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Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy 被引量:1
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作者 Xiaoqin Ma Jun Wang +1 位作者 Wenchang Yu Qinli Zhang 《Computers, Materials & Continua》 SCIE EI 2024年第5期2063-2083,共21页
The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attr... The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data. 展开更多
关键词 Hybrid decision information systems fuzzy conditional information entropy attribute reduction fuzzy relationship rough set theory(RST)
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Application of the Conditional Nonlinear Local Lyapunov Exponent to Second-Kind Predictability
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作者 Ming ZHANG Ruiqiang DING +2 位作者 Quanjia ZHONG Jianping LI Deyu LU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第9期1769-1786,共18页
In order to quantify the influence of external forcings on the predictability limit using observational data,the author introduced an algorithm of the conditional nonlinear local Lyapunov exponent(CNLLE)method.The eff... In order to quantify the influence of external forcings on the predictability limit using observational data,the author introduced an algorithm of the conditional nonlinear local Lyapunov exponent(CNLLE)method.The effectiveness of this algorithm is validated and compared with the nonlinear local Lyapunov exponent(NLLE)and signal-to-noise ratio methods using a coupled Lorenz model.The results show that the CNLLE method is able to capture the slow error growth constrained by external forcings,therefore,it can quantify the predictability limit induced by the external forcings.On this basis,a preliminary attempt was made to apply this method to measure the influence of ENSO on the predictability limit for both atmospheric and oceanic variable fields.The spatial distribution of the predictability limit induced by ENSO is similar to that arising from the initial conditions calculated by the NLLE method.This similarity supports ENSO as the major predictable signal for weather and climate prediction.In addition,a ratio of predictability limit(RPL)calculated by the CNLLE method to that calculated by the NLLE method was proposed.The RPL larger than 1 indicates that the external forcings can significantly benefit the long-term predictability limit.For instance,ENSO can effectively extend the predictability limit arising from the initial conditions of sea surface temperature over the tropical Indian Ocean by approximately four months,as well as the predictability limit of sea level pressure over the eastern and western Pacific Ocean.Moreover,the impact of ENSO on the geopotential height predictability limit is primarily confined to the troposphere. 展开更多
关键词 conditional nonlinear local Lyapunov exponent second-kind predictability coupled Lorenz model ENSO
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Conditional Generative Adversarial Network Enabled Localized Stress Recovery of Periodic Composites
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作者 Chengkan Xu Xiaofei Wang +2 位作者 Yixuan Li Guannan Wang He Zhang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第7期957-974,共18页
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
关键词 Periodic composites localized stress recovery conditional generative adversarial network
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Censored Composite Conditional Quantile Screening for High-Dimensional Survival Data
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作者 LIU Wei LI Yingqiu 《应用概率统计》 CSCD 北大核心 2024年第5期783-799,共17页
In this paper,we introduce the censored composite conditional quantile coefficient(cC-CQC)to rank the relative importance of each predictor in high-dimensional censored regression.The cCCQC takes advantage of all usef... In this paper,we introduce the censored composite conditional quantile coefficient(cC-CQC)to rank the relative importance of each predictor in high-dimensional censored regression.The cCCQC takes advantage of all useful information across quantiles and can detect nonlinear effects including interactions and heterogeneity,effectively.Furthermore,the proposed screening method based on cCCQC is robust to the existence of outliers and enjoys the sure screening property.Simulation results demonstrate that the proposed method performs competitively on survival datasets of high-dimensional predictors,particularly when the variables are highly correlated. 展开更多
关键词 high-dimensional survival data censored composite conditional quantile coefficient sure screening property rank consistency property
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Mixed D-vine copula-based conditional quantile model for stochastic monthly streamflow simulation
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作者 Wen-zhuo Wang Zeng-chuan Dong +3 位作者 Tian-yan Zhang Li Ren Lian-qing Xue Teng Wu 《Water Science and Engineering》 EI CAS CSCD 2024年第1期13-20,共8页
Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate b... Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.To address this limitation,this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations.This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas.The up-to-down sequential method,which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach,was used to determine the structures of multivariate Dvine copulas.The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station,the inflow control station of the Longyangxia Reservoir in the Yellow River Basin.The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow.This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization. 展开更多
关键词 Stochastic monthly streamflow simulation Mixed D-vine copula conditional quantile model Up-to-down sequential method Tangnaihai hydrological station
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Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search
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作者 Xiao Liu Pingting Lin +2 位作者 Fan Bu Shaoling Zhuang Shoudao Huang 《CES Transactions on Electrical Machines and Systems》 EI CSCD 2024年第1期32-42,共11页
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
关键词 Generator optimization Gaussian Process Regression(GPR) conditional Likelihood Lower Bound Search(CLLBS) Constraint improvement expectation(CEI) Finite element calculation
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The potential mechanism and clinical application value of remote ischemic conditioning in stroke
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作者 Yajun Zhu Xiaoguo Li +6 位作者 Xingwei Lei Liuyang Tang Daochen Wen Bo Zeng Xiaofeng Zhang Zichao Huang Zongduo Guo 《Neural Regeneration Research》 SCIE CAS 2025年第6期1613-1627,共15页
Some studies have confirmed the neuroprotective effect of remote ischemic conditioning against stroke. Although numerous animal researches have shown that the neuroprotective effect of remote ischemic conditioning may... Some studies have confirmed the neuroprotective effect of remote ischemic conditioning against stroke. Although numerous animal researches have shown that the neuroprotective effect of remote ischemic conditioning may be related to neuroinflammation, cellular immunity, apoptosis, and autophagy, the exact underlying molecular mechanisms are unclear. This review summarizes the current status of different types of remote ischemic conditioning methods in animal and clinical studies and analyzes their commonalities and differences in neuroprotective mechanisms and signaling pathways. Remote ischemic conditioning has emerged as a potential therapeutic approach for improving stroke-induced brain injury owing to its simplicity, non-invasiveness, safety, and patient tolerability. Different forms of remote ischemic conditioning exhibit distinct intervention patterns, timing, and application range. Mechanistically, remote ischemic conditioning can exert neuroprotective effects by activating the Notch1/phosphatidylinositol 3-kinase/Akt signaling pathway, improving cerebral perfusion, suppressing neuroinflammation, inhibiting cell apoptosis, activating autophagy, and promoting neural regeneration. While remote ischemic conditioning has shown potential in improving stroke outcomes, its full clinical translation has not yet been achieved. 展开更多
关键词 Akt apoptosis autophagy cerebral perfusion cerebral vascular stenosis clinical transformation hemorrhagic stroke ischemic stroke NEUROINFLAMMATION neuroprotection Notch1 PI3K remote ischemic conditioning STROKE
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Semantic role labeling based on conditional random fields 被引量:9
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作者 于江德 樊孝忠 +1 位作者 庞文博 余正涛 《Journal of Southeast University(English Edition)》 EI CAS 2007年第3期361-364,共4页
Due to the fact that semantic role labeling (SRL) is very necessary for deep natural language processing, a method based on conditional random fields (CRFs) is proposed for the SRL task. This method takes shallow ... Due to the fact that semantic role labeling (SRL) is very necessary for deep natural language processing, a method based on conditional random fields (CRFs) is proposed for the SRL task. This method takes shallow syntactic parsing as the foundation, phrases or named entities as the labeled units, and the CRFs model is trained to label the predicates' semantic roles in a sentence. The key of the method is parameter estimation and feature selection for the CRFs model. The L-BFGS algorithm was employed for parameter estimation, and three category features: features based on sentence constituents, features based on predicate, and predicate-constituent features as a set of features for the model were selected. Evaluation on the datasets of CoNLL-2005 SRL shared task shows that the method can obtain better performance than the maximum entropy model, and can achieve 80. 43 % precision and 63. 55 % recall for semantic role labeling. 展开更多
关键词 semantic role labeling conditional random fields parameter estimation feature selection
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Analysis of the Conditional Correlations from Different Genetic Systems Between the Protein Content and the Appearance Quality Traits of Indica Rice 被引量:4
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作者 葛国科 郑希 +2 位作者 吴建国 叶子弘 石春海 《Journal of Genetics and Genomics》 SCIE CAS CSCD 北大核心 2007年第2期129-137,共9页
A factorial mating design in two environments was conducted using 7 cytoplasmic male sterile lines (A) and 5 restorer lines (R) along with their F1 (A × R) and F2 populations. The unconditional and conditio... A factorial mating design in two environments was conducted using 7 cytoplasmic male sterile lines (A) and 5 restorer lines (R) along with their F1 (A × R) and F2 populations. The unconditional and conditional analyses of genetic models and the corresponding statistic methods, including endospermic, cytoplasmic, and maternal plant genetic systems, were used to analyze the genetic relationships between protein content (PC) and the appearance quality traits of indica rice (Oryza sativa L.). The results from unconditional analysis indicated that PC was significantly correlated with the appearance quality traits of rice, except for the brown rice thickness (BRT). Only the genetic covariance between PC and the brown rice width (BRW) was positively correlative, whereas all the other pairwise traits were negatively correlative. The results from conditional analysis revealed that the weight of brown rice (WBR) or the amylose content (AC) could significantly affect the relationships between PC and the appearance quality traits of indica rice. The conditional analysis showed that WBR might negatively affect the relationships between PC and the brown rice length (BRL), BRW, or BRT through the geuotype x environmental (GE) interaction effects, but positively affected the relationships between PC and the ratio of brown rice length to width (RLW) or the ratio of brown rice length to thickness (RLT). The amylase content could positively affect the relationships between PC and BRL, RLW, RLT through the cytoplasmic effects and maternal additive effects, but negatively affected the relationships between PC and BRW. 展开更多
关键词 indica rice (Oryza sativa L.) COVARIANCE unconditional and conditional analysis methods protein content amylose content appearance quality
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TONE MODELING BASED ON HIDDEN CONDITIONAL RANDOM FIELDS AND DISCRIMINATIVE MODEL WEIGHT TRAINING 被引量:1
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作者 黄浩 朱杰 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2008年第1期43-50,共8页
The use of hidden conditional random fields (HCRFs) for tone modeling is explored. The tone recognition performance is improved using HCRFs by taking advantage of intra-syllable dynamic, inter-syllable dynamic and d... The use of hidden conditional random fields (HCRFs) for tone modeling is explored. The tone recognition performance is improved using HCRFs by taking advantage of intra-syllable dynamic, inter-syllable dynamic and duration features. When the tone model is integrated into continuous speech recognition, the discriminative model weight training (DMWT) is proposed. Acoustic and tone scores are scaled by model weights discriminatively trained by the minimum phone error (MPE) criterion. Two schemes of weight training are evaluated and a smoothing technique is used to make training robust to overtraining problem. Experiments show that the accuracies of tone recognition and large vocabulary continuous speech recognition (LVCSR) can be improved by the HCRFs based tone model. Compared with the global weight scheme, continuous speech recognition can be improved by the discriminative trained weight combinations. 展开更多
关键词 speech recognition MODELS hidden conditional random fields minimum phone error
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SOLVABILITY RESULTS OF A CONDITIONAL INPUT-OUTPUT EQUATION BASED ON A TYPE OF NONLINEAR LEONTIEF MODEL
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作者 胡问鸣 刘颖范 沙春林 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2003年第2期224-229,共6页
A class of nonlinear and continuous type Leontief model and its corresponding conditional input-output equation are introduced, and two basic problems under the so called positive or negative boundary assumption are p... A class of nonlinear and continuous type Leontief model and its corresponding conditional input-output equation are introduced, and two basic problems under the so called positive or negative boundary assumption are presented. By approaches of nonlinear analysis some solvability results of this equation and continuous perturbation properties of the relative solution sets are obtained, and some economic significance are illustrated by the remark. 展开更多
关键词 conditional Leontief model input-output equation positive (negative) boundary assumption nonlinear analysis SOLVABILITY continuous disturbance
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Ensemble Forecasts of Tropical Cyclone Track with Orthogonal Conditional Nonlinear Optimal Perturbations 被引量:13
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作者 Zhenhua HUO Wansuo DUAN Feifan ZHOU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2019年第2期231-247,共17页
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
关键词 ENSEMBLE FORECAST initial PERTURBATION conditional nonlinear optimal PERTURBATION TROPICAL CYCLONE
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Application of the Conditional Nonlinear Optimal Perturbation Method to the Predictability Study of the Kuroshio Large Meander 被引量:25
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作者 WANG Qiang MU Mu Henk A.DIJKSTRA 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2012年第1期118-134,共17页
A reduced-gravity barotropic shallow-water model was used to simulate the Kuroshio path variations. The results show that the model was able to capture the essential features of these path variations. We used one simu... A reduced-gravity barotropic shallow-water model was used to simulate the Kuroshio path variations. The results show that the model was able to capture the essential features of these path variations. We used one simulation of the model as the reference state and investigated the effects of errors in model parameters on the prediction of the transition to the Kuroshio large meander (KLM) state using the conditional nonlinear optimal parameter perturbation (CNOP-P) method. Because of their relatively large uncertainties, three model parameters were considered: the interracial friction coefficient, the wind-stress amplitude, and the lateral friction coefficient. We determined the CNOP-Ps optimized for each of these three parameters independently, and we optimized all three parameters simultaneously using the Spectral Projected Gradient 2 (SPG2) algorithm. Similarly, the impacts caused by errors in initial conditions were examined using the conditional nonlinear optimal initial perturbation (CNOP-I) method. Both the CNOP-I and CNOP-Ps can result in significant prediction errors of the KLM over a lead time of 240 days. But the prediction error caused by CNOP-I is greater than that caused by CNOP-P. The results of this study indicate not only that initial condition errors have greater effects on the prediction of the KLM than errors in model parameters but also that the latter cannot be ignored. Hence, to enhance the forecast skill of the KLM in this model, the initial conditions should first be improved, the model parameters should use the best possible estimates. 展开更多
关键词 conditional nonlinear optimal perturbation Kuroshio large meander PREDICTABILITY model parameters
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Identification of unconditional and conditional QTL for oil, protein and starch content in maize 被引量:10
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作者 Yuqiu Guo Xiaohong Yang +4 位作者 Subhash Chander Jianbing Yan Jun Zhang Tongming Song Jiansheng Li 《The Crop Journal》 SCIE CAS 2013年第1期34-42,共9页
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
关键词 ZEA mays OIL Protein STARCH Unconditional QTL conditional QTL
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Conditional survival in patients with gallbladder cancer 被引量:3
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作者 Yi-Jun Kim Kyubo Kim 《Chinese Journal of Cancer》 SCIE CAS CSCD 2017年第12期744-756,共13页
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
关键词 GALLBLADDER CANCER conditional SURVIVAL SEER
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Conditional QTL Mapping of Sedimentation Volume on Seven Quality Traits in Common Wheat 被引量:7
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作者 DENG Zhi-ying ZHAO Liang +6 位作者 LIU Bin ZHANG Kun-pu CHEN Jian-sheng QU Hou-lan SUN Cai-ling ZHANG Yong-xiang TIAN Ji-chun 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2013年第12期2125-2133,共9页
To evaluate the possible genetic interrelationships between flour components and the sedimentation volume(SD),a doubled haploid(DH) population comprising 168 lines were used to identify the conditional quantitativ... To evaluate the possible genetic interrelationships between flour components and the sedimentation volume(SD),a doubled haploid(DH) population comprising 168 lines were used to identify the conditional quantitative trait loci(QTLs) for SD in three environments.Ten additive QTLs and 15 pairs of epistatic QTLs were detected for SD through unconditional and conditional QTL mapping.Three major additive QTLs were detected for SD conditioned on the seven quality traits.Two additive QTLs were found to be independent of these traits.Three additive QTLs were suppressed by three of the seven traits because of non-detection in unconditional mapping.Three pairs of epistatic QTLs were completely affected by the seven traits because of detection in unconditional mapping but no-detection in conditional mapping.Twelve pairs of epistatic QTLs were detected in conditional mapping.Our results indicated that conditional mapping could contribute to a better understanding of the interdependence of different and closely correlated traits at the QTL molecular level,especially some minor QTLs were found.The conditional mapping approach provides new insights that will make it possible to avoid the disadvantages of different traits by breeding through molecular design. 展开更多
关键词 wheat(Triticum aestivum L.) sedimentation volume conditional QTL mapping
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Detection and characterization of regulatory elements using probabilistic conditional random field and hidden Markov models 被引量:3
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作者 Hongyan Wang Xiaobo Zhou 《Chinese Journal of Cancer》 SCIE CAS CSCD 2013年第4期186-194,共9页
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
关键词 Epigenetics HISTONE modification conditional RANDOM field REGULATORY elements
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A Variant Constrained Genetic Algorithm for Solving Conditional Nonlinear Optimal Perturbations 被引量:6
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作者 ZHENG Qin SHA Jianxin +1 位作者 SHU Hang LU Xiaoqing 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2014年第1期219-229,共11页
A variant constrained genetic algorithm (VCGA) for effective tracking of conditional nonlinear optimal perturbations (CNOPs) is presented. Compared with traditional constraint handling methods, the treatment of th... A variant constrained genetic algorithm (VCGA) for effective tracking of conditional nonlinear optimal perturbations (CNOPs) is presented. Compared with traditional constraint handling methods, the treatment of the constraint condition in VCGA is relatively easy to implement. Moreover, it does not require adjustments to indefinite pararneters. Using a hybrid crossover operator and the newly developed multi-ply mutation operator, VCGA improves the performance of GAs. To demonstrate the capability of VCGA to catch CNOPS in non-smooth cases, a partial differential equation, which has "on off" switches in its forcing term, is employed as the nonlinear model. To search global CNOPs of the nonlinear model, numerical experiments using VCGA, the traditional gradient descent algorithm based on the adjoint method (ADJ), and a GA using tournament selection operation and the niching technique (GA-DEB) were performed. The results with various initial reference states showed that, in smooth cases, all three optimization methods are able to catch global CNOPs. Nevertheless, in non-smooth situations, a large proportion of CNOPs captured by the ADJ are local. Compared with ADJ, the performance of GA-DEB shows considerable improvement, but it is far below VCGA. Further, the impacts of population sizes on both VCGA and GA-DEB were investigated. The results were used to estimate the computation time of ~CGA and GA-DEB in obtaining CNOPs. The computational costs for VCGA, GA-DEB and ADJ to catch CNOPs of the nonlinear model are also compared. 展开更多
关键词 genetic algorithm conditional nonlinear optimal perturbation "on-off" switch adjoint rrtethod
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Analysis of Conditional Value-at-Risk for Newsvendor with Holding and Backorder Cost under Market Search 被引量:4
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作者 LI Jianbin GAO Chengxiu +1 位作者 HU Wei YANG Lei 《Wuhan University Journal of Natural Sciences》 CAS 2007年第6期979-984,共6页
We consider a distribution system with one supplier and two retailers. For the two retailers, they face different demand and are both risk averse. We study a single period model which the supplier has ample goods and ... We consider a distribution system with one supplier and two retailers. For the two retailers, they face different demand and are both risk averse. We study a single period model which the supplier has ample goods and the retailers order goods separately. Market search is measured as the fraction of customers who unsatisfied with their "local" retailer due to stock-out, and search for the goods at the other retailer before leaving the system. We investigate how the retailers game for order quantity in a Conditional Value-at-Risk framework and study how risk averse degree, market search level, holding cost and backorder cost influence the optimal order strategies. Furthermore, we use uniform distribution to illustrate these results and obtain Nash equilibrium of order strategies. 展开更多
关键词 risk averse conditional Value-at-Risk market search game theory
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Unconditional and Conditional QTL Mapping for Tiller Numbers at Various Stages with Single Segment Substitution Lines in Rice(Oryza sativa L.) 被引量:6
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作者 ZHAO Fang-ming LIU Gui-fu ZHU Hai-tao DING Xiao-hua ZENG Rui-zhen ZHANG Ze-min LI Wen-tao ZHANG Gui-quan 《Agricultural Sciences in China》 CAS CSCD 2008年第3期257-265,共9页
Tiller is one of the most important agronomic traits which influences quantity and quality of effective panicles and finally influences yield in rice. It is important to understand "static" and "dynamic" informati... Tiller is one of the most important agronomic traits which influences quantity and quality of effective panicles and finally influences yield in rice. It is important to understand "static" and "dynamic" information of the QTLs for tillers in rice. This work was the first time to simultaneously map unconditional and conditional QTLs for tiller numbers at various stages by using single segment substitution lines in rice. Fourteen QTLs for tiller number, distributing on the corresponding substitution segments of chromosomes 1, 2, 3, 4, 6, 7 and 8 were detected. Both the number and the effect of the QTLs for tiller number were various at different stages, from 6 to 9 in the number and from 1.49 to 3.49 in the effect, respectively. Tiller number QTLs expressed in a time order, mainly detected at three stages of 0-7 d, 14-21 d and 35-42 d after transplanting with 6 positive, 9 random and 6 negative expressing QTLs, respectively. Each of the QTLs expressed one time at least during the whole duration of rice. The tiller number at a specific stage was determined by sum of QTL effects estimated by the unconditional method, while the increasing or decreasing number in a given time interval was controlled by the total of QTL effects estimated by the conditional method. These results demonstrated that it is highly effective and accurate for mapping of the QTLs by using single segment substitution lines and the conditional analysis methodology. 展开更多
关键词 single segment substitution line unconditional QTL mapping conditional QTL mapping tiller number RICE
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