Medium-low temperature geothermal resources are abundant in the Guanxian fault depression.An essential foundation for the effective development and use of geothermal resources is the study of the genetic model and res...Medium-low temperature geothermal resources are abundant in the Guanxian fault depression.An essential foundation for the effective development and use of geothermal resources is the study of the genetic model and resource assessment of the geothermal system.This study examines the geothermal geological circumstances,hydrochemical features,and geothermal field characteristics based on the regional geological structure and prior research findings.The appraisal of geothermal resources is done,and a conceptual model of the geothermal system in the research area is built.The findings indicate that the Guan xian fault depression's geothermal resources are primarily Guantao Formation sandstone heat reservoirs.The geothermal water at the wellhead has a temperature between 54℃and 60℃,and its primary chemistry is Cl·SO_(4)-Na.Deep thermal conduction heats the geothermal water,which is then laterally supplied to the reservoir after being largely restored by air precipitation from the western Taihang Mountains.With an annual exploitable geothermal resource of 6,782×10^(12)J,or 23.14×10^(4)tons of standard coal,the Guantao Formation sandstone reservoir in the Guanxian depression has a geothermal resource of about 620.10×10^(16)J.An area of 18 million m^(2)can be heated by geothermal extraction per year,demonstrating the potential for geothermal resources and their high development and use value.展开更多
A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction （NCI） as well as their genotype by environment （GE） interaction for quantitative...A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction （NCI） as well as their genotype by environment （GE） interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction （AUP） method. Data on four quantitative traits （boll number, lint percentage, fiber length, and micronaire） in Upland cotton （Gossypium hirsutum L.） were analyzed as a worked example to show the effectiveness of the model.展开更多
The widespread Carboniferous KT-I dolomite in the eastern margin of the Pre-Caspian Basin is an important hydrocarbon reservoir. The dolomite lithology is dominated by crystalline dolomite. The δ18O values range from...The widespread Carboniferous KT-I dolomite in the eastern margin of the Pre-Caspian Basin is an important hydrocarbon reservoir. The dolomite lithology is dominated by crystalline dolomite. The δ18O values range from -6.71‰ to 2.45‰, and average 0.063‰, obviously larger than -2.5‰, indicating low-temperature dolomite of evaporation origin. Stable strontium isotope ratios （87Sr/86Sr） range from 0.70829 to 0.70875 and average 0.708365, very consistent with 87Sr/86Sr ratios in Carboniferous seawater. Chemical analysis of Ca and Mg elements shows that the dolomite has 9.1 mole% excess Ca or even higher before stabilization. The degree of order of dolomite is medium–slightly poor, varying in a range of 0.336-0.504 and averaging 0.417. It suggests that the dolomite formed under near-surface conditions. There are two models for the origin of the Carboniferous KT-I dolomite reservoir. These are 1） the evaporation concentration – weathering crust model and 2） the shoal facies – seepage reflux model. The former is mainly developed in restricted platforms – evaporate platforms of restricted marine deposition environments with a representation of dolomite associated with gypsum and mudstone. The latter mainly formed in platform edge shoals and intra-platform shoals and is controlled by dolomitization due to high salinity sea water influx from adjacent restricted sea or evaporate platform.展开更多
This study was conducted to investigate the genetic regularity of indexes related to freshness keeping and its molecular basis by acquiring 6 generations （P1, P2, F1, B1, B2 and F2） of an inbred line T3 with long fr...This study was conducted to investigate the genetic regularity of indexes related to freshness keeping and its molecular basis by acquiring 6 generations （P1, P2, F1, B1, B2 and F2） of an inbred line T3 with long freshness period × an inbred line T15 with short freshness period in sweet corn. The genetic analysis of the indexes was performed by major gene＋polygene mixed genetic model combined with the genetic analysis combining six generations.The results showed that the decreasing rate of the postharvest sugar content in the T3 was controlled by two pairs of additive-dominante-epistatic major genes＋additive-dominant polygenes; each segregating generation was affected by its major genes, the heritability of major genes and polygene in the B1 generation was 74.63% and 17.67%, respectively; the heritability of major gene and potygene in the B2 was 91.98% and 0,00%, respectively; and the heritability of major gene and polygene inthe F2 was 82.67%, and 12.93%, respectively.展开更多
We have systematically investigated the feature, genetic model and distribution of calcareous insulating layers in marine strata of the Ⅰ oil group in member 2 of Zhujiang formation(ZJ2I oil formation), western Pearl...We have systematically investigated the feature, genetic model and distribution of calcareous insulating layers in marine strata of the Ⅰ oil group in member 2 of Zhujiang formation(ZJ2I oil formation), western Pearl River Mouth basin(PRMB) in the north of the South China Sea by using data such as cores, thin sections, X-ray diffraction of whole-rock, and calcite cement carbon and oxygen isotopes. The lithology of the calcareous insulating layers in the study area is mainly composed of the terrigenous clastic bioclastic limestone and a small amount of fine-grained calcareous sandstone. On this basis, two genetic models of calcareous insulating layers are established, including the evaporation seawater genetic model and shallow burial meteoric water genetic model. The calcareous insulating layers of the evaporation seawater genetic model developed in the foreshore subfacies, mainly at the top of the 1-1 strata and 1-3 strata. The calcareous insulating layers of the shallow burial meteoric water genetic model developed in the backshore subfacies, primarily in the 1-2 strata.展开更多
In the early 1980's, the author proposed his view that copper-nickel sulphide deposts are of ore magma origin. For more than ten years, this view has aroused attention of his colleagues at home and abroad. In this...In the early 1980's, the author proposed his view that copper-nickel sulphide deposts are of ore magma origin. For more than ten years, this view has aroused attention of his colleagues at home and abroad. In this paper an attempt is made to deal with the genetic model for ore magma of copper-nickel sulphide deposits in more details on the basis of geological, geochemical, petrophysico - chemical and thermodynamic studies of the Chibaisong copper-nickel sulphide deposit in the Changbai Mountains, Jilin province.展开更多
With increasing the number of wind power generators,the consumption time of electromagnetic simulation of the wind farm explodes.To reduce the simulation time while meeting the accuracy requirement,a genetic clusterin...With increasing the number of wind power generators,the consumption time of electromagnetic simulation of the wind farm explodes.To reduce the simulation time while meeting the accuracy requirement,a genetic clustering-based equivalent model is proposed for the wind farm with numerous doubly fed induction generators.In the proposed model,active power together with the reactive power and the wind speed are selected to form the set of clustering indicators.A normalization technique is utilized to cope with the multiple orders of magnitude in these factors.An exponential fitness value is formulated as a function of the sorting number of the primary fitness value,and the fitness-based selection probability is constructed to overcome the property of premature and slow convergence of the genetic clustering algorithm.The sum of squares due to error is used to determine the optimal clustering number.In addition,a decoupled parameter equivalence method is adopted to obtain the equivalent parameters of the collection network.Simulation results and comparisons with various methods under different voltage scenarios show the feasibility and effectiveness of the proposed model.展开更多
Under-fitting problems usually occur in regression models for dam safety monitoring.To overcome the local convergence of the regression, a genetic algorithm (GA) was proposed using a real parameter coding, a ranking s...Under-fitting problems usually occur in regression models for dam safety monitoring.To overcome the local convergence of the regression, a genetic algorithm (GA) was proposed using a real parameter coding, a ranking selection operator, an arithmetical crossover operator and a uniform mutation operator, and calculated the least-square error of the observed and computed values as its fitness function. The elitist strategy was used to improve the speed of the convergence. After that, the modified genetic algorithm was applied to reassess the coefficients of the regression model and a genetic regression model was set up. As an example, a slotted gravity dam in the Northeast of China was introduced. The computational results show that the genetic regression model can solve the under-fitting problems perfectly.展开更多
The inheritance of stripe disease resistance in a rice restorer line C224 was analyzed using the mixed effect model of major gene plus polygene for quantitative traits.In addition,the resistance was investigated in se...The inheritance of stripe disease resistance in a rice restorer line C224 was analyzed using the mixed effect model of major gene plus polygene for quantitative traits.In addition,the resistance was investigated in seven crosses of C224 with maintainer lines.The results showed that the stripe resistance of C224 was controlled by two major genes with additive-dominance-epistasis effects plus polygenes with additive-dominance effects （E-1 model）.These two genes had additive effects of-12.47% and-24.75%,respectively,showing negative dominance effects.There were significant epistasis and interaction effects between the two major genes.The heritability of the two major genes was 92.12%,while that of polygenes was 2.74%,indicating that the stripe resistance had dominant major gene effect.Of the seven crosses,five displayed high or medium resistance to the stripe disease.展开更多
The use of the three genetic models viz. additive, dominant and recessive in </span><span style="font-family:Verdana;">Genome-wide association study (GWAS) is a common and powerful ap</span>...The use of the three genetic models viz. additive, dominant and recessive in </span><span style="font-family:Verdana;">Genome-wide association study (GWAS) is a common and powerful ap</span><span style="font-family:Verdana;">proach to study the association between genetic variants and a trait (disease). The selection of these models depends on the pattern of inheritance and the scope </span><span style="font-family:Verdana;">of the study. GWAS typically focuses on single-nucleotide polymorphism</span><span style="font-family:Verdana;"> (SNPs) and common human diseases in a case-control setup. In order to study this type of association between the risk genotype and the phenotype for a given inheritance pattern, the use of these genetic models helps to identify the disease risk appropriately. This study provides an overview of the existing genetic models (additive, dominant and recessive) and a practical demonstration of these model tests for the contingency tables of SNP genotypes and the disease phenotypes in a case-control setting.展开更多
China is rich in geothermal resources,especially in Fujian Province,where 207 exposed hot springs have been discovered.The maximum temperature recorded in geothermal wells is above 121℃ in this province,indicating a ...China is rich in geothermal resources,especially in Fujian Province,where 207 exposed hot springs have been discovered.The maximum temperature recorded in geothermal wells is above 121℃ in this province,indicating a high geothermal resource potential.However,large-scale breakthroughs in geothermal exploration are hindered by a lack of clear geothermal genetic models.In this study,the genetic model of a faultcontrolled mediumelow-temperature convection geothermal zone in the Fujian coastal area was determined by considering the tectonic characteristics of the area and the hydrochemical characteristics of the geothermal fluid(recharge,runoff and discharge characteristics,geothermal reservoir temperature,geothermal fluid circulation depth and renewability).The results showed that the exposed hot springs and high-temperature geothermal boreholes were concentrated in the Fu'aneNanjing and ChangleeZhao'an fault zones.At the intersection or faultbend of these two fault zones,there was strong stress release and activity,as demonstrated in the exposed parts of the high-temperature geothermal resources.The ChangleeZhao'an fault zone had a greater circulation depth,with an average heat storage temperature of 140℃,reflecting high geothermal resource potential.Considering the current temperature of the hot springs,Xiamen Bay and NanjingeJiulong River were identified as the next geothermal development zones.展开更多
QTL mapping for seven quality traits was conducted by using 254 recombinant inbred lines （RIL） derived from a japonica-japonica rice cross of Xiushui 79/C Bao. The seven traits investigated were grain length （GL）,...QTL mapping for seven quality traits was conducted by using 254 recombinant inbred lines （RIL） derived from a japonica-japonica rice cross of Xiushui 79/C Bao. The seven traits investigated were grain length （GL）, grain length to width ratio （LWR）, chalk grain rate （CGR）, chalkiness degree （CD）, gelatinization temperature （GT）, amylose content （AC） and gel consistency （GC） of head rice. Three mapping methods employed were composite interval mapping in QTLMapper 2.0 software based on mixed linear model （MCIM）, inclusive composite interval mapping in QTL IciMapping 3.0 software based on stepwise regression linear model （ICIM） and multiple interval mapping with regression forward selection in Windows QTL Cartographer 2.5 based on multiple regression analysis （MIMR）. Results showed that five QTLs with additive effect （A-QTLs） were detected by all the three methods simultaneously, two by two methods simultaneously, and 23 by only one method. Five A-QTLs were detected by MCIM, nine by ICIM and 28 by MIMR. The contribution rates of single A-QTL ranged from 0.89% to 38.07%. All the QTLs with epistatic effect （E-QTLs） detected by MIMR were not detected by the other two methods. Fourteen pairs of E-QTLs were detected by both MCIM and ICIM, and 142 pairs of E-QTLs were detected by only one method. Twenty-five pairs of E-QTLs were detected by MCIM, 141 pairs by ICIM and four pairs by MIMR. The contribution rates of single pair of E-QTL were from 2.60% to 23.78%. In the Xiu-Bao RIL population, epistatic effect played a major role in the variation of GL and CD, and additive effect was the dominant in the variation of LWR, while both epistatic effect and additive effect had equal importance in the variation of CGR, AC, GT and GC. QTLs detected by two or more methods simultaneously were highly reliable, and could be applied to improve the quality traits in japonica hybrid rice.展开更多
This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used ...This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection.展开更多
This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) ...This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) algorithm is used for Nonlinear Parameter Estimation (NPE) of dynamic model structures. In addition, GPM integrates the results of Nonlinear Time Series Analysis (NTSA) to adjust the parameters and takes them as the criteria of established models. Experiments showed the effectiveness of such improvements on chaotic time series modeling.展开更多
In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its s...In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.展开更多
It is recognized that developing valid animal models is essential for the research on the neurobiological mechanisms of (and treatments for) psychiatric disorders, even when these are as complex as schizophrenia. To b...It is recognized that developing valid animal models is essential for the research on the neurobiological mechanisms of (and treatments for) psychiatric disorders, even when these are as complex as schizophrenia. To be considered a valid analogue of the disorder, a given model should present good face validity (i.e. similarity of symptoms), good predictive validity (i.e. similarity of treatment effects and potential for discovering novel treatments) and enough construct validity (i.e. the model should help discover neurobiological mechanisms underlying the disorder or some relevant symptoms). The complexity of symptoms (positive, negative and cognitive) of schizophrenia makes it a very difficult task for a model to mimic all the main features of the disorder, but some rodent (mouse and rat) models have behavioural and even neurobiological phenotype characteristics resembling positive-like symptoms, cognitive symptoms and some neurochemical features of schizophrenia. As several recent works have already reviewed the main behavioural and developmental models, as well as the most used drug-induced, lesion-induced and genetic mouse models, the present review focuses on describing the most relevant genetically-based rat models of schizophrenia-relevant symptoms. Thus, we discuss several selective breeding programs leading to rat lines/strains which present impaired prepulse inhibition (PPI) of the acoustic startle response and (in some cases) latent inhibition deficits (both of which may be considered as endophenotypes of schizophrenia related with pre-attentive processes and attention, respectively), as well as other schizophrenia-relevant symptoms (e.g. learning deficits). Evidence is presented for the effects of genetic background on PPI (and other symptoms/phenotypes), as well as for environmental influences on genetic predisposition to enhanced apomorphine (mixed dopamine receptor agonist) effects. Some of the described rat models appear to present face validity and, to a certain extent, construct validity. While efforts should be made to evaluate the predictive validity of these genetic rat models, we propose that they have the advantage (over mouse knockouts, for example) of better representing “normal” genetic, neurobiological and phenotype variation, thus allowing the study of associations among them by means of genetic mapping or gene expression studies.展开更多
The prediction accuracy of existing models of the rolling force of a thick plate is always very low.To address this problem,a high-precision genetic algorithm-backpropagation network(GA-BP)model of deformation resista...The prediction accuracy of existing models of the rolling force of a thick plate is always very low.To address this problem,a high-precision genetic algorithm-backpropagation network(GA-BP)model of deformation resistance was built,and its integration with the traditional fitted model was further established.Then,a novel rolling force model was obtained by embedding the integration model of deformation resistance in the original model of rolling force.According to this research idea,the industrial data are normalized at first.On this basis,the interactions among the process parameters were disclosed through the variance analysis,and then described by various virtual factors.These factors are set as part of input parameters.Then,the optimal structure of the GA-BP model of deformation resistance was determined and an integration model of deformation resistance was built.Finally,a novel rolling force model is obtained by substituting the traditional fitted deformation resistance into the Sims model with the integration model of the deformation resistance.The results proves that the introduction of virtual factors can increase the hit rate of±5%from 75.8%to 78%and can reduce the root mean square error from 4.72%to 4.48%.Besides,it is found that the mean relative error of the traditional fitted deformation resistance is 0.142,while that of the modified deformation resistance is only 0.03.In addition,the mean relative error in the original rolling force model is 0.145,while that of the present model is only 0.03.展开更多
Computer simulation permits answering theoretical and applied questions in animal and plant breeding.Blib is a novel multi-module simulation platform,which is able to handle more complicated genetic effects and models...Computer simulation permits answering theoretical and applied questions in animal and plant breeding.Blib is a novel multi-module simulation platform,which is able to handle more complicated genetic effects and models than most existing tools.In this study,we describe one major and unified application module of Blib,i.e.,ISB(abbreviated from in silico breeding),for simulating the three categories of breeding programs for developing clonal,pure-line and hybrid cultivars in plants.Genetic models on environments and breeding-targeted traits,one or several parental populations,and a number of breeding methods are key elements to run simulation experiments in ISB,which are arranged in three external input files by given formats.Applications of ISB are illustrated by three case studies,representing the three categories of plant breeding programs.Under the condition that 5000 F1 progenies were generated and tested from 50 heterozygous parents,Case study I showed that 50 crosses,each of 100 progenies,made the best balance between genetic achievement and field cost.In Case study II,one optimum breeding method was identified by which the pure lines with high yield and medium maturity could be developed.Case study III investigated the genetic consequence in hybrid breeding from five testers.One tester was identified for the simultaneous improvement in F1 hybrids and inbred lines.In summary,ISB identified a balanced crossing scheme,an optimum pure-line selection method,and an optimized tester in three case studies which are relevant to plant breeding.We believe the prediction by simulation would be highly required in front of the next generation of breeding to be driven by informatics and intelligence.展开更多
Parkinson’s disease(PD)relates to defective mitochondrial quality control in the dopaminergic motor network.Genetic studies have revealed that PINK1 and Parkin mutations are indicative of a heightened propensity to P...Parkinson’s disease(PD)relates to defective mitochondrial quality control in the dopaminergic motor network.Genetic studies have revealed that PINK1 and Parkin mutations are indicative of a heightened propensity to PD onset,pinpointing mitophagy and inflammation as the culprit pathways involved in neuronal loss in the substantia nigra(SNpc).In a reciprocal manner,LRRK2 functions in the regulation of basal flux and inflammatory responses responsible for PINK1/Parkin-dependent mitophagy activation.Pharmacological intervention in these diseasemodifying pathways may facilitate the development of novel PD therapeutics,despite the current lack of an established drug evaluation model.As such,we reviewed the feasibility of employing the versatile global Pink1knockout(KO)rat model as a self-sufficient,spontaneous PD model for investigating both disease etiology and drug pharmacology.These rats retain clinical features encompassing basal mitophagic flux changes with PD progression.We demonstrate the versatility of this PD rat model based on the incorporation of additional experimental insults to recapitulate the proinflammatory responses observed in PD patients.展开更多
Conventional plant breeding largely depends on phenotypic selection and breeder＇s experience, therefore the breeding efficiency is low and the predictions are inaccurate. Along with the fast development in molecular ...Conventional plant breeding largely depends on phenotypic selection and breeder＇s experience, therefore the breeding efficiency is low and the predictions are inaccurate. Along with the fast development in molecular biology and biotechnology, a large amount of biological data is available for genetic studies of important breeding traits in plants, which in turn allows the conduction of genotypic selection in the breeding process. However, gene information has not been effectively used in crop improvement because of the lack of appropriate tools. The simulation approach can utilize the vast and diverse genetic information, predict the cross performance, and compare different selection methods. Thus, the best performing crosses and effective breeding strategies can be identified. QuLine is a computer tool capable of defining a range, from simple to complex genetic models, and simulating breeding processes for developing final advanced lines. On the basis of the results from simulation experiments, breeders can optimize their breeding methodology and greatly improve the breeding efficiency. In this article, the underlying principles of simulation modeling in crop enhancement is initially introduced, following which several applications of QuLine are summarized, by comparing the different selection strategies, the precision parental selection, using known gene information, and the design approach in breeding. Breeding simulation allows the definition of complicated genetic models consisting of multiple alleles, pleiotropy, epistasis, and genes, by environment interaction, and provides a useful tool for breeders, to efficiently use the wide spectrum of genetic data and information available.展开更多
基金funded by the Hebei Province Natural Resources Science and Technology Project(13000024P00F2D410443X).
文摘Medium-low temperature geothermal resources are abundant in the Guanxian fault depression.An essential foundation for the effective development and use of geothermal resources is the study of the genetic model and resource assessment of the geothermal system.This study examines the geothermal geological circumstances,hydrochemical features,and geothermal field characteristics based on the regional geological structure and prior research findings.The appraisal of geothermal resources is done,and a conceptual model of the geothermal system in the research area is built.The findings indicate that the Guan xian fault depression's geothermal resources are primarily Guantao Formation sandstone heat reservoirs.The geothermal water at the wellhead has a temperature between 54℃and 60℃,and its primary chemistry is Cl·SO_(4)-Na.Deep thermal conduction heats the geothermal water,which is then laterally supplied to the reservoir after being largely restored by air precipitation from the western Taihang Mountains.With an annual exploitable geothermal resource of 6,782×10^(12)J,or 23.14×10^(4)tons of standard coal,the Guantao Formation sandstone reservoir in the Guanxian depression has a geothermal resource of about 620.10×10^(16)J.An area of 18 million m^(2)can be heated by geothermal extraction per year,demonstrating the potential for geothermal resources and their high development and use value.
基金This work was supported by Chinese National Programs for High Technology Research and Development(973 Program)(No.2004CB117306).
文摘A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction （NCI） as well as their genotype by environment （GE） interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction （AUP） method. Data on four quantitative traits （boll number, lint percentage, fiber length, and micronaire） in Upland cotton （Gossypium hirsutum L.） were analyzed as a worked example to show the effectiveness of the model.
文摘The widespread Carboniferous KT-I dolomite in the eastern margin of the Pre-Caspian Basin is an important hydrocarbon reservoir. The dolomite lithology is dominated by crystalline dolomite. The δ18O values range from -6.71‰ to 2.45‰, and average 0.063‰, obviously larger than -2.5‰, indicating low-temperature dolomite of evaporation origin. Stable strontium isotope ratios （87Sr/86Sr） range from 0.70829 to 0.70875 and average 0.708365, very consistent with 87Sr/86Sr ratios in Carboniferous seawater. Chemical analysis of Ca and Mg elements shows that the dolomite has 9.1 mole% excess Ca or even higher before stabilization. The degree of order of dolomite is medium–slightly poor, varying in a range of 0.336-0.504 and averaging 0.417. It suggests that the dolomite formed under near-surface conditions. There are two models for the origin of the Carboniferous KT-I dolomite reservoir. These are 1） the evaporation concentration – weathering crust model and 2） the shoal facies – seepage reflux model. The former is mainly developed in restricted platforms – evaporate platforms of restricted marine deposition environments with a representation of dolomite associated with gypsum and mudstone. The latter mainly formed in platform edge shoals and intra-platform shoals and is controlled by dolomitization due to high salinity sea water influx from adjacent restricted sea or evaporate platform.
文摘This study was conducted to investigate the genetic regularity of indexes related to freshness keeping and its molecular basis by acquiring 6 generations （P1, P2, F1, B1, B2 and F2） of an inbred line T3 with long freshness period × an inbred line T15 with short freshness period in sweet corn. The genetic analysis of the indexes was performed by major gene＋polygene mixed genetic model combined with the genetic analysis combining six generations.The results showed that the decreasing rate of the postharvest sugar content in the T3 was controlled by two pairs of additive-dominante-epistatic major genes＋additive-dominant polygenes; each segregating generation was affected by its major genes, the heritability of major genes and polygene in the B1 generation was 74.63% and 17.67%, respectively; the heritability of major gene and potygene in the B2 was 91.98% and 0,00%, respectively; and the heritability of major gene and polygene inthe F2 was 82.67%, and 12.93%, respectively.
基金Project(51534006)supported by the Key Program of National Natural Science Foundation of ChinaProject(2014CB239005)supported by the National Key Basic Research and Development,ChinaProjects(41772150,51674211)supported by the National Natural Science Foundation of China。
文摘We have systematically investigated the feature, genetic model and distribution of calcareous insulating layers in marine strata of the Ⅰ oil group in member 2 of Zhujiang formation(ZJ2I oil formation), western Pearl River Mouth basin(PRMB) in the north of the South China Sea by using data such as cores, thin sections, X-ray diffraction of whole-rock, and calcite cement carbon and oxygen isotopes. The lithology of the calcareous insulating layers in the study area is mainly composed of the terrigenous clastic bioclastic limestone and a small amount of fine-grained calcareous sandstone. On this basis, two genetic models of calcareous insulating layers are established, including the evaporation seawater genetic model and shallow burial meteoric water genetic model. The calcareous insulating layers of the evaporation seawater genetic model developed in the foreshore subfacies, mainly at the top of the 1-1 strata and 1-3 strata. The calcareous insulating layers of the shallow burial meteoric water genetic model developed in the backshore subfacies, primarily in the 1-2 strata.
文摘In the early 1980's, the author proposed his view that copper-nickel sulphide deposts are of ore magma origin. For more than ten years, this view has aroused attention of his colleagues at home and abroad. In this paper an attempt is made to deal with the genetic model for ore magma of copper-nickel sulphide deposits in more details on the basis of geological, geochemical, petrophysico - chemical and thermodynamic studies of the Chibaisong copper-nickel sulphide deposit in the Changbai Mountains, Jilin province.
基金the National Key R&D Program of China(No.2019YFE0114700)the Key R&D Program in Hunan Province of China(No.2021GK2020)+1 种基金the Natural Science Foundation of Hunan Province of China(No.2021JJ30079)the Project of Philosophy and Social Science Research in Yiyang City(No.2022YS191)。
文摘With increasing the number of wind power generators,the consumption time of electromagnetic simulation of the wind farm explodes.To reduce the simulation time while meeting the accuracy requirement,a genetic clustering-based equivalent model is proposed for the wind farm with numerous doubly fed induction generators.In the proposed model,active power together with the reactive power and the wind speed are selected to form the set of clustering indicators.A normalization technique is utilized to cope with the multiple orders of magnitude in these factors.An exponential fitness value is formulated as a function of the sorting number of the primary fitness value,and the fitness-based selection probability is constructed to overcome the property of premature and slow convergence of the genetic clustering algorithm.The sum of squares due to error is used to determine the optimal clustering number.In addition,a decoupled parameter equivalence method is adopted to obtain the equivalent parameters of the collection network.Simulation results and comparisons with various methods under different voltage scenarios show the feasibility and effectiveness of the proposed model.
文摘Under-fitting problems usually occur in regression models for dam safety monitoring.To overcome the local convergence of the regression, a genetic algorithm (GA) was proposed using a real parameter coding, a ranking selection operator, an arithmetical crossover operator and a uniform mutation operator, and calculated the least-square error of the observed and computed values as its fitness function. The elitist strategy was used to improve the speed of the convergence. After that, the modified genetic algorithm was applied to reassess the coefficients of the regression model and a genetic regression model was set up. As an example, a slotted gravity dam in the Northeast of China was introduced. The computational results show that the genetic regression model can solve the under-fitting problems perfectly.
基金supported by the Guiding Plans for Natural Sciences Foundation of Liaoning Province,China(Grant No.20092207)the Special Foundation for Young Scientists of Liaoning Rice Research Institute,Shenyang,China(Grant No.DZS-2008-1)
文摘The inheritance of stripe disease resistance in a rice restorer line C224 was analyzed using the mixed effect model of major gene plus polygene for quantitative traits.In addition,the resistance was investigated in seven crosses of C224 with maintainer lines.The results showed that the stripe resistance of C224 was controlled by two major genes with additive-dominance-epistasis effects plus polygenes with additive-dominance effects （E-1 model）.These two genes had additive effects of-12.47% and-24.75%,respectively,showing negative dominance effects.There were significant epistasis and interaction effects between the two major genes.The heritability of the two major genes was 92.12%,while that of polygenes was 2.74%,indicating that the stripe resistance had dominant major gene effect.Of the seven crosses,five displayed high or medium resistance to the stripe disease.
文摘The use of the three genetic models viz. additive, dominant and recessive in </span><span style="font-family:Verdana;">Genome-wide association study (GWAS) is a common and powerful ap</span><span style="font-family:Verdana;">proach to study the association between genetic variants and a trait (disease). The selection of these models depends on the pattern of inheritance and the scope </span><span style="font-family:Verdana;">of the study. GWAS typically focuses on single-nucleotide polymorphism</span><span style="font-family:Verdana;"> (SNPs) and common human diseases in a case-control setup. In order to study this type of association between the risk genotype and the phenotype for a given inheritance pattern, the use of these genetic models helps to identify the disease risk appropriately. This study provides an overview of the existing genetic models (additive, dominant and recessive) and a practical demonstration of these model tests for the contingency tables of SNP genotypes and the disease phenotypes in a case-control setting.
基金supported by China Huaneng Group science and technology projects(No.HNKJ21-HF310,and HNKJ22-H10)China Huaneng Group science and technology project(Research and Application of Thermal Energy Evaluation and Gas Coupling Technology in Fengdong Huaneng Heating Zone,TY-21-HJK09)China Huaneng Group High-Level Talents Programme(Research on Spatial Distribution and Control Technology of Methane in Yunnan Diandong Mining Area).
文摘China is rich in geothermal resources,especially in Fujian Province,where 207 exposed hot springs have been discovered.The maximum temperature recorded in geothermal wells is above 121℃ in this province,indicating a high geothermal resource potential.However,large-scale breakthroughs in geothermal exploration are hindered by a lack of clear geothermal genetic models.In this study,the genetic model of a faultcontrolled mediumelow-temperature convection geothermal zone in the Fujian coastal area was determined by considering the tectonic characteristics of the area and the hydrochemical characteristics of the geothermal fluid(recharge,runoff and discharge characteristics,geothermal reservoir temperature,geothermal fluid circulation depth and renewability).The results showed that the exposed hot springs and high-temperature geothermal boreholes were concentrated in the Fu'aneNanjing and ChangleeZhao'an fault zones.At the intersection or faultbend of these two fault zones,there was strong stress release and activity,as demonstrated in the exposed parts of the high-temperature geothermal resources.The ChangleeZhao'an fault zone had a greater circulation depth,with an average heat storage temperature of 140℃,reflecting high geothermal resource potential.Considering the current temperature of the hot springs,Xiamen Bay and NanjingeJiulong River were identified as the next geothermal development zones.
基金supported by the National High Technology Research and Development Program of China (Grant No. 2010AA101301)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QTL mapping for seven quality traits was conducted by using 254 recombinant inbred lines （RIL） derived from a japonica-japonica rice cross of Xiushui 79/C Bao. The seven traits investigated were grain length （GL）, grain length to width ratio （LWR）, chalk grain rate （CGR）, chalkiness degree （CD）, gelatinization temperature （GT）, amylose content （AC） and gel consistency （GC） of head rice. Three mapping methods employed were composite interval mapping in QTLMapper 2.0 software based on mixed linear model （MCIM）, inclusive composite interval mapping in QTL IciMapping 3.0 software based on stepwise regression linear model （ICIM） and multiple interval mapping with regression forward selection in Windows QTL Cartographer 2.5 based on multiple regression analysis （MIMR）. Results showed that five QTLs with additive effect （A-QTLs） were detected by all the three methods simultaneously, two by two methods simultaneously, and 23 by only one method. Five A-QTLs were detected by MCIM, nine by ICIM and 28 by MIMR. The contribution rates of single A-QTL ranged from 0.89% to 38.07%. All the QTLs with epistatic effect （E-QTLs） detected by MIMR were not detected by the other two methods. Fourteen pairs of E-QTLs were detected by both MCIM and ICIM, and 142 pairs of E-QTLs were detected by only one method. Twenty-five pairs of E-QTLs were detected by MCIM, 141 pairs by ICIM and four pairs by MIMR. The contribution rates of single pair of E-QTL were from 2.60% to 23.78%. In the Xiu-Bao RIL population, epistatic effect played a major role in the variation of GL and CD, and additive effect was the dominant in the variation of LWR, while both epistatic effect and additive effect had equal importance in the variation of CGR, AC, GT and GC. QTLs detected by two or more methods simultaneously were highly reliable, and could be applied to improve the quality traits in japonica hybrid rice.
基金Supported by the National Natural Science Foundation of China(21076179)the National Basic Research Program of China(2012CB720500)
文摘This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection.
基金Project (Nos. 60174009 and 70071017) supported by the NationalNatural Science Foundation of China
文摘This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) algorithm is used for Nonlinear Parameter Estimation (NPE) of dynamic model structures. In addition, GPM integrates the results of Nonlinear Time Series Analysis (NTSA) to adjust the parameters and takes them as the criteria of established models. Experiments showed the effectiveness of such improvements on chaotic time series modeling.
基金This project is supported by Key Science-Technology Project of Shanghai City Tenth Five-Year-Plan, China (No.031111002)Specialized Research Fund for the Doctoral Program of Higher Education, China (No.20040247033)Municipal Key Basic Research Program of Shanghai, China (No.05JC14060)
文摘In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.
基金Supported by grants for the MICINN(PSI2009-10532)“Fundacio La Marato TV3”(ref.092630/31)and 2009SGR-0051.I.O.is recipient of a PhD FI fellowship(DGR 2014).
文摘It is recognized that developing valid animal models is essential for the research on the neurobiological mechanisms of (and treatments for) psychiatric disorders, even when these are as complex as schizophrenia. To be considered a valid analogue of the disorder, a given model should present good face validity (i.e. similarity of symptoms), good predictive validity (i.e. similarity of treatment effects and potential for discovering novel treatments) and enough construct validity (i.e. the model should help discover neurobiological mechanisms underlying the disorder or some relevant symptoms). The complexity of symptoms (positive, negative and cognitive) of schizophrenia makes it a very difficult task for a model to mimic all the main features of the disorder, but some rodent (mouse and rat) models have behavioural and even neurobiological phenotype characteristics resembling positive-like symptoms, cognitive symptoms and some neurochemical features of schizophrenia. As several recent works have already reviewed the main behavioural and developmental models, as well as the most used drug-induced, lesion-induced and genetic mouse models, the present review focuses on describing the most relevant genetically-based rat models of schizophrenia-relevant symptoms. Thus, we discuss several selective breeding programs leading to rat lines/strains which present impaired prepulse inhibition (PPI) of the acoustic startle response and (in some cases) latent inhibition deficits (both of which may be considered as endophenotypes of schizophrenia related with pre-attentive processes and attention, respectively), as well as other schizophrenia-relevant symptoms (e.g. learning deficits). Evidence is presented for the effects of genetic background on PPI (and other symptoms/phenotypes), as well as for environmental influences on genetic predisposition to enhanced apomorphine (mixed dopamine receptor agonist) effects. Some of the described rat models appear to present face validity and, to a certain extent, construct validity. While efforts should be made to evaluate the predictive validity of these genetic rat models, we propose that they have the advantage (over mouse knockouts, for example) of better representing “normal” genetic, neurobiological and phenotype variation, thus allowing the study of associations among them by means of genetic mapping or gene expression studies.
基金funded by the National Natural Science Foundation of China(Grant Nos.52274388,U1960105 and 52074187)the authors express gratitude to reviewers for precious suggestions.
文摘The prediction accuracy of existing models of the rolling force of a thick plate is always very low.To address this problem,a high-precision genetic algorithm-backpropagation network(GA-BP)model of deformation resistance was built,and its integration with the traditional fitted model was further established.Then,a novel rolling force model was obtained by embedding the integration model of deformation resistance in the original model of rolling force.According to this research idea,the industrial data are normalized at first.On this basis,the interactions among the process parameters were disclosed through the variance analysis,and then described by various virtual factors.These factors are set as part of input parameters.Then,the optimal structure of the GA-BP model of deformation resistance was determined and an integration model of deformation resistance was built.Finally,a novel rolling force model is obtained by substituting the traditional fitted deformation resistance into the Sims model with the integration model of the deformation resistance.The results proves that the introduction of virtual factors can increase the hit rate of±5%from 75.8%to 78%and can reduce the root mean square error from 4.72%to 4.48%.Besides,it is found that the mean relative error of the traditional fitted deformation resistance is 0.142,while that of the modified deformation resistance is only 0.03.In addition,the mean relative error in the original rolling force model is 0.145,while that of the present model is only 0.03.
基金supported by Biological Breeding-National Science and Technology Major Project(2023ZD0407501)National Natural Science Foundation of China(31861143003)Innovation Program of Chinese Academy of Agricultural Sciences.
文摘Computer simulation permits answering theoretical and applied questions in animal and plant breeding.Blib is a novel multi-module simulation platform,which is able to handle more complicated genetic effects and models than most existing tools.In this study,we describe one major and unified application module of Blib,i.e.,ISB(abbreviated from in silico breeding),for simulating the three categories of breeding programs for developing clonal,pure-line and hybrid cultivars in plants.Genetic models on environments and breeding-targeted traits,one or several parental populations,and a number of breeding methods are key elements to run simulation experiments in ISB,which are arranged in three external input files by given formats.Applications of ISB are illustrated by three case studies,representing the three categories of plant breeding programs.Under the condition that 5000 F1 progenies were generated and tested from 50 heterozygous parents,Case study I showed that 50 crosses,each of 100 progenies,made the best balance between genetic achievement and field cost.In Case study II,one optimum breeding method was identified by which the pure lines with high yield and medium maturity could be developed.Case study III investigated the genetic consequence in hybrid breeding from five testers.One tester was identified for the simultaneous improvement in F1 hybrids and inbred lines.In summary,ISB identified a balanced crossing scheme,an optimum pure-line selection method,and an optimized tester in three case studies which are relevant to plant breeding.We believe the prediction by simulation would be highly required in front of the next generation of breeding to be driven by informatics and intelligence.
基金supported by the KIZ-CUHK Joint Lab of Bioresources and Molecular Research of Common Diseases(4750378)the VC Discretionary Fund provided to the Hong Kong Branch of Chinese Academy of Science Center for Excellence in Animal Evolution and Genetics(Acc 8601011)partially by the State Key Laboratory CUHKJinan MOE Key Laboratory for Regenerative medicine(2622009)。
文摘Parkinson’s disease(PD)relates to defective mitochondrial quality control in the dopaminergic motor network.Genetic studies have revealed that PINK1 and Parkin mutations are indicative of a heightened propensity to PD onset,pinpointing mitophagy and inflammation as the culprit pathways involved in neuronal loss in the substantia nigra(SNpc).In a reciprocal manner,LRRK2 functions in the regulation of basal flux and inflammatory responses responsible for PINK1/Parkin-dependent mitophagy activation.Pharmacological intervention in these diseasemodifying pathways may facilitate the development of novel PD therapeutics,despite the current lack of an established drug evaluation model.As such,we reviewed the feasibility of employing the versatile global Pink1knockout(KO)rat model as a self-sufficient,spontaneous PD model for investigating both disease etiology and drug pharmacology.These rats retain clinical features encompassing basal mitophagic flux changes with PD progression.We demonstrate the versatility of this PD rat model based on the incorporation of additional experimental insults to recapitulate the proinflammatory responses observed in PD patients.
文摘Conventional plant breeding largely depends on phenotypic selection and breeder＇s experience, therefore the breeding efficiency is low and the predictions are inaccurate. Along with the fast development in molecular biology and biotechnology, a large amount of biological data is available for genetic studies of important breeding traits in plants, which in turn allows the conduction of genotypic selection in the breeding process. However, gene information has not been effectively used in crop improvement because of the lack of appropriate tools. The simulation approach can utilize the vast and diverse genetic information, predict the cross performance, and compare different selection methods. Thus, the best performing crosses and effective breeding strategies can be identified. QuLine is a computer tool capable of defining a range, from simple to complex genetic models, and simulating breeding processes for developing final advanced lines. On the basis of the results from simulation experiments, breeders can optimize their breeding methodology and greatly improve the breeding efficiency. In this article, the underlying principles of simulation modeling in crop enhancement is initially introduced, following which several applications of QuLine are summarized, by comparing the different selection strategies, the precision parental selection, using known gene information, and the design approach in breeding. Breeding simulation allows the definition of complicated genetic models consisting of multiple alleles, pleiotropy, epistasis, and genes, by environment interaction, and provides a useful tool for breeders, to efficiently use the wide spectrum of genetic data and information available.
