Ploidy and fruit trait variation in oil-tea Camellia:Implications for ploidy breeding

Plant polyploidy often occurs in conjunction with higher yield and superior quality.Therefore,obtaining polyploid germplasms is a significant part of breeding.The oil-tea Camellia tree is an important native woody plant that produces high-quality edible oil and includes many species of Camellia with different ploidies.However,whether higher ploidy levels in oil-tea Camellia trees are related to better traits remains unclear.In this study,the ploidy levels of 30 different oil-tea Camellia strains in three different species in the Sect.Paracamellia were determined by flow cytometry and chromosome preparation,and the phenotypic characteristics and fatty acid compositions of the fruits were examined by field observations and laboratory analyses.The correlations between the ploidy level of oil-tea Camellia and the main traits of the fruit were investigated.Our results showed that 10 Camellia lanceoleosa strains were diploid,10 Camellia meiocarpa strains were tetraploid and 10 Camellia oleifera strains were hexaploid.Hexaploid C.oleifera had larger fruit size and weight,more seeds per fruit,greater seed weight per fruit,higher oil content and greater yield per crown width than tetraploid C.meiocarpa and diploid C.lanceoleosa,but their fruit peel thickness and fresh seed rate were significantly lower,and these traits were significantly correlated with ploidy level.In addition,in terms of fatty acid composition,hexaploid C.oleifera had a higher oleic acid content than tetraploid C.meiocarpa and diploid C.lanceoleosa,but their linoleic acid,linolenic acid and arachidonic acid contents were lower.The contents of palmitic acid,stearic acid and total unsaturated fatty acids were not significantly correlated with ploidy level.In conclusion,certain correlations exist between the main characteristics of oil-tea Camellia fruit and the ploidy level,and increasing the ploidy level led to an increase in fruit yield with no effect on oil composition.The discovery of variations in the main characteristics of oil-tea Camellia fruit with different ploidies will facilitate germplasm innovation and lay a foundation for ploidy breeding and mechanistic research on fruit traits.

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

Monitoring and evaluation of the water quality of the Lower Neches River, Texas, USA

Increasing bacteria levels in the Lower Neches River caused by Hurricane Harvey has been of a serious concern.This study is to analyze the historical water sampling measurements and real-time water quality data collected with wireless sensors to monitor and evaluate water quality under different hydrological and hydraulic conditions.The statistical and Pearson correlation analysis on historical water samples determines that alkalinity,chloride,hardness,conductivity,and pH are highly correlated,and they decrease with increasing flow rate due to dilution.The flow rate has positive correlations with Escherichia coli,total suspended solids,and turbidity,which demonstrates that runoff is one of the causes of the elevated bacteria and sediment loadings in the river.The correlation between E.coli and turbidity indicates that turbidity greater than 45 nephelometric turbidity units in the Neches River can serve as a proxy for E.coli to indicate the bacterial outbreak.A series of statistical tools and an innovative two-layer data smoothing filter are developed to detect outliers,fill missing values,and filter spikes of the sensor measurements.The correlation analysis on the sensor data illustrates that the elevated sediment/bacteria/algae in the river is either caused by the first flush rain and heavy rain events in December to March or practices of land use and land cover.Therefore,utilizing sensor measurements along with rainfall and discharge data is recommended to monitor and evaluate water quality,then in turn to provide early alerts on water resources management decisions.

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

Three-Dimensional Sound Source Location Algorithm for Subsea Leakage Using Hydrophone

Leakages from subsea oil and gas equipment cause substantial economic losses and damage to marine ecosystem,so it is essential to locate the source of the leak.However,due to the complexity and variability of the marine environment,the signals collected by hydrophone contain a variety of noises,which makes it challenging to extract useful signals for localization.To solve this problem,a hydrophone denoising algorithm is proposed based on variational modal decomposition(VMD)with grey wolf optimization.First,the average envelope entropy is used as the fitness function of the grey wolf optimizer to find the optimal solution for the parameters K andα.Afterward,the VMD algorithm decomposes the original signal parameters to obtain the intrinsic mode functions(IMFs).Subsequently,the number of interrelationships between each IMF and the original signal was calculated,the threshold value was set,and the noise signal was removed to calculate the time difference using the valid signal obtained by reconstruction.Finally,the arrival time difference is used to locate the origin of the leak.The localization accuracy of the method in finding leaks is investigated experimentally by constructing a simulated leak test rig,and the effectiveness and feasibility of the method are verified.

Natural gas exploration potential and favorable targets of Permian Fengcheng Formation in the western Central Depression of Junggar Basin,NW China

Based on the organic geochemical data and the molecular and stable carbon isotopic compositions of natural gas of the Lower Permian Fengcheng Formation in the western Central Depression of Junggar Basin,combined with sedimentary environment analysis and hydrocarbon-generating simulation,the gas-generating potential of the Fengcheng source rock is evaluated,the distribution of large-scale effective source kitchen is described,the genetic types of natural gas are clarified,and four types of favorable exploration targets are selected.The results show that:(1)The Fengcheng Formation is a set of oil-prone source rocks,and the retained liquid hydrocarbon is conducive to late cracking into gas,with characteristics of high gas-generating potential and late accumulation;(2)The maximum thickness of Fengcheng source rock reaches 900 m.The source rock has entered the main gas-generating stage in Penyijingxi and Shawan sags,and the area with gas-generating intensity greater than 20×10^(8) m^(3)/km^(2) is approximately 6500 km^(2).(3)Around the western Central Depression,highly mature oil-type gas with light carbon isotope composition was identified to be derived from the Fengcheng source rocks mainly,while the rest was coal-derived gas from the Carboniferous source rock;(4)Four types of favorable exploration targets with exploration potential were developed in the western Central Depression which are structural traps neighboring to the source,stratigraphic traps neighboring to the source,shale-gas type within the source,and structural traps within the source.Great attention should be paid to these targets.

Meta-analysis of the association between chronic periodontitis and chronic kidney disease

BACKGROUND Many scholars have performed several clinical studies have investigated the association between chronic periodontitis(CP)and chronic kidney disease(CKD).However,there are still differences between these research results,and there is no unified conclusion.Therefore,a systematic review is required to understand this issue fully.AIM To explore the correlation between CP and CKD.METHODS Literature on the correlation between CP and CKD,as well as the clinical attachment level(CAL)and pocket probing depth(PPD)of CKD and non-CKD,were retrieved from PubMed,Embase,the Cochrane Library,and Web of Science repositories until January 2024.After the effective data were extracted,data processing and statistics were performed using Stata 12.0.RESULTS Of the 22 studies,13 were related to CP and CKD,and 9 reported CAL and PPD in patients with CKD and healthy controls.Meta-analysis of the correlation between CP and CKD revealed that CKD probability in people with CP was 1.54 times that of healthy individuals[relative risk=1.54,95%confidence interval(CI):1.40-1.70],and CP incidence in patients with CKD was 1.98 times that of healthy individuals[overall risk(OR)=1.98,95%CI:1.53-2.57].Meta-analysis of CAL and PPD evaluations between CKD patients and healthy individuals showed that CAL and PPD levels were higher in CKD patients[standard mean difference(SMD)of CAL=0.65,95%CI:0.29-1.01;SMD of PPD=0.33,95%CI:0.02-0.63].CONCLUSION A bidirectional association exists between CP and CKD.CKD risk is increased in CP patients and vice versa.Periodontal tissue or tooth loss risks increase over time in CKD patients.

Tensile strength and failure behavior of rock-mortar interfaces: Direct and indirect measurements

The tensile strength at the rock-concrete interface is one of the crucial factors controlling the failure mechanisms of structures,such as concrete gravity dams.Despite the critical importance of the failure mechanism and tensile strength of rock-concrete interfaces,understanding of these factors remains very limited.This study investigated the tensile strength and fracturing processes at rock-mortar interfaces subjected to direct and indirect tensile loadings.Digital image correlation(DIC)and acoustic emission(AE)techniques were used to monitor the failure mechanisms of specimens subjected to direct tension and indirect loading(Brazilian tests).The results indicated that the direct tensile strength of the rock-mortar specimens was lower than their indirect tensile strength,with a direct/indirect tensile strength ratio of 65%.DIC strain field data and moment tensor inversions(MTI)of AE events indicated that a significant number of shear microcracks occurred in the specimens subjected to the Brazilian test.The presence of these shear microcracks,which require more energy to break,resulted in a higher tensile strength during the Brazilian tests.In contrast,microcracks were predominantly tensile in specimens subjected to direct tension,leading to a lower tensile strength.Spatiotemporal monitoring of the cracking processes in the rock-mortar interfaces revealed that they show AE precursors before failure under the Brazilian test,whereas they show a minimal number of AE events before failure under direct tension.Due to different microcracking mechanisms,specimens tested under Brazilian tests showed lower roughness with flatter fracture surfaces than those tested under direct tension with jagged and rough fracture surfaces.The results of this study shed light on better understanding the micromechanics of damage in the rock-concrete interfaces for a safer design of engineering structures.

Impacts of climate change and human activities on vegetation dynamics on the Mongolian Plateau, East Asia from 2000 to 2023

The Mongolian Plateau in East Asia is one of the largest contingent arid and semi-arid areas of the world.Under the impacts of climate change and human activities,desertification is becoming increasingly severe on the Mongolian Plateau.Understanding the vegetation dynamics in this region can better characterize its ecological changes.In this study,based on Moderate Resolution Imaging Spectroradiometer(MODIS)images,we calculated the kernel normalized difference vegetation index(kNDVI)on the Mongolian Plateau from 2000 to 2023,and analyzed the changes in kNDVI using the Theil-Sen median trend analysis and Mann-Kendall significance test.We further investigated the impact of climate change on kNDVI change using partial correlation analysis and composite correlation analysis,and quantified the effects of climate change and human activities on kNDVI change by residual analysis.The results showed that kNDVI on the Mongolian Plateau was increasing overall,and the vegetation recovery area in the southern region was significantly larger than that in the northern region.About 50.99%of the plateau showed dominant climate-driven effects of temperature,precipitation,and wind speed on kNDVI change.Residual analysis showed that climate change and human activities together contributed to 94.79%of the areas with vegetation improvement.Appropriate human activities promoted the recovery of local vegetation,and climate change inhibited vegetation growth in the northern part of the Mongolian Plateau.This study provides scientific data for understanding the regional ecological environment status and future changes and developing effective ecological protection measures on the Mongolian Plateau.

Genetic parameter evaluation for growth and cold resistance traits of the giant freshwater prawn Macrobrachium rosenbergii

The giant freshwater prawn Macrobrachium rosenbergii distributed from tropical to subtropical regions,is a warm-water species,and its survival temperature is 14-35°C,which greatly limits its culture cycle and culture area in China.Therefore,it is urgent to cultivate a new high quality,high yield variety with improved cold-resistance,but the genetic parameters for cold-resistance traits are unknown in M.rosenbergii.In this study,the cold-resistance of adult M.rosenbergii populations was tested using the indoor artificial cooling method.Individuals were selected from 139 families of Shufeng G3 generation and cultured for 200 days.A linear mixed model was constructed by ASReml-R to evaluate the genetic parameters of the cold-resistance trait(cooling degree hours,CDH)and growth traits(body weight,BW,and body length,BL)based on the restricted maximum likelihood(REML)method.The results show that the heritability of CDH was low(0.12±0.05),while the growth traits(BW and BL)had low to moderate heritability,with 0.20±0.06 for BW and 0.06±0.04 for BL.The phenotypic and genetic correlation between BW and BL was significantly positive,but significantly negative phenotypic and genetic correlations were detected between CDH and BW and between CDH and BL.Furthermore,the analysis of the differences between cold-resistance and phenotypic traits showed that the female reproductive status,exoskeleton hardness and claw number of adult prawns had a great influence on the cold-resistance of M.rosenbergii(P<0.05),indicating that adults with claws and hard exoskeletons are preferred as parents in subsequent breeding selection.The present results can be attributed to the selection and breeding of a new cold-resistant variety of M.rosenbergii.

Structural identification and antioxidative activity evaluation of flaxseed lignan macromolecules: structure-activity correlation

Flaxseed lignan macromolecules(FLM)are a class of important secondary metabolites in fl axseed,which have been widely concerned due to their biological and pharmacological properties,especially for their antioxidative activity.For the composition and structure of FLM,our results confirmed that ferulic acid glycoside(FerAG)was directly ester-linked with herbacetin diglucoside(HDG)or pinoresinol diglucoside(PDG),which might determine the beginning of FLM biosynthesis.Additionally,p-coumaric acid glycoside(CouAG)might determine the end of chain extension during FLM synthesis in fl axseed.FLM exhibited higher antioxidative activity in polar systems,as shown by its superior 1,1-diphenyl-2-picrylhydrazyl(DPPH)free radical scavenging capacity compared to the 2,2’-azinobis(3-ehtylbenzothiazolin-6-sulfnic acid)(ABTS)cation free radical scavenging capacity in non-polar systems.Moreover,the antioxidative activity of FLM was found to be highly dependent on its composition and structure.In particular,it was positively correlated with the number of phenolic hydroxyl groups(longer FLM chains)and inversely related to the steric hindrance at the ends(lower levels of FerAG and CouAG).These fi ndings verifi ed the potential application of FLM in nonpolar systems,particularly in functional food emulsions。

Origin of condensate oil and natural gas in Bozhong 19-6 gas field,Bohai Bay Basin

The discovery of the Bozhong 19-6 gas field has opened a new frontier for deep gas exploration in the Bohai Bay Basin,with a great potential for further gas exploration.However,poor understanding of oil and gas origin has been limiting the exploration progress in this area.To clarify the origin of condensate oil and gas in Bozhong 19-6 gas field,this study adequately utilized the organic geochemical analysis data to investigate the composition and geochemical characteristics of condensate oil and natural gas,and analyzed the relationship between condensate oil and the three sets of source rocks in the nearby subsags.Results show that the lighter components dominate the condensate oil,with a forward type predominance.The parent material of crude oil was primarily deposited in a shallow,clay-rich,low-salinity,weakly reducing aquatic environment.The condensate and natural gas have similar parent source characteristics and maturity,with Ro ranging from 1.4%to 1.6%.Both are products of high maturity stage,indicating that they are hydrocarbon compounds produced by the same group of source rocks in the same stage.Oil-sources correlation shows that condensate oil and gas mainly originate from the source rocks of the third member of Shahejie Formation in the nearby subsags of the Bozhong 19-6 structural belt.

A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.

Evaluation of frictional pressure drop correlations for air-water and air-oil two-phase flow in pipeline-riser system

Accurate prediction of the frictional pressure drop is important for the design and operation of subsea oil and gas transporting system considering the length of the pipeline. The applicability of the correlations to pipeline-riser flow needs evaluation since the flow condition in pipeline-riser is quite different from the original data where they were derived from. In the present study, a comprehensive evaluation of 24prevailing correlation in predicting frictional pressure drop is carried out based on experimentally measured data of air-water and air-oil two-phase flows in pipeline-riser. Experiments are performed in a system having different configuration of pipeline-riser with the inclination of the downcomer varied from-2°to-5°to investigated the effect of the elbow on the frictional pressure drop in the riser. The inlet gas velocity ranges from 0.03 to 6.2 m/s, and liquid velocity varies from 0.02 to 1.3 m/s. A total of885 experimental data points including 782 on air-water flows and 103 on air-oil flows are obtained and used to access the prediction ability of the correlations. Comparison of the predicted results with the measured data indicate that a majority of the investigated correlations under-predict the pressure drop on severe slugging. The result of this study highlights the requirement of new method considering the effect of pipe layout on the frictional pressure drop.

Differences and similarities in radial growth of Betula species to climate change

Betula platyphylla and Betula costata are important species in mixed broadleaved-Korean pine(Pinus koraiensis)forests.However,the specific ways in which their growth is affected by warm temperatures and drought remain unclear.To address this issue,60 and 62 tree-ring cores of B.platyphylla and B.costata were collected in Yichun,China.Using dendrochronological methods,the response and adaptation of these species to climate change were examined.A“hysteresis effect”was found in the rings of both species,linked to May–September moisture conditions of the previous year.Radial growth of B.costata was positively correlated with the standardized precipitation-evapotranspiration index(SPEI),the precipitation from September to October of the previous year,and the relative humidity in October of the previous year.Growth of B.costata is primarily restricted by moisture conditions from September to October.In contrast,B.platyphylla growth is mainly limited by minimum temperatures in May–June of both the previous and current years.After droughts,B.platyphylla had a faster recovery rate compared to B.costata.In the context of rising temperatures since 1980,the correlation between B.platyphylla growth and monthly SPEI became positive and strengthened over time,while the growth of B.costata showed no conspicuous change.Our findings suggest that the growth of B.platyphylla is already affected by warming temperatures,whereas B.costata may become limited if warming continues or intensifies.Climate change could disrupt the succession of these species,possibly accelerating the succession of pioneer species.The results of this research are of great significance for understanding how the growth changes of birch species under warming and drying conditions,and contribute to understanding the structural adaptation of mixed broadleaved-Korean pine(Pinus koraiensis)forests under climate change.

Evaluation and Influencing Factors on Particle Agglomeration in RAP

Asphalt extraction test and scanning electron microscopy(SEM) were used for analysis of agglomerations of reclaimed asphalt pavement(RAP) particles. In order to quantify the agglomeration degree of RAP, the fineness modulus ratio(FMR) and the percentage loss index(PLI) were proposed. In addition, grey correlation analysis was conducted to discuss the relationship between particle agglomerations and RAP size,asphalt content(AC), and surface area. Two indexes indicate that the agglomeration degree increases in general as the RAP size reduces. This can be attributed to that particles are prone to agglomeration in the case of higher AC. Based on the SEM images and the material composition of RAP, the particle agglomeration in RAP can be classified into weak agglomeration and strong agglomeration. Grey correlation analysis shows that AC is the crucial factor affecting the agglomeration degree and RAP variability. In order to produce consistent and stable reclaimed mixtures, disposal measures of RAP are suggested to lower the AC of RAP.

Spatiotemporal Prediction of Urban Traffics Based on Deep GNN

Traffic prediction already plays a significant role in applications like traffic planning and urban management,but it is still difficult to capture the highly non-linear and complicated spatiotemporal correlations of traffic data.As well as to fulfil both long-termand short-termprediction objectives,a better representation of the temporal dependency and global spatial correlation of traffic data is needed.In order to do this,the Spatiotemporal Graph Neural Network(S-GNN)is proposed in this research as amethod for traffic prediction.The S-GNN simultaneously accepts various traffic data as inputs and investigates the non-linear correlations between the variables.In terms of modelling,the road network is initially represented as a spatiotemporal directed graph,with the features of the samples at the time step being captured by a convolution module.In order to assign varying attention weights to various adjacent area nodes of the target node,the adjacent areas information of nodes in the road network is then aggregated using a graph network.The data is output using a fully connected layer at the end.The findings show that S-GNN can improve short-and long-term traffic prediction accuracy to a greater extent;in comparison to the control model,the RMSE of S-GNN is reduced by about 0.571 to 9.288 and the MAE(Mean Absolute Error)by about 0.314 to 7.678.The experimental results on two real datasets,Pe MSD7(M)and PEMS-BAY,also support this claim.

Track correlation algorithm based on CNN-LSTM for swarm targets

The rapid development of unmanned aerial vehicle(UAV) swarm, a new type of aerial threat target, has brought great pressure to the air defense early warning system. At present, most of the track correlation algorithms only use part of the target location, speed, and other information for correlation.In this paper, the artificial neural network method is used to establish the corresponding intelligent track correlation model and method according to the characteristics of swarm targets.Precisely, a route correlation method based on convolutional neural networks (CNN) and long short-term memory (LSTM)Neural network is designed. In this model, the CNN is used to extract the formation characteristics of UAV swarm and the spatial position characteristics of single UAV track in the formation,while the LSTM is used to extract the time characteristics of UAV swarm. Experimental results show that compared with the traditional algorithms, the algorithm based on CNN-LSTM neural network can make full use of multiple feature information of the target, and has better robustness and accuracy for swarm targets.

Roughness characterization and shearing dislocation failure for rock-backfill interface

Shearing dislocation is a common failure type for rock–backfill interfaces because of backfill sedimentation and rock strata movement in backfill mining goaf.This paper designed a test method for rock–backfill shearing dislocation.Using digital image techno-logy and three-dimensional(3D)laser morphology scanning techniques,a set of 3D models with rough joint surfaces was established.Further,the mechanical behavior of rock–backfill shearing dislocation was investigated using a direct shear test.The effects of interface roughness on the shear–displacement curve and failure characteristics of rock–backfill specimens were considered.The 3D fractal dimen-sion,profile line joint roughness coefficient(JRC),profile line two-dimensional fractal dimension,and the surface curvature of the frac-tures were obtained.The correlation characterization of surface roughness was then analyzed,and the shear strength could be measured and calculated using JRC.The results showed the following:there were three failure threshold value points in rock–backfill shearing dis-location:30%–50%displacement before the peak,70%–90%displacement before the peak,and 100%displacement before the peak to post-peak,which could be a sign for rock–backfill shearing dislocation failure.The surface JRC could be used to judge the rock–backfill shearing dislocation failure,including post-peak sliding,uniform variations,and gradient change,corresponding to rock–backfill disloca-tion failure on the field site.The research reveals the damage mechanism for rock–backfill complexes based on the free joint surface,fills the gap of existing shearing theoretical systems for isomerism complexes,and provides a theoretical basis for the prevention and control of possible disasters in backfill mining.

Study of baryon number transport dynamics and strangeness conservation effects using Ω-hadron correlations

In nuclear collisions at RHIC energies, an excess of Ω hyperons over ■ is observed, indicating that Ω has a net baryon number despite s and s quarks being produced in pairs. The baryon number in Ω may have been transported from the incident nuclei and/or produced in the baryon-pair production of Ω with other types of anti-hyperons such as Ξ. To investigate these two scenarios, we propose to measure the correlations between Ω and K and between Ω and anti-hyperons. We use two versions, the default and string-melting, of a multiphase transport(AMPT) model to illustrate the method for measuring the correlation and to demonstrate the general shape of the correlation. We present the Ω-hadron correlations from simulated Au+Au collisions at ■ =7.7 and 14.6 Ge V and discuss the dependence on the collision energy and on the hadronization scheme in these two AMPT versions. These correlations can be used to explore the mechanism of baryon number transport and the effects of baryon number and strangeness conservation on nuclear collisions.