Structural damage in heterogeneousmaterials typically originates frommicrostructures where stress concentration occurs.Therefore,evaluating the magnitude and location of localized stress distributions within microstru...Structural damage in heterogeneousmaterials typically originates frommicrostructures where stress concentration occurs.Therefore,evaluating the magnitude and location of localized stress distributions within microstructures under external loading is crucial.Repeating unit cells(RUCs)are commonly used to represent microstructural details and homogenize the effective response of composites.This work develops a machine learning-based micromechanics tool to accurately predict the stress distributions of extracted RUCs.The locally exact homogenization theory efficiently generates the microstructural stresses of RUCs with a wide range of parameters,including volume fraction,fiber/matrix property ratio,fiber shapes,and loading direction.Subsequently,the conditional generative adversarial network(cGAN)is employed and constructed as a surrogate model to establish the statistical correlation between these parameters and the corresponding localized stresses.The stresses predicted by cGAN are validated against the remaining true data not used for training,showing good agreement.This work demonstrates that the cGAN-based micromechanics tool effectively captures the local responses of composite RUCs.It can be used for predicting potential crack initiations starting from microstructures and evaluating the effective behavior of periodic composites.展开更多
The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regressi...The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.展开更多
The shear behavior of large-scale weak intercalation shear zones(WISZs)often governs the stability of foundations,rock slopes,and underground structures.However,due to their wide distribution,undulating morphology,com...The shear behavior of large-scale weak intercalation shear zones(WISZs)often governs the stability of foundations,rock slopes,and underground structures.However,due to their wide distribution,undulating morphology,complex fabrics,and varying degrees of contact states,characterizing the shear behavior of natural and complex large-scale WISZs precisely is challenging.This study proposes an analytical method to address this issue,based on geological fieldwork and relevant experimental results.The analytical method utilizes the random field theory and Kriging interpolation technique to simplify the spatial uncertainties of the structural and fabric features for WISZs into the spatial correlation and variability of their mechanical parameters.The Kriging conditional random field of the friction angle of WISZs is embedded in the discrete element software 3DEC,enabling activation analysis of WISZ C2 in the underground caverns of the Baihetan hydropower station.The results indicate that the activation scope of WISZ C2 induced by the excavation of underground caverns is approximately 0.5e1 times the main powerhouse span,showing local activation.Furthermore,the overall safety factor of WISZ C2 follows a normal distribution with an average value of 3.697.展开更多
BACKGROUND The prognosis of many patients with distant metastatic hepatocellular carcinoma(HCC)improved after they survived for several months.Compared with tradi-tional survival analysis,conditional survival(CS)which...BACKGROUND The prognosis of many patients with distant metastatic hepatocellular carcinoma(HCC)improved after they survived for several months.Compared with tradi-tional survival analysis,conditional survival(CS)which takes into account changes in survival risk could be used to describe dynamic survival probabilities.AIM To evaluate CS of distant metastatic HCC patients.METHODS Patients diagnosed with distant metastatic HCC between 2010 and 2015 were extracted from the Surveillance,Epidemiology and End Results database.Univariate and multivariate Cox regression analysis were used to identify factors for overall survival(OS),while competing risk model was used to identify risk factors for cancer-specific survival(CSS).Six-month CS was used to calculate the probability of survival for an additional 6 mo at a specific time after initial diagnosis,and standardized difference(d)was used to evaluate the survival differences between subgroups.Nomograms were constructed to predict CS.Positiveα-fetoprotein expression,higher T stage(T3 and T4),N1 stage,non-primary site surgery,non-chemotherapy,non-radiotherapy,and lung metastasis were independent risk factors for actual OS and CSS through univariate and multivariate analysis.Actual survival rates decreased over time,while CS rates gradually increased.As for the 6-month CS,the survival difference caused by chemotherapy and radiotherapy gradually disappeared over time,and the survival difference caused by lung metastasis reversed.Moreover,the influence of age and gender on survival gradually appeared.Nomograms were fitted for patients who have lived for 2,4 and 6 mo to predict 6-month conditional OS and CSS,respectively.The area under the curve(AUC)of nomograms for conditional OS decreased as time passed,and the AUC for conditional CSS gradually increased.CONCLUSION CS for distant metastatic HCC patients substantially increased over time.With dynamic risk factors,nomograms constructed at a specific time could predict more accurate survival rates.展开更多
Using data from the Surveillance, Epidemiology, and End Results (SEER) Program based at the National Cancer Institute in the US, conditional survival rates are reported for 1,988 Ewing Sarcoma patients diagnosed durin...Using data from the Surveillance, Epidemiology, and End Results (SEER) Program based at the National Cancer Institute in the US, conditional survival rates are reported for 1,988 Ewing Sarcoma patients diagnosed during the period 2000-2015. These patients represent the experience of 26.5% of the US population. Specifically, 5-year conditional relative survival rates are calculated for these patients for the first eight years subsequent to diagnosis of their cancer by Extent of Disease (EOD) (Localized, Regional, and Distant as coded by the SEER Program), gender, and age (<18, 18 - 34, and 35+). Findings include showing how the conditional survival rate patterns improve over time and that there are differences by gender, age, and EOD.展开更多
Learning to handle hypothetical situations in a new language is always difficult(Catford,et al.,1974).This rule holds true for Moroccan Arabic(henceforth MA)speakers learning English because grammatical devices in the...Learning to handle hypothetical situations in a new language is always difficult(Catford,et al.,1974).This rule holds true for Moroccan Arabic(henceforth MA)speakers learning English because grammatical devices in the two languages differ in almost all equivalent situations.For instance,while English verb forms are used to indicate tense in conditional sentences,MA uses them to indicate aspect.Adopting the typology of conditional constructions suggested by Dancygier(1999)and Dancygier&Sweetser(2005),this study provides a contrastive analysis of conditionals in English and MA to predict the possible errors EFL/ESL learners are likely to make while learning English.The analysis shows that the main discrepancy between English conditionals and MA conditionals lies in the verb form used by the two systems.Accordingly,if EFL/ESL learners are influenced by verb form in their L1,they are likely to face some challenges while learning English conditionals.That is,they are likely to use the past tense in the protases of English predictive conditionals and generic conditionals since the perfective form of the verb is used in the protases of these two types in MA.Concerning the protases of English non-predictive conditionals,Moroccan EFL/ESL learners are likely to use either the past tense or the present tense since both the perfective and the imperfective forms of the verb are possible in the protases of MA non-predictive conditionals.However,due to the fact that the perfective form is the prototypical form in the protases of conditionals in MA,EFL/ESL learners are likely to use the past tense more often than the present tense.The analysis also shows that EFL/ESL learners tend to use the present tense in the apodoses of English conditionals since the prevalent form in the apodoses of MA conditionals is the imperfective.展开更多
Conditionally t-diagnosable and t-diagnosable are important in system level diagnosis. Therefore,it is valuable to identify whether the system is conditionally t-diagnosable or t-diagnosable and derive the correspondi...Conditionally t-diagnosable and t-diagnosable are important in system level diagnosis. Therefore,it is valuable to identify whether the system is conditionally t-diagnosable or t-diagnosable and derive the corresponding conditional diagnosability and diagnosability. In the paper,distinguishable measures of pairs of distinct faulty sets with a new perspective on establishing functions are focused.Applying distinguishable function and decision function,it is determined whether a system is conditionally t-diagnosable( or t-diagnosable) or not under the PMC( Preparata,Metze,and Chien)model directly. Based on the decision function,a novel conditional diagnosability algorithm under the PMC model is introduced which can calculate conditional diagnosability rapidly.展开更多
Oil, protein and starch are key chemical components of maize kernels. A population of 245 recombinant inbred lines(RILs) derived from a cross between a high-oil inbred line, By804, and a regular inbred line, B73, was ...Oil, protein and starch are key chemical components of maize kernels. A population of 245 recombinant inbred lines(RILs) derived from a cross between a high-oil inbred line, By804, and a regular inbred line, B73, was used to dissect the genetic interrelationships among oil, starch and protein content at the individual QTL level by unconditional and conditional QTL mapping. Combined phenotypic data over two years with a genetic linkage map constructed using 236 markers, nine, five and eight unconditional QTL were detected for oil, protein and starch content, respectively. Some QTL for oil, protein and starch content were clustered in the same genomic regions and the direction of their effects was consistent with the sign of their correlation. In conditional QTL mapping, 37(29/8) unconditional QTL were not detected or showed reduced effects, four QTL demonstrated similar effects under unconditional and conditional QTL mapping, and 17 additional QTL were identified by conditional QTL mapping. These results imply that there is a strong genetic relationship among oil, protein and starch content in maize kernels. The information generated in the present investigation could be helpful in marker-assisted breeding for maize varieties with desirable kernel quality traits.展开更多
Unconditional and conditional QTL mapping were conducted for growth duration (GD), plant height (PH) and effective panicle number per plant (PN) using a recombinant inbred line (RIL) population derived from a cross be...Unconditional and conditional QTL mapping were conducted for growth duration (GD), plant height (PH) and effective panicle number per plant (PN) using a recombinant inbred line (RIL) population derived from a cross between two japonica rice varieties Xiushui 79 and C Bao. The RIL population consisted of 254 lines was planted in two environments, Nanjing and Sihong, Jiangsu Province, China. Results showed that additive effects were major in all of QTLs for GD, PH and PN detected by the two methods, and the epistatic effects explained a small proportion of phenotypic variation. No interactions were detected between additive QTL and environment, and between epistatic QTL pairs and environment. After growth duration was adjusted to an identical level, RM80-160bp was detected as an applicable elite allele for PN, with an additive effect of 0.71. When effective panicle number per plant was adjusted to an identical level, RM448-240bp was detected as an applicable elite allele for GD, with an additive effect of 4.64. After plant height was adjusted to an identical level, RM80-160bp was detected as an applicable elite allele for PN, with an additive effect of 0.62, and RM448-240bp was detected as an applicable elite allele for GD, with an additive effect of 3.89. These applicable elite alleles could be used to improve target traits without influencing the other two traits.展开更多
This paper preliminarily investigates the application of the orthogonal conditional nonlinear optimal perturbations(CNOPs)–based ensemble forecast technique in MM5(Fifth-generation Pennsylvania State University–Nati...This paper preliminarily investigates the application of the orthogonal conditional nonlinear optimal perturbations(CNOPs)–based ensemble forecast technique in MM5(Fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model). The results show that the ensemble forecast members generated by the orthogonal CNOPs present large spreads but tend to be located on the two sides of real tropical cyclone(TC) tracks and have good agreements between ensemble spreads and ensemble-mean forecast errors for TC tracks. Subsequently, these members reflect more reasonable forecast uncertainties and enhance the orthogonal CNOPs–based ensemble-mean forecasts to obtain higher skill for TC tracks than the orthogonal SVs(singular vectors)–, BVs(bred vectors)– and RPs(random perturbations)–based ones. The results indicate that orthogonal CNOPs of smaller magnitudes should be adopted to construct the initial ensemble perturbations for short lead–time forecasts, but those of larger magnitudes should be used for longer lead–time forecasts due to the effects of nonlinearities. The performance of the orthogonal CNOPs–based ensemble-mean forecasts is case-dependent,which encourages evaluating statistically the forecast skill with more TC cases. Finally, the results show that the ensemble forecasts with only initial perturbations in this work do not increase the forecast skill of TC intensity, which may be related with both the coarse model horizontal resolution and the model error.展开更多
By altering the electrostatic charge of histones or providing binding sites to protein recognition molecules, Chromatin marks have been proposed to regulate gene expression, a property that has motivated researchers t...By altering the electrostatic charge of histones or providing binding sites to protein recognition molecules, Chromatin marks have been proposed to regulate gene expression, a property that has motivated researchers to link these marks to cis-regulatory elements. With the help of next generation sequencing technologies, we can now correlate one specific chromatin mark with regulatory elements (e.g. enhancers or promoters) and also build tools, such as hidden Markov models, to gain insight into mark combinations. However, hidden Markov models have limitation for their character of generative models and assume that a current observation depends only on a current hidden state in the chain. Here, we employed two graphical probabilistic models, namely the linear conditional random field model and multivariate hidden Markov model, to mark gene regions with different states based on recurrent and spatially coherent character of these eight marks. Both models revealed chromatin states that may correspond to enhancers and promoters, transcribed regions, transcriptional elongation, and low-signal regions. We also found that the linear conditional random field model was more effective than the hidden Markov model in recognizing regulatory elements, such as promoter-, enhancer-, and transcriptional elongation-associated regions, which gives us a better choice.展开更多
Background: Conditional survival(CS) has been established as a clinically relevant prognostic factor for cancer survivors, and the CS in gallbladder(GB) cancer has not yet been fully evaluated. In this study, we evalu...Background: Conditional survival(CS) has been established as a clinically relevant prognostic factor for cancer survivors, and the CS in gallbladder(GB) cancer has not yet been fully evaluated. In this study, we evaluated the cancerspecific CS rate and cancer-specific survival(CSS) rate in patients with GB cancer at multiple time points and investigated prognostic factors which affect cancer-specific CS rate to provide more accurate survival information.Methods: Between 2004 and 2013, a total of 9760 patients with GB cancer were identified from the Surveillance,Epidemiology, and End Results(SEER) data. The 3-year cancer-specific CS rate was calculated using the covariateadjusted survival function in the Cox model for each year since diagnosis, and the results were analyzed together with the adjusted CSS rates at the same time points. Cox proportional hazards regression was performed to ascertain the individual contribution of factors associated with CSS rate at diagnosis and cancer-specific CS rates at 1,3, and 5 years after diagnosis.Results: The adjusted 5-year CSS rate was 26.1 %. The adjusted 3-year cancer-specific CS rates at 1,2,3,4, and 5 years after diagnosis were 55.5,72.2,81.5,86.8, and 90.5%, respectively. At the time of diagnosis, age, race, histology, grade,T, N, and M categories, surgery, radiotherapy, insurance status, and marriage status were significant prognostic factors of CSS. Five years after diagnosis, however,T and M categories were significant prognostic factors for survivors(P = 0.007 and P = 0.009, respectively), whereas surgery and radiotherapy were not.Conclusions: T and M categories were significant prognostic factors even 5 years after the initial diagnosis, whereas local treatments at the time of diagnosis were not, suggesting that patients with GB cancer at high risks might need further adjuvant therapy after primary treatments. The combined analysis of CSS and cancer-specific CS rates offered more accurate survival information for patients who have already survived a certain period of time after diagnosis.展开更多
With the application of artificial intelligence technology in the power industry,the knowledge graph is expected to play a key role in power grid dispatch processes,intelligent maintenance,and customer service respons...With the application of artificial intelligence technology in the power industry,the knowledge graph is expected to play a key role in power grid dispatch processes,intelligent maintenance,and customer service response provision.Knowledge graphs are usually constructed based on entity recognition.Specifically,based on the mining of entity attributes and relationships,domain knowledge graphs can be constructed through knowledge fusion.In this work,the entities and characteristics of power entity recognition are analyzed,the mechanism of entity recognition is clarified,and entity recognition techniques are analyzed in the context of the power domain.Power entity recognition based on the conditional random fields (CRF) and bidirectional long short-term memory (BLSTM) models is investigated,and the two methods are comparatively analyzed.The results indicated that the CRF model,with an accuracy of 83%,can better identify the power entities compared to the BLSTM.The CRF approach can thus be applied to the entity extraction for knowledge graph construction in the power field.展开更多
In a multiprocessor systems, it is important to local and to replace the faulty processors to maintain systempsilas high reliability. The fault diagnosis, which is the process of identifying fault processors in a mult...In a multiprocessor systems, it is important to local and to replace the faulty processors to maintain systempsilas high reliability. The fault diagnosis, which is the process of identifying fault processors in a multiprocessor system through testing. The conditional diagnosis requires that for each processor u in a system, all the processors that are directly connected to u do not fail at the same time. In this paper, we study the conditional diagnosability of the n-dimensional locally twisted cubes. After showing some properties of the locally twisted cubes, we prove that it under the PMC model is 4n – 7 for n ≥ 5.展开更多
In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is es...In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is established by using a visual long short term memory network in the three-dimensional(3D)space and the motion estimations jointly performed on object trajectory segments.Object visual field information is added to the long short term memory network to improve the accuracy of the motion related object pair selection and motion estimation.To address the uncertainty of the length and interval of trajectory segments,a multimode long short term memory network is proposed for the object motion estimation.The tracking performance is evaluated using the PETS2009 dataset.The experimental results show that the proposed method achieves better performance than the tracking methods based on the independent motion estimation.展开更多
Based on two kinds of proxy data, a tree-ring width chronology at Huashan and the wetness/dryness grade series around Xi’an in north-centralChina, thes presat study demonstrates how different types of proxy climatere...Based on two kinds of proxy data, a tree-ring width chronology at Huashan and the wetness/dryness grade series around Xi’an in north-centralChina, thes presat study demonstrates how different types of proxy climaterecords can be combined to give a more reliable estimate of past climate thaneither record can be done individually. With comparison and correction of thetwo data sets, various statistical models can be developed from individual andcombined senes. Among them, the best combined model produced by theconditional quantile adjustmat method can be selected for reconstruction ofApril-July rainfall at Huashan back to 1600 A.D.展开更多
MicroRNAs( miRNAs) are reported to be associated with various diseases. The identification of disease-related miRNAs would be beneficial to the disease diagnosis and prognosis. However,in contrast with the widely avai...MicroRNAs( miRNAs) are reported to be associated with various diseases. The identification of disease-related miRNAs would be beneficial to the disease diagnosis and prognosis. However,in contrast with the widely available expression profiling, the limited knowledge of molecular function restrict the development of previous methods based on network similarity measure. To construct reliable training data,the decision fusion method is used to prioritize the results of existing methods. After that,the performance of decision fusion method is validated. Furthermore,in consideration of the long range dependencies of successive expression values,Hidden Conditional Random Field model( HCRF) is selected and applied to miRNA expression profiling to infer disease-associated miRNAs. The results show that HCRF achieves superior performance and outperforms the previous methods. The results also demonstrate the power of using expression profiling for discovering disease-associated miRNAs.展开更多
Factoring quadratics over Z is a staple of introductory algebra and textbooks tend to create the impression that doable factorizations are fairly common. To the contrary, if coefficients of a general quadratic are sel...Factoring quadratics over Z is a staple of introductory algebra and textbooks tend to create the impression that doable factorizations are fairly common. To the contrary, if coefficients of a general quadratic are selected randomly without restriction, the probability that a factorization exists is zero. We achieve a specific quantification of the probability of factoring quadratics by taking a new approach that considers the absolute size of coefficients to be a parameter n. This restriction allows us to make relative likelihood estimates based on finite sample spaces. Our probability estimates are then conditioned on the size parameter n and the behavior of the conditional estimates may be studied as the parameter is varied. Specifically, we enumerate how many formal factored expressions could possibly correspond to a quadratic for a given size parameter. The conditional probability of factorization as a function of n is just the ratio of this enumeration to the total number of possible quadratics consistent with n. This approach is patterned after the well-known case where factorizations are carried out over a finite field. We review the finite field method as background for our method of dealing with Z [x]. The monic case is developed independently of the general case because it is simpler and the resulting probability estimating formula is more accurate. We conclude with a comparison of our theoretical probability estimates with exact data generated by a computer search for factorable quadratics corresponding to various parameter values.展开更多
This paper aims to explore how learners of English as a second language(ESL)acquire English conditional sentences and what causes their difficulties,especially focusing on how their native languages affect their acqui...This paper aims to explore how learners of English as a second language(ESL)acquire English conditional sentences and what causes their difficulties,especially focusing on how their native languages affect their acquisition of the conditional sentences.Interviews were carried out with four undergraduate ESL students of University of Central Oklahoma in the United States who are respectively Chinese,Korean,French,and Greek.By conducting interviews with them,the participants’perceptions of acquiring English conditional sentences will be collected and analyzed.There will be some typical errors of constructing conditional sentences demonstrated.Moreover,some pedagogical implications will also be provided,which will help students have a better command of the conditional sentences.展开更多
基金the support from the National Key R&D Program of China underGrant(Grant No.2020YFA0711700)the National Natural Science Foundation of China(Grant Nos.52122801,11925206,51978609,U22A20254,and U23A20659)G.W.is supported by the National Natural Science Foundation of China(Nos.12002303,12192210 and 12192214).
文摘Structural damage in heterogeneousmaterials typically originates frommicrostructures where stress concentration occurs.Therefore,evaluating the magnitude and location of localized stress distributions within microstructures under external loading is crucial.Repeating unit cells(RUCs)are commonly used to represent microstructural details and homogenize the effective response of composites.This work develops a machine learning-based micromechanics tool to accurately predict the stress distributions of extracted RUCs.The locally exact homogenization theory efficiently generates the microstructural stresses of RUCs with a wide range of parameters,including volume fraction,fiber/matrix property ratio,fiber shapes,and loading direction.Subsequently,the conditional generative adversarial network(cGAN)is employed and constructed as a surrogate model to establish the statistical correlation between these parameters and the corresponding localized stresses.The stresses predicted by cGAN are validated against the remaining true data not used for training,showing good agreement.This work demonstrates that the cGAN-based micromechanics tool effectively captures the local responses of composite RUCs.It can be used for predicting potential crack initiations starting from microstructures and evaluating the effective behavior of periodic composites.
基金supported in part by the National Key Research and Development Program of China(2019YFB1503700)the Hunan Natural Science Foundation-Science and Education Joint Project(2019JJ70063)。
文摘The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.
基金support from the Key Projects of the Yalong River Joint Fund of the National Natural Science Foundation of China(Grant No.U1865203)the Innovation Team of Changjiang River Scientific Research Institute(Grant Nos.CKSF2021715/YT and CKSF2023305/YT)。
文摘The shear behavior of large-scale weak intercalation shear zones(WISZs)often governs the stability of foundations,rock slopes,and underground structures.However,due to their wide distribution,undulating morphology,complex fabrics,and varying degrees of contact states,characterizing the shear behavior of natural and complex large-scale WISZs precisely is challenging.This study proposes an analytical method to address this issue,based on geological fieldwork and relevant experimental results.The analytical method utilizes the random field theory and Kriging interpolation technique to simplify the spatial uncertainties of the structural and fabric features for WISZs into the spatial correlation and variability of their mechanical parameters.The Kriging conditional random field of the friction angle of WISZs is embedded in the discrete element software 3DEC,enabling activation analysis of WISZ C2 in the underground caverns of the Baihetan hydropower station.The results indicate that the activation scope of WISZ C2 induced by the excavation of underground caverns is approximately 0.5e1 times the main powerhouse span,showing local activation.Furthermore,the overall safety factor of WISZ C2 follows a normal distribution with an average value of 3.697.
文摘BACKGROUND The prognosis of many patients with distant metastatic hepatocellular carcinoma(HCC)improved after they survived for several months.Compared with tradi-tional survival analysis,conditional survival(CS)which takes into account changes in survival risk could be used to describe dynamic survival probabilities.AIM To evaluate CS of distant metastatic HCC patients.METHODS Patients diagnosed with distant metastatic HCC between 2010 and 2015 were extracted from the Surveillance,Epidemiology and End Results database.Univariate and multivariate Cox regression analysis were used to identify factors for overall survival(OS),while competing risk model was used to identify risk factors for cancer-specific survival(CSS).Six-month CS was used to calculate the probability of survival for an additional 6 mo at a specific time after initial diagnosis,and standardized difference(d)was used to evaluate the survival differences between subgroups.Nomograms were constructed to predict CS.Positiveα-fetoprotein expression,higher T stage(T3 and T4),N1 stage,non-primary site surgery,non-chemotherapy,non-radiotherapy,and lung metastasis were independent risk factors for actual OS and CSS through univariate and multivariate analysis.Actual survival rates decreased over time,while CS rates gradually increased.As for the 6-month CS,the survival difference caused by chemotherapy and radiotherapy gradually disappeared over time,and the survival difference caused by lung metastasis reversed.Moreover,the influence of age and gender on survival gradually appeared.Nomograms were fitted for patients who have lived for 2,4 and 6 mo to predict 6-month conditional OS and CSS,respectively.The area under the curve(AUC)of nomograms for conditional OS decreased as time passed,and the AUC for conditional CSS gradually increased.CONCLUSION CS for distant metastatic HCC patients substantially increased over time.With dynamic risk factors,nomograms constructed at a specific time could predict more accurate survival rates.
文摘Using data from the Surveillance, Epidemiology, and End Results (SEER) Program based at the National Cancer Institute in the US, conditional survival rates are reported for 1,988 Ewing Sarcoma patients diagnosed during the period 2000-2015. These patients represent the experience of 26.5% of the US population. Specifically, 5-year conditional relative survival rates are calculated for these patients for the first eight years subsequent to diagnosis of their cancer by Extent of Disease (EOD) (Localized, Regional, and Distant as coded by the SEER Program), gender, and age (<18, 18 - 34, and 35+). Findings include showing how the conditional survival rate patterns improve over time and that there are differences by gender, age, and EOD.
文摘Learning to handle hypothetical situations in a new language is always difficult(Catford,et al.,1974).This rule holds true for Moroccan Arabic(henceforth MA)speakers learning English because grammatical devices in the two languages differ in almost all equivalent situations.For instance,while English verb forms are used to indicate tense in conditional sentences,MA uses them to indicate aspect.Adopting the typology of conditional constructions suggested by Dancygier(1999)and Dancygier&Sweetser(2005),this study provides a contrastive analysis of conditionals in English and MA to predict the possible errors EFL/ESL learners are likely to make while learning English.The analysis shows that the main discrepancy between English conditionals and MA conditionals lies in the verb form used by the two systems.Accordingly,if EFL/ESL learners are influenced by verb form in their L1,they are likely to face some challenges while learning English conditionals.That is,they are likely to use the past tense in the protases of English predictive conditionals and generic conditionals since the perfective form of the verb is used in the protases of these two types in MA.Concerning the protases of English non-predictive conditionals,Moroccan EFL/ESL learners are likely to use either the past tense or the present tense since both the perfective and the imperfective forms of the verb are possible in the protases of MA non-predictive conditionals.However,due to the fact that the perfective form is the prototypical form in the protases of conditionals in MA,EFL/ESL learners are likely to use the past tense more often than the present tense.The analysis also shows that EFL/ESL learners tend to use the present tense in the apodoses of English conditionals since the prevalent form in the apodoses of MA conditionals is the imperfective.
基金Supported by the National Natural Science Foundation of China(No.61562046)Science and Technology Project of Jiangxi Provincial Education Department(No.GJJ150777,GJJ160742)
文摘Conditionally t-diagnosable and t-diagnosable are important in system level diagnosis. Therefore,it is valuable to identify whether the system is conditionally t-diagnosable or t-diagnosable and derive the corresponding conditional diagnosability and diagnosability. In the paper,distinguishable measures of pairs of distinct faulty sets with a new perspective on establishing functions are focused.Applying distinguishable function and decision function,it is determined whether a system is conditionally t-diagnosable( or t-diagnosable) or not under the PMC( Preparata,Metze,and Chien)model directly. Based on the decision function,a novel conditional diagnosability algorithm under the PMC model is introduced which can calculate conditional diagnosability rapidly.
基金supported by the National High Technology Research Program of China (No. 2012AA101104)
文摘Oil, protein and starch are key chemical components of maize kernels. A population of 245 recombinant inbred lines(RILs) derived from a cross between a high-oil inbred line, By804, and a regular inbred line, B73, was used to dissect the genetic interrelationships among oil, starch and protein content at the individual QTL level by unconditional and conditional QTL mapping. Combined phenotypic data over two years with a genetic linkage map constructed using 236 markers, nine, five and eight unconditional QTL were detected for oil, protein and starch content, respectively. Some QTL for oil, protein and starch content were clustered in the same genomic regions and the direction of their effects was consistent with the sign of their correlation. In conditional QTL mapping, 37(29/8) unconditional QTL were not detected or showed reduced effects, four QTL demonstrated similar effects under unconditional and conditional QTL mapping, and 17 additional QTL were identified by conditional QTL mapping. These results imply that there is a strong genetic relationship among oil, protein and starch content in maize kernels. The information generated in the present investigation could be helpful in marker-assisted breeding for maize varieties with desirable kernel quality traits.
基金supported by the Program of National High Technology Research and Development, Ministry of Science and Technology, China (Grant No. 2010AA101301)the Program of Introducing Talents of Discipline to University in China (Grant No. B08025)+1 种基金the Program of Introducing International Advanced Agricultural Science and Technology in China (Grant No. 2006-G8 [4]-31-1) the Program of Science-Technology Basis and Conditional Platform in China (Grant No. 505005)
文摘Unconditional and conditional QTL mapping were conducted for growth duration (GD), plant height (PH) and effective panicle number per plant (PN) using a recombinant inbred line (RIL) population derived from a cross between two japonica rice varieties Xiushui 79 and C Bao. The RIL population consisted of 254 lines was planted in two environments, Nanjing and Sihong, Jiangsu Province, China. Results showed that additive effects were major in all of QTLs for GD, PH and PN detected by the two methods, and the epistatic effects explained a small proportion of phenotypic variation. No interactions were detected between additive QTL and environment, and between epistatic QTL pairs and environment. After growth duration was adjusted to an identical level, RM80-160bp was detected as an applicable elite allele for PN, with an additive effect of 0.71. When effective panicle number per plant was adjusted to an identical level, RM448-240bp was detected as an applicable elite allele for GD, with an additive effect of 4.64. After plant height was adjusted to an identical level, RM80-160bp was detected as an applicable elite allele for PN, with an additive effect of 0.62, and RM448-240bp was detected as an applicable elite allele for GD, with an additive effect of 3.89. These applicable elite alleles could be used to improve target traits without influencing the other two traits.
基金jointly sponsored by the National Key Research and Development Program of China (2018YFC1506402)the National Natural Science Foundation of China (Grant Nos.41475100 and 41805081)the Global Regional Assimilation and Prediction System Development Program of the China Meteorological Administration (GRAPES-FZZX2018)
文摘This paper preliminarily investigates the application of the orthogonal conditional nonlinear optimal perturbations(CNOPs)–based ensemble forecast technique in MM5(Fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model). The results show that the ensemble forecast members generated by the orthogonal CNOPs present large spreads but tend to be located on the two sides of real tropical cyclone(TC) tracks and have good agreements between ensemble spreads and ensemble-mean forecast errors for TC tracks. Subsequently, these members reflect more reasonable forecast uncertainties and enhance the orthogonal CNOPs–based ensemble-mean forecasts to obtain higher skill for TC tracks than the orthogonal SVs(singular vectors)–, BVs(bred vectors)– and RPs(random perturbations)–based ones. The results indicate that orthogonal CNOPs of smaller magnitudes should be adopted to construct the initial ensemble perturbations for short lead–time forecasts, but those of larger magnitudes should be used for longer lead–time forecasts due to the effects of nonlinearities. The performance of the orthogonal CNOPs–based ensemble-mean forecasts is case-dependent,which encourages evaluating statistically the forecast skill with more TC cases. Finally, the results show that the ensemble forecasts with only initial perturbations in this work do not increase the forecast skill of TC intensity, which may be related with both the coarse model horizontal resolution and the model error.
基金funded by grants from the NIH R01LM010185-03(Zhou),NIH U01HL111560-01(Zhou),NIH 1R01DE022676-01(Zhou),and DoD TATRC (Zhou)
文摘By altering the electrostatic charge of histones or providing binding sites to protein recognition molecules, Chromatin marks have been proposed to regulate gene expression, a property that has motivated researchers to link these marks to cis-regulatory elements. With the help of next generation sequencing technologies, we can now correlate one specific chromatin mark with regulatory elements (e.g. enhancers or promoters) and also build tools, such as hidden Markov models, to gain insight into mark combinations. However, hidden Markov models have limitation for their character of generative models and assume that a current observation depends only on a current hidden state in the chain. Here, we employed two graphical probabilistic models, namely the linear conditional random field model and multivariate hidden Markov model, to mark gene regions with different states based on recurrent and spatially coherent character of these eight marks. Both models revealed chromatin states that may correspond to enhancers and promoters, transcribed regions, transcriptional elongation, and low-signal regions. We also found that the linear conditional random field model was more effective than the hidden Markov model in recognizing regulatory elements, such as promoter-, enhancer-, and transcriptional elongation-associated regions, which gives us a better choice.
文摘Background: Conditional survival(CS) has been established as a clinically relevant prognostic factor for cancer survivors, and the CS in gallbladder(GB) cancer has not yet been fully evaluated. In this study, we evaluated the cancerspecific CS rate and cancer-specific survival(CSS) rate in patients with GB cancer at multiple time points and investigated prognostic factors which affect cancer-specific CS rate to provide more accurate survival information.Methods: Between 2004 and 2013, a total of 9760 patients with GB cancer were identified from the Surveillance,Epidemiology, and End Results(SEER) data. The 3-year cancer-specific CS rate was calculated using the covariateadjusted survival function in the Cox model for each year since diagnosis, and the results were analyzed together with the adjusted CSS rates at the same time points. Cox proportional hazards regression was performed to ascertain the individual contribution of factors associated with CSS rate at diagnosis and cancer-specific CS rates at 1,3, and 5 years after diagnosis.Results: The adjusted 5-year CSS rate was 26.1 %. The adjusted 3-year cancer-specific CS rates at 1,2,3,4, and 5 years after diagnosis were 55.5,72.2,81.5,86.8, and 90.5%, respectively. At the time of diagnosis, age, race, histology, grade,T, N, and M categories, surgery, radiotherapy, insurance status, and marriage status were significant prognostic factors of CSS. Five years after diagnosis, however,T and M categories were significant prognostic factors for survivors(P = 0.007 and P = 0.009, respectively), whereas surgery and radiotherapy were not.Conclusions: T and M categories were significant prognostic factors even 5 years after the initial diagnosis, whereas local treatments at the time of diagnosis were not, suggesting that patients with GB cancer at high risks might need further adjuvant therapy after primary treatments. The combined analysis of CSS and cancer-specific CS rates offered more accurate survival information for patients who have already survived a certain period of time after diagnosis.
基金supported by Science and Technology Project of State Grid Corporation(Research and Application of Intelligent Energy Meter Quality Analysis and Evaluation Technology Based on Full Chain Data)
文摘With the application of artificial intelligence technology in the power industry,the knowledge graph is expected to play a key role in power grid dispatch processes,intelligent maintenance,and customer service response provision.Knowledge graphs are usually constructed based on entity recognition.Specifically,based on the mining of entity attributes and relationships,domain knowledge graphs can be constructed through knowledge fusion.In this work,the entities and characteristics of power entity recognition are analyzed,the mechanism of entity recognition is clarified,and entity recognition techniques are analyzed in the context of the power domain.Power entity recognition based on the conditional random fields (CRF) and bidirectional long short-term memory (BLSTM) models is investigated,and the two methods are comparatively analyzed.The results indicated that the CRF model,with an accuracy of 83%,can better identify the power entities compared to the BLSTM.The CRF approach can thus be applied to the entity extraction for knowledge graph construction in the power field.
文摘In a multiprocessor systems, it is important to local and to replace the faulty processors to maintain systempsilas high reliability. The fault diagnosis, which is the process of identifying fault processors in a multiprocessor system through testing. The conditional diagnosis requires that for each processor u in a system, all the processors that are directly connected to u do not fail at the same time. In this paper, we study the conditional diagnosability of the n-dimensional locally twisted cubes. After showing some properties of the locally twisted cubes, we prove that it under the PMC model is 4n – 7 for n ≥ 5.
文摘In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is established by using a visual long short term memory network in the three-dimensional(3D)space and the motion estimations jointly performed on object trajectory segments.Object visual field information is added to the long short term memory network to improve the accuracy of the motion related object pair selection and motion estimation.To address the uncertainty of the length and interval of trajectory segments,a multimode long short term memory network is proposed for the object motion estimation.The tracking performance is evaluated using the PETS2009 dataset.The experimental results show that the proposed method achieves better performance than the tracking methods based on the independent motion estimation.
文摘Based on two kinds of proxy data, a tree-ring width chronology at Huashan and the wetness/dryness grade series around Xi’an in north-centralChina, thes presat study demonstrates how different types of proxy climaterecords can be combined to give a more reliable estimate of past climate thaneither record can be done individually. With comparison and correction of thetwo data sets, various statistical models can be developed from individual andcombined senes. Among them, the best combined model produced by theconditional quantile adjustmat method can be selected for reconstruction ofApril-July rainfall at Huashan back to 1600 A.D.
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.61271346,61571163,61532014,61402132 and 91335112)
文摘MicroRNAs( miRNAs) are reported to be associated with various diseases. The identification of disease-related miRNAs would be beneficial to the disease diagnosis and prognosis. However,in contrast with the widely available expression profiling, the limited knowledge of molecular function restrict the development of previous methods based on network similarity measure. To construct reliable training data,the decision fusion method is used to prioritize the results of existing methods. After that,the performance of decision fusion method is validated. Furthermore,in consideration of the long range dependencies of successive expression values,Hidden Conditional Random Field model( HCRF) is selected and applied to miRNA expression profiling to infer disease-associated miRNAs. The results show that HCRF achieves superior performance and outperforms the previous methods. The results also demonstrate the power of using expression profiling for discovering disease-associated miRNAs.
文摘Factoring quadratics over Z is a staple of introductory algebra and textbooks tend to create the impression that doable factorizations are fairly common. To the contrary, if coefficients of a general quadratic are selected randomly without restriction, the probability that a factorization exists is zero. We achieve a specific quantification of the probability of factoring quadratics by taking a new approach that considers the absolute size of coefficients to be a parameter n. This restriction allows us to make relative likelihood estimates based on finite sample spaces. Our probability estimates are then conditioned on the size parameter n and the behavior of the conditional estimates may be studied as the parameter is varied. Specifically, we enumerate how many formal factored expressions could possibly correspond to a quadratic for a given size parameter. The conditional probability of factorization as a function of n is just the ratio of this enumeration to the total number of possible quadratics consistent with n. This approach is patterned after the well-known case where factorizations are carried out over a finite field. We review the finite field method as background for our method of dealing with Z [x]. The monic case is developed independently of the general case because it is simpler and the resulting probability estimating formula is more accurate. We conclude with a comparison of our theoretical probability estimates with exact data generated by a computer search for factorable quadratics corresponding to various parameter values.
文摘This paper aims to explore how learners of English as a second language(ESL)acquire English conditional sentences and what causes their difficulties,especially focusing on how their native languages affect their acquisition of the conditional sentences.Interviews were carried out with four undergraduate ESL students of University of Central Oklahoma in the United States who are respectively Chinese,Korean,French,and Greek.By conducting interviews with them,the participants’perceptions of acquiring English conditional sentences will be collected and analyzed.There will be some typical errors of constructing conditional sentences demonstrated.Moreover,some pedagogical implications will also be provided,which will help students have a better command of the conditional sentences.
