volume rate,and the increasing immersion degree exacerbates the microstructure deterioration of sandstone.Moreover,the proposed model can effectively estimate the freeze-thaw damage of partially immersed sandstone with different immersion volume rates.展开更多
Coriolis effects,encompassing the dilative,compressive,and deflective manifestations,constitute pivotal considerations in the centrifugal modelling of high-speed granular run-out processes.Notably,under the deflective...Coriolis effects,encompassing the dilative,compressive,and deflective manifestations,constitute pivotal considerations in the centrifugal modelling of high-speed granular run-out processes.Notably,under the deflective Coriolis condition,the velocity component parallel to the rotational axis exerts no influence on the magnitude of Coriolis acceleration.This circumstance implies a potential mitigation of the Coriolis force's deflective impact.Regrettably,extant investigations predominantly emphasize the dilative and compressive Coriolis effects,largely neglecting the pragmatic import of the deflective Coriolis condition.In pursuit of this gap,a series of discrete element method(DEM)simulations have been conducted to scrutinize the feasibility of centrifugal modelling for dry granular run-out processes under deflective Coriolis conditions.The findings concerning the deflective Coriolis effect reveal a consistent rise in the run-out distance by 2%–16%,a modest increase in bulk flow velocity of under 4%,and a slight elevation in average flow depth by no more than 25%.These alterations display smaller dependence on the specific testing conditions due to the granular flow undergoing dual deflections in opposing directions.This underscores the significance and utility of the deflective Coriolis condition.Notably,the anticipated reduction in error in predicting the final run-out distance is substantial,potentially reaching a 150%improvement compared to predictions made under the dilative and compressive Coriolis conditions.Therefore,the deflective Coriolis condition is advised when the final run-out distance of the granular flow is the main concern.To mitigate the impact of Coriolis acceleration,a greater initial height of the granular column is recommended,with a height/width ratio exceeding 1,as the basal friction of the granular material plays a crucial role in mitigating the deflective Coriolis effect.For more transverse-uniform flow properties,the width of the granular column should be as large as possible.展开更多
The initial stresses widely exist in elastic materials.While achieving a continuum stress-free configuration through compatible unloading is desirable,mechanical unloading alone frequently proves insufficient,posing c...The initial stresses widely exist in elastic materials.While achieving a continuum stress-free configuration through compatible unloading is desirable,mechanical unloading alone frequently proves insufficient,posing challenges in avoiding virtual stress-free configurations.In this paper,we introduce a novel concept of equivalent temperature variation to counteract the incompatible initial strain.Our focus is on initially stressed cylindrical and spherical elastomers,where we first derive the Saint-Venant,Beltrami-Michell,and Volterra integral conditions in orthogonal curvilinear coordinates using the exterior differential form theory.It is shown that for any given axially or spherically distributed initial stress,an equivalent temperature variation always exists.Furthermore,we propose two innovative initial stress forms based on the steady-state heat conduction.By introducing an equivalent temperature variation,the initial stress can be released through a compatible thermo-mechanical unloading process,offering valuable insights into the constitutive theory of initially stressed elastic materials.展开更多
This paper is concerned with a non-intrusive anomaly detection method for carving machine systems with variant working conditions,and a novel unsupervised detection framework that integrates convolutional autoencoder(...This paper is concerned with a non-intrusive anomaly detection method for carving machine systems with variant working conditions,and a novel unsupervised detection framework that integrates convolutional autoencoder(CAE)and Gaussian mixture hidden Markov model(GMHMM)is proposed.Firstly,the built-in sensor information under normal conditions is recorded,and a 1D convolutional autoencoder is employed to compress high-dimensional time series,thereby transforming the anomaly detection problem in high-dimensional space into a density estimation problem in a latent low-dimensional space.Then,two separate estimation networks are utilized to predict the mixture memberships and state transition probabilities for each sample,enabling GMHMM to handle low-dimensional representations and multi-condition information.Furthermore,a cost function comprising CAE reconstruction and GMHMM probability assessment is constructed for the low-dimensional representation generation and subsequent density estimation in an end-to-end fashion,and the joint optimization effectively enhances the anomaly detection performance.Finally,experiments are carried out on a self-developed multi-axis carving machine platform to validate the effectiveness and superiority of the proposed method.展开更多
Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain c...Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.展开更多
Frost heave in water-bearing rock masses poses significant threats to geotechnical engineering.This paper developed a novel three-dimensional(3D)frost model,based on the combined finite-discrete element method(FDEM),t...Frost heave in water-bearing rock masses poses significant threats to geotechnical engineering.This paper developed a novel three-dimensional(3D)frost model,based on the combined finite-discrete element method(FDEM),to investigate the frost heave process in rock masses where thermal transfer,water migration,water-ice phase transition(ice growth)and ice-rock interaction are explicitly simulated.The proposed model is first validated against existing experimental and analytical solutions,and further applied to investigate path-dependent frost heave behavior under various freezing conditions.Results show that freezing direction plays a vital role in the dynamic ice growth and ice-rock interaction,thus affecting the frost heave behavior.In the top-down freezing regime,ice plugs form first at the crack's top surface,sealing the crack and preventing water migration,which can amplify ice pressure.Parametric studies,including rock Young's modulus,ice-rock friction,and rock hydraulic conductivity,further reveal that the temporal aspects of ice development and rock mechanical response strongly affect ice-rock interaction and hence the frost heave mechanism.Furthermore,some typical phenomena(e.g.water/ice extrusion and frost cracking)can also be well captured in this model.This novel numerical framework sheds new light on frost heave behavior and enriches our understanding of frost heave mechanisms and ice-rock interaction processes within cold environment engineering projects.展开更多
In addition to the organic matter type,abundance,thermal maturity,and shale reservoir space,the preservation conditions of source rocks play a key factor in affecting the quantity and quality of retained hydrocarbons ...In addition to the organic matter type,abundance,thermal maturity,and shale reservoir space,the preservation conditions of source rocks play a key factor in affecting the quantity and quality of retained hydrocarbons in source rocks of lacustrine shale,yet this aspect has received little attention.This paper,based on the case analysis,explores how preservation conditions influence the enrichment of mobile hydrocarbons in shale oil.Research showns that good preservation conditions play three key roles.(1)Ensure the retention of sufficient light hydrocarbons(C_(1)–C_(13)),medium hydrocarbons(C_(14)–C_(25))and small molecular aromatics(including 1–2 benzene rings)in the formation,which enhances the fluidity and flow of shale oil;(2)Maintain a high energy field(abnormally high pressure),thus facilitating the maximum outflow of shale oil;(3)Ensure that the retained hydrocarbons have the miscible flow condition of multi-component hydrocarbons(light hydrocarbons,medium hydrocarbons,heavy hydrocarbons,and heteroatomic compounds),so that the heavy hydrocarbons(C_(25+))and heavy components(non-hydrocarbons and asphaltenes)have improved fluidity and maximum flow capacity.In conclusion,in addition to the advantages of organic matter type,abundance,thermal maturity,and reservoir space,good preservation conditions of shale layers are essential for the formation of economically viable shale oil reservoirs,which should be incorporated into the evaluation criteria of shale oil-rich areas/segments and considered a necessary factor when selecting favorable exploration targets.展开更多
Human dental pulp stem cell transplantation has been shown to be an effective therapeutic strategy for spinal cord injury.However,whether the human dental pulp stem cell secretome can contribute to functional recovery...Human dental pulp stem cell transplantation has been shown to be an effective therapeutic strategy for spinal cord injury.However,whether the human dental pulp stem cell secretome can contribute to functional recovery after spinal cord injury remains unclear.In the present study,we established a rat model of spinal cord injury based on impact injury from a dropped weight and then intraperitoneally injected the rats with conditioned medium from human dental pulp stem cells.We found that the conditioned medium effectively promoted the recovery of sensory and motor functions in rats with spinal cord injury,decreased expression of the microglial pyroptosis markers NLRP3,GSDMD,caspase-1,and interleukin-1β,promoted axonal and myelin regeneration,and inhibited the formation of glial scars.In addition,in a lipopolysaccharide-induced BV2 microglia model,conditioned medium from human dental pulp stem cells protected cells from pyroptosis by inhibiting the NLRP3/caspase-1/interleukin-1βpathway.These results indicate that conditioned medium from human dental pulp stem cells can reduce microglial pyroptosis by inhibiting the NLRP3/caspase-1/interleukin-1βpathway,thereby promoting the recovery of neurological function after spinal cord injury.Therefore,conditioned medium from human dental pulp stem cells may become an alternative therapy for spinal cord injury.展开更多
Dolichospermum spp.and Microcystis spp.are two common cyanobacteria that form blooms in the Changjiang(Yangtze)River basin,but the environmental conditions for their succession in large lakes are still unclear.Based o...Dolichospermum spp.and Microcystis spp.are two common cyanobacteria that form blooms in the Changjiang(Yangtze)River basin,but the environmental conditions for their succession in large lakes are still unclear.Based on daily monitoring data from Meiliang Bay in Taihu Lake from March to June,2016-2018,we studied the environmental conditions necessary for the succession of these two cyanobacteria.Results show that from March to June,the dominant genera of cyanobacteria experienced succession and co-dominated with Microcystis.The succession process included three stages.In StageⅠ,the biomass of Dolichospermum and Microcystis was similar(March),but Dolichospermum was dominant for most of the period.In StageⅡ,dominance alternated between Dolichospermum and Microcystis(April to mid-May).In StageⅢ,the biomass of Microcystis dominated(mid-May to June).In addition,temperature and nutrients across the three stages varied significantly.The average temperature increased continuously from 10.9 to 18.4,and to 24.2℃.The total nitrogen content decreased from 2.87 to 2.40,and to 1.86 mg/L.The total phosphorus content increased from 0.08 to 0.09,and to 0.12 mg/L.Correlation analysis revealed that Microcystis biomass was positively correlated with temperature and total phosphorus.Dolichospermum biomass was positively correlated with total nitrogen.Classification and regression tree displays that when the temperature was below 18.1℃,Dolichospermum dominated;above 18.1℃,Microcystis took over.Further analysis revealed that when temperature reached 18℃,the biomass of Microcystis increased exponentially,and the biomass of Dolichospermum exhibited a Gaussian distribution trend.This finding indicated that temperature was the key factor in the succession of Dolichospermum and Microcystis in nutrient-rich shallow lakes.As nitrogen and phosphorus concentrations decrease,the dominant species of cyanobacteria will diversify its development.The results of this study provide a foundation for risk prediction and control strategies for cyanobacterial blooms in lakes and reservoirs.展开更多
In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken a...In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.展开更多
Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate b...Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.To address this limitation,this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations.This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas.The up-to-down sequential method,which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach,was used to determine the structures of multivariate Dvine copulas.The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station,the inflow control station of the Longyangxia Reservoir in the Yellow River Basin.The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow.This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization.展开更多
Neuromorphic hardware equipped with associative learn-ing capabilities presents fascinating applications in the next generation of artificial intelligence.However,research into synaptic devices exhibiting complex asso...Neuromorphic hardware equipped with associative learn-ing capabilities presents fascinating applications in the next generation of artificial intelligence.However,research into synaptic devices exhibiting complex associative learning behaviors is still nascent.Here,an optoelec-tronic memristor based on Ag/TiO_(2) Nanowires:ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors.Effective implementation of synaptic behaviors,including long and short-term plasticity,and learning-forgetting-relearning behaviors,were achieved in the device through the application of light and electrical stimuli.Leveraging the optoelectronic co-modulated characteristics,a simulation of neuromorphic computing was conducted,resulting in a handwriting digit recognition accuracy of 88.9%.Furthermore,a 3×7 memristor array was constructed,confirming its application in artificial visual memory.Most importantly,complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli,respectively.After training through associative pairs,reflexes could be triggered solely using light stimuli.Comprehen-sively,under specific optoelectronic signal applications,the four features of classical conditioning,namely acquisition,extinction,recovery,and generalization,were elegantly emulated.This work provides an optoelectronic memristor with associative behavior capabilities,offering a pathway for advancing brain-machine interfaces,autonomous robots,and machine self-learning in the future.展开更多
The Guanpo pegmatite field in the North Qinling orogenic belt(NQB),China,hosts the most abundant LCT pegmatites.However,their emplacement conditions and structural control remain unexplored.In this contribution,we inv...The Guanpo pegmatite field in the North Qinling orogenic belt(NQB),China,hosts the most abundant LCT pegmatites.However,their emplacement conditions and structural control remain unexplored.In this contribution,we investigated it combining pegmatite orientation measurement with oxygen isotope geothermometry and fluid inclusion study.The orientations of type A1 pegmatites(P_(f)<σ_(2))are predominantly influenced by P-and T-fractures due to simple shearing in Shiziping dextral thrust shear zone during D_(2)deformation,whereas type A2 pegmatites(contemporaneous with D_(4))are governed by hydraulic fractures aligned with S_(0)and S_(0+1)stemming from fluid pressure(P_(f)<σ_(2)).Additionally,type B pegmatites(P_(f)≤σ_(2))exhibit orientations shaped by en echelon extensional fractures in local ductile shear zones(contemporaneous with D_(3)).The albite-quartz oxygen isotope geothermometry and microthermometric analysis of fluid inclusions in elbaites from the latest pegmatites(including types B and A2)suggest that the crystallization P-T for late magmatic and hydrothermal stages are 527.5-559.2℃,320℃,3.1-3.6 kbar and 2.0 kbar,respectively.Our observations along with previous studies suggest that the genesis of the LCT pegmatites was a long-term,multi-stage event during early Paleozoic orogeny(including the collision stage)of the NQB,and was facilitated by various local fractures.展开更多
基金supported partly by the National Natural Science Foundation of China,No.82071332the Chongqing Natural Science Foundation Joint Fund for Innovation and Development,No.CSTB2023NSCQ-LZX0041 (both to ZG)。
文摘Some studies have confirmed the neuroprotective effect of remote ischemic conditioning against stroke. Although numerous animal researches have shown that the neuroprotective effect of remote ischemic conditioning may be related to neuroinflammation, cellular immunity, apoptosis, and autophagy, the exact underlying molecular mechanisms are unclear. This review summarizes the current status of different types of remote ischemic conditioning methods in animal and clinical studies and analyzes their commonalities and differences in neuroprotective mechanisms and signaling pathways. Remote ischemic conditioning has emerged as a potential therapeutic approach for improving stroke-induced brain injury owing to its simplicity, non-invasiveness, safety, and patient tolerability. Different forms of remote ischemic conditioning exhibit distinct intervention patterns, timing, and application range. Mechanistically, remote ischemic conditioning can exert neuroprotective effects by activating the Notch1/phosphatidylinositol 3-kinase/Akt signaling pathway, improving cerebral perfusion, suppressing neuroinflammation, inhibiting cell apoptosis, activating autophagy, and promoting neural regeneration. While remote ischemic conditioning has shown potential in improving stroke outcomes, its full clinical translation has not yet been achieved.
文摘Gassy soils are distributed in relatively shallow layers the Quaternary deposit in Hangzhou Bay area. The shallow gassy soils significantly affect the construction of underground projects. Proper characterization of spatial distribution of shallow gassy soils is indispensable prior to construction of underground projects in the area. Due to the costly conditions required in the site investigation for gassy soils, only a limited number of gas pressure data can be obtained in engineering practice, which leads to the uncertainty in characterizing spatial distribution of gassy soils. Determining the number of boreholes for investigating gassy soils and their corresponding locations is pivotal to reducing construction risk induced by gassy soils. However, this primarily relies on the engineering experience in the current site investigation practice. This study develops a probabilistic site investigation optimization method for planning investigation schemes (including the number and locations of boreholes) of gassy soils based on the conditional random field and Monte Carlo simulation. The proposed method aims to provide an optimal investigation scheme before the site investigation based on prior knowledge. Finally, the proposed approach is illustrated using a case study.
文摘The study of the morphometric parameters of the three most abundant species in the lower course of the Kouilou River (Chrysichthys auratus, Liza falcipinnis and Pellonula vorax) was carried out. The standard length of Chrysichthys auratus varies between 43.57 and 210 mm, for an average of 96.70 ± 28.63 mm;the weight varies between 2.92 and 140.83 mg, an average of 73.03 ± 21.62 mg. The condition coefficient is equal to 4.42 ± 1.52. Liza falcipinnis has a standard length which varies between 59.9 mm and 158.08 mm for an average of 88.15 ± 29.74 mm;its weight varies between 4.77 and 76.21 mg, an average of 18.61 ± 11.82 mg. The condition coefficient is equal to 2.47 ± 1.57. Pellonula vorax has a standard length which varies between 60.33 mm and 117.72 mm;for an average of 80.48 ± 17.75 mm;the weight varies between 3.61 and 25.17 mg, an average of 9.03 ± 3.61 mg. The condition coefficient is equal to 2.17 ± 0.57. These three species have a minor allometric growth.
基金supported by the National Natural Science Foundation of China(Grant No.91744311).
文摘We used observed concentrations of air pollutants,reanalyzed meteorological parameters,and results from the Goddard Earth Observing System Chemical Transport Model to examine the relationships between concentrations of maximum daily 8-h average ozone(MDA8 O_(3)),PM_(2.5)(particulate matter with diameter of 2.5μm or less),and PM_(2.5)components and 2-m temperature(T2)or relative humidity(RH),as well as the effectiveness of precursor emission reductions on the control of O_(3) and PM_(2.5) in Beijing–Tianjin–Hebei(BTH)under different summertime temperature and humidity conditions.Both observed(simulated)MDA8 O_(3) and PM_(2.5) concentrations increased as T2 went up,with linear trends of 4.8(3.2)ppb℃^(−1) and 1.9(1.5)μg m^(−3)℃^(−1),respectively.Model results showed that the decreases in MDA8 O_(3) from precursor emission reductions were more sensitive to T2 than to RH.Reducing a larger proportion of volatile organic compound(VOC)emissions at higher T2 was more effective for the control of summertime O_(3) in BTH.For the control of summertime PM_(2.5) in BTH,reducing nitrogen oxides(NOx)combined with a small proportion of VOCs was the best measure.The magnitude of reduction in PM_(2.5) from reducing precursor emissions was more sensitive to RH than to T2,with the best efficiency at high RH.Results from this study are helpful for formulating effective policies to tackle O_(3) and PM_(2.5) pollution in BTH.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(Grant No.2022D01B 187)。
文摘Federated learning(FL)is a distributed machine learning paradigm for edge cloud computing.FL can facilitate data-driven decision-making in tactical scenarios,effectively addressing both data volume and infrastructure challenges in edge environments.However,the diversity of clients in edge cloud computing presents significant challenges for FL.Personalized federated learning(pFL)received considerable attention in recent years.One example of pFL involves exploiting the global and local information in the local model.Current pFL algorithms experience limitations such as slow convergence speed,catastrophic forgetting,and poor performance in complex tasks,which still have significant shortcomings compared to the centralized learning.To achieve high pFL performance,we propose FedCLCC:Federated Contrastive Learning and Conditional Computing.The core of FedCLCC is the use of contrastive learning and conditional computing.Contrastive learning determines the feature representation similarity to adjust the local model.Conditional computing separates the global and local information and feeds it to their corresponding heads for global and local handling.Our comprehensive experiments demonstrate that FedCLCC outperforms other state-of-the-art FL algorithms.
基金supported by the Strategic Research and Consulting Project of the Chinese Academy of Engineering[grant number 2024-XBZD-14]the National Natural Science Foundation of China[grant numbers 42192553 and 41922036]the Fundamental Research Funds for the Central Universities–Cemac“GeoX”Interdisciplinary Program[grant number 020714380207]。
文摘The impacts of lateral boundary conditions(LBCs)provided by numerical models and data-driven networks on convective-scale ensemble forecasts are investigated in this study.Four experiments are conducted on the Hangzhou RDP(19th Hangzhou Asian Games Research Development Project on Convective-scale Ensemble Prediction and Application)testbed,with the LBCs respectively sourced from National Centers for Environmental Prediction(NCEP)Global Forecast System(GFS)forecasts with 33 vertical levels(Exp_GFS),Pangu forecasts with 13 vertical levels(Exp_Pangu),Fuxi forecasts with 13 vertical levels(Exp_Fuxi),and NCEP GFS forecasts with the vertical levels reduced to 13(the same as those of Exp_Pangu and Exp_Fuxi)(Exp_GFSRDV).In general,Exp_Pangu performs comparably to Exp_GFS,while Exp_Fuxi shows slightly inferior performance compared to Exp_Pangu,possibly due to its less accurate large-scale predictions.Therefore,the ability of using data-driven networks to efficiently provide LBCs for convective-scale ensemble forecasts has been demonstrated.Moreover,Exp_GFSRDV has the worst convective-scale forecasts among the four experiments,which indicates the potential improvement of using data-driven networks for LBCs by increasing the vertical levels of the networks.However,the ensemble spread of the four experiments barely increases with lead time.Thus,each experiment has insufficient ensemble spread to present realistic forecast uncertainties,which will be investigated in a future study.
文摘Although time-dependent deformation of geomaterials underpins slope-failure prediction models,the influence of strain rate on shearing strength and deformation behavior of loess remains unclear.The consolidated undrained(CU)and drained(CD)triaxial testing elucidated the impact of strain rate(0.005–0.3 mm/min)on strength envelopes,deformation moduli,pore pressures,and dilatancy characteristics of unsaturated and quasi-saturated loess.Under drained conditions with a controlled matric suction of 50 kPa,increasing strain rates from 0.005 mm/min to 0.011 mm/min induced decreases in failure deviatoric stress(qf),initial deformation modulus(Ei),and cohesion(c),while friction angles remained unaffected.Specimens displayed initial contractive volumetric strains transitioning to dilation across varying confining pressures.Higher rates diminished contractive volumetric strains and drainage volumes,indicating reduced densification and strength in the shear zone.Under undrained conditions,both unsaturated and quasi-saturated(pore pressure coefficient B=0.75)loess exhibited deteriorating mechanical properties with increasing rates from 0.03 mm/min to 0.3 mm/min.For unsaturated loess,reduced contractive volumetric strains at higher rates manifested relatively looser structures in the pre-peak stress phase.The strength decrement in quasi-saturated loess arose from elevated excess porewater pressures diminishing effective stresses.Negative porewater pressures emerged in quasi-saturated loess at lower confining pressures and strain rates.Compared to previous studies,the qf and Ei exhibited rate sensitivity below threshold values before attaining minima with marginal subsequent influence.The underlying mechanism mirrors the transition from creep to accelerated deformation phase of landslides.
基金funding support from the National Natural Science Foundation of China(Grant No.12172019).
文摘In cold regions,rock structures will be weakened by freeze-thaw cycles under various water immersion conditions.Determining how water immersion conditions impact rock deterioration under freeze-thaw cycles is critical to assess accurately the frost resistance of engineered rock.In this paper,freeze-thaw cycles(temperature range of-20℃-20℃)were performed on the sandstones in different water immersion conditions(fully,partially and non-immersed in water).Then,computed tomography(CT)tests were conducted on the sandstones when the freeze-thaw number reached 0,5,10,15,20 and 30.Next,the effects of water immersion conditions on the microstructure deterioration of sandstone under freezethaw cycles were evaluated using CT spatial imaging,porosity and damage factor.Finally,focusing on the partially immersed condition,the immersion volume rate was defined to understand the effects of immersion degree on the freeze-thaw damage of sandstone and to propose a damage model considering the freeze-thaw number and immersion degree.The results show that with increasing freeze-thaw number,the porosities and damage factors under fully and partially immersed conditions increase continuously,while those under non-immersed condition first increase and then remain approximately constant.The most severe freeze-thaw damage occurs in fully immersed condition,followed by partially immersed condition and finally non-immersed condition.Interestingly,the freeze-thaw number and the immersion volume rate both impact the microstructure deterioration of the partially immersed sandstone.For the same freeze-thaw number,the damage factor increases approximately linearly with increasing immersion volume rate,and the increasing immersion degree exacerbates the microstructure deterioration of sandstone.Moreover,the proposed model can effectively estimate the freeze-thaw damage of partially immersed sandstone with different immersion volume rates.
基金supported by the National Natural Science Foundation of China(Grant Nos.42120104008 and 42307214)the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20230620).
文摘Coriolis effects,encompassing the dilative,compressive,and deflective manifestations,constitute pivotal considerations in the centrifugal modelling of high-speed granular run-out processes.Notably,under the deflective Coriolis condition,the velocity component parallel to the rotational axis exerts no influence on the magnitude of Coriolis acceleration.This circumstance implies a potential mitigation of the Coriolis force's deflective impact.Regrettably,extant investigations predominantly emphasize the dilative and compressive Coriolis effects,largely neglecting the pragmatic import of the deflective Coriolis condition.In pursuit of this gap,a series of discrete element method(DEM)simulations have been conducted to scrutinize the feasibility of centrifugal modelling for dry granular run-out processes under deflective Coriolis conditions.The findings concerning the deflective Coriolis effect reveal a consistent rise in the run-out distance by 2%–16%,a modest increase in bulk flow velocity of under 4%,and a slight elevation in average flow depth by no more than 25%.These alterations display smaller dependence on the specific testing conditions due to the granular flow undergoing dual deflections in opposing directions.This underscores the significance and utility of the deflective Coriolis condition.Notably,the anticipated reduction in error in predicting the final run-out distance is substantial,potentially reaching a 150%improvement compared to predictions made under the dilative and compressive Coriolis conditions.Therefore,the deflective Coriolis condition is advised when the final run-out distance of the granular flow is the main concern.To mitigate the impact of Coriolis acceleration,a greater initial height of the granular column is recommended,with a height/width ratio exceeding 1,as the basal friction of the granular material plays a crucial role in mitigating the deflective Coriolis effect.For more transverse-uniform flow properties,the width of the granular column should be as large as possible.
基金Project supported by the National Natural Science Foundation of China(Nos.12241205 and 12032019)the National Key Research and Development Program of China(No.2022YFA1203200)the Strategic Priority Research Program of Chinese Academy of Sciences(Nos.XDB0620101 and XDB0620103)。
文摘The initial stresses widely exist in elastic materials.While achieving a continuum stress-free configuration through compatible unloading is desirable,mechanical unloading alone frequently proves insufficient,posing challenges in avoiding virtual stress-free configurations.In this paper,we introduce a novel concept of equivalent temperature variation to counteract the incompatible initial strain.Our focus is on initially stressed cylindrical and spherical elastomers,where we first derive the Saint-Venant,Beltrami-Michell,and Volterra integral conditions in orthogonal curvilinear coordinates using the exterior differential form theory.It is shown that for any given axially or spherically distributed initial stress,an equivalent temperature variation always exists.Furthermore,we propose two innovative initial stress forms based on the steady-state heat conduction.By introducing an equivalent temperature variation,the initial stress can be released through a compatible thermo-mechanical unloading process,offering valuable insights into the constitutive theory of initially stressed elastic materials.
基金Supported by the National Natural Science Foundation of China(No.62203390).
文摘This paper is concerned with a non-intrusive anomaly detection method for carving machine systems with variant working conditions,and a novel unsupervised detection framework that integrates convolutional autoencoder(CAE)and Gaussian mixture hidden Markov model(GMHMM)is proposed.Firstly,the built-in sensor information under normal conditions is recorded,and a 1D convolutional autoencoder is employed to compress high-dimensional time series,thereby transforming the anomaly detection problem in high-dimensional space into a density estimation problem in a latent low-dimensional space.Then,two separate estimation networks are utilized to predict the mixture memberships and state transition probabilities for each sample,enabling GMHMM to handle low-dimensional representations and multi-condition information.Furthermore,a cost function comprising CAE reconstruction and GMHMM probability assessment is constructed for the low-dimensional representation generation and subsequent density estimation in an end-to-end fashion,and the joint optimization effectively enhances the anomaly detection performance.Finally,experiments are carried out on a self-developed multi-axis carving machine platform to validate the effectiveness and superiority of the proposed method.
基金funded by the Natural Science Foundation of China(Grant Nos.42377164 and 41972280)the Badong National Observation and Research Station of Geohazards(Grant No.BNORSG-202305).
文摘Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.
基金supported by the Natural Sciences and Engineering Research Council of Canada(Grant Nos.Discovery 341275,and CRDPJ 543894-19)NSERC/Energi Simulation Industrial Research Chair programState Key Laboratory of Geohazard Prevention and Geoenvironment Protection Open Fund(Grant No.SKLGP2024K001).
文摘Frost heave in water-bearing rock masses poses significant threats to geotechnical engineering.This paper developed a novel three-dimensional(3D)frost model,based on the combined finite-discrete element method(FDEM),to investigate the frost heave process in rock masses where thermal transfer,water migration,water-ice phase transition(ice growth)and ice-rock interaction are explicitly simulated.The proposed model is first validated against existing experimental and analytical solutions,and further applied to investigate path-dependent frost heave behavior under various freezing conditions.Results show that freezing direction plays a vital role in the dynamic ice growth and ice-rock interaction,thus affecting the frost heave behavior.In the top-down freezing regime,ice plugs form first at the crack's top surface,sealing the crack and preventing water migration,which can amplify ice pressure.Parametric studies,including rock Young's modulus,ice-rock friction,and rock hydraulic conductivity,further reveal that the temporal aspects of ice development and rock mechanical response strongly affect ice-rock interaction and hence the frost heave mechanism.Furthermore,some typical phenomena(e.g.water/ice extrusion and frost cracking)can also be well captured in this model.This novel numerical framework sheds new light on frost heave behavior and enriches our understanding of frost heave mechanisms and ice-rock interaction processes within cold environment engineering projects.
基金Supported by the National Natural Science Foundation of China(U22B6004)Project of PetroChina Research Institute of Petroleum Exploration and Development(2022yjcq03)Core Technology Key Project of China Petroleum Changqing Oilfield Company(KJZX2023-01).
文摘In addition to the organic matter type,abundance,thermal maturity,and shale reservoir space,the preservation conditions of source rocks play a key factor in affecting the quantity and quality of retained hydrocarbons in source rocks of lacustrine shale,yet this aspect has received little attention.This paper,based on the case analysis,explores how preservation conditions influence the enrichment of mobile hydrocarbons in shale oil.Research showns that good preservation conditions play three key roles.(1)Ensure the retention of sufficient light hydrocarbons(C_(1)–C_(13)),medium hydrocarbons(C_(14)–C_(25))and small molecular aromatics(including 1–2 benzene rings)in the formation,which enhances the fluidity and flow of shale oil;(2)Maintain a high energy field(abnormally high pressure),thus facilitating the maximum outflow of shale oil;(3)Ensure that the retained hydrocarbons have the miscible flow condition of multi-component hydrocarbons(light hydrocarbons,medium hydrocarbons,heavy hydrocarbons,and heteroatomic compounds),so that the heavy hydrocarbons(C_(25+))and heavy components(non-hydrocarbons and asphaltenes)have improved fluidity and maximum flow capacity.In conclusion,in addition to the advantages of organic matter type,abundance,thermal maturity,and reservoir space,good preservation conditions of shale layers are essential for the formation of economically viable shale oil reservoirs,which should be incorporated into the evaluation criteria of shale oil-rich areas/segments and considered a necessary factor when selecting favorable exploration targets.
基金supported by the Research Foundation of Technology Committee of Tongzhou District,No.KJ2019CX001(to SX).
文摘Human dental pulp stem cell transplantation has been shown to be an effective therapeutic strategy for spinal cord injury.However,whether the human dental pulp stem cell secretome can contribute to functional recovery after spinal cord injury remains unclear.In the present study,we established a rat model of spinal cord injury based on impact injury from a dropped weight and then intraperitoneally injected the rats with conditioned medium from human dental pulp stem cells.We found that the conditioned medium effectively promoted the recovery of sensory and motor functions in rats with spinal cord injury,decreased expression of the microglial pyroptosis markers NLRP3,GSDMD,caspase-1,and interleukin-1β,promoted axonal and myelin regeneration,and inhibited the formation of glial scars.In addition,in a lipopolysaccharide-induced BV2 microglia model,conditioned medium from human dental pulp stem cells protected cells from pyroptosis by inhibiting the NLRP3/caspase-1/interleukin-1βpathway.These results indicate that conditioned medium from human dental pulp stem cells can reduce microglial pyroptosis by inhibiting the NLRP3/caspase-1/interleukin-1βpathway,thereby promoting the recovery of neurological function after spinal cord injury.Therefore,conditioned medium from human dental pulp stem cells may become an alternative therapy for spinal cord injury.
基金Supported by the National Natural Science Foundation of China(No.42007159)the Network Security and Informatization Project of Chinese Academy of Sciences(No.CAS-WX2021SF-050402)+2 种基金the Water Science and Technology Project of Jiangsu Province(No.2020004)the Key Project of Nanjing Institute of Geography and LimnologyChinese Academy of Sciences(No.NIGLAS2022GS03)。
文摘Dolichospermum spp.and Microcystis spp.are two common cyanobacteria that form blooms in the Changjiang(Yangtze)River basin,but the environmental conditions for their succession in large lakes are still unclear.Based on daily monitoring data from Meiliang Bay in Taihu Lake from March to June,2016-2018,we studied the environmental conditions necessary for the succession of these two cyanobacteria.Results show that from March to June,the dominant genera of cyanobacteria experienced succession and co-dominated with Microcystis.The succession process included three stages.In StageⅠ,the biomass of Dolichospermum and Microcystis was similar(March),but Dolichospermum was dominant for most of the period.In StageⅡ,dominance alternated between Dolichospermum and Microcystis(April to mid-May).In StageⅢ,the biomass of Microcystis dominated(mid-May to June).In addition,temperature and nutrients across the three stages varied significantly.The average temperature increased continuously from 10.9 to 18.4,and to 24.2℃.The total nitrogen content decreased from 2.87 to 2.40,and to 1.86 mg/L.The total phosphorus content increased from 0.08 to 0.09,and to 0.12 mg/L.Correlation analysis revealed that Microcystis biomass was positively correlated with temperature and total phosphorus.Dolichospermum biomass was positively correlated with total nitrogen.Classification and regression tree displays that when the temperature was below 18.1℃,Dolichospermum dominated;above 18.1℃,Microcystis took over.Further analysis revealed that when temperature reached 18℃,the biomass of Microcystis increased exponentially,and the biomass of Dolichospermum exhibited a Gaussian distribution trend.This finding indicated that temperature was the key factor in the succession of Dolichospermum and Microcystis in nutrient-rich shallow lakes.As nitrogen and phosphorus concentrations decrease,the dominant species of cyanobacteria will diversify its development.The results of this study provide a foundation for risk prediction and control strategies for cyanobacterial blooms in lakes and reservoirs.
基金This work is funded by the National Natural Science Foundation of China(Grant Nos.42377164 and 52079062)the National Science Fund for Distinguished Young Scholars of China(Grant No.52222905).
文摘In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.
基金supported by the National Natural Science Foundation of China(Grant No.52109010)the Postdoctoral Science Foundation of China(Grant No.2021M701047)the China National Postdoctoral Program for Innovative Talents(Grant No.BX20200113).
文摘Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.To address this limitation,this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations.This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas.The up-to-down sequential method,which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach,was used to determine the structures of multivariate Dvine copulas.The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station,the inflow control station of the Longyangxia Reservoir in the Yellow River Basin.The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow.This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization.
基金This work was supported by the Jinan City-University Integrated Development Strategy Project under Grant(JNSX2023017)National Research Foundation of Korea(NRF)grant funded by the Korea government(MIST)(RS-2023-00302751)+1 种基金by the National Research Foundation of Korea(NRF)funded by the Ministry of Education under Grants 2018R1A6A1A03025242 and 2018R1D1A1A09083353by Qilu Young Scholar Program of Shandong University.
文摘Neuromorphic hardware equipped with associative learn-ing capabilities presents fascinating applications in the next generation of artificial intelligence.However,research into synaptic devices exhibiting complex associative learning behaviors is still nascent.Here,an optoelec-tronic memristor based on Ag/TiO_(2) Nanowires:ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors.Effective implementation of synaptic behaviors,including long and short-term plasticity,and learning-forgetting-relearning behaviors,were achieved in the device through the application of light and electrical stimuli.Leveraging the optoelectronic co-modulated characteristics,a simulation of neuromorphic computing was conducted,resulting in a handwriting digit recognition accuracy of 88.9%.Furthermore,a 3×7 memristor array was constructed,confirming its application in artificial visual memory.Most importantly,complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli,respectively.After training through associative pairs,reflexes could be triggered solely using light stimuli.Comprehen-sively,under specific optoelectronic signal applications,the four features of classical conditioning,namely acquisition,extinction,recovery,and generalization,were elegantly emulated.This work provides an optoelectronic memristor with associative behavior capabilities,offering a pathway for advancing brain-machine interfaces,autonomous robots,and machine self-learning in the future.
基金supported by the National Key R&D Program of China(Grant Nos.2021YFC2901902 and 2019YFC0605202)。
文摘The Guanpo pegmatite field in the North Qinling orogenic belt(NQB),China,hosts the most abundant LCT pegmatites.However,their emplacement conditions and structural control remain unexplored.In this contribution,we investigated it combining pegmatite orientation measurement with oxygen isotope geothermometry and fluid inclusion study.The orientations of type A1 pegmatites(P_(f)<σ_(2))are predominantly influenced by P-and T-fractures due to simple shearing in Shiziping dextral thrust shear zone during D_(2)deformation,whereas type A2 pegmatites(contemporaneous with D_(4))are governed by hydraulic fractures aligned with S_(0)and S_(0+1)stemming from fluid pressure(P_(f)<σ_(2)).Additionally,type B pegmatites(P_(f)≤σ_(2))exhibit orientations shaped by en echelon extensional fractures in local ductile shear zones(contemporaneous with D_(3)).The albite-quartz oxygen isotope geothermometry and microthermometric analysis of fluid inclusions in elbaites from the latest pegmatites(including types B and A2)suggest that the crystallization P-T for late magmatic and hydrothermal stages are 527.5-559.2℃,320℃,3.1-3.6 kbar and 2.0 kbar,respectively.Our observations along with previous studies suggest that the genesis of the LCT pegmatites was a long-term,multi-stage event during early Paleozoic orogeny(including the collision stage)of the NQB,and was facilitated by various local fractures.
