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...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.展开更多
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 ...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.展开更多
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 ...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.展开更多
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 th...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.展开更多
Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal cha...Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks.However,3D CT blocks necessitate significantly higher hardware resources during the learning phase.Therefore,efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks.In this paper,we propose a ULD network with the enhanced temporal correlation for this purpose,named TCE-Net.The designed TCE module is applied to enrich the discriminate feature representation of multiple sequential CT slices.Besides,we employ multi-scale feature maps to facilitate the localization and detection of lesions in various sizes.Extensive experiments are conducted on the DeepLesion benchmark demonstrate that thismethod achieves 66.84%and 78.18%for FS@0.5 and FS@1.0,respectively,outperforming compared state-of-the-art methods.展开更多
With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The networ...With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The network security environment in the era of big data presents the characteristics of large amounts of data,high diversity,and high real-time requirements.Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats.This paper proposes a machine-learning security defense algorithm based on metadata association features.Emphasize control over unauthorized users through privacy,integrity,and availability.The user model is established and the mapping between the user model and the metadata of the data source is generated.By analyzing the user model and its corresponding mapping relationship,the query of the user model can be decomposed into the query of various heterogeneous data sources,and the integration of heterogeneous data sources based on the metadata association characteristics can be realized.Define and classify customer information,automatically identify and perceive sensitive data,build a behavior audit and analysis platform,analyze user behavior trajectories,and complete the construction of a machine learning customer information security defense system.The experimental results show that when the data volume is 5×103 bit,the data storage integrity of the proposed method is 92%.The data accuracy is 98%,and the success rate of data intrusion is only 2.6%.It can be concluded that the data storage method in this paper is safe,the data accuracy is always at a high level,and the data disaster recovery performance is good.This method can effectively resist data intrusion and has high air traffic control security.It can not only detect all viruses in user data storage,but also realize integrated virus processing,and further optimize the security defense effect of user big data.展开更多
AIM:To assess the repeatability,interocular correlation,and agreement of quantitative swept-source optical coherence tomography angiography(OCTA)optic nerve head(ONH)parameters in healthy subjects.METHODS:Thir ty-thre...AIM:To assess the repeatability,interocular correlation,and agreement of quantitative swept-source optical coherence tomography angiography(OCTA)optic nerve head(ONH)parameters in healthy subjects.METHODS:Thir ty-three healthy subjects were enrolled.The ONH of both eyes were imaged four times by a swept-source-OCTA using a 3 mm×3 mm scanning protocol.Images of the radial peripapillary capillary were analyzed by a customized Matlab program,and the vessel density,fractal dimension,and vessel diameter index were measured.The repeatability of the four scans was determined by the intraclass correlation coefficient(ICC).The most well-centered optic disc from the four repeated scans was then selected for the interocular correlation and agreement analysis using the Pearson correlation coefficient,ICC and Bland-Altman plots.RESULTS:All swept-source-OCTA ONH parameters exhibited certain repeatability,with ICC>0.760 and coefficient of variation(CoV)≤7.301%.The obvious interocular correlation was observed for papillary vessel density(ICC=0.857),vessel diameter index(ICC=0.857)and fractal dimension(ICC=0.906),while circumpapillary vessel density exhibited moderate interocular correlation(ICC=0.687).Bland-Altman plots revealed an agreement range of-5.26%to 6.21%for circumpapillary vessel density.CONCLUSION:OCTA ONH parameters demonstrate good repeatability in healthy subjects.The interocular correlations of papillary vessel density,fractal dimension and vessel diameter index are high,but the correlation for circumpapillary vessel density is moderate.展开更多
Beam splitting is one of the main approaches to achieving x-ray ghost imaging, and the intensity correlation between diffraction beam and transmission beam will directly affect the imaging quality. In this paper, we i...Beam splitting is one of the main approaches to achieving x-ray ghost imaging, and the intensity correlation between diffraction beam and transmission beam will directly affect the imaging quality. In this paper, we investigate the intensity correlation between the split x-ray beams by Laue diffraction of stress-free crystal. The analysis based on the dynamical theory of x-ray diffraction indicates that the spatial resolution of diffraction image and transmission image are reduced due to the position shift of the exit beam. In the experimental setup, a stress-free crystal with a thickness of hundredmicrometers-level is used for beam splitting. The crystal is in a non-dispersive configuration equipped with a double-crystal monochromator to ensure that the dimension of the diffraction beam and transmission beam are consistent. A correlation coefficient of 0.92 is achieved experimentally and the high signal-to-noise ratio of the x-ray ghost imaging is anticipated.Results of this paper demonstrate that the developed beam splitter of Laue crystal has the potential in the efficient data acquisition of x-ray ghost imaging.展开更多
Cross-Project Defect Prediction(CPDP)is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target project.However,existing CPDP methods only consi...Cross-Project Defect Prediction(CPDP)is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target project.However,existing CPDP methods only consider linear correlations between features(indicators)of the source and target projects.These models are not capable of evaluating non-linear correlations between features when they exist,for example,when there are differences in data distributions between the source and target projects.As a result,the performance of such CPDP models is compromised.In this paper,this paper proposes a novel CPDP method based on Synthetic Minority Oversampling Technique(SMOTE)and Deep Canonical Correlation Analysis(DCCA),referred to as S-DCCA.Canonical Correlation Analysis(CCA)is employed to address the issue of non-linear correlations between features of the source and target projects.S-DCCA extends CCA by incorporating the MlpNet model for feature extraction from the dataset.The redundant features are then eliminated by maximizing the correlated feature subset using the CCA loss function.Finally,cross-project defect prediction is achieved through the application of the SMOTE data sampling technique.Area Under Curve(AUC)and F1 scores(F1)are used as evaluation metrics.This paper conducted experiments on 27 projects from four public datasets to validate the proposed method.The results demonstrate that,on average,our method outperforms all baseline approaches by at least 1.2%in AUC and 5.5%in F1 score.This indicates that the proposed method exhibits favorable performance characteristics.展开更多
When evaluating an area's seismic risk or resilience,it is necessary to use the spatial correlation to analyze the ground motion parameters of multiple sites together in an earthquake.These two large earthquakes i...When evaluating an area's seismic risk or resilience,it is necessary to use the spatial correlation to analyze the ground motion parameters of multiple sites together in an earthquake.These two large earthquakes in Türkiye provided the possibility for spatial correlation analysis of ground motion intensity measurements in this area.Based on the strong motion records provided by The Disaster and Emergency Management Authority of Türkiye(AFAD),this study uses the local ground motion prediction equation in Türkiye to give spatial correlation analysis of Intensity Measurements.This study gives an exponential model based on a semivariogram and compares it with the correlation model obtained from previous studies.展开更多
BACKGROUND Postpartum depression(PPD)not only affects the psychological and physiological aspects of maternal health but can also affect neonatal growth and development.Partners who are in close contact with parturien...BACKGROUND Postpartum depression(PPD)not only affects the psychological and physiological aspects of maternal health but can also affect neonatal growth and development.Partners who are in close contact with parturient women play a key role in communication and emotional support.This study explores the PPD support relationship with partners and its influencing factors,which is believed to establish psychological well-being and improve maternal partner support.AIM To explore the correlation between PPD and partner support during breastfeeding and its influencing factors.METHODS Convenience sampling was used to select lactating women(200 women)who underwent postpartum examinations at the Huzhou Maternity and Child Health Care Hospital from July 2022 to December 2022.A cross-sectional survey was conducted on the basic information(general information questionnaire),depression level[edinburgh postnatal depression scale(EPDS)],and partner support score[dyadic coping inventory(DCI)]of the selected subjects.Pearson’s correlation analysis was used to analyze the correlation between PPD and DCI in lactating women.Factors affecting PPD levels during lactation were analyzed using multiple linear regression.RESULTS The total average score of EPDS in 200 lactating women was(9.52±1.53),and the total average score of DCI was(115.78±14.90).Dividing the EPDS,the dimension scores were:emotional loss(1.91±0.52),anxiety(3.84±1.05),and depression(3.76±0.96).Each dimension of the DCI was subdivided into:Pressure communication(26.79±6.71),mutual support(39.76±9.63),negative support(24.97±6.68),agent support(6.87±1.92),and joint support(17.39±4.19).Pearson’s correlation analysis demonstrated that the total mean score and individual dimension scores of EPDS during breastfeeding were inversely correlated with the total score of partner support,stress communication,mutual support,and cosupport(P<0.05).The total mean score of the EPDS and its dimensions were positively correlated with negative support(P<0.05).Multiple linear regression analysis showed that the main factors affecting PPD during breastfeeding were marital harmony,newborn health,stress communication,mutual support,negative support,cosupport,and the total score of partner support(P<0.05).CONCLUSION PPD during breastfeeding was associated with marital harmony,newborn health,stress communication,mutual support,negative support,joint support,and the total DCI score.展开更多
The district cooling system (DCS) with ice storage can reduce the peak electricity demand of the business district buildings it serves, improve system efficiency, and lower operational costs. This study utilizes a mon...The district cooling system (DCS) with ice storage can reduce the peak electricity demand of the business district buildings it serves, improve system efficiency, and lower operational costs. This study utilizes a monitoring and control platform for DCS with ice storage to analyze historical parameter values related to system operation and executed operations. We assess the distribution of cooling loads among various devices within the DCS, identify operational characteristics of the system through correlation analysis and principal component analysis (PCA), and subsequently determine key parameters affecting changes in cooling loads. Accurate forecasting of cooling loads is crucial for determining optimal control strategies. The research process can be summarized briefly as follows: data preprocessing, parameter analysis, parameter selection, and validation of load forecasting performance. The study reveals that while individual devices in the system perform well, there is considerable room for improving overall system efficiency. Six principal components have been identified as input parameters for the cold load forecasting model, with each of these components having eigenvalues greater than 1 and contributing to an accumulated variance of 87.26%, and during the dimensionality reduction process, we obtained a confidence ellipse with a 95% confidence interval. Regarding cooling load forecasting, the Relative Absolute Error (RAE) value of the light gradient boosting machine (lightGBM) algorithm is 3.62%, Relative Root Mean Square Error (RRMSE) is 42.75%, and R-squared value (R<sup>2</sup>) is 92.96%, indicating superior forecasting performance compared to other commonly used cooling load forecasting algorithms. This research provides valuable insights and auxiliary guidance for data analysis and optimizing operations in practical engineering applications. .展开更多
Modern cloud services are monitored by numerous multidomain and multivendor monitoring tools,which generate massive numbers of alerts and events that are not actionable.These alerts usually carry isolated messages tha...Modern cloud services are monitored by numerous multidomain and multivendor monitoring tools,which generate massive numbers of alerts and events that are not actionable.These alerts usually carry isolated messages that are missing service contexts.Administrators become inundated with tickets caused by such alert events when they are routed directly to incident management systems.Noisy alerts increase the risk of crucial warnings going undetected and leading to service outages.One of the feasible ways to cope with the above problems involves revealing the correlations behind a large number of alerts and then aggregating the related alerts according to their correlations.Based on these guidelines,AlertInsight,a framework for alert event reduction,is proposed in this paper.In AlertInsight,the correlations among event sources are found by mining a sequence of historical events.Then,event correlation knowledge is employed to build an online detector targeting the correlated events that are hidden in the event stream.Finally,the correlated events are aggregated into a single high-level event for alert reduction.Because of theweaknesses of the commonly used pairwise correlation analysis methods in complex environments,an innovative approach for multiple correlation mining,which overcomes computational complexity challenges by scanning panoramic views of historical episodes from the perspective of holism,is proposed in this paper.In addition,a neural network-based correlated event detector that can learn the event correlation knowledge generated from correlation mining and then detect the correlated events in a sequence online is proposed.Experiments are conducted to test the effectiveness of AlertInsight.The experimental results(precision=0.92,recall=0.93,and F1-score=0.93)demonstrate the performance of AlertInsight for the recognition of multiple correlated alerts and its competence for alert reduction.展开更多
Shrimp sauce,one of the traditional salt-fermented food in China,has a unique flavor that is influenced by the resident microflora.The quality of salt-fermented shrimp sauce was evaluated in this work by determining t...Shrimp sauce,one of the traditional salt-fermented food in China,has a unique flavor that is influenced by the resident microflora.The quality of salt-fermented shrimp sauce was evaluated in this work by determining the total volatile basic nitrogen(TVB-N),the amino acid nitrogen(AAN),organic acid,5’-nucleotide and free amino acids(FAA).Moreover,the dynamics of microbial diversity during processing was investigated by using high-throughput sequencing technology.The results showed that the AAN,TVB-N,organic acid,5’-nucleotide and FAA content were in range of 0.93-1.42 g/100 mL,49.91-236.27 mg/100 mL,6.65-20.68 mg/mL,3.51-6.56 mg/mL and 81.27-102.90 mg/mL.Among the microbial diversity found in the shrimp sauce,Tetragenococcus,Flavobacterium,Polaribacter,Haematospirillum and Staphylococcus were the predominant genera.Correlation analysis indicated that the bacteria Tetragenococcus and Staphylococcus were important in the formation of non-volatile compounds.Tetragenococcus positively correlated with a variety of FAAs;Staphylococcus positively correlated with 5’-nucleotides.The analysis indicated that Tetragenococcus and Staphylococcus were the core genera affecting non-volatile components.These findings indicate the dynamics of the bacterial community and non-volatile components inter-relationships during shrimp sauce fermentation and provide a theoretical basis for improving the fermentation process of shrimp sauce.展开更多
BACKGROUND Radical surgery is the most commonly used treatment for hepatocellular carcinoma(HCC).However,the surgical effect remains not ideal,and prognostic evaluation is insufficient.Furthermore,clinical interventio...BACKGROUND Radical surgery is the most commonly used treatment for hepatocellular carcinoma(HCC).However,the surgical effect remains not ideal,and prognostic evaluation is insufficient.Furthermore,clinical intervention is rife with uncertainty and not conducive to prolonging patient survival.AIM To explore correlations between the systemic immune inflammatory index(SII)and geriatric nutritional risk index(GNRI)and HCC operation prognosis.METHODS This retrospective study included and collected follow up data from 100 HCC.Kaplan–Meier survival curves were used to analyze the correlation between SII and GNRI scores and survival.SII and GNRI were calculated as follows:SII=neutrophil count×platelet count/lymphocyte count;GNRI=[1.489×albumin(g/L)+41.7×actual weight/ideal weight].We analyzed the predictive efficacy of the SII and GNRI in HCC patients using receiver operating characteristic(ROC)curves,and the relationships between the SII,GNRI,and survival rate using Kaplan–Meier survival curves.Cox regression analysis was utilized to analyze independent risk factors influencing prognosis.RESULTS After 1 year of follow-up,24 patients died and 76 survived.The area under the curve(AUC),sensitivity,specificity,and the optimal cutoff value of SII were 0.728(95%confidence interval:0.600-0.856),79.2%,63.2%,and 309.14,respectively.According to ROC curve analysis results for predicting postoperative death in HCC patients,the AUC of SII and GNRI combination was higher than that of SII or GNRI alone,and SII was higher than that of GNRI(P<0.05).The proportion of advanced differentiated tumors,tumor maximum diameter(5–10 cm,>10 cm),lymph node metastasis,and TNM stage III-IV in patients with SII>309.14 was higher than that in patients with SII≤309.14(P<0.05).The proportion of patients aged>70 years was higher in patients with GNRI≤98 than that in patients with GNRI>98(P<0.05).The 1-year survival rate of the SII>309.14 group(compared with the SII≤309.14 group)and GNRI≤98 group(compared with the GNRI>98 group)was lower(P<0.05).CONCLUSION The prognosis after radical resection of HCC is related to the SII and GNRI and poor in high SII or low GNRI patients.展开更多
The origin and source of the petroleum in the Jurassic reservoirs within the eastern Fukang sub-depression were geochemically investigated.They show thermal maturities matching the peak generation stage,while the cond...The origin and source of the petroleum in the Jurassic reservoirs within the eastern Fukang sub-depression were geochemically investigated.They show thermal maturities matching the peak generation stage,while the condensates are at the early stage of intense cracking.Oils and condensates may have experienced mild evaporative fractionation,while mixing of severely biodegraded with non-biodegraded oils has occurred.Using biomarkers and isotopes,petroleums were classified into GroupⅠ,ⅡandⅢgenetic groups,with GroupⅢfurther divided intoⅢa andⅢb subgroups.GroupⅠpetroleum displays heavy carbon isotopes,a strong predominance of pristine over phytane,high C_(19)and C_(20)tricyclic and C_(24)tetracyclic terpanes,low gammacerane,and dominant C_(29)steranes,while GroupⅡshows light carbon isotopes,a predominance of phytane over pristine,high C_(21)and C_(23)tricyclic with low C_(24)tetracyclic terpanes,high gammacerane and dominant C_(27)steranes.GroupⅢa petroleum shows mixing compositions of GroupⅠandⅡ,while GroupⅢb displays similar compositions to Group I,but with significantly higher Ts,C_(29)Ts and C_(30)diahopane proportions.Oil-source rock correlation suggests GroupⅠandⅡpetroleums originate from Jurassic and Permian source rocks,respectively,while GroupⅢa are mixtures sourced from these rocks andⅢb are mixtures from Jurassic and Triassic source rocks.展开更多
The mesomechanics of geotechnical materials are closely related to the macromechanical properties,especially the mesoscale evolution of shear bands,which is helpful for understanding the failure mechanism of geotechni...The mesomechanics of geotechnical materials are closely related to the macromechanical properties,especially the mesoscale evolution of shear bands,which is helpful for understanding the failure mechanism of geotechnical materials.However,there is lack of effective quantitative analysis method for the complex evolution mechanism of threedimensional shear bands.In this work,we used X-ray computed tomography(CT)to reconstruct volume images and used the digital volume correlation(DVC)method to calculate the three-dimensional strain fields of granite residual soil samples at different loading stages.The trend of the failure surface of the shear bands was obtained by the planar fitting method,and the connectivity index was constructed according to the projection characteristics of the shear bands on the failure trend surface.The results support the following findings:the connectivity index of the shear band increases rapidly and then slowly with increasing axial strain,which is characterized by a near'S'curve.As the stress reaches the peak value,the connectivity index of the shear bands almost exceeds 0.7.The contribution of the new shear band volume to the connectivity of the shear bands becomes increasingly small with increasing axial loading.Affected by quartz grains and stress at the initial stage,the dip angle gradually and finally approaches the included angle of the maximum shear stress from the discrete state with increasing axial loading.The tendency and dip angle of the resulting shear bands are dynamic,and the tendency slightly deflects with increasing loading.展开更多
We investigate the electronic structure ofβ-uranium,which has five nonequivalent atomic sites in its unit cell,by means of the density functional theory plus Hubbard-U correction with U from linear response calculati...We investigate the electronic structure ofβ-uranium,which has five nonequivalent atomic sites in its unit cell,by means of the density functional theory plus Hubbard-U correction with U from linear response calculation.It is found that the 5f electronic correlations inβ-uranium are moderate.More interestingly,their strengths are site selective,depending on the local atomic environment of the present uranium atom.As a consequence,the occupation matrices and partial 5f density of states ofβ-uranium manifest site dependence.In addition,the complicate experimental structure ofβ-uranium could be well reproduced within this theoretical framework.展开更多
In this work, the solubility data of 9-fluorenone in 11 pure solvents(methanol, ethanol, n-propanol, isopropanol, n-butanol, iso-butanol, acetonitrile, ethyl formate, ethyl acetate, dimethyl sulfoxide, n-hexane)were m...In this work, the solubility data of 9-fluorenone in 11 pure solvents(methanol, ethanol, n-propanol, isopropanol, n-butanol, iso-butanol, acetonitrile, ethyl formate, ethyl acetate, dimethyl sulfoxide, n-hexane)were measured by the gravimetric method from 278.15 K to 318.15 K under atmospheric pressure. The results showed that the solubility of 9-fluorenone in all tested solvents increased with the raised temperature. The solubility data were correlated by the modified Apelblat equation, λh model and NRTL(nonradom two fluid) model. The average relative deviation(ARD) correlated by three thermodynamic models in different solvents was all below 5%, which indicated that the three thermodynamic models fit the solubility data well. Furthermore, the mixing thermodynamic properties of 9-fluorenone in pure solvent systems were calculated via NRTL model. The results indicated the dissolution process of 9-fluorenone is spontaneous and entropically favorable. The solubility and the mixing thermodynamic properties provided in this paper would play an important role in industrial manufacture and follow-up operation of 9-fluorenone.展开更多
The anisotropy induced by rock bedding structures is usually manifested in the mechanical behaviors and failure modes of rocks.Brazilian tests are conducted for seven groups of shale specimens featuring different bedd...The anisotropy induced by rock bedding structures is usually manifested in the mechanical behaviors and failure modes of rocks.Brazilian tests are conducted for seven groups of shale specimens featuring different bedding angles. Acoustic emission (AE) and digital image correlation (DIC) technologies are used to monitor the in-situ failure of the specimens. Furthermore, the crack morphology of damaged samples is observed through scanning electron microscopy (SEM). Results reveal the structural dependence on the tensile mechanical behavior of shales. The shale disk exhibits compression in the early stage of the experiment with varying locations and durations. The location of the compression area moves downward and gradually disappears when the bedding angle increases. The macroscopic failure is well characterized by AE event location results, and the dominant frequency distribution is related to the bedding angle. The b-value is found to be stress-dependent.The crack turning angle between layers and the number of cracks crossing the bedding both increase with the bedding angle, indicating competition between crack propagations. SEM results revealed that the failure modes of the samples can be classified into three types:tensile failure along beddings with shear failure of the matrix, ladder shear failure along beddings with tensile failure of the matrix, and shear failure along multiple beddings with tensile failure of the matrix.展开更多
文摘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.
基金funded by the National Natural Science Foundation of China(61991413)the China Postdoctoral Science Foundation(2019M651142)+1 种基金the Natural Science Foundation of Liaoning Province(2021-KF-12-07)the Natural Science Foundations of Liaoning Province(2023-MS-322).
文摘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.
基金supported by the Key R&D Project of the Ministry of Science and Technology of China(2020YFB1808005)。
文摘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.
基金Shanghai Rising-Star Program(Grant No.21QA1403400)Shanghai Sailing Program(Grant No.20YF1414800)Shanghai Key Laboratory of Power Station Automation Technology(Grant No.13DZ2273800).
文摘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.
基金Taishan Young Scholars Program of Shandong Province,Key Development Program for Basic Research of Shandong Province(ZR2020ZD44).
文摘Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks.However,3D CT blocks necessitate significantly higher hardware resources during the learning phase.Therefore,efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks.In this paper,we propose a ULD network with the enhanced temporal correlation for this purpose,named TCE-Net.The designed TCE module is applied to enrich the discriminate feature representation of multiple sequential CT slices.Besides,we employ multi-scale feature maps to facilitate the localization and detection of lesions in various sizes.Extensive experiments are conducted on the DeepLesion benchmark demonstrate that thismethod achieves 66.84%and 78.18%for FS@0.5 and FS@1.0,respectively,outperforming compared state-of-the-art methods.
基金This work was supported by the National Natural Science Foundation of China(U2133208,U20A20161).
文摘With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The network security environment in the era of big data presents the characteristics of large amounts of data,high diversity,and high real-time requirements.Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats.This paper proposes a machine-learning security defense algorithm based on metadata association features.Emphasize control over unauthorized users through privacy,integrity,and availability.The user model is established and the mapping between the user model and the metadata of the data source is generated.By analyzing the user model and its corresponding mapping relationship,the query of the user model can be decomposed into the query of various heterogeneous data sources,and the integration of heterogeneous data sources based on the metadata association characteristics can be realized.Define and classify customer information,automatically identify and perceive sensitive data,build a behavior audit and analysis platform,analyze user behavior trajectories,and complete the construction of a machine learning customer information security defense system.The experimental results show that when the data volume is 5×103 bit,the data storage integrity of the proposed method is 92%.The data accuracy is 98%,and the success rate of data intrusion is only 2.6%.It can be concluded that the data storage method in this paper is safe,the data accuracy is always at a high level,and the data disaster recovery performance is good.This method can effectively resist data intrusion and has high air traffic control security.It can not only detect all viruses in user data storage,but also realize integrated virus processing,and further optimize the security defense effect of user big data.
基金Natural Science Foundation of Guangdong Province(No.2018A0303130306)Shantou Science and Technology Program(No.190917085269835,No.200629165261641).
文摘AIM:To assess the repeatability,interocular correlation,and agreement of quantitative swept-source optical coherence tomography angiography(OCTA)optic nerve head(ONH)parameters in healthy subjects.METHODS:Thir ty-three healthy subjects were enrolled.The ONH of both eyes were imaged four times by a swept-source-OCTA using a 3 mm×3 mm scanning protocol.Images of the radial peripapillary capillary were analyzed by a customized Matlab program,and the vessel density,fractal dimension,and vessel diameter index were measured.The repeatability of the four scans was determined by the intraclass correlation coefficient(ICC).The most well-centered optic disc from the four repeated scans was then selected for the interocular correlation and agreement analysis using the Pearson correlation coefficient,ICC and Bland-Altman plots.RESULTS:All swept-source-OCTA ONH parameters exhibited certain repeatability,with ICC>0.760 and coefficient of variation(CoV)≤7.301%.The obvious interocular correlation was observed for papillary vessel density(ICC=0.857),vessel diameter index(ICC=0.857)and fractal dimension(ICC=0.906),while circumpapillary vessel density exhibited moderate interocular correlation(ICC=0.687).Bland-Altman plots revealed an agreement range of-5.26%to 6.21%for circumpapillary vessel density.CONCLUSION:OCTA ONH parameters demonstrate good repeatability in healthy subjects.The interocular correlations of papillary vessel density,fractal dimension and vessel diameter index are high,but the correlation for circumpapillary vessel density is moderate.
基金Project supported by the National Key Research and Development Program of China (Grant Nos.2022YFF0709103,2022YFA1603601,2021YFF0601203,and 2021YFA1600703)the National Natural Science Foundation of China (Grant No.81430087)the Shanghai Pilot Program for Basic Research-Chinese Academy of Sciences,Shanghai Branch (Grant No.JCYJ-SHFY-2021-010)。
文摘Beam splitting is one of the main approaches to achieving x-ray ghost imaging, and the intensity correlation between diffraction beam and transmission beam will directly affect the imaging quality. In this paper, we investigate the intensity correlation between the split x-ray beams by Laue diffraction of stress-free crystal. The analysis based on the dynamical theory of x-ray diffraction indicates that the spatial resolution of diffraction image and transmission image are reduced due to the position shift of the exit beam. In the experimental setup, a stress-free crystal with a thickness of hundredmicrometers-level is used for beam splitting. The crystal is in a non-dispersive configuration equipped with a double-crystal monochromator to ensure that the dimension of the diffraction beam and transmission beam are consistent. A correlation coefficient of 0.92 is achieved experimentally and the high signal-to-noise ratio of the x-ray ghost imaging is anticipated.Results of this paper demonstrate that the developed beam splitter of Laue crystal has the potential in the efficient data acquisition of x-ray ghost imaging.
基金NationalNatural Science Foundation of China,Grant/AwardNumber:61867004National Natural Science Foundation of China Youth Fund,Grant/Award Number:41801288.
文摘Cross-Project Defect Prediction(CPDP)is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target project.However,existing CPDP methods only consider linear correlations between features(indicators)of the source and target projects.These models are not capable of evaluating non-linear correlations between features when they exist,for example,when there are differences in data distributions between the source and target projects.As a result,the performance of such CPDP models is compromised.In this paper,this paper proposes a novel CPDP method based on Synthetic Minority Oversampling Technique(SMOTE)and Deep Canonical Correlation Analysis(DCCA),referred to as S-DCCA.Canonical Correlation Analysis(CCA)is employed to address the issue of non-linear correlations between features of the source and target projects.S-DCCA extends CCA by incorporating the MlpNet model for feature extraction from the dataset.The redundant features are then eliminated by maximizing the correlated feature subset using the CCA loss function.Finally,cross-project defect prediction is achieved through the application of the SMOTE data sampling technique.Area Under Curve(AUC)and F1 scores(F1)are used as evaluation metrics.This paper conducted experiments on 27 projects from four public datasets to validate the proposed method.The results demonstrate that,on average,our method outperforms all baseline approaches by at least 1.2%in AUC and 5.5%in F1 score.This indicates that the proposed method exhibits favorable performance characteristics.
基金jointly supported by the National Natural Science Foundation of China U1901602,U2239252)the National Key R&D Program of China(No.2019YFE0115700)+1 种基金the Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration(Grant No.2021EEEVL0202)the Natural Science Foundation of Heilongjiang Province(LH2020E021)。
文摘When evaluating an area's seismic risk or resilience,it is necessary to use the spatial correlation to analyze the ground motion parameters of multiple sites together in an earthquake.These two large earthquakes in Türkiye provided the possibility for spatial correlation analysis of ground motion intensity measurements in this area.Based on the strong motion records provided by The Disaster and Emergency Management Authority of Türkiye(AFAD),this study uses the local ground motion prediction equation in Türkiye to give spatial correlation analysis of Intensity Measurements.This study gives an exponential model based on a semivariogram and compares it with the correlation model obtained from previous studies.
基金Supported by Medical Health Science and Technology Project of Huzhou City,No.2022GY41.
文摘BACKGROUND Postpartum depression(PPD)not only affects the psychological and physiological aspects of maternal health but can also affect neonatal growth and development.Partners who are in close contact with parturient women play a key role in communication and emotional support.This study explores the PPD support relationship with partners and its influencing factors,which is believed to establish psychological well-being and improve maternal partner support.AIM To explore the correlation between PPD and partner support during breastfeeding and its influencing factors.METHODS Convenience sampling was used to select lactating women(200 women)who underwent postpartum examinations at the Huzhou Maternity and Child Health Care Hospital from July 2022 to December 2022.A cross-sectional survey was conducted on the basic information(general information questionnaire),depression level[edinburgh postnatal depression scale(EPDS)],and partner support score[dyadic coping inventory(DCI)]of the selected subjects.Pearson’s correlation analysis was used to analyze the correlation between PPD and DCI in lactating women.Factors affecting PPD levels during lactation were analyzed using multiple linear regression.RESULTS The total average score of EPDS in 200 lactating women was(9.52±1.53),and the total average score of DCI was(115.78±14.90).Dividing the EPDS,the dimension scores were:emotional loss(1.91±0.52),anxiety(3.84±1.05),and depression(3.76±0.96).Each dimension of the DCI was subdivided into:Pressure communication(26.79±6.71),mutual support(39.76±9.63),negative support(24.97±6.68),agent support(6.87±1.92),and joint support(17.39±4.19).Pearson’s correlation analysis demonstrated that the total mean score and individual dimension scores of EPDS during breastfeeding were inversely correlated with the total score of partner support,stress communication,mutual support,and cosupport(P<0.05).The total mean score of the EPDS and its dimensions were positively correlated with negative support(P<0.05).Multiple linear regression analysis showed that the main factors affecting PPD during breastfeeding were marital harmony,newborn health,stress communication,mutual support,negative support,cosupport,and the total score of partner support(P<0.05).CONCLUSION PPD during breastfeeding was associated with marital harmony,newborn health,stress communication,mutual support,negative support,joint support,and the total DCI score.
文摘The district cooling system (DCS) with ice storage can reduce the peak electricity demand of the business district buildings it serves, improve system efficiency, and lower operational costs. This study utilizes a monitoring and control platform for DCS with ice storage to analyze historical parameter values related to system operation and executed operations. We assess the distribution of cooling loads among various devices within the DCS, identify operational characteristics of the system through correlation analysis and principal component analysis (PCA), and subsequently determine key parameters affecting changes in cooling loads. Accurate forecasting of cooling loads is crucial for determining optimal control strategies. The research process can be summarized briefly as follows: data preprocessing, parameter analysis, parameter selection, and validation of load forecasting performance. The study reveals that while individual devices in the system perform well, there is considerable room for improving overall system efficiency. Six principal components have been identified as input parameters for the cold load forecasting model, with each of these components having eigenvalues greater than 1 and contributing to an accumulated variance of 87.26%, and during the dimensionality reduction process, we obtained a confidence ellipse with a 95% confidence interval. Regarding cooling load forecasting, the Relative Absolute Error (RAE) value of the light gradient boosting machine (lightGBM) algorithm is 3.62%, Relative Root Mean Square Error (RRMSE) is 42.75%, and R-squared value (R<sup>2</sup>) is 92.96%, indicating superior forecasting performance compared to other commonly used cooling load forecasting algorithms. This research provides valuable insights and auxiliary guidance for data analysis and optimizing operations in practical engineering applications. .
文摘Modern cloud services are monitored by numerous multidomain and multivendor monitoring tools,which generate massive numbers of alerts and events that are not actionable.These alerts usually carry isolated messages that are missing service contexts.Administrators become inundated with tickets caused by such alert events when they are routed directly to incident management systems.Noisy alerts increase the risk of crucial warnings going undetected and leading to service outages.One of the feasible ways to cope with the above problems involves revealing the correlations behind a large number of alerts and then aggregating the related alerts according to their correlations.Based on these guidelines,AlertInsight,a framework for alert event reduction,is proposed in this paper.In AlertInsight,the correlations among event sources are found by mining a sequence of historical events.Then,event correlation knowledge is employed to build an online detector targeting the correlated events that are hidden in the event stream.Finally,the correlated events are aggregated into a single high-level event for alert reduction.Because of theweaknesses of the commonly used pairwise correlation analysis methods in complex environments,an innovative approach for multiple correlation mining,which overcomes computational complexity challenges by scanning panoramic views of historical episodes from the perspective of holism,is proposed in this paper.In addition,a neural network-based correlated event detector that can learn the event correlation knowledge generated from correlation mining and then detect the correlated events in a sequence online is proposed.Experiments are conducted to test the effectiveness of AlertInsight.The experimental results(precision=0.92,recall=0.93,and F1-score=0.93)demonstrate the performance of AlertInsight for the recognition of multiple correlated alerts and its competence for alert reduction.
基金support from the National Key R&D Program of China (2019YFD0901903)the Innovation Team Project of Hebei (Province) Modern Agricultural Industry Technology System (HBCT2018170207)the Postgraduate Research & Practice Innovation Program of Jiangsu Province (SJCX20_1426)
文摘Shrimp sauce,one of the traditional salt-fermented food in China,has a unique flavor that is influenced by the resident microflora.The quality of salt-fermented shrimp sauce was evaluated in this work by determining the total volatile basic nitrogen(TVB-N),the amino acid nitrogen(AAN),organic acid,5’-nucleotide and free amino acids(FAA).Moreover,the dynamics of microbial diversity during processing was investigated by using high-throughput sequencing technology.The results showed that the AAN,TVB-N,organic acid,5’-nucleotide and FAA content were in range of 0.93-1.42 g/100 mL,49.91-236.27 mg/100 mL,6.65-20.68 mg/mL,3.51-6.56 mg/mL and 81.27-102.90 mg/mL.Among the microbial diversity found in the shrimp sauce,Tetragenococcus,Flavobacterium,Polaribacter,Haematospirillum and Staphylococcus were the predominant genera.Correlation analysis indicated that the bacteria Tetragenococcus and Staphylococcus were important in the formation of non-volatile compounds.Tetragenococcus positively correlated with a variety of FAAs;Staphylococcus positively correlated with 5’-nucleotides.The analysis indicated that Tetragenococcus and Staphylococcus were the core genera affecting non-volatile components.These findings indicate the dynamics of the bacterial community and non-volatile components inter-relationships during shrimp sauce fermentation and provide a theoretical basis for improving the fermentation process of shrimp sauce.
基金the Soft Science Research Project of Liuzhou Association for Science and Technology,No.20200120Self-funded scientific research project of Guangxi Zhuang Autonomous Region Health Commission,No.Z20200258.
文摘BACKGROUND Radical surgery is the most commonly used treatment for hepatocellular carcinoma(HCC).However,the surgical effect remains not ideal,and prognostic evaluation is insufficient.Furthermore,clinical intervention is rife with uncertainty and not conducive to prolonging patient survival.AIM To explore correlations between the systemic immune inflammatory index(SII)and geriatric nutritional risk index(GNRI)and HCC operation prognosis.METHODS This retrospective study included and collected follow up data from 100 HCC.Kaplan–Meier survival curves were used to analyze the correlation between SII and GNRI scores and survival.SII and GNRI were calculated as follows:SII=neutrophil count×platelet count/lymphocyte count;GNRI=[1.489×albumin(g/L)+41.7×actual weight/ideal weight].We analyzed the predictive efficacy of the SII and GNRI in HCC patients using receiver operating characteristic(ROC)curves,and the relationships between the SII,GNRI,and survival rate using Kaplan–Meier survival curves.Cox regression analysis was utilized to analyze independent risk factors influencing prognosis.RESULTS After 1 year of follow-up,24 patients died and 76 survived.The area under the curve(AUC),sensitivity,specificity,and the optimal cutoff value of SII were 0.728(95%confidence interval:0.600-0.856),79.2%,63.2%,and 309.14,respectively.According to ROC curve analysis results for predicting postoperative death in HCC patients,the AUC of SII and GNRI combination was higher than that of SII or GNRI alone,and SII was higher than that of GNRI(P<0.05).The proportion of advanced differentiated tumors,tumor maximum diameter(5–10 cm,>10 cm),lymph node metastasis,and TNM stage III-IV in patients with SII>309.14 was higher than that in patients with SII≤309.14(P<0.05).The proportion of patients aged>70 years was higher in patients with GNRI≤98 than that in patients with GNRI>98(P<0.05).The 1-year survival rate of the SII>309.14 group(compared with the SII≤309.14 group)and GNRI≤98 group(compared with the GNRI>98 group)was lower(P<0.05).CONCLUSION The prognosis after radical resection of HCC is related to the SII and GNRI and poor in high SII or low GNRI patients.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.20CX02108A)the Development Fund of the Key Laboratory of Deep Oil&Gas,China University of Petroleum(East China)。
文摘The origin and source of the petroleum in the Jurassic reservoirs within the eastern Fukang sub-depression were geochemically investigated.They show thermal maturities matching the peak generation stage,while the condensates are at the early stage of intense cracking.Oils and condensates may have experienced mild evaporative fractionation,while mixing of severely biodegraded with non-biodegraded oils has occurred.Using biomarkers and isotopes,petroleums were classified into GroupⅠ,ⅡandⅢgenetic groups,with GroupⅢfurther divided intoⅢa andⅢb subgroups.GroupⅠpetroleum displays heavy carbon isotopes,a strong predominance of pristine over phytane,high C_(19)and C_(20)tricyclic and C_(24)tetracyclic terpanes,low gammacerane,and dominant C_(29)steranes,while GroupⅡshows light carbon isotopes,a predominance of phytane over pristine,high C_(21)and C_(23)tricyclic with low C_(24)tetracyclic terpanes,high gammacerane and dominant C_(27)steranes.GroupⅢa petroleum shows mixing compositions of GroupⅠandⅡ,while GroupⅢb displays similar compositions to Group I,but with significantly higher Ts,C_(29)Ts and C_(30)diahopane proportions.Oil-source rock correlation suggests GroupⅠandⅡpetroleums originate from Jurassic and Permian source rocks,respectively,while GroupⅢa are mixtures sourced from these rocks andⅢb are mixtures from Jurassic and Triassic source rocks.
基金supported by the Building Fund for the Academic Innovation Team of Shantou University (CN)(NTF21017)the Special Fund for Science and Technology of Guangdong Province in2021 (STKJ2021181)the National Natural Science Foundation of China (Grant nos.12272394)
文摘The mesomechanics of geotechnical materials are closely related to the macromechanical properties,especially the mesoscale evolution of shear bands,which is helpful for understanding the failure mechanism of geotechnical materials.However,there is lack of effective quantitative analysis method for the complex evolution mechanism of threedimensional shear bands.In this work,we used X-ray computed tomography(CT)to reconstruct volume images and used the digital volume correlation(DVC)method to calculate the three-dimensional strain fields of granite residual soil samples at different loading stages.The trend of the failure surface of the shear bands was obtained by the planar fitting method,and the connectivity index was constructed according to the projection characteristics of the shear bands on the failure trend surface.The results support the following findings:the connectivity index of the shear band increases rapidly and then slowly with increasing axial strain,which is characterized by a near'S'curve.As the stress reaches the peak value,the connectivity index of the shear bands almost exceeds 0.7.The contribution of the new shear band volume to the connectivity of the shear bands becomes increasingly small with increasing axial loading.Affected by quartz grains and stress at the initial stage,the dip angle gradually and finally approaches the included angle of the maximum shear stress from the discrete state with increasing axial loading.The tendency and dip angle of the resulting shear bands are dynamic,and the tendency slightly deflects with increasing loading.
基金supported by the National Natural Science Foundation of China (Grant Nos.22176181,11874329,11934020,and U1930121)the Foundation of the President of China Academy of Engineering Physics (Grant No.YZJJZQ2022011)the Foundation of Science and Technology on Surface Physics and Chemistry Laboratory (Grant No.WDZC202101)。
文摘We investigate the electronic structure ofβ-uranium,which has five nonequivalent atomic sites in its unit cell,by means of the density functional theory plus Hubbard-U correction with U from linear response calculation.It is found that the 5f electronic correlations inβ-uranium are moderate.More interestingly,their strengths are site selective,depending on the local atomic environment of the present uranium atom.As a consequence,the occupation matrices and partial 5f density of states ofβ-uranium manifest site dependence.In addition,the complicate experimental structure ofβ-uranium could be well reproduced within this theoretical framework.
基金supported by Tianjin Municipal Natural Science Foundation (21JCYBJC00600)。
文摘In this work, the solubility data of 9-fluorenone in 11 pure solvents(methanol, ethanol, n-propanol, isopropanol, n-butanol, iso-butanol, acetonitrile, ethyl formate, ethyl acetate, dimethyl sulfoxide, n-hexane)were measured by the gravimetric method from 278.15 K to 318.15 K under atmospheric pressure. The results showed that the solubility of 9-fluorenone in all tested solvents increased with the raised temperature. The solubility data were correlated by the modified Apelblat equation, λh model and NRTL(nonradom two fluid) model. The average relative deviation(ARD) correlated by three thermodynamic models in different solvents was all below 5%, which indicated that the three thermodynamic models fit the solubility data well. Furthermore, the mixing thermodynamic properties of 9-fluorenone in pure solvent systems were calculated via NRTL model. The results indicated the dissolution process of 9-fluorenone is spontaneous and entropically favorable. The solubility and the mixing thermodynamic properties provided in this paper would play an important role in industrial manufacture and follow-up operation of 9-fluorenone.
基金financially supported by the National Natural Science Foundation of China (No.51934003)the Major Science and Technology Special Project of Yunnan Province,China(Nos.202102AF080001 and 202102AG050024)。
文摘The anisotropy induced by rock bedding structures is usually manifested in the mechanical behaviors and failure modes of rocks.Brazilian tests are conducted for seven groups of shale specimens featuring different bedding angles. Acoustic emission (AE) and digital image correlation (DIC) technologies are used to monitor the in-situ failure of the specimens. Furthermore, the crack morphology of damaged samples is observed through scanning electron microscopy (SEM). Results reveal the structural dependence on the tensile mechanical behavior of shales. The shale disk exhibits compression in the early stage of the experiment with varying locations and durations. The location of the compression area moves downward and gradually disappears when the bedding angle increases. The macroscopic failure is well characterized by AE event location results, and the dominant frequency distribution is related to the bedding angle. The b-value is found to be stress-dependent.The crack turning angle between layers and the number of cracks crossing the bedding both increase with the bedding angle, indicating competition between crack propagations. SEM results revealed that the failure modes of the samples can be classified into three types:tensile failure along beddings with shear failure of the matrix, ladder shear failure along beddings with tensile failure of the matrix, and shear failure along multiple beddings with tensile failure of the matrix.
