In order to carry out the genetic improvement of turbot upper thermal tolerance, it is necessary to estimate the genetic parameters of UTT（upper thermal tolerance） and growth-related traits. The objective of this st...In order to carry out the genetic improvement of turbot upper thermal tolerance, it is necessary to estimate the genetic parameters of UTT（upper thermal tolerance） and growth-related traits. The objective of this study was to estimate genetic parameters for BW（body weight） and UTT in a two-generational turbot（Scophthalmus maximus L.） pedigree derived from four imported turbot stocks（England, France, Denmark and Norway）. A total of 42 families including 20 families from G1 generation and 22 families from G2 generation were used to test upper thermal tolerance（40–50 animals per family） in this study and the body weight of individuals were measured. The heritability of BW and UTT and the correlation between these two traits were estimated based on an individual animal model using Bayesian method based on two types of animal models with and without maternal effects.These results showed that the heritabilities for BW and UTT and phenotypic and genetic correlations between the two traits estimated from model without maternal effects were 0.239±0.141, 0.111±0.080, 0.075±0.026 and–0.019±0.011, respectively. The corresponding values from model with maternal effects were 0.203±0.115,0.055±0.026, 0.047±0.034 and –0.024±0.028, respectively. The maternal effects of BW and UTT were 0.050±0.017 and 0.013±0.004, respectively. The maternal effects had a certain influence on the genetic evaluation of the two traits. The findings of this paper provided the necessary background to determine the best selection strategy to be adopted in the genetic improvement program.展开更多
Network attack graphs are originally used to evaluate what the worst security state is when a concerned net-work is under attack. Combined with intrusion evidence such like IDS alerts, attack graphs can be further use...Network attack graphs are originally used to evaluate what the worst security state is when a concerned net-work is under attack. Combined with intrusion evidence such like IDS alerts, attack graphs can be further used to perform security state posterior inference (i.e. inference based on observation experience). In this area, Bayesian network is an ideal mathematic tool, however it can not be directly applied for the following three reasons: 1) in a network attack graph, there may exist directed cycles which are never permitted in a Bayesian network, 2) there may exist temporal partial ordering relations among intrusion evidence that can-not be easily modeled in a Bayesian network, and 3) just one Bayesian network cannot be used to infer both the current and the future security state of a network. In this work, we improve an approximate Bayesian posterior inference algorithm–the likelihood-weighting algorithm to resolve the above obstacles. We give out all the pseudocodes of the algorithm and use several examples to demonstrate its benefit. Based on this, we further propose a network security assessment and enhancement method along with a small network scenario to exemplify its usage.展开更多
Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of t...Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of the network were obtained. After the selection of input variables using stepwise/multiple linear regression method in SPSS i1.0 software, the BRBPNN model was established between chlorophyll-α and environmental parameters, biological parameters. The achieved optimal network structure was 3-11-1 with the correlation coefficients and the mean square errors for the training set and the test set as 0.999 and 0.000？8426, 0.981 and 0.0216 respectively. The sum of square weights between each input neuron and the hidden layer of optimal BRBPNN models of different structures indicated that the effect of individual input parameter on chlorophyll- α declined in the order of alga amount 〉 secchi disc depth（SD） 〉 electrical conductivity （EC）. Additionally, it also demonstrated that the contributions of these three factors were the maximal for the change of chlorophyll-α concentration, total phosphorus（TP） and total nitrogen（TN） were the minimal. All the results showed that BRBPNN model was capable of automated regularization parameter selection and thus it may ensure the excellent generation ability and robustness. Thus, this study laid the foundation for the application of BRBPNN model in the analysis of aquatic ecological data（chlorophyll-α prediction） and the explanation about the effective eutrophication treatment measures for Nanzui water area in Dongting Lake.展开更多
An accurate understanding of the condition of a pipe is important for maintaining acceptable levels of service and providing appropriate strategies for maintenance and rehabilitation in water supply systems. Many fact...An accurate understanding of the condition of a pipe is important for maintaining acceptable levels of service and providing appropriate strategies for maintenance and rehabilitation in water supply systems. Many factors contribute to pipe deterioration. To consolidate information on these factors to assess the condition of water pipes, this study employed a new ap-proach based on Bayesian configuration against pipe condition to generate factor weights. Ten pipe factors from three pipe ma-terials (cast iron, ductile cast iron and steel) were used in this study. The factors included size, age, inner coating, outer coating, soil condition, bedding condition, trench depth, electrical recharge, the number of road lanes, material, and operational pressure. To address identification problems that arise when switching from pipe factor information to actual pipe condition, informative prior factor weight distribution based on the literature and previous knowledge of water pipe assessment was used. The influence of each factor on the results of pipe assessment was estimated. Results suggested that factors that with smaller weight values or with weights having relative stable posterior means and narrow uncertainty bounds, would have less influence on pipe conditions. The model was the most sensitive to variations of pipe age. Using numerical experiments of different factor combinations, a simplified model, excluding factors such as trench depth, electrical recharge, and the number of road lanes, is provided. The proposed Bayesian inference approach provides a more reliable assessment of pipe deterioration.展开更多
BACKGROUND Intrahepatic cholangiocarcinoma(ICC)is a highly malignant liver cancer subtype with limited effective treatment options.Emerging evidence suggests that inflammatory factors play a critical role in ICC progr...BACKGROUND Intrahepatic cholangiocarcinoma(ICC)is a highly malignant liver cancer subtype with limited effective treatment options.Emerging evidence suggests that inflammatory factors play a critical role in ICC progression within the tumor microenvironment(TME).However,causal relationships between specific inflammatory factors and ICC risk remain unclear.AIM To investigate the causal relationship between inflammatory factors and ICC.METHODS This study used Mendelian randomization(MR)and Bayesian weighted MR(BWMR)analyses to investigate the causal impact of inflammatory factors on ICC risk.Genetic data from genome-wide association studies were utilized to identify and validate instrumental variables for 91 inflammatory factors,followed by sensitivity analyses to ensure robustness.RESULTS MR analysis identified significant associations between elevated levels of artemin and matrix metalloproteinase(MMP)-10 and increased ICC risk.BWMR and meta-MR analysis results validated these associations.Sensitivity analyses confirmed the stability of these findings,indicating that specific inflammatory factors may contribute causally to ICC development.CONCLUSION This study provides evidence that certain inflammatory factors,particularly artemin and MMP-10,are causally linked to ICC risk,identifying them as potential risk factors and therapeutic targeting.These findings enhance the understanding of the inflammatory components of the TME in ICC,supporting the development of targeted intervention strategies.展开更多
基金The Earmarked Fund for Modern Agro-Industry Technology Research System under contract No.CARS-47-G01the Ao Shan Talents Cultivation Program supported by Qingdao National Laboratory for Marine Science and Technology under contract No.2017ASTCP-OS04+3 种基金the Key Research and Development Plan of Shandong under contract No.2016GSF115019the Agricultural Fine Breed Project of Shandong under contract No.2016LZGC031Chinese Acdemy of Fishery Sciences Basal Research Fund under contract No.2016HY-JC0301the Special Financial Grant from the China Postdoctoral Science Foundation under contract No.2016T90661
文摘In order to carry out the genetic improvement of turbot upper thermal tolerance, it is necessary to estimate the genetic parameters of UTT（upper thermal tolerance） and growth-related traits. The objective of this study was to estimate genetic parameters for BW（body weight） and UTT in a two-generational turbot（Scophthalmus maximus L.） pedigree derived from four imported turbot stocks（England, France, Denmark and Norway）. A total of 42 families including 20 families from G1 generation and 22 families from G2 generation were used to test upper thermal tolerance（40–50 animals per family） in this study and the body weight of individuals were measured. The heritability of BW and UTT and the correlation between these two traits were estimated based on an individual animal model using Bayesian method based on two types of animal models with and without maternal effects.These results showed that the heritabilities for BW and UTT and phenotypic and genetic correlations between the two traits estimated from model without maternal effects were 0.239±0.141, 0.111±0.080, 0.075±0.026 and–0.019±0.011, respectively. The corresponding values from model with maternal effects were 0.203±0.115,0.055±0.026, 0.047±0.034 and –0.024±0.028, respectively. The maternal effects of BW and UTT were 0.050±0.017 and 0.013±0.004, respectively. The maternal effects had a certain influence on the genetic evaluation of the two traits. The findings of this paper provided the necessary background to determine the best selection strategy to be adopted in the genetic improvement program.
文摘Network attack graphs are originally used to evaluate what the worst security state is when a concerned net-work is under attack. Combined with intrusion evidence such like IDS alerts, attack graphs can be further used to perform security state posterior inference (i.e. inference based on observation experience). In this area, Bayesian network is an ideal mathematic tool, however it can not be directly applied for the following three reasons: 1) in a network attack graph, there may exist directed cycles which are never permitted in a Bayesian network, 2) there may exist temporal partial ordering relations among intrusion evidence that can-not be easily modeled in a Bayesian network, and 3) just one Bayesian network cannot be used to infer both the current and the future security state of a network. In this work, we improve an approximate Bayesian posterior inference algorithm–the likelihood-weighting algorithm to resolve the above obstacles. We give out all the pseudocodes of the algorithm and use several examples to demonstrate its benefit. Based on this, we further propose a network security assessment and enhancement method along with a small network scenario to exemplify its usage.
文摘Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of the network were obtained. After the selection of input variables using stepwise/multiple linear regression method in SPSS i1.0 software, the BRBPNN model was established between chlorophyll-α and environmental parameters, biological parameters. The achieved optimal network structure was 3-11-1 with the correlation coefficients and the mean square errors for the training set and the test set as 0.999 and 0.000？8426, 0.981 and 0.0216 respectively. The sum of square weights between each input neuron and the hidden layer of optimal BRBPNN models of different structures indicated that the effect of individual input parameter on chlorophyll- α declined in the order of alga amount 〉 secchi disc depth（SD） 〉 electrical conductivity （EC）. Additionally, it also demonstrated that the contributions of these three factors were the maximal for the change of chlorophyll-α concentration, total phosphorus（TP） and total nitrogen（TN） were the minimal. All the results showed that BRBPNN model was capable of automated regularization parameter selection and thus it may ensure the excellent generation ability and robustness. Thus, this study laid the foundation for the application of BRBPNN model in the analysis of aquatic ecological data（chlorophyll-α prediction） and the explanation about the effective eutrophication treatment measures for Nanzui water area in Dongting Lake.
基金Project supported by the National Construction of High-Quality University Projects of Graduate (No. 2008102915)the National Specially Major Fund of Water Pollution Control and Management (No. 2008ZX07314-005)the Tianjin Science and Technology Support Program (No. 09ZCGYSF00600), China
文摘An accurate understanding of the condition of a pipe is important for maintaining acceptable levels of service and providing appropriate strategies for maintenance and rehabilitation in water supply systems. Many factors contribute to pipe deterioration. To consolidate information on these factors to assess the condition of water pipes, this study employed a new ap-proach based on Bayesian configuration against pipe condition to generate factor weights. Ten pipe factors from three pipe ma-terials (cast iron, ductile cast iron and steel) were used in this study. The factors included size, age, inner coating, outer coating, soil condition, bedding condition, trench depth, electrical recharge, the number of road lanes, material, and operational pressure. To address identification problems that arise when switching from pipe factor information to actual pipe condition, informative prior factor weight distribution based on the literature and previous knowledge of water pipe assessment was used. The influence of each factor on the results of pipe assessment was estimated. Results suggested that factors that with smaller weight values or with weights having relative stable posterior means and narrow uncertainty bounds, would have less influence on pipe conditions. The model was the most sensitive to variations of pipe age. Using numerical experiments of different factor combinations, a simplified model, excluding factors such as trench depth, electrical recharge, and the number of road lanes, is provided. The proposed Bayesian inference approach provides a more reliable assessment of pipe deterioration.
基金Supported by National Key Research and Development Program of China,No.2021YFA1301104.
文摘BACKGROUND Intrahepatic cholangiocarcinoma(ICC)is a highly malignant liver cancer subtype with limited effective treatment options.Emerging evidence suggests that inflammatory factors play a critical role in ICC progression within the tumor microenvironment(TME).However,causal relationships between specific inflammatory factors and ICC risk remain unclear.AIM To investigate the causal relationship between inflammatory factors and ICC.METHODS This study used Mendelian randomization(MR)and Bayesian weighted MR(BWMR)analyses to investigate the causal impact of inflammatory factors on ICC risk.Genetic data from genome-wide association studies were utilized to identify and validate instrumental variables for 91 inflammatory factors,followed by sensitivity analyses to ensure robustness.RESULTS MR analysis identified significant associations between elevated levels of artemin and matrix metalloproteinase(MMP)-10 and increased ICC risk.BWMR and meta-MR analysis results validated these associations.Sensitivity analyses confirmed the stability of these findings,indicating that specific inflammatory factors may contribute causally to ICC development.CONCLUSION This study provides evidence that certain inflammatory factors,particularly artemin and MMP-10,are causally linked to ICC risk,identifying them as potential risk factors and therapeutic targeting.These findings enhance the understanding of the inflammatory components of the TME in ICC,supporting the development of targeted intervention strategies.
