The establishment of crop yield estimating model based on microwave and optical satellite images can conduct the mutual verification of the accuracy of the reported crop yield and the precision of the estimating model...The establishment of crop yield estimating model based on microwave and optical satellite images can conduct the mutual verification of the accuracy of the reported crop yield and the precision of the estimating model. With Shou County and Huaiyuan County of Anhui Province as the experimental fields of winter wheat producing areas, the linear winter wheat yield estimating models were established by adopting backscattering coefficient and Normalized Difference Vegetation Index（NDVI） based on images from the synthetic aperture radar（SAR）—RDARSAT-2 and HJ satellite photographed in mid-April and early May, 2014, and then comparisons were conducted on the accuracy of the yield estimating models. The accuracies of the yield estimating models established using co-polarized（HH） and cross-polarized（HV） modes of SAR in Jiangou Town, Shou County were 68.37% and 74.01%, respectively, while the accuracies in Longkang Town, Huaiyuan County were 63.10%and 69.10%, respectively. Accuracies of yield estimating models established by HJ satellite data were 69.52% and 66.43% in Shou County and Huaiyuan County, respectively. Accuracies of winter yield estimating model based on HJ satellite data and that based on SAR were closed, and the yield difference of winter wheat in the lodging region was analyzed in detail. The model results laid the foundation and accumulated experience for the verification, parameters correction and promotion of the winter wheat yield estimating model.展开更多
[Objective] The aim was to compare and analyze microwave coherent and incoherent scattering models in a corn field. [Method] In the research, based on a coherent scattering model （Stile）, we proposed a coherent scat...[Objective] The aim was to compare and analyze microwave coherent and incoherent scattering models in a corn field. [Method] In the research, based on a coherent scattering model （Stile）, we proposed a coherent scattering model exclusive for corn, in which, physical optics （PO） and infinite-length dielectric cylinder were used to calculate single-scattering matrices of corn leaves and stalks. In addition, coherent components produced from interaction among the scattering mechanisms were also considered and this coherent model was compared with the Michigan Mi- crowave Canopy Scattering （MIMICS） model. The measured data in a corn filed in Gongzhuling in Jilin Province were used as the input parameters of the coherent and incoherent models. We simulated backscattering coefficients of VV and HH po- larization at L and C bands and made a comparison between the simulation results. [Result] The simulation results at L-band were poor, which indicated that we could not find regularity at early growth stage of vegetation. In addition, comparisons be- tween coherent and incoherent scattering models proved that the coherence triggered by the scattering mechanism was small. [Conclusion] In the research, we analyzed differences between coherent and incoherent scattering models with change of incident angle, and further analysis on the differences with change of vegetation and soil needed to be made in future.展开更多
Dry matter intake （DMI） prediction models of NRC （2001）, Fox et aL （2004） and Fuentes-Pila et aL （2003） were targeted in the present study, and the objective was to evaluate their prediction accuracy with feed...Dry matter intake （DMI） prediction models of NRC （2001）, Fox et aL （2004） and Fuentes-Pila et aL （2003） were targeted in the present study, and the objective was to evaluate their prediction accuracy with feeding trial data of 32 lactating Holstein cows fed two total mixed rations with different forage source. Thirty-two cows were randomly assigned to one of two total mixed ration groups： a ration containing a mixed forage （MF） of 3.7% Chinese wildrye, 28.4% alfalfa hay and 26.5% corn silage diet and another ration containing 33.8% corn stover （CS） as unique forage source. The actual DMI was greater in MF group than in CS group （P=0.064）. The NRC model to predict DMI resulted in the lowest root mean square prediction error for both MF and CS groups （1.09 kg d-1 vs. 1.28 kg d-1） and the highest accuracy and precision based on concordance correlation coefficient for both MF and CS diet （0.89 vs. 0.87）. Except the NRC model, the other two models presented mean and linear biases in both MF and CS diets when prediction residuals were plotted against predicted DMI values （P〈0.001）. The DMI variation in MF was caused by week of lactation （55.6%）, milk yield （13.9%）, milk fat percentage （7.1%） and dietary neutral detergent fiber （13.3%）, while the variation in CS was caused by week of lactation （50.9%）, live body weight （28.2%）, milk yield （8.4%）, milk fat percentage （5.2%） and dietary neutral detergent fibre （3.8%）. In a brief, the NRC model to predict DMI is comparatively acceptable for lactating dairy cows fed two total mixed rations with different forage source.展开更多
Background： Effective methods for managing patients with solitary pulmonary nodules（SPNs） depend critically on the predictive probability of malignancy.Methods： Between July 2009 and June 2011, data on gender, age...Background： Effective methods for managing patients with solitary pulmonary nodules（SPNs） depend critically on the predictive probability of malignancy.Methods： Between July 2009 and June 2011, data on gender, age, cancer history, tumor familial history, smoking status, tumor location, nodule size, spiculation, calcification, the tumor border, and the final pathological diagnosis were collected retrospectively from 154 surgical patients with an SPN measuring 3-30 mm. Each final diagnosis was compared with the probability calculated by three predicted models—the Mayo, VA, and Peking University（PU） models. The accuracy of each model was assessed using area under the receiver operating characteristics（ROC） and calibration curves.Results： The area under the ROC curve of the PU model [0.800; 95% confidence interval（CI）： 0.708-0.891] was higher than that of the Mayo model（0.753; 95% CI： 0.650-0.857） or VA model（0.728; 95% CI： 0.623-0.833）; however, this finding was not statistically significant. To varying degrees, calibration curves showed that all three models overestimated malignancy.Conclusions： The three predicted models have similar accuracy for prediction of SPN malignancy, although the accuracy is not sufficient. For Chinese patients, the PU model may has greater predictive power.Background： Here, we introduced our short experience on the application of a new CUSA Excel ultrasonic aspiration system, which was provided by Integra Lifesciences corporation, in skull base meningiomas resection.Methods： Ten patients with anterior, middle skull base and sphenoid ridge meningioma were operated using the CUSA Excel ultrasonic aspiration system at the Neurosurgery Department of Shanghai Huashan Hospital from August 2014 to October 2014. There were six male and four female patients, aged from 38 to 61 years old（the mean age was 48.5 years old）. Five cases with tumor located at anterior skull base, three cases with tumor on middle skull base, and two cases with tumor on sphenoid ridge.Results： All the patents received total resection of meningiomas with the help of this new tool, and the critical brain vessels and nerves were preserved during operations. All the patients recovered well after operation.Conclusions： This new CUSA Excel ultrasonic aspiration system has the advantage of preserving vital brain arteries and cranial nerves during skull base meningioma resection, which is very important for skull base tumor operations. This key step would ensure a well prognosis for patients. We hope the neurosurgeons would benefit from this kind of technique.Background： The purposes of this study were to explore the effects of high mobility group protein box 1（HMGB1） gene on the growth, proliferation, apoptosis, invasion, and metastasis of glioma cells, with an attempt to provide potential therapeutic targets for the treatment of glioma. Methods： The expressions of HMGB1 in glioma cells（U251, U-87 MG and LN-18） and one control cell line（SVG p12） were detected by real time PCR and Western blotting, respectively. Then, the effects of HMGB1 on the biological behaviors of glioma cells were detected： the expression of HMGB1 in human glioma cell lines U251 and U-87 MG were suppressed using RNAi technique, then the influences of HMGB1 on the viability, cycle, apoptosis, and invasion abilities of U251 and U-87 MG cells were analyzed using in a Transwell invasion chamber. Also, the effects of HMGB1 on the expressions of cyclin D1, Bax, Bcl-2, and MMP 9 were detected. Results： As shown by real-time PCR and Western blotting, the expression of HMGB1 significantly increased in glioma cells（U251, U-87 MG, and LN-18） in comparison with the control cell line（SVG p12）; the vitality, proliferation and invasive capabilities of U251 and U-87 MG cells in the HMGB1 siR NA-transfected group were significantly lower than those in the blank control group and negative control（NC） siR NA group（P〈0.05） but showed no significant difference between the blank control group and NC siR NA group. The percentage of apoptotic U251 and U-87 MG cells was significantly higher in the HMGB1 siR NA-transfected group than in the blank control group and NC siR NA group（P〈0.05） but was similar between the latter two groups. The HMGB1 siR NA-transfected group had significantly lower expression levels of Cyclin D1, Bcl-2, and MMP-9 protein in U251 and U-87 MG cells and significantly higher expression of Bax protein than in the blank control group and NC siR NA group（P〈0.05）; the expression profiles of cyclin D1, Bax, Bcl-2, and MMP 9 showed no significant change in both blank control group and NC siR NA group. Conclusions： HMGB1 gene may promote the proliferation and migration of glioma cells and suppress its effects of apoptosis. Inhibition of the expression of HMGB1 gene can suppress the proliferation and migration of glioma cells and promote their apoptosis. Our observations provided a new target for intervention and treatment of glioma.展开更多
Potential evapotranspiration(EPET)is usually calculated by empirical methods from surface meteorological variables,such as temperature,radiation and wind speed.The in-situ measured pan evaporation(ETpan)can also be us...Potential evapotranspiration(EPET)is usually calculated by empirical methods from surface meteorological variables,such as temperature,radiation and wind speed.The in-situ measured pan evaporation(ETpan)can also be used as a proxy for EPET.In this study,EPET values computed from ten models are compared with observed ETpan data in ten Chinese river basins for the period 1961−2013.The daily observed meteorological variables at 2267 stations are used as the input to those models,and a ranking scheme is applied to rank the statistical quantities(ratio of standard deviations,correlation coefficient,and ratio of trends)between ETpan and modeled EPET in different river basins.There are large deviations between the modeled EPET and the ETpan in both the magnitude and the annual trend at most stations.In eight of the basins(except for Southeast and Southwest China),ETpan shows decreasing trends with magnitudes ranging between−0.01 mm d−1 yr−1 and−0.03 mm d−1 yr−1,while the decreasing trends in modeled EPET are less than−0.01 mm d−1 yr−1.Inter comparisons among different models in different river basins suggest that PETHam1 is the best model in the Pearl River basin,PETHam2 outperforms other models in the Huaihe River,Yangtze River and Yellow River basins,and PETFAO is the best model for the remaining basins.Sensitivity analyses reveal that wind speed and sunshine duration are two important factors for decreasing EPET in most basins except in Southeast and Southwest China.The increasing EPET trend in Southeast China is mainly attributed to the reduced relative humidity.展开更多
Driven by rapid technological advancements and economic growth,mineral extraction and metal refining have increased dramatically,generating huge volumes of tailings and mine waste(TMWs).Investigating the morphological...Driven by rapid technological advancements and economic growth,mineral extraction and metal refining have increased dramatically,generating huge volumes of tailings and mine waste(TMWs).Investigating the morphological fractions of heavy metals and metalloids(HMMs)in TMWs is key to evaluating their leaching potential into the environment;however,traditional experiments are time-consuming and labor-intensive.In this study,10 machine learning(ML)algorithms were used and compared for rapidly predicting the morphological fractions of HMMs in TMWs.A dataset comprising 2376 data points was used,with mineral composition,elemental properties,and total concentration used as inputs and concentration of morphological fraction used as output.After grid search optimization,the extra tree model performed the best,achieving coefficient of determination(R2)of 0.946 and 0.942 on the validation and test sets,respectively.Electronegativity was found to have the greatest impact on the morphological fraction.The models’performance was enhanced by applying an ensemble method to the top three optimal ML models,including gradient boosting decision tree,extra trees and categorical boosting.Overall,the proposed framework can accurately predict the concentrations of different morphological fractions of HMMs in TMWs.This approach can minimize detection time,aid in the safe management and recovery of TMWs.展开更多
Tailings produced by mining and ore smelting are a major source of soil pollution.Understanding the speciation of heavy metals(HMs)in tailings is essential for soil remediation and sustainable development.Given the co...Tailings produced by mining and ore smelting are a major source of soil pollution.Understanding the speciation of heavy metals(HMs)in tailings is essential for soil remediation and sustainable development.Given the complex and time-consuming nature of traditional sequential laboratory extraction methods for determining the forms of HMs in tailings,a rapid and precise identification approach is urgently required.To address this issue,a general empirical prediction method for HM occurrence was developed using machine learning(ML).The compositional information of the tailings,properties of the HMs,and sequential extraction steps were used as inputs to calculate the percentages of the seven forms of HMs.After the models were tuned and compared,extreme gradient boosting,gradient boosting decision tree,and categorical boosting methods were found to be the top three performing ML models,with the coefficient of determination(R^(2))values on the testing set exceeding 0.859.Feature importance analysis for these three optimal models indicated that electronegativity was the most important factor affecting the occurrence of HMs,with an average feature importance of 0.4522.The subsequent use of stacking as a model integration method enabled the ability of the ML models to predict HM occurrence forms to be further improved,and resulting in an increase of R^(2) to 0.879.Overall,this study developed a robust technique for predicting the occurrence forms in tailings and provides an important reference for the environmental assessment and recycling of tailings.展开更多
To address the installation challenges of a 2-m ring Gregorian telescope system,and similar optical systems with a small width-to-radius ratio,we propose a detection method combining local interferometry with a compar...To address the installation challenges of a 2-m ring Gregorian telescope system,and similar optical systems with a small width-to-radius ratio,we propose a detection method combining local interferometry with a comparison model.This method enhances the precision of system calibration by establishing a dataset that delineates the relationship between secondary mirror misalignment and wavefront aberration,subsequently inferring the misalignment from interferometric detection results during the calibration process.For the 2-m ring telescope,we develop a detection model using five local sub-apertures,enabling a root-mean-square detection accuracy of 0:0225λ(λ=632:8 nm)for full-aperture wavefront aberration.The calibration results for the 2-m Ring Solar Telescope system indicate that the root-mean-square value of sub-aperture wavefront aberration reaches 0.104λ,and the root-mean-square value of spliced full-aperture measurement yields reaches 0.112λ.This method offers a novel approach for calibrating small width-toradius ratio telescope systems and can be applied to the calibration of other irregular-aperture optical systems.展开更多
The monsoon intraseasonal oscillation(MISO)is the dominant variability over the Indian Ocean during the Indian summer monsoon(ISM)season and is characterized by pronounced northward propagation.Previous studies have s...The monsoon intraseasonal oscillation(MISO)is the dominant variability over the Indian Ocean during the Indian summer monsoon(ISM)season and is characterized by pronounced northward propagation.Previous studies have shown that general circulation models(GCMs)still have difficulty in simulating the northwardpropagating MISO,and that the role of air-sea interaction in MISO is unclear.In this study,14 atmosphere-ocean coupled GCMs(CGCMs)and the corresponding atmosphere-only GCMs(AGCMs)are selected from Phase 6 of the Coupled Model Intercomparison Project(CMIP6)to assess their performance in reproducing MISO and the associated vortex tilting mechanism.The results show that both CGCMs and AGCMs are able to well simulate the significant relationship between MISO and vortex tilting.However,80%of CGCMs show better simulation skills for MISO than AGCMs in CMIP6.In AGCMs,the poor model fidelity in MISO is due to the failure simulation of vortex tilting.Moreover,it is found that failure to simulate the downward motion to the north of convection is responsible for the poor simulation of vortex tilting in AGCMs.In addition,it is observed that there is a significant relationship between the simulated sea surface temperature gradient and simulated vertical velocity shear in the meridional direction.These findings indicate that air-sea interaction may play a vital role in simulating vertical motions in tilting and MISO processes.This work offers us a specific target to improve the MISO simulation and further studies are needed to elucidate the physical processes of this air-sea interaction coupling with vortex tilting.展开更多
In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocal...In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocally diffusive species and degenerately diffusive species.We prove that the traveling wavefronts are exponentially stable,when the initial perturbation around the traveling waves decays exponentially as x→-∞,but in other locations,the initial data can be arbitrarily large.The adopted methods are the weighted energy with the comparison principle and squeezing technique.展开更多
In this paper, the many indices used in validation of crop models, such as RMSE （root mean square errors）, Sd （standard error of absolute difference）, da （mean absolute difference）, dap （ratio of da to the mean...In this paper, the many indices used in validation of crop models, such as RMSE （root mean square errors）, Sd （standard error of absolute difference）, da （mean absolute difference）, dap （ratio of da to the mean observation）, r （correlation）, and R2 （determination coefficient）, are compared for the same rice architectural parameter model, and their advantages and disadvantages are analyzed. A new index for validation of crop models, dap between the observed and the simulated values, is proposed, with dap〈5% as the suggested standard for precision of crop models. The different kinds of validation methods in crop models should be combined in the following aspects：（1） calculating da and dap; （2） calculating the RMSE or Sd; （3） calculating r and R2, at the same time, plotting 1：1 diagram.展开更多
OBJECTIVE: To help researchers selecting appropriate data mining models to provide better evidence for the clinical practice of Traditional Chinese Medicine(TCM) diagnosis and therapy.METHODS: Clinical issues based on...OBJECTIVE: To help researchers selecting appropriate data mining models to provide better evidence for the clinical practice of Traditional Chinese Medicine(TCM) diagnosis and therapy.METHODS: Clinical issues based on data mining models were comprehensively summarized from four significant elements of the clinical studies:symptoms, symptom patterns, herbs, and efficacy.Existing problems were further generalized to determine the relevant factors of the performance of data mining models, e.g. data type, samples, parameters, variable labels. Combining these relevant factors, the TCM clinical data features were compared with regards to statistical characters and informatics properties. Data models were compared simultaneously from the view of applied conditions and suitable scopes.RESULTS: The main application problems were the inconsistent data type and the small samples for the used data mining models, which caused the inappropriate results, even the mistake results. These features, i.e. advantages, disadvantages, satisfied data types, tasks of data mining, and the TCM issues, were summarized and compared.CONCLUSION: By aiming at the special features of different data mining models, the clinical doctors could select the suitable data mining models to resolve the TCM problem.展开更多
The rat high-impact free weight drop model mimics the diffuse axonal injury caused by severe traumatic brain injury in humans,while severe controlled cortical impact can produce a severe traumatic brain injury model u...The rat high-impact free weight drop model mimics the diffuse axonal injury caused by severe traumatic brain injury in humans,while severe controlled cortical impact can produce a severe traumatic brain injury model using precise strike parameters.In this study,we compare the pathological mechanisms and pathological changes between two rat severe brain injury models to identify the similarities and differences.The severe controlled cortical impact model was produced by an electronic controlled cortical impact device,while the severe free weight drop model was produced by dropping a 500 g free weight from a height of 1.8 m through a plastic tube.Body temperature and mortality were recorded,and neurological deficits were assessed with the modified neurological severity score.Brain edema and bloodbrain barrier damage were evaluated by assessing brain water content and Evans blue extravasation.In addition,a cytokine array kit was used to detect inflammatory cytokines.Neuronal apoptosis in the brain and brainstem was quantified by immunofluorescence staining.Both the severe controlled cortical impact and severe free weight drop models exhibited significant neurological impairments and body temperature fluctuations.More severe motor dysfunction was observed in the severe controlled cortical impact model,while more severe cognitive dysfunction was observed in the severe free weight drop model.Brain edema,inflammatory cytokine changes and cortical neuronal apoptosis were more substantial and blood-brain barrier damage was more focal in the severe controlled cortical impact group compared with the severe free weight drop group.The severe free weight drop model presented with more significant apoptosis in the brainstem and diffused blood-brain barrier damage,with higher mortality and lower repeatability compared with the severe controlled cortical impact group.Severe brainstem damage was not found in the severe controlled cortical impact model.These results indicate that the severe controlled cortical impact model is relatively more stable,more reproducible,and shows obvious cerebral pathological changes at an earlier stage.Therefore,the severe controlled cortical impact model is likely more suitable for studies on severe focal traumatic brain injury,while the severe free weight drop model may be more apt for studies on diffuse axonal injury.All experimental procedures were approved by the Ethics Committee of Animal Experiments of Tianjin Medical University,China(approval No.IRB2012-028-02)in Febru ary 2012.展开更多
Atmospheric CO_(2)is one of key parameters to estimate air-sea CO_(2)flux.The Orbiting Carbon Observatory-2(OCO-2)satellite has observed the column-averaged dry-air mole fractions of global atmospheric carbon dioxide(...Atmospheric CO_(2)is one of key parameters to estimate air-sea CO_(2)flux.The Orbiting Carbon Observatory-2(OCO-2)satellite has observed the column-averaged dry-air mole fractions of global atmospheric carbon dioxide(XCO_(2))since 2014.In this study,the OCO-2 XCO_(2)products were compared between in-situ data from the Total Carbon Column Network(TCCON)and Global Monitoring Division(GMD),and modeling data from CarbonTracker2019 over global ocean and land.Results showed that the OCO-2 XCO_(2)data are consistent with the TCCON and GMD in situ XCO_(2)data,with mean absolute biases of 0.25×10^(-6)and 0.67×10^(-6),respectively.Moreover,the OCO-2 XCO_(2)data are also consistent with the CarbonTracker2019 modeling XCO_(2)data,with mean absolute biases of 0.78×10^(-6)over ocean and 1.02×10^(-6)over land.The results indicated the high accuracy of the OCO-2 XCO_(2)product over global ocean which could be applied to estimate the air-sea CO_(2)flux.展开更多
The Chinese mainland is subject to complicated plate interactions that give rise to its complex structure and tectonics. While several seismic velocity models have been developed for the Chinese mainland, apparent dis...The Chinese mainland is subject to complicated plate interactions that give rise to its complex structure and tectonics. While several seismic velocity models have been developed for the Chinese mainland, apparent discrepancies exist and, so far, little effort has been made to evaluate their reliability and consistency. Such evaluations are important not only for the application and interpretation of model results but also for future model improvement. To address this problem, here we compare five published shear-wave velocity models with a focus on model consistency. The five models were derived from different datasets and methods (i.e., body waves, surface waves from earthquakes, surface waves from noise interferometry, and full waves) and interpolated into uniform horizontal grids (0.5° × 0.5°) with vertical sampling points at 5 km, 10 km, and then 20 km intervals to a depth of 160 km below the surface, from which we constructed an averaged model (AM) as a common reference for comparative study. We compare both the absolute velocity values and perturbation patterns of these models. Our comparisons show that the models have large (> 4%) differences in absolute values, and these differences are independent of data coverage and model resolution. The perturbation patterns of the models also show large differences, although some of the models show a high degree of consistency within certain depth ranges. The observed inconsistencies may reflect limited model resolution but, more importantly, systematic differences in the datasets and methods employed. Thus, despite several seismic models being published for this region, there is significant room for improvement. In particular, the inconsistencies in both data and methodologies need to be resolved in future research. Finally, we constructed a merged model (ChinaM-S1.0) that incorporates the more robust features of the five published models. As the existing models are constrained by different datasets and methods, the merged model serves as a new type of reference model that incorporates the common features from the joint datasets and methods for the shear-wave velocity structure of the Chinese mainland lithosphere.展开更多
The margin of the Tibetan Plateau of Southwest China is one of the most seismically active regions of China and is the location of the China Seismic Experimental Site(CSES).Many studies have developed seismic velocity...The margin of the Tibetan Plateau of Southwest China is one of the most seismically active regions of China and is the location of the China Seismic Experimental Site(CSES).Many studies have developed seismic velocity models of Southwest China,but few have compared and evaluated these models which is important for further model improvement.Thus,we compared six published seismic shear-wave velocity models of Southwest China on absolute velocity and velocity perturbation patterns.The models are derived from different types of data(e.g.,surface waves from ambient noise and earthquakes,body-wave travel times,receiver functions)and inversion methods.We interpolated the models into a uniform horizontal grid(0.5°×0.5°)and vertically sampled them at 5,10,20,30,40,and 60 km depths.We found significant differences between the six models.Then,we selected three of them that showed greater consistency for further comparison.Our further comparisons revealed systematic biases between models in absolute velocity that may be related to different data types.The perturbation pattern of the model is especially divergent in the shallow part,but more consistent in the deep part.We conducted synthetic and inversion tests to explore possible causes and our results imply that systematic differences between the data,differences in methods,and other factors may directly affect the model.Therefore,the Southwest China velocity model still has considerable room for improvement,and the impact of inconsistency between different data types on the model needs further research.Finally,we proposed a new reference shear-wave velocity model of Southwest China(SwCM-S1.0)based on the three selected models with high consistency.We believe that this model is a better representation of more robust features of the models that are based on different data sets.展开更多
Jerome Model and Horace Model are the two influential translation models in the translation field. This article tries to find the similarities and differences between these two models.
Compound Poisson risk model has been simulated. It has started with exponential claim sizes. The simulations have checked for infinite ruin probabilities. An appropriate time window has been chosen to estimate and com...Compound Poisson risk model has been simulated. It has started with exponential claim sizes. The simulations have checked for infinite ruin probabilities. An appropriate time window has been chosen to estimate and compare ruin probabilities. The infinite ruin probabilities of two-compound Poisson risk process have estimated and compared them with standard theoretical results.展开更多
基金Supported by the National Natural Science Foundation of China(41205126)the Discipline Construction and Macroscopic Agricultural Research Project of Anhui Academy of Agricultural Sciences(13A1424)+2 种基金the Fund for Youth Innovation of Anhui Academy of Agricultural Sciences(14B1460)the Innovative Research Team for Agricultural Disaster Risk Analysis in Anhui ProvinceAnhui Academy of Agricultural Sciences(14C1409)~~
文摘The establishment of crop yield estimating model based on microwave and optical satellite images can conduct the mutual verification of the accuracy of the reported crop yield and the precision of the estimating model. With Shou County and Huaiyuan County of Anhui Province as the experimental fields of winter wheat producing areas, the linear winter wheat yield estimating models were established by adopting backscattering coefficient and Normalized Difference Vegetation Index（NDVI） based on images from the synthetic aperture radar（SAR）—RDARSAT-2 and HJ satellite photographed in mid-April and early May, 2014, and then comparisons were conducted on the accuracy of the yield estimating models. The accuracies of the yield estimating models established using co-polarized（HH） and cross-polarized（HV） modes of SAR in Jiangou Town, Shou County were 68.37% and 74.01%, respectively, while the accuracies in Longkang Town, Huaiyuan County were 63.10%and 69.10%, respectively. Accuracies of yield estimating models established by HJ satellite data were 69.52% and 66.43% in Shou County and Huaiyuan County, respectively. Accuracies of winter yield estimating model based on HJ satellite data and that based on SAR were closed, and the yield difference of winter wheat in the lodging region was analyzed in detail. The model results laid the foundation and accumulated experience for the verification, parameters correction and promotion of the winter wheat yield estimating model.
基金Supported by Hunan Provincial Natural Science Foundation(10JJ4027)Opening Fund of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing(10R01)~~
文摘[Objective] The aim was to compare and analyze microwave coherent and incoherent scattering models in a corn field. [Method] In the research, based on a coherent scattering model （Stile）, we proposed a coherent scattering model exclusive for corn, in which, physical optics （PO） and infinite-length dielectric cylinder were used to calculate single-scattering matrices of corn leaves and stalks. In addition, coherent components produced from interaction among the scattering mechanisms were also considered and this coherent model was compared with the Michigan Mi- crowave Canopy Scattering （MIMICS） model. The measured data in a corn filed in Gongzhuling in Jilin Province were used as the input parameters of the coherent and incoherent models. We simulated backscattering coefficients of VV and HH po- larization at L and C bands and made a comparison between the simulation results. [Result] The simulation results at L-band were poor, which indicated that we could not find regularity at early growth stage of vegetation. In addition, comparisons be- tween coherent and incoherent scattering models proved that the coherence triggered by the scattering mechanism was small. [Conclusion] In the research, we analyzed differences between coherent and incoherent scattering models with change of incident angle, and further analysis on the differences with change of vegetation and soil needed to be made in future.
基金financially supported by the National Natural Science Foundation of China(31572435)the National Key Research and Development Plan(2016YFD0700205,2016YFD0700201)
文摘Dry matter intake （DMI） prediction models of NRC （2001）, Fox et aL （2004） and Fuentes-Pila et aL （2003） were targeted in the present study, and the objective was to evaluate their prediction accuracy with feeding trial data of 32 lactating Holstein cows fed two total mixed rations with different forage source. Thirty-two cows were randomly assigned to one of two total mixed ration groups： a ration containing a mixed forage （MF） of 3.7% Chinese wildrye, 28.4% alfalfa hay and 26.5% corn silage diet and another ration containing 33.8% corn stover （CS） as unique forage source. The actual DMI was greater in MF group than in CS group （P=0.064）. The NRC model to predict DMI resulted in the lowest root mean square prediction error for both MF and CS groups （1.09 kg d-1 vs. 1.28 kg d-1） and the highest accuracy and precision based on concordance correlation coefficient for both MF and CS diet （0.89 vs. 0.87）. Except the NRC model, the other two models presented mean and linear biases in both MF and CS diets when prediction residuals were plotted against predicted DMI values （P〈0.001）. The DMI variation in MF was caused by week of lactation （55.6%）, milk yield （13.9%）, milk fat percentage （7.1%） and dietary neutral detergent fiber （13.3%）, while the variation in CS was caused by week of lactation （50.9%）, live body weight （28.2%）, milk yield （8.4%）, milk fat percentage （5.2%） and dietary neutral detergent fibre （3.8%）. In a brief, the NRC model to predict DMI is comparatively acceptable for lactating dairy cows fed two total mixed rations with different forage source.
基金granted by the initiative research scheme for college student, Guangdong, China (No. 1212110046)
文摘Background： Effective methods for managing patients with solitary pulmonary nodules（SPNs） depend critically on the predictive probability of malignancy.Methods： Between July 2009 and June 2011, data on gender, age, cancer history, tumor familial history, smoking status, tumor location, nodule size, spiculation, calcification, the tumor border, and the final pathological diagnosis were collected retrospectively from 154 surgical patients with an SPN measuring 3-30 mm. Each final diagnosis was compared with the probability calculated by three predicted models—the Mayo, VA, and Peking University（PU） models. The accuracy of each model was assessed using area under the receiver operating characteristics（ROC） and calibration curves.Results： The area under the ROC curve of the PU model [0.800; 95% confidence interval（CI）： 0.708-0.891] was higher than that of the Mayo model（0.753; 95% CI： 0.650-0.857） or VA model（0.728; 95% CI： 0.623-0.833）; however, this finding was not statistically significant. To varying degrees, calibration curves showed that all three models overestimated malignancy.Conclusions： The three predicted models have similar accuracy for prediction of SPN malignancy, although the accuracy is not sufficient. For Chinese patients, the PU model may has greater predictive power.Background： Here, we introduced our short experience on the application of a new CUSA Excel ultrasonic aspiration system, which was provided by Integra Lifesciences corporation, in skull base meningiomas resection.Methods： Ten patients with anterior, middle skull base and sphenoid ridge meningioma were operated using the CUSA Excel ultrasonic aspiration system at the Neurosurgery Department of Shanghai Huashan Hospital from August 2014 to October 2014. There were six male and four female patients, aged from 38 to 61 years old（the mean age was 48.5 years old）. Five cases with tumor located at anterior skull base, three cases with tumor on middle skull base, and two cases with tumor on sphenoid ridge.Results： All the patents received total resection of meningiomas with the help of this new tool, and the critical brain vessels and nerves were preserved during operations. All the patients recovered well after operation.Conclusions： This new CUSA Excel ultrasonic aspiration system has the advantage of preserving vital brain arteries and cranial nerves during skull base meningioma resection, which is very important for skull base tumor operations. This key step would ensure a well prognosis for patients. We hope the neurosurgeons would benefit from this kind of technique.Background： The purposes of this study were to explore the effects of high mobility group protein box 1（HMGB1） gene on the growth, proliferation, apoptosis, invasion, and metastasis of glioma cells, with an attempt to provide potential therapeutic targets for the treatment of glioma. Methods： The expressions of HMGB1 in glioma cells（U251, U-87 MG and LN-18） and one control cell line（SVG p12） were detected by real time PCR and Western blotting, respectively. Then, the effects of HMGB1 on the biological behaviors of glioma cells were detected： the expression of HMGB1 in human glioma cell lines U251 and U-87 MG were suppressed using RNAi technique, then the influences of HMGB1 on the viability, cycle, apoptosis, and invasion abilities of U251 and U-87 MG cells were analyzed using in a Transwell invasion chamber. Also, the effects of HMGB1 on the expressions of cyclin D1, Bax, Bcl-2, and MMP 9 were detected. Results： As shown by real-time PCR and Western blotting, the expression of HMGB1 significantly increased in glioma cells（U251, U-87 MG, and LN-18） in comparison with the control cell line（SVG p12）; the vitality, proliferation and invasive capabilities of U251 and U-87 MG cells in the HMGB1 siR NA-transfected group were significantly lower than those in the blank control group and negative control（NC） siR NA group（P〈0.05） but showed no significant difference between the blank control group and NC siR NA group. The percentage of apoptotic U251 and U-87 MG cells was significantly higher in the HMGB1 siR NA-transfected group than in the blank control group and NC siR NA group（P〈0.05） but was similar between the latter two groups. The HMGB1 siR NA-transfected group had significantly lower expression levels of Cyclin D1, Bcl-2, and MMP-9 protein in U251 and U-87 MG cells and significantly higher expression of Bax protein than in the blank control group and NC siR NA group（P〈0.05）; the expression profiles of cyclin D1, Bax, Bcl-2, and MMP 9 showed no significant change in both blank control group and NC siR NA group. Conclusions： HMGB1 gene may promote the proliferation and migration of glioma cells and suppress its effects of apoptosis. Inhibition of the expression of HMGB1 gene can suppress the proliferation and migration of glioma cells and promote their apoptosis. Our observations provided a new target for intervention and treatment of glioma.
基金supported by the National Natural Science Foundation of China(Grant No.41875106)the National Key R&D Program of China(Grant No.2016YFA0602401)。
文摘Potential evapotranspiration(EPET)is usually calculated by empirical methods from surface meteorological variables,such as temperature,radiation and wind speed.The in-situ measured pan evaporation(ETpan)can also be used as a proxy for EPET.In this study,EPET values computed from ten models are compared with observed ETpan data in ten Chinese river basins for the period 1961−2013.The daily observed meteorological variables at 2267 stations are used as the input to those models,and a ranking scheme is applied to rank the statistical quantities(ratio of standard deviations,correlation coefficient,and ratio of trends)between ETpan and modeled EPET in different river basins.There are large deviations between the modeled EPET and the ETpan in both the magnitude and the annual trend at most stations.In eight of the basins(except for Southeast and Southwest China),ETpan shows decreasing trends with magnitudes ranging between−0.01 mm d−1 yr−1 and−0.03 mm d−1 yr−1,while the decreasing trends in modeled EPET are less than−0.01 mm d−1 yr−1.Inter comparisons among different models in different river basins suggest that PETHam1 is the best model in the Pearl River basin,PETHam2 outperforms other models in the Huaihe River,Yangtze River and Yellow River basins,and PETFAO is the best model for the remaining basins.Sensitivity analyses reveal that wind speed and sunshine duration are two important factors for decreasing EPET in most basins except in Southeast and Southwest China.The increasing EPET trend in Southeast China is mainly attributed to the reduced relative humidity.
基金Project(2024JJ2074) supported by the Natural Science Foundation of Hunan Province,ChinaProject(22376221) supported by the National Natural Science Foundation of ChinaProject(2023QNRC001) supported by the Young Elite Scientists Sponsorship Program by CAST,China。
文摘Driven by rapid technological advancements and economic growth,mineral extraction and metal refining have increased dramatically,generating huge volumes of tailings and mine waste(TMWs).Investigating the morphological fractions of heavy metals and metalloids(HMMs)in TMWs is key to evaluating their leaching potential into the environment;however,traditional experiments are time-consuming and labor-intensive.In this study,10 machine learning(ML)algorithms were used and compared for rapidly predicting the morphological fractions of HMMs in TMWs.A dataset comprising 2376 data points was used,with mineral composition,elemental properties,and total concentration used as inputs and concentration of morphological fraction used as output.After grid search optimization,the extra tree model performed the best,achieving coefficient of determination(R2)of 0.946 and 0.942 on the validation and test sets,respectively.Electronegativity was found to have the greatest impact on the morphological fraction.The models’performance was enhanced by applying an ensemble method to the top three optimal ML models,including gradient boosting decision tree,extra trees and categorical boosting.Overall,the proposed framework can accurately predict the concentrations of different morphological fractions of HMMs in TMWs.This approach can minimize detection time,aid in the safe management and recovery of TMWs.
基金financially supported by the Natural Science Foundation of Hunan Province,China(No.2024JJ2074)the National Natural Science Foundation of China(No.22376221)the Young Elite Scientists Sponsorship Program by CAST,China(No.2023QNRC001).
文摘Tailings produced by mining and ore smelting are a major source of soil pollution.Understanding the speciation of heavy metals(HMs)in tailings is essential for soil remediation and sustainable development.Given the complex and time-consuming nature of traditional sequential laboratory extraction methods for determining the forms of HMs in tailings,a rapid and precise identification approach is urgently required.To address this issue,a general empirical prediction method for HM occurrence was developed using machine learning(ML).The compositional information of the tailings,properties of the HMs,and sequential extraction steps were used as inputs to calculate the percentages of the seven forms of HMs.After the models were tuned and compared,extreme gradient boosting,gradient boosting decision tree,and categorical boosting methods were found to be the top three performing ML models,with the coefficient of determination(R^(2))values on the testing set exceeding 0.859.Feature importance analysis for these three optimal models indicated that electronegativity was the most important factor affecting the occurrence of HMs,with an average feature importance of 0.4522.The subsequent use of stacking as a model integration method enabled the ability of the ML models to predict HM occurrence forms to be further improved,and resulting in an increase of R^(2) to 0.879.Overall,this study developed a robust technique for predicting the occurrence forms in tailings and provides an important reference for the environmental assessment and recycling of tailings.
基金supported by the Jiangsu Provincial Key Research and Development Program(BE2022072)the National Natural Science Foundation of China(12141304)the Natural Science Foundation of Jiangsu Province(BK20231134).
文摘To address the installation challenges of a 2-m ring Gregorian telescope system,and similar optical systems with a small width-to-radius ratio,we propose a detection method combining local interferometry with a comparison model.This method enhances the precision of system calibration by establishing a dataset that delineates the relationship between secondary mirror misalignment and wavefront aberration,subsequently inferring the misalignment from interferometric detection results during the calibration process.For the 2-m ring telescope,we develop a detection model using five local sub-apertures,enabling a root-mean-square detection accuracy of 0:0225λ(λ=632:8 nm)for full-aperture wavefront aberration.The calibration results for the 2-m Ring Solar Telescope system indicate that the root-mean-square value of sub-aperture wavefront aberration reaches 0.104λ,and the root-mean-square value of spliced full-aperture measurement yields reaches 0.112λ.This method offers a novel approach for calibrating small width-toradius ratio telescope systems and can be applied to the calibration of other irregular-aperture optical systems.
基金The Zhejiang Provincial Natural Science Foundation of China under contract No.LR19D060001the Scientific Research Fund of the Second Institute of Oceanography,Ministry of Natural Resources,under contract No.JB2206+1 种基金the China Postdoctoral Science Foundation under contract Nos 2022M711010 and 2021M703792the National Natural Science Foundation of China under contract No.42106003。
文摘The monsoon intraseasonal oscillation(MISO)is the dominant variability over the Indian Ocean during the Indian summer monsoon(ISM)season and is characterized by pronounced northward propagation.Previous studies have shown that general circulation models(GCMs)still have difficulty in simulating the northwardpropagating MISO,and that the role of air-sea interaction in MISO is unclear.In this study,14 atmosphere-ocean coupled GCMs(CGCMs)and the corresponding atmosphere-only GCMs(AGCMs)are selected from Phase 6 of the Coupled Model Intercomparison Project(CMIP6)to assess their performance in reproducing MISO and the associated vortex tilting mechanism.The results show that both CGCMs and AGCMs are able to well simulate the significant relationship between MISO and vortex tilting.However,80%of CGCMs show better simulation skills for MISO than AGCMs in CMIP6.In AGCMs,the poor model fidelity in MISO is due to the failure simulation of vortex tilting.Moreover,it is found that failure to simulate the downward motion to the north of convection is responsible for the poor simulation of vortex tilting in AGCMs.In addition,it is observed that there is a significant relationship between the simulated sea surface temperature gradient and simulated vertical velocity shear in the meridional direction.These findings indicate that air-sea interaction may play a vital role in simulating vertical motions in tilting and MISO processes.This work offers us a specific target to improve the MISO simulation and further studies are needed to elucidate the physical processes of this air-sea interaction coupling with vortex tilting.
基金Supported by the National Natural Science Foundation of China(Grant No.12261081).
文摘In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocally diffusive species and degenerately diffusive species.We prove that the traveling wavefronts are exponentially stable,when the initial perturbation around the traveling waves decays exponentially as x→-∞,but in other locations,the initial data can be arbitrarily large.The adopted methods are the weighted energy with the comparison principle and squeezing technique.
基金supported by the National High-Tech R&D Program (2006AA10Z230,2006AA10Z219-1)the National Natural Science Foundation of China (31171455)+3 种基金the Jiangsu Province Agricultural Scientific Technology Innovation Fund, China (CX(10)221, CX (11)2042)the Agricultural Scientific Technology Support Program, Jiangsu Province, China (BE2008397,BE2011342)the No-Profit Industry (Meteorology) Research Program, China (GYHY201006027, GYHY201106027)the Jiangsu Government Scholarship for Overseas Studies, China
文摘In this paper, the many indices used in validation of crop models, such as RMSE （root mean square errors）, Sd （standard error of absolute difference）, da （mean absolute difference）, dap （ratio of da to the mean observation）, r （correlation）, and R2 （determination coefficient）, are compared for the same rice architectural parameter model, and their advantages and disadvantages are analyzed. A new index for validation of crop models, dap between the observed and the simulated values, is proposed, with dap〈5% as the suggested standard for precision of crop models. The different kinds of validation methods in crop models should be combined in the following aspects：（1） calculating da and dap; （2） calculating the RMSE or Sd; （3） calculating r and R2, at the same time, plotting 1：1 diagram.
基金Supported by Research on Pattern differentiation of AIDS based on Graph Theroy of National Natural Science Foundation of China(No.81202858)Research on Intervention Evaluation of TCM Health Differentiation of National Key Technology Support Program(No.2012BAI25B02)+3 种基金Research and Development in Digital Information System of Traditional Chinese Medicine of National 863 Program of China(No.2012AA02A609)Acupuncture Efficacy of Gastrointestinal Dysfunction(No.ZZ05003)Acupuncture-point Specialty Analysis based on Image Processing Technology(No.ZZ03090)of Self-selected subject of China Academy of Chinese Medical SciencesSemantic Recognition of Tongue and Pulse based on Image Content of the Beijing Key Laboratory of Advanced Information Science and Network Technology(No.XDXX1306)
文摘OBJECTIVE: To help researchers selecting appropriate data mining models to provide better evidence for the clinical practice of Traditional Chinese Medicine(TCM) diagnosis and therapy.METHODS: Clinical issues based on data mining models were comprehensively summarized from four significant elements of the clinical studies:symptoms, symptom patterns, herbs, and efficacy.Existing problems were further generalized to determine the relevant factors of the performance of data mining models, e.g. data type, samples, parameters, variable labels. Combining these relevant factors, the TCM clinical data features were compared with regards to statistical characters and informatics properties. Data models were compared simultaneously from the view of applied conditions and suitable scopes.RESULTS: The main application problems were the inconsistent data type and the small samples for the used data mining models, which caused the inappropriate results, even the mistake results. These features, i.e. advantages, disadvantages, satisfied data types, tasks of data mining, and the TCM issues, were summarized and compared.CONCLUSION: By aiming at the special features of different data mining models, the clinical doctors could select the suitable data mining models to resolve the TCM problem.
基金supported by the National Natural Science Foundation of China,No.81671221(to RCJ)
文摘The rat high-impact free weight drop model mimics the diffuse axonal injury caused by severe traumatic brain injury in humans,while severe controlled cortical impact can produce a severe traumatic brain injury model using precise strike parameters.In this study,we compare the pathological mechanisms and pathological changes between two rat severe brain injury models to identify the similarities and differences.The severe controlled cortical impact model was produced by an electronic controlled cortical impact device,while the severe free weight drop model was produced by dropping a 500 g free weight from a height of 1.8 m through a plastic tube.Body temperature and mortality were recorded,and neurological deficits were assessed with the modified neurological severity score.Brain edema and bloodbrain barrier damage were evaluated by assessing brain water content and Evans blue extravasation.In addition,a cytokine array kit was used to detect inflammatory cytokines.Neuronal apoptosis in the brain and brainstem was quantified by immunofluorescence staining.Both the severe controlled cortical impact and severe free weight drop models exhibited significant neurological impairments and body temperature fluctuations.More severe motor dysfunction was observed in the severe controlled cortical impact model,while more severe cognitive dysfunction was observed in the severe free weight drop model.Brain edema,inflammatory cytokine changes and cortical neuronal apoptosis were more substantial and blood-brain barrier damage was more focal in the severe controlled cortical impact group compared with the severe free weight drop group.The severe free weight drop model presented with more significant apoptosis in the brainstem and diffused blood-brain barrier damage,with higher mortality and lower repeatability compared with the severe controlled cortical impact group.Severe brainstem damage was not found in the severe controlled cortical impact model.These results indicate that the severe controlled cortical impact model is relatively more stable,more reproducible,and shows obvious cerebral pathological changes at an earlier stage.Therefore,the severe controlled cortical impact model is likely more suitable for studies on severe focal traumatic brain injury,while the severe free weight drop model may be more apt for studies on diffuse axonal injury.All experimental procedures were approved by the Ethics Committee of Animal Experiments of Tianjin Medical University,China(approval No.IRB2012-028-02)in Febru ary 2012.
基金The National Key Research and Development Programme of China under contract No.2017YFA0603004the Fund of Southern Marine Science and Engineering Guangdong Laboratory(Zhanjiang)(Zhanjiang Bay Laboratory)under contract No.ZJW-2019-08+1 种基金the National Natural Science Foundation of China under contract Nos 41825014,41676172 and 41676170the Global Change and Air-Sea Interaction Project of China under contract Nos GASI-02-SCS-YGST2-01,GASI-02-PACYGST2-01 and GASI-02-IND-YGST2-01。
文摘Atmospheric CO_(2)is one of key parameters to estimate air-sea CO_(2)flux.The Orbiting Carbon Observatory-2(OCO-2)satellite has observed the column-averaged dry-air mole fractions of global atmospheric carbon dioxide(XCO_(2))since 2014.In this study,the OCO-2 XCO_(2)products were compared between in-situ data from the Total Carbon Column Network(TCCON)and Global Monitoring Division(GMD),and modeling data from CarbonTracker2019 over global ocean and land.Results showed that the OCO-2 XCO_(2)data are consistent with the TCCON and GMD in situ XCO_(2)data,with mean absolute biases of 0.25×10^(-6)and 0.67×10^(-6),respectively.Moreover,the OCO-2 XCO_(2)data are also consistent with the CarbonTracker2019 modeling XCO_(2)data,with mean absolute biases of 0.78×10^(-6)over ocean and 1.02×10^(-6)over land.The results indicated the high accuracy of the OCO-2 XCO_(2)product over global ocean which could be applied to estimate the air-sea CO_(2)flux.
基金supportedby the Special Fund of the Instituteof Geophysics,China Earthquake Administration(Grant No.DQJB21B32)the National Natural Science Foundation of China(No.U1939204).
文摘The Chinese mainland is subject to complicated plate interactions that give rise to its complex structure and tectonics. While several seismic velocity models have been developed for the Chinese mainland, apparent discrepancies exist and, so far, little effort has been made to evaluate their reliability and consistency. Such evaluations are important not only for the application and interpretation of model results but also for future model improvement. To address this problem, here we compare five published shear-wave velocity models with a focus on model consistency. The five models were derived from different datasets and methods (i.e., body waves, surface waves from earthquakes, surface waves from noise interferometry, and full waves) and interpolated into uniform horizontal grids (0.5° × 0.5°) with vertical sampling points at 5 km, 10 km, and then 20 km intervals to a depth of 160 km below the surface, from which we constructed an averaged model (AM) as a common reference for comparative study. We compare both the absolute velocity values and perturbation patterns of these models. Our comparisons show that the models have large (> 4%) differences in absolute values, and these differences are independent of data coverage and model resolution. The perturbation patterns of the models also show large differences, although some of the models show a high degree of consistency within certain depth ranges. The observed inconsistencies may reflect limited model resolution but, more importantly, systematic differences in the datasets and methods employed. Thus, despite several seismic models being published for this region, there is significant room for improvement. In particular, the inconsistencies in both data and methodologies need to be resolved in future research. Finally, we constructed a merged model (ChinaM-S1.0) that incorporates the more robust features of the five published models. As the existing models are constrained by different datasets and methods, the merged model serves as a new type of reference model that incorporates the common features from the joint datasets and methods for the shear-wave velocity structure of the Chinese mainland lithosphere.
基金supported by Open Fund from Sino Probe Laboratory(No.Sinoprobe Lab 202201)the National Natural Science Foundation of China(No.U1939204)the Special Fund of the Institute of Geophysics,China Earthquake Administration(No.DQJB21B32)
文摘The margin of the Tibetan Plateau of Southwest China is one of the most seismically active regions of China and is the location of the China Seismic Experimental Site(CSES).Many studies have developed seismic velocity models of Southwest China,but few have compared and evaluated these models which is important for further model improvement.Thus,we compared six published seismic shear-wave velocity models of Southwest China on absolute velocity and velocity perturbation patterns.The models are derived from different types of data(e.g.,surface waves from ambient noise and earthquakes,body-wave travel times,receiver functions)and inversion methods.We interpolated the models into a uniform horizontal grid(0.5°×0.5°)and vertically sampled them at 5,10,20,30,40,and 60 km depths.We found significant differences between the six models.Then,we selected three of them that showed greater consistency for further comparison.Our further comparisons revealed systematic biases between models in absolute velocity that may be related to different data types.The perturbation pattern of the model is especially divergent in the shallow part,but more consistent in the deep part.We conducted synthetic and inversion tests to explore possible causes and our results imply that systematic differences between the data,differences in methods,and other factors may directly affect the model.Therefore,the Southwest China velocity model still has considerable room for improvement,and the impact of inconsistency between different data types on the model needs further research.Finally,we proposed a new reference shear-wave velocity model of Southwest China(SwCM-S1.0)based on the three selected models with high consistency.We believe that this model is a better representation of more robust features of the models that are based on different data sets.
文摘Jerome Model and Horace Model are the two influential translation models in the translation field. This article tries to find the similarities and differences between these two models.
文摘Compound Poisson risk model has been simulated. It has started with exponential claim sizes. The simulations have checked for infinite ruin probabilities. An appropriate time window has been chosen to estimate and compare ruin probabilities. The infinite ruin probabilities of two-compound Poisson risk process have estimated and compared them with standard theoretical results.
