Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign cur...Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic volatility (SV), stochastic correlation (SC), and stochastic exchange rate (SER) models to determine the best combination of these models for Monte Carlo (MC) simulation pricing. In addition, we test the performance of all model variants with constant correlation as a benchmark. We find that a combination of GARCH-Jump SV, Weibull SC, and Ornstein Uhlenbeck (OU) SER performs best. In addition, we analyze different discretization schemes and their results. In our simulations, the Milstein scheme yields the best balance between execution times and lower standard deviations of price estimates. Furthermore, we find that incorporating mean reversion into stochastic correlation and stochastic FX rate modeling is beneficial for MC simulation pricing. We improve the accuracy of our simulations by implementing antithetic variates variance reduction. Finally, we derive the correlation risk parameters Cora and Gora in our framework so that correlation hedging of quanto options can be performed.展开更多
Portfolio selection based on the global minimum variance(GMV)model remains a significant focus in financial research.The covariance matrix,central to the GMV model,determines portfolio weights,and its accurate estimat...Portfolio selection based on the global minimum variance(GMV)model remains a significant focus in financial research.The covariance matrix,central to the GMV model,determines portfolio weights,and its accurate estimation is key to effective strategies.Based on the decomposition form of the covariance matrix.This paper introduces semi-variance for improved financial asymmetric risk measurement;addresses asymmetry in financial asset correlations using distance,asymmetric,and Chatterjee correlations to refine covariance matrices;and proposes three new covariance matrix models to enhance risk assessment and portfolio selection strategies.Testing with data from 30 stocks across various sectors of the Chinese market confirms the strong performance of the proposed strategies.展开更多
Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with ot...Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.展开更多
Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery...Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery of high-entropy alloys(HEAs)comprising multi-principal elements.Owing to the four“core-effects”,these alloys exhibit exceptional properties including better structural stability,high strength and ductility,improved fatigue/fracture toughness,high corrosion and oxidation resistance,superconductiv-ity,magnetic properties,and good thermal properties.Different synthesis routes have been designed and used to meet the properties of interest for particular applications with varying dimensions.How-ever,HEAs are providing new opportunities and challenges for computational modelling of the complex structure-property correlations and in predictions of phase stability necessary for optimum performance of the alloy.Several attempts have been made to understand these alloys by empirical and computa-tional models,and data-driven approaches to accelerate the materials discovery with a desired set of properties.The present review discusses advances and inferences from simulations and models spanning multiple length and time scales explaining a comprehensive set of structure-properties relations.Addi-tionally,the role of machine learning approaches is also reviewed,underscoring the transformative role of computational modelling in unravelling the multifaceted properties and applications of HEAs,and the scope for future efforts in this direction.展开更多
BACKGROUND Resilience is an individual’s ability and psychological rebound capacity to adapt well after experiencing adversity,trauma,etc.Patients with strong resilience can face illnesses actively.AIM To determine t...BACKGROUND Resilience is an individual’s ability and psychological rebound capacity to adapt well after experiencing adversity,trauma,etc.Patients with strong resilience can face illnesses actively.AIM To determine the association of resilience with coping styles and quality of life in patients with malignancies.METHODS This study included patients with malignant tumors who were hospitalized at Fuyang Hospital Affiliated to Anhui Medical University from March 2022 to March 2024.The Connor-Davidson Resilience Scale,Medical Coping Modes Questionnaire,Social Support Rating Scale,and the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 were utilized to assess patients’resilience,coping styles,social support,and quality of life,respectively.Pearson correlation analysis was conducted to assess the correlations.RESULTS A total of 175 patients with malignant tumors demonstrated no marked difference in terms of age,education level,employment status,monthly household income,and disease staging(P<0.05).Further,patients with malignancies demonstrated scores of 17.49±1.20,17.27±1.46,and 11.19±1.29 points in terms of coping styles in confrontation,avoidance,and resignation dimensions,respectively.Subjective support,objective support,and support utilization scores in terms of social support were 10.67±1.80,11.26±2.08,and 9.24±1.14 points,respectively.The total resilience score and tenacity,self-improvement,and optimism dimension scores were positively correlatedwith the confrontation coping style score,whereas the total resilience score and tenacity and self-improvementscores were negatively associated with avoidance and resignation coping style scores(P<0.05).The total resiliencescore and the tenacity dimension score were positively associated with physical,role,cognitive,emotional,andsocial functions,as well as global health status(P<0.05),and were inversely related to fatigue,insomnia,andeconomic difficulties(P<0.05).CONCLUSIONThe resilience of patients with malignancies is positively associated with the confrontation dimension in the copingstyle,the total and various social support domain scores,and the overall quality of life.Clinical medical staff needto pay attention to the effect of medical coping styles and social support on the resilience level of patients withmalignancies to further improve their quality of life.展开更多
Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the m...Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the measurements. At MF3E, moderate variability was observed in apparent electrical conductivity shallow (ECas), slope, and ECa ratio measurements, with coefficients of variation ranging from 20% to 27%. In contrast, MF11S exhibited higher variability, particularly in ECas and ECad (deep) measurements, which exceeded 30% in their coefficient of variation values, indicating significant differences in soil composition and moisture content. Correlation analysis revealed strong positive relationships between the near-infrared-to-red ratio and red reflectance (r = 0.897***) soil values at MF3E. MF11S demonstrated a strong negative correlation between ECas and ECad readings with the x-coordinate (r ***). Scatter plots and fitted models illustrated the complexity of relationships, with many showing nonlinear trends. These findings emphasize the need for continuous monitoring and advanced modeling to understand the dynamic nature of soil properties and their implications for agricultural practices. Future research should explore the underlying mechanisms driving variability in the soil characteristics to enhance soil management strategies at the study sites.展开更多
The Fushan Depression is one of the petroliferous depressions in the Beibuwan Basin,South China Sea.Previous studies have preliminarily explored the origin and source of crude oils in some areas of this depression.Nev...The Fushan Depression is one of the petroliferous depressions in the Beibuwan Basin,South China Sea.Previous studies have preliminarily explored the origin and source of crude oils in some areas of this depression.Nevertheless,no systematic investigations on the classification and origin of oils and hy-drocarbon migration processes have been made for the entire petroleum system in this depression,which has significantly hindered the hydrocarbon exploration in the region.A total of 32 mudstone and 58 oil samples from the Fushan Depression were analyzed to definite the detailed oil-source correlation within the sequence and sedimentary framework.The organic matter of third member of Paleogene Liushagang Formation(Els(3))source rocks,both deltaic and lacustrine mudstone,are algal-dominated with high abundance of C_(23)tricyclic terpane and C_(30)4-methylsteranes.The deltaic source rocks occur-ring in the first member(Els_(1))and second member(Els_(2))of the Paleogene Liushagang Formation are characterized by high abundance of C_(19+20)tricyclic terpane and oleanane,reflecting a more terrestrial plants contribution.While lacustrine source rocks of Els_(1)and Els_(2)display the reduced input of terrige-nous organic matter with relatively low abundance of C 19+20 tricyclic terpane and oleanane.Three types of oils were identified by their biomarker compositions in this study.Most of the oils discovered in the Huachang and Bailian Els_(1)reservoir belong to group A and were derived from lacustrine source rocks of Els_(1)and Els_(2).Group B oils are found within the Els_(1)and Els_(2)reservoirs,showing a close relation to the deltaic source rocks of Els_(1)and Els_(2),respectively.Group C oils,occurring in the Els3 reservoirs,have a good affinity with the Els3 source rocks.The spatial distribution and accumulation of different groups of oils are mainly controlled by the sedimentary facies and specific structural conditions.The Els_(2)reservoir in the Yong'an area belonging to Group B oil,are adjacent to the source kitchen and could be considered as the favorable exploration area in the future.展开更多
Geomagnetic observatory data are crucial for all branches of geophysics because they can contribute to earthquake research by detecting anomalies in the Earth’s magnetic field.Recently,data records from the Misallat(...Geomagnetic observatory data are crucial for all branches of geophysics because they can contribute to earthquake research by detecting anomalies in the Earth’s magnetic field.Recently,data records from the Misallat(MLT)and Abu Simbel(ABS)Egyptian geomagnetic observatories were processed and found to be of good quality.In this study,Egyptian observatory data were tested during both quiet and disturbed events and compared with data from INTERMAGNET observatories worldwide at different latitudes and within a narrow range of longitudes in both hemispheres.This study investigated the relationships between magnetic field components from Egyptian observatories and those from INTERMAGNET observatories using graphical representations of the X components;Pearson’s correlation for the X,Y,Z,and F components;cross-correlation for the X component;and wavelet coherence for the F component.The results of this study showed a high correlation between Egyptian observatories and all utilized INTERMAGNET stations,except those located at high latitudes,during both quiet and disturbed events.Additionally,the study confirmed the observed consistency between Egyptian observatories and selected INTERMAGNET stations.Therefore,Egyptian observatories can feasibly fill the gap in the Middle East and North Africa.展开更多
Passive acoustic monitoring(PAM)technology is increasingly becoming one of the mainstream methods for bird monitoring.However,detecting bird audio within complex natural acoustic environments using PAM devices remains...Passive acoustic monitoring(PAM)technology is increasingly becoming one of the mainstream methods for bird monitoring.However,detecting bird audio within complex natural acoustic environments using PAM devices remains a significant challenge.To enhance the accuracy(ACC)of bird audio detection(BAD)and reduce both false negatives and false positives,this study proposes a BAD method based on a Dual-Feature Enhancement Fusion Model(DFEFM).This method incorporates per-channel energy normalization(PCEN)to suppress noise in the input audio and utilizes mel-frequency cepstral coefficients(MFCC)and frequency correlation matrices(FCM)as input features.It achieves deep feature-level fusion of MFCC and FCM on the channel dimension through two independent multi-layer convolutional network branches,and further integrates Spatial and Channel Synergistic Attention(SCSA)and Multi-Head Attention(MHA)modules to enhance the fusion effect of the aforementioned two deep features.Experimental results on the DCASE2018 BAD dataset show that our proposed method achieved an ACC of 91.4%and an AUC value of 0.963,with false negative and false positive rates of 11.36%and 7.40%,respectively,surpassing existing methods.The method also demonstrated detection ACC above 92%and AUC values above 0.987 on datasets from three sites of different natural scenes in Beijing.Testing on the NVIDIA Jetson Nano indicated that the method achieved an ACC of 89.48%when processing an average of 10 s of audio,with a response time of only 0.557 s,showing excellent processing efficiency.This study provides an effective method for filtering non-bird vocalization audio in bird vocalization monitoring devices,which helps to save edge storage and information transmission costs,and has significant application value for wild bird monitoring and ecological research.展开更多
Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithm...Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.展开更多
BACKGROUND Previous cellular studies have demonstrated that elevated expression of Cx43 promotes the degradation of cyclin E1 and inhibits cell proliferation through ubiquitination.Conversely,reduced expression result...BACKGROUND Previous cellular studies have demonstrated that elevated expression of Cx43 promotes the degradation of cyclin E1 and inhibits cell proliferation through ubiquitination.Conversely,reduced expression results in a loss of this capacity to facilitate cyclin E degradation.The ubiquitination and degradation of cyclin E1 may be associated with phosphorylation at specific sites on the protein,with Cx43 potentially enhancing this process by facilitating the phosphorylation of these critical residues.AIM To investigate the correlation between expression of Cx43,SKP1/Cullin1/F-box(SCF)FBXW7,p-cyclin E1(ser73,thr77,thr395)and clinicopathological indexes in colon cancer.METHODS Expression levels of Cx43,SCF^(FBXW7),p-cyclin E1(ser73,thr77,thr395)in 38 clinical colon cancer samples were detected by immunohistochemistry and were analyzed by statistical methods to discuss their correlations.RESULTS Positive rate of Cx43,SCF^(FBXW7),p-cyclin E1(Ser73),p-cyclin E1(Thr77)and p-cyclin E1(Thr395)in detected samples were 76.32%,76.32%,65.79%,5.26%and 55.26%respectively.Positive expressions of these proteins were not related to the tissue type,degree of tissue differentiation or lymph node metastasis.Cx43 and SCF^(FBXW7)(r=0.749),p-cyclin E1(Ser73)(r=0.667)and p-cyclin E1(Thr395)(r=0.457),SCF^(FBXW7) and p-cyclin E1(Ser73)(r=0.703)and p-cyclin E1(Thr395)(0.415)were correlated in colon cancer(P<0.05),and expressions of the above proteins were positively correlated in colon cancer.CONCLUSION Cx43 may facilitate the phosphorylation of cyclin E1 at the Ser73 and Thr195 sites through its interaction with SCF^(FBXW7),thereby influencing the ubiquitination and degradation of cyclin E1.展开更多
The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precisio...The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precision.To ensure its accuracy of detection,it is necessary to correlate their thermal models to in-orbit da⁃ta.In this work,an investigation of intelligent correlation method named Intelligent Correlation Platform for Ther⁃mal Model(ICP-TM)was established,the advanced Kriging surrogate model and efficient adaptive region opti⁃mization algorithm were introduced.After the correlation with this method for FY-3E/HIRAS-Ⅱ,the results indi⁃cate that compared with the data in orbit,the error of the thermal model has decreased from 5 K to within±1 K in cold case(10℃).Then,the correlated model is validated in hot case(20℃),and the correlated model exhibits good universality.This correlation precision is also much superiors to the general ones like 3 K in other similar lit⁃erature.Furthermore,the process is finished in 8 days using ICP-TM,the efficiency is much better than 3 months based on manual.The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model,this contributes to the precise thermal control of subsequent infrared optical payloads.展开更多
By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integra...By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integral. The effect of noncanonical strength, off-axis distance and vortex sign on spatial correlation singularities in far field is stressed. Furthermore, far-field OAM spectra and densities are also investigated, and the OAM detection and crosstalk probabilities are discussed. The results show that the number of dislocations of SCS always equals the sum of absolute values of topological charges for canonical or noncanonical vortex pairs. Although the sum of the product of each OAM mode and its power weight equals the algebraic sum of topological charges for canonical vortex pairs, the relationship no longer holds in the noncanonical case except for opposite-charge vortex pairs. The changes of off-axis distance, noncanonical strength or coherence length can lead to a more dominant power in adjacent mode than that in center detection mode, which also indicates that crosstalk probabilities of adjacent modes exceed the center detection probability. This work may provide potential applications in OAM-based optical communication, imaging, sensing and computing.展开更多
BACKGROUND The occurrence of chronic pain and disability after acute orthopedic trauma is significantly correlated with psychological factors,particularly depression and anxiety.As such,assessment of these factors is ...BACKGROUND The occurrence of chronic pain and disability after acute orthopedic trauma is significantly correlated with psychological factors,particularly depression and anxiety.As such,assessment of these factors is crucial for postoperative rehabilitation.AIM To investigate the correlation between chronic pain,disability,and psychological factors(depression and anxiety)after acute orthopedic trauma surgery.METHODS Data from 120 patients,who underwent surgery for acute orthopedic trauma at Xi’an Traditional Chinese Medicine Hospital(Shaanxi Province,China)between June 2022 and June 2024,were retrospectively analyzed.Basic information and postoperative pain metrics[visual analog scale(VAS)],disability rating index(DRI),Hamilton anxiety rating scale(HAMA)and Hamilton depression rating scale(HAMD)were collected from electronic medical records.Pearson’s correlation analysis was used to examine associations between chronic pain VAS,DRI,HAMD,and HAMA scores.RESULTS Among the 120 patients[79(65.8%)males and 41(34.2%)females],postoperative VAS scores were significantly associated with HAMD and HAMA scores,with correlation coefficients of 0.625(P=0.027)and 0.568(P<0.001),respectively.Postoperative DRI scores were also significantly associated with HAMD and HAMA scores,with correlation coefficients of 0.683 and 0.557,respectively(both P<0.001).CONCLUSION Chronic pain and disability after surgery for acute orthopedic trauma are significantly correlated with psychological factors(depression and anxiety).Multidisciplinary teams should integrate mental health services to improve patient outcomes.展开更多
BACKGROUND Insomnia is a common sleep disorder that negatively impacts quality of life and is frequently comorbid with depression and anxiety.Chronic insomnia affects approximately 15%of the global population,with hig...BACKGROUND Insomnia is a common sleep disorder that negatively impacts quality of life and is frequently comorbid with depression and anxiety.Chronic insomnia affects approximately 15%of the global population,with higher prevalence among females and the elderly.While existing research suggests a bidirectional relationship between insomnia and emotional disorders,the specific impact of insomnia severity on depression,anxiety,and quality of life remains unclear.This study investigates the correlation between insomnia severity and these factors in psychiatric outpatients,hypothesizing that greater insomnia severity is associated with higher levels of depression and anxiety,as well as poorer quality of life.AIM To explore the correlation between insomnia severity and depression,anxiety,and quality of life in primary chronic insomnia patients.METHODS From June to December 2023,345 patients with primary insomnia in Chifeng city were recruited and divided into three groups based on Pittsburgh sleep quality index(PSQI)scores:Mild(n=137),moderate(n=162),and severe(n=46).Demographic data were collected via questionnaires.Self-rating depression scale(SDS),self-rating anxiety scale(SAS),PSQI,and short form 36(SF-36)scores were compared,and Pearson and partial correlation analyses were performed.RESULTS The greater the degree of insomnia,the greater the symptoms of depression and anxiety(P<0.001).The more severe the insomnia,the lower the SF-36 score(excluding body pain),and the difference between the three groups was statist ically significant(P<0.001).Pearson correlation analysis and partial correlation analysis depicted the SDS score and SAS score were apparently positively correlated with the severity of insomnia(P<0.001).Pearson correlation analysis and partial correlation analysis depicted the SF-36 scores were apparently positively correlated with the severity of insomnia(P<0.05).CONCLUSION Depression and anxiety are independent factors influencing insomnia severity in primary chronic insomnia patients.Higher depression/anxiety levels correlate with worse insomnia,impacting quality of life.展开更多
Objective:To investigate the differences in childhood trauma and life events between adolescents with depression and healthy controls,and to analyze the correlations between these factors and depressive symptoms.As su...Objective:To investigate the differences in childhood trauma and life events between adolescents with depression and healthy controls,and to analyze the correlations between these factors and depressive symptoms.As such,we aim to provide theoretical foundations for early identification and intervention.Methods:This cross-sectional study enrolled 90 hospitalized adolescents with depression(case group)and 91 healthy adolescents(control group).Childhood Trauma Questionnaire(CTQ),Adolescent Self-Rating Life Events Checklist(ASLEC),and Children’s Depression Inventory(CDI)were administered to assess trauma history,life event stressors,and depressive symptoms.Statistical analyses included independent samples t-tests,chi-square tests,and Pearson correlation analysis.Results:The case group demonstrated a significantly higher proportion of only-child families(28.9%).ASLEC and CDI scores were significantly elevated in the case group compared to the control group(P<0.05).In comparison,CTQ scores were lower in the case group(P=0.025).Positive correlations were identified between CDI scores and both CTQ(r=0.261)and ASLEC(r=0.218)in the case group.Conclusion:Child-hood trauma and recent life event stressors demonstrate significant associations with adolescent depressive symp-toms,potentially mediated through emotional dysregulation and negative cognitive bias.Implementation of early trauma screening protocols combined with stress management interventions(e.g.,cognitive behavioral therapy)and family system optimization strategies may effectively mitigate depression risk in this population.展开更多
Uncertainties about natural gas source and hydrocarbon accumulation seriously restrict oil and gas exploration in the Lianggaoshan Formation(J_(2) l)in the Eastern Sichuan Basin,which has demonstrated great exploratio...Uncertainties about natural gas source and hydrocarbon accumulation seriously restrict oil and gas exploration in the Lianggaoshan Formation(J_(2) l)in the Eastern Sichuan Basin,which has demonstrated great exploration potential in recent years.This study determines the origin of natural gas and the hydrocarbon accumulation model of J_(2) l in the Eastern Sichuan Basin.A new sample pretreatment method named gas purge-microsyringe extraction was employed and confi rmed to be a practical and eff ective method for preparing condensate oil and collecting source rock extract samples.The source rocks of J_(2) l exhibited moderate to good qualities,characterized by high TOC values,dominance of type Ⅱ_(1) and Ⅱ_(2) kerogens,and high thermal maturities.Biomarker and aromatic characteristics revealed that the source rocks of J_(2) l were deposited in brackish water with weak anoxic conditions.The natural gas in J_(2) l was an organic thermogenic gas generated from the secondary cracking of crude oil,indicating that this natural gas was mainly derived from the source rocks of J_(2) l.The condensate oil-source rock correlation further confi rmed the accuracy of the gas-source correlation results.Based on burial,thermal and hydrocarbon-generating histories,two hydrocarbon charging periods(141–133 Ma and 119–112 Ma)and four hydrocarbon accumulation periods of J_(2) l were determined.Combined with structural evolution,depositional histories and reservoir conditions,a simple gas reservoir accumulation model of J_(2) l was developed,which was identifi ed as a“self-generating and self-storing”gas reservoir.展开更多
The fatigue of heavy-haul railway bridges is considered a key concern due to high stress levels and cyclic loading.The evaluation of fatigue reliability is required to include factor correlations.A major challenge is ...The fatigue of heavy-haul railway bridges is considered a key concern due to high stress levels and cyclic loading.The evaluation of fatigue reliability is required to include factor correlations.A major challenge is presented by the construction of the cumulative distribution function(CDF)and the description of correlations between random variables.In this study,the copula function is used to analyze the fatigue failure probability of the Shuohuang heavy-haul railway bridge.A C-vine copula(CVC)-based joint probability density function(JPDF)is derived with eight correlated parameters.To enhance efficiency in small failure probability calculations,the subset simulation and most probable point(MPP)Monte Carlo importance sampling are introduced based on the Rosenblatt transform and C-vine model.Comparisons with traditional Monte Carlo methods confirm that high accuracy and efficiency are achieved.The results show that when parameter correlations are ignored,failure probability is underestimated,increasing safety risks in bridge assessments.展开更多
Methane in-situ explosive fracturing technology produces shale debris particles within fracture channels,enabling a self-propping effect that enhances the fracture network conductivity and long-term stability.This stu...Methane in-situ explosive fracturing technology produces shale debris particles within fracture channels,enabling a self-propping effect that enhances the fracture network conductivity and long-term stability.This study employs X-ray computed tomography(CT)and digital volume correlation(DVC)to investigate the microstructural evolution and hydromechanical responses of shale self-propped fracture under varying confining pressures,highlighting the critical role of shale particles in maintaining fracture conductivity.Results indicate that the fracture aperture in the self-propped sample is significantly larger than in the unpropped sample throughout the loading process,with shale particles tending to crush rather than embedded into the matrix,thus maintaining flow pathways.As confining pressure increases,contact areas between fracture surfaces and particles expand,enhancing the system's stability and compressive resistance.Geometric analyses show flow paths becoming increasingly concentrated and branched under high stress.This resulted in a significant reduction in connectivity,restricting fracture permeability and amplifying the nonlinear gas flow behavior.This study introduces a permeability-strain recovery zone and a novel sensitivity parameter m,delineating stress sensitivity boundaries for permeability and normal strain,with m-value increasing with stress,revealing four characteristic regions.These findings offer theoretical support for optimizing fracturing techniques to enhance resource extraction efficiency.展开更多
As the proportion of newenergy increases,the traditional cumulant method(CM)produces significant errorswhen performing probabilistic load flow(PLF)calculations with large-scale wind power integrated.Considering the wi...As the proportion of newenergy increases,the traditional cumulant method(CM)produces significant errorswhen performing probabilistic load flow(PLF)calculations with large-scale wind power integrated.Considering the wind speed correlation,a multi-scenario PLF calculation method that combines random sampling and segmented discrete wind farm power was proposed.Firstly,based on constructing discrete scenes of wind farms,the Nataf transform is used to handle the correlation between wind speeds.Then,the random sampling method determines the output probability of discrete wind power scenarios when wind speed exhibits correlation.Finally,the PLF calculation results of each scenario areweighted and superimposed following the total probability formula to obtain the final power flow calculation result.Verified in the IEEE standard node system,the absolute percent error(APE)for the mean and standard deviation(SD)of the node voltages and branch active power are all within 1%,and the average root mean square(AMSR)values of the probability curves are all less than 1%.展开更多
文摘Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic volatility (SV), stochastic correlation (SC), and stochastic exchange rate (SER) models to determine the best combination of these models for Monte Carlo (MC) simulation pricing. In addition, we test the performance of all model variants with constant correlation as a benchmark. We find that a combination of GARCH-Jump SV, Weibull SC, and Ornstein Uhlenbeck (OU) SER performs best. In addition, we analyze different discretization schemes and their results. In our simulations, the Milstein scheme yields the best balance between execution times and lower standard deviations of price estimates. Furthermore, we find that incorporating mean reversion into stochastic correlation and stochastic FX rate modeling is beneficial for MC simulation pricing. We improve the accuracy of our simulations by implementing antithetic variates variance reduction. Finally, we derive the correlation risk parameters Cora and Gora in our framework so that correlation hedging of quanto options can be performed.
基金National Natural Science Foundation of China(Project No.:12201579)。
文摘Portfolio selection based on the global minimum variance(GMV)model remains a significant focus in financial research.The covariance matrix,central to the GMV model,determines portfolio weights,and its accurate estimation is key to effective strategies.Based on the decomposition form of the covariance matrix.This paper introduces semi-variance for improved financial asymmetric risk measurement;addresses asymmetry in financial asset correlations using distance,asymmetric,and Chatterjee correlations to refine covariance matrices;and proposes three new covariance matrix models to enhance risk assessment and portfolio selection strategies.Testing with data from 30 stocks across various sectors of the Chinese market confirms the strong performance of the proposed strategies.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 11875042 and 11505114)the Shanghai Project for Construction of Top Disciplines (Grant No. USST-SYS-01)。
文摘Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.
基金the Science and Engineering Re-search Board(SERB),India for providing the financial assistance to support this work(Project No.SRG/2020/002449).
文摘Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery of high-entropy alloys(HEAs)comprising multi-principal elements.Owing to the four“core-effects”,these alloys exhibit exceptional properties including better structural stability,high strength and ductility,improved fatigue/fracture toughness,high corrosion and oxidation resistance,superconductiv-ity,magnetic properties,and good thermal properties.Different synthesis routes have been designed and used to meet the properties of interest for particular applications with varying dimensions.How-ever,HEAs are providing new opportunities and challenges for computational modelling of the complex structure-property correlations and in predictions of phase stability necessary for optimum performance of the alloy.Several attempts have been made to understand these alloys by empirical and computa-tional models,and data-driven approaches to accelerate the materials discovery with a desired set of properties.The present review discusses advances and inferences from simulations and models spanning multiple length and time scales explaining a comprehensive set of structure-properties relations.Addi-tionally,the role of machine learning approaches is also reviewed,underscoring the transformative role of computational modelling in unravelling the multifaceted properties and applications of HEAs,and the scope for future efforts in this direction.
文摘BACKGROUND Resilience is an individual’s ability and psychological rebound capacity to adapt well after experiencing adversity,trauma,etc.Patients with strong resilience can face illnesses actively.AIM To determine the association of resilience with coping styles and quality of life in patients with malignancies.METHODS This study included patients with malignant tumors who were hospitalized at Fuyang Hospital Affiliated to Anhui Medical University from March 2022 to March 2024.The Connor-Davidson Resilience Scale,Medical Coping Modes Questionnaire,Social Support Rating Scale,and the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 were utilized to assess patients’resilience,coping styles,social support,and quality of life,respectively.Pearson correlation analysis was conducted to assess the correlations.RESULTS A total of 175 patients with malignant tumors demonstrated no marked difference in terms of age,education level,employment status,monthly household income,and disease staging(P<0.05).Further,patients with malignancies demonstrated scores of 17.49±1.20,17.27±1.46,and 11.19±1.29 points in terms of coping styles in confrontation,avoidance,and resignation dimensions,respectively.Subjective support,objective support,and support utilization scores in terms of social support were 10.67±1.80,11.26±2.08,and 9.24±1.14 points,respectively.The total resilience score and tenacity,self-improvement,and optimism dimension scores were positively correlatedwith the confrontation coping style score,whereas the total resilience score and tenacity and self-improvementscores were negatively associated with avoidance and resignation coping style scores(P<0.05).The total resiliencescore and the tenacity dimension score were positively associated with physical,role,cognitive,emotional,andsocial functions,as well as global health status(P<0.05),and were inversely related to fatigue,insomnia,andeconomic difficulties(P<0.05).CONCLUSIONThe resilience of patients with malignancies is positively associated with the confrontation dimension in the copingstyle,the total and various social support domain scores,and the overall quality of life.Clinical medical staff needto pay attention to the effect of medical coping styles and social support on the resilience level of patients withmalignancies to further improve their quality of life.
文摘Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the measurements. At MF3E, moderate variability was observed in apparent electrical conductivity shallow (ECas), slope, and ECa ratio measurements, with coefficients of variation ranging from 20% to 27%. In contrast, MF11S exhibited higher variability, particularly in ECas and ECad (deep) measurements, which exceeded 30% in their coefficient of variation values, indicating significant differences in soil composition and moisture content. Correlation analysis revealed strong positive relationships between the near-infrared-to-red ratio and red reflectance (r = 0.897***) soil values at MF3E. MF11S demonstrated a strong negative correlation between ECas and ECad readings with the x-coordinate (r ***). Scatter plots and fitted models illustrated the complexity of relationships, with many showing nonlinear trends. These findings emphasize the need for continuous monitoring and advanced modeling to understand the dynamic nature of soil properties and their implications for agricultural practices. Future research should explore the underlying mechanisms driving variability in the soil characteristics to enhance soil management strategies at the study sites.
基金funded by the South Oil Exploration and Development Company of PetroChina(2021-HNYJ-010).
文摘The Fushan Depression is one of the petroliferous depressions in the Beibuwan Basin,South China Sea.Previous studies have preliminarily explored the origin and source of crude oils in some areas of this depression.Nevertheless,no systematic investigations on the classification and origin of oils and hy-drocarbon migration processes have been made for the entire petroleum system in this depression,which has significantly hindered the hydrocarbon exploration in the region.A total of 32 mudstone and 58 oil samples from the Fushan Depression were analyzed to definite the detailed oil-source correlation within the sequence and sedimentary framework.The organic matter of third member of Paleogene Liushagang Formation(Els(3))source rocks,both deltaic and lacustrine mudstone,are algal-dominated with high abundance of C_(23)tricyclic terpane and C_(30)4-methylsteranes.The deltaic source rocks occur-ring in the first member(Els_(1))and second member(Els_(2))of the Paleogene Liushagang Formation are characterized by high abundance of C_(19+20)tricyclic terpane and oleanane,reflecting a more terrestrial plants contribution.While lacustrine source rocks of Els_(1)and Els_(2)display the reduced input of terrige-nous organic matter with relatively low abundance of C 19+20 tricyclic terpane and oleanane.Three types of oils were identified by their biomarker compositions in this study.Most of the oils discovered in the Huachang and Bailian Els_(1)reservoir belong to group A and were derived from lacustrine source rocks of Els_(1)and Els_(2).Group B oils are found within the Els_(1)and Els_(2)reservoirs,showing a close relation to the deltaic source rocks of Els_(1)and Els_(2),respectively.Group C oils,occurring in the Els3 reservoirs,have a good affinity with the Els3 source rocks.The spatial distribution and accumulation of different groups of oils are mainly controlled by the sedimentary facies and specific structural conditions.The Els_(2)reservoir in the Yong'an area belonging to Group B oil,are adjacent to the source kitchen and could be considered as the favorable exploration area in the future.
文摘Geomagnetic observatory data are crucial for all branches of geophysics because they can contribute to earthquake research by detecting anomalies in the Earth’s magnetic field.Recently,data records from the Misallat(MLT)and Abu Simbel(ABS)Egyptian geomagnetic observatories were processed and found to be of good quality.In this study,Egyptian observatory data were tested during both quiet and disturbed events and compared with data from INTERMAGNET observatories worldwide at different latitudes and within a narrow range of longitudes in both hemispheres.This study investigated the relationships between magnetic field components from Egyptian observatories and those from INTERMAGNET observatories using graphical representations of the X components;Pearson’s correlation for the X,Y,Z,and F components;cross-correlation for the X component;and wavelet coherence for the F component.The results of this study showed a high correlation between Egyptian observatories and all utilized INTERMAGNET stations,except those located at high latitudes,during both quiet and disturbed events.Additionally,the study confirmed the observed consistency between Egyptian observatories and selected INTERMAGNET stations.Therefore,Egyptian observatories can feasibly fill the gap in the Middle East and North Africa.
基金supported by the Beijing Natural Science Foundation(5252014)the National Natural Science Foundation of China(62303063)。
文摘Passive acoustic monitoring(PAM)technology is increasingly becoming one of the mainstream methods for bird monitoring.However,detecting bird audio within complex natural acoustic environments using PAM devices remains a significant challenge.To enhance the accuracy(ACC)of bird audio detection(BAD)and reduce both false negatives and false positives,this study proposes a BAD method based on a Dual-Feature Enhancement Fusion Model(DFEFM).This method incorporates per-channel energy normalization(PCEN)to suppress noise in the input audio and utilizes mel-frequency cepstral coefficients(MFCC)and frequency correlation matrices(FCM)as input features.It achieves deep feature-level fusion of MFCC and FCM on the channel dimension through two independent multi-layer convolutional network branches,and further integrates Spatial and Channel Synergistic Attention(SCSA)and Multi-Head Attention(MHA)modules to enhance the fusion effect of the aforementioned two deep features.Experimental results on the DCASE2018 BAD dataset show that our proposed method achieved an ACC of 91.4%and an AUC value of 0.963,with false negative and false positive rates of 11.36%and 7.40%,respectively,surpassing existing methods.The method also demonstrated detection ACC above 92%and AUC values above 0.987 on datasets from three sites of different natural scenes in Beijing.Testing on the NVIDIA Jetson Nano indicated that the method achieved an ACC of 89.48%when processing an average of 10 s of audio,with a response time of only 0.557 s,showing excellent processing efficiency.This study provides an effective method for filtering non-bird vocalization audio in bird vocalization monitoring devices,which helps to save edge storage and information transmission costs,and has significant application value for wild bird monitoring and ecological research.
基金supported in part by the National Natural Science Foundation of China (No. U23B2011)。
文摘Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.
基金Supported by Innovative Practice Platform for Undergraduate Students,School of Public Health Xiamen University,No.2021001.
文摘BACKGROUND Previous cellular studies have demonstrated that elevated expression of Cx43 promotes the degradation of cyclin E1 and inhibits cell proliferation through ubiquitination.Conversely,reduced expression results in a loss of this capacity to facilitate cyclin E degradation.The ubiquitination and degradation of cyclin E1 may be associated with phosphorylation at specific sites on the protein,with Cx43 potentially enhancing this process by facilitating the phosphorylation of these critical residues.AIM To investigate the correlation between expression of Cx43,SKP1/Cullin1/F-box(SCF)FBXW7,p-cyclin E1(ser73,thr77,thr395)and clinicopathological indexes in colon cancer.METHODS Expression levels of Cx43,SCF^(FBXW7),p-cyclin E1(ser73,thr77,thr395)in 38 clinical colon cancer samples were detected by immunohistochemistry and were analyzed by statistical methods to discuss their correlations.RESULTS Positive rate of Cx43,SCF^(FBXW7),p-cyclin E1(Ser73),p-cyclin E1(Thr77)and p-cyclin E1(Thr395)in detected samples were 76.32%,76.32%,65.79%,5.26%and 55.26%respectively.Positive expressions of these proteins were not related to the tissue type,degree of tissue differentiation or lymph node metastasis.Cx43 and SCF^(FBXW7)(r=0.749),p-cyclin E1(Ser73)(r=0.667)and p-cyclin E1(Thr395)(r=0.457),SCF^(FBXW7) and p-cyclin E1(Ser73)(r=0.703)and p-cyclin E1(Thr395)(0.415)were correlated in colon cancer(P<0.05),and expressions of the above proteins were positively correlated in colon cancer.CONCLUSION Cx43 may facilitate the phosphorylation of cyclin E1 at the Ser73 and Thr195 sites through its interaction with SCF^(FBXW7),thereby influencing the ubiquitination and degradation of cyclin E1.
基金Supported by the National Key Research and Development Program of China(2022YFB3904803)。
文摘The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precision.To ensure its accuracy of detection,it is necessary to correlate their thermal models to in-orbit da⁃ta.In this work,an investigation of intelligent correlation method named Intelligent Correlation Platform for Ther⁃mal Model(ICP-TM)was established,the advanced Kriging surrogate model and efficient adaptive region opti⁃mization algorithm were introduced.After the correlation with this method for FY-3E/HIRAS-Ⅱ,the results indi⁃cate that compared with the data in orbit,the error of the thermal model has decreased from 5 K to within±1 K in cold case(10℃).Then,the correlated model is validated in hot case(20℃),and the correlated model exhibits good universality.This correlation precision is also much superiors to the general ones like 3 K in other similar lit⁃erature.Furthermore,the process is finished in 8 days using ICP-TM,the efficiency is much better than 3 months based on manual.The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model,this contributes to the precise thermal control of subsequent infrared optical payloads.
文摘By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integral. The effect of noncanonical strength, off-axis distance and vortex sign on spatial correlation singularities in far field is stressed. Furthermore, far-field OAM spectra and densities are also investigated, and the OAM detection and crosstalk probabilities are discussed. The results show that the number of dislocations of SCS always equals the sum of absolute values of topological charges for canonical or noncanonical vortex pairs. Although the sum of the product of each OAM mode and its power weight equals the algebraic sum of topological charges for canonical vortex pairs, the relationship no longer holds in the noncanonical case except for opposite-charge vortex pairs. The changes of off-axis distance, noncanonical strength or coherence length can lead to a more dominant power in adjacent mode than that in center detection mode, which also indicates that crosstalk probabilities of adjacent modes exceed the center detection probability. This work may provide potential applications in OAM-based optical communication, imaging, sensing and computing.
文摘BACKGROUND The occurrence of chronic pain and disability after acute orthopedic trauma is significantly correlated with psychological factors,particularly depression and anxiety.As such,assessment of these factors is crucial for postoperative rehabilitation.AIM To investigate the correlation between chronic pain,disability,and psychological factors(depression and anxiety)after acute orthopedic trauma surgery.METHODS Data from 120 patients,who underwent surgery for acute orthopedic trauma at Xi’an Traditional Chinese Medicine Hospital(Shaanxi Province,China)between June 2022 and June 2024,were retrospectively analyzed.Basic information and postoperative pain metrics[visual analog scale(VAS)],disability rating index(DRI),Hamilton anxiety rating scale(HAMA)and Hamilton depression rating scale(HAMD)were collected from electronic medical records.Pearson’s correlation analysis was used to examine associations between chronic pain VAS,DRI,HAMD,and HAMA scores.RESULTS Among the 120 patients[79(65.8%)males and 41(34.2%)females],postoperative VAS scores were significantly associated with HAMD and HAMA scores,with correlation coefficients of 0.625(P=0.027)and 0.568(P<0.001),respectively.Postoperative DRI scores were also significantly associated with HAMD and HAMA scores,with correlation coefficients of 0.683 and 0.557,respectively(both P<0.001).CONCLUSION Chronic pain and disability after surgery for acute orthopedic trauma are significantly correlated with psychological factors(depression and anxiety).Multidisciplinary teams should integrate mental health services to improve patient outcomes.
文摘BACKGROUND Insomnia is a common sleep disorder that negatively impacts quality of life and is frequently comorbid with depression and anxiety.Chronic insomnia affects approximately 15%of the global population,with higher prevalence among females and the elderly.While existing research suggests a bidirectional relationship between insomnia and emotional disorders,the specific impact of insomnia severity on depression,anxiety,and quality of life remains unclear.This study investigates the correlation between insomnia severity and these factors in psychiatric outpatients,hypothesizing that greater insomnia severity is associated with higher levels of depression and anxiety,as well as poorer quality of life.AIM To explore the correlation between insomnia severity and depression,anxiety,and quality of life in primary chronic insomnia patients.METHODS From June to December 2023,345 patients with primary insomnia in Chifeng city were recruited and divided into three groups based on Pittsburgh sleep quality index(PSQI)scores:Mild(n=137),moderate(n=162),and severe(n=46).Demographic data were collected via questionnaires.Self-rating depression scale(SDS),self-rating anxiety scale(SAS),PSQI,and short form 36(SF-36)scores were compared,and Pearson and partial correlation analyses were performed.RESULTS The greater the degree of insomnia,the greater the symptoms of depression and anxiety(P<0.001).The more severe the insomnia,the lower the SF-36 score(excluding body pain),and the difference between the three groups was statist ically significant(P<0.001).Pearson correlation analysis and partial correlation analysis depicted the SDS score and SAS score were apparently positively correlated with the severity of insomnia(P<0.001).Pearson correlation analysis and partial correlation analysis depicted the SF-36 scores were apparently positively correlated with the severity of insomnia(P<0.05).CONCLUSION Depression and anxiety are independent factors influencing insomnia severity in primary chronic insomnia patients.Higher depression/anxiety levels correlate with worse insomnia,impacting quality of life.
基金Research Project of Yunnan Provincial Psychiatric Hospital(SJKY-2023-10).
文摘Objective:To investigate the differences in childhood trauma and life events between adolescents with depression and healthy controls,and to analyze the correlations between these factors and depressive symptoms.As such,we aim to provide theoretical foundations for early identification and intervention.Methods:This cross-sectional study enrolled 90 hospitalized adolescents with depression(case group)and 91 healthy adolescents(control group).Childhood Trauma Questionnaire(CTQ),Adolescent Self-Rating Life Events Checklist(ASLEC),and Children’s Depression Inventory(CDI)were administered to assess trauma history,life event stressors,and depressive symptoms.Statistical analyses included independent samples t-tests,chi-square tests,and Pearson correlation analysis.Results:The case group demonstrated a significantly higher proportion of only-child families(28.9%).ASLEC and CDI scores were significantly elevated in the case group compared to the control group(P<0.05).In comparison,CTQ scores were lower in the case group(P=0.025).Positive correlations were identified between CDI scores and both CTQ(r=0.261)and ASLEC(r=0.218)in the case group.Conclusion:Child-hood trauma and recent life event stressors demonstrate significant associations with adolescent depressive symp-toms,potentially mediated through emotional dysregulation and negative cognitive bias.Implementation of early trauma screening protocols combined with stress management interventions(e.g.,cognitive behavioral therapy)and family system optimization strategies may effectively mitigate depression risk in this population.
基金supported by the grants from the National Natural Science Foundation of China(grant nos.41902153,42072140,42102133 and 42202170)Natural Science Foundation Project of Chongqing(grant nos.cstc2021jcyj-msxmX0455,CSTB2022NSCQ-JQX0031 and CSTB2022NSCQ-MSX1586)Science and Technology Research Program of Chongqing Municipal Education Commission(grant nos.KJQN202101544,KJZD-M202101502).
文摘Uncertainties about natural gas source and hydrocarbon accumulation seriously restrict oil and gas exploration in the Lianggaoshan Formation(J_(2) l)in the Eastern Sichuan Basin,which has demonstrated great exploration potential in recent years.This study determines the origin of natural gas and the hydrocarbon accumulation model of J_(2) l in the Eastern Sichuan Basin.A new sample pretreatment method named gas purge-microsyringe extraction was employed and confi rmed to be a practical and eff ective method for preparing condensate oil and collecting source rock extract samples.The source rocks of J_(2) l exhibited moderate to good qualities,characterized by high TOC values,dominance of type Ⅱ_(1) and Ⅱ_(2) kerogens,and high thermal maturities.Biomarker and aromatic characteristics revealed that the source rocks of J_(2) l were deposited in brackish water with weak anoxic conditions.The natural gas in J_(2) l was an organic thermogenic gas generated from the secondary cracking of crude oil,indicating that this natural gas was mainly derived from the source rocks of J_(2) l.The condensate oil-source rock correlation further confi rmed the accuracy of the gas-source correlation results.Based on burial,thermal and hydrocarbon-generating histories,two hydrocarbon charging periods(141–133 Ma and 119–112 Ma)and four hydrocarbon accumulation periods of J_(2) l were determined.Combined with structural evolution,depositional histories and reservoir conditions,a simple gas reservoir accumulation model of J_(2) l was developed,which was identifi ed as a“self-generating and self-storing”gas reservoir.
基金Project supported by the National Natural Science Foundation of China(No.52278180)。
文摘The fatigue of heavy-haul railway bridges is considered a key concern due to high stress levels and cyclic loading.The evaluation of fatigue reliability is required to include factor correlations.A major challenge is presented by the construction of the cumulative distribution function(CDF)and the description of correlations between random variables.In this study,the copula function is used to analyze the fatigue failure probability of the Shuohuang heavy-haul railway bridge.A C-vine copula(CVC)-based joint probability density function(JPDF)is derived with eight correlated parameters.To enhance efficiency in small failure probability calculations,the subset simulation and most probable point(MPP)Monte Carlo importance sampling are introduced based on the Rosenblatt transform and C-vine model.Comparisons with traditional Monte Carlo methods confirm that high accuracy and efficiency are achieved.The results show that when parameter correlations are ignored,failure probability is underestimated,increasing safety risks in bridge assessments.
基金financially supported by the National Key Research and Development Program of China (No.2020YFA0711800)the National Science Fund for Distinguished Young Scholars (No.51925404)+2 种基金the Graduate Innovation Program of China University of Mining and Technology (No.2023WLKXJ149)the Fundamental Research Funds for the Central Universities (No.2023XSCX040)the Postgraduate Research Practice Innovation Program of Jiangsu Province (No.KYCX23_2864)。
文摘Methane in-situ explosive fracturing technology produces shale debris particles within fracture channels,enabling a self-propping effect that enhances the fracture network conductivity and long-term stability.This study employs X-ray computed tomography(CT)and digital volume correlation(DVC)to investigate the microstructural evolution and hydromechanical responses of shale self-propped fracture under varying confining pressures,highlighting the critical role of shale particles in maintaining fracture conductivity.Results indicate that the fracture aperture in the self-propped sample is significantly larger than in the unpropped sample throughout the loading process,with shale particles tending to crush rather than embedded into the matrix,thus maintaining flow pathways.As confining pressure increases,contact areas between fracture surfaces and particles expand,enhancing the system's stability and compressive resistance.Geometric analyses show flow paths becoming increasingly concentrated and branched under high stress.This resulted in a significant reduction in connectivity,restricting fracture permeability and amplifying the nonlinear gas flow behavior.This study introduces a permeability-strain recovery zone and a novel sensitivity parameter m,delineating stress sensitivity boundaries for permeability and normal strain,with m-value increasing with stress,revealing four characteristic regions.These findings offer theoretical support for optimizing fracturing techniques to enhance resource extraction efficiency.
基金supported by Basic Science Research Program through the National Natural Science Foundation of China(Grant No.61867003).
文摘As the proportion of newenergy increases,the traditional cumulant method(CM)produces significant errorswhen performing probabilistic load flow(PLF)calculations with large-scale wind power integrated.Considering the wind speed correlation,a multi-scenario PLF calculation method that combines random sampling and segmented discrete wind farm power was proposed.Firstly,based on constructing discrete scenes of wind farms,the Nataf transform is used to handle the correlation between wind speeds.Then,the random sampling method determines the output probability of discrete wind power scenarios when wind speed exhibits correlation.Finally,the PLF calculation results of each scenario areweighted and superimposed following the total probability formula to obtain the final power flow calculation result.Verified in the IEEE standard node system,the absolute percent error(APE)for the mean and standard deviation(SD)of the node voltages and branch active power are all within 1%,and the average root mean square(AMSR)values of the probability curves are all less than 1%.
