In cold regions,the dynamic compressive strength(DCS)of rock damaged by freeze-thaw weathering significantly influences the stability of rock engineering.Nevertheless,testing the dynamic strength under freeze-thaw wea...In cold regions,the dynamic compressive strength(DCS)of rock damaged by freeze-thaw weathering significantly influences the stability of rock engineering.Nevertheless,testing the dynamic strength under freeze-thaw weathering conditions is often both time-consuming and expensive.Therefore,this study considers the effect of characteristic impedance on DCS and aims to quickly determine the DCS of frozen-thawed rocks through the application of machine-learning techniques.Initially,a database of DCS for frozen-thawed rocks,comprising 216 rock specimens,was compiled.Three external load parameters(freeze-thaw cycle number,confining pressure,and impact pressure)and two rock parameters(characteristic impedance and porosity)were selected as input variables,with DCS as the predicted target.This research optimized the kernel scale,penalty factor,and insensitive loss coefficient of the support vector regression(SVR)model using five swarm intelligent optimization algorithms,leading to the development of five hybrid models.In addition,a statistical DCS prediction equation using multiple linear regression techniques was developed.The performance of the prediction models was comprehensively evaluated using two error indexes and two trend indexes.A sensitivity analysis based on the cosine amplitude method has also been conducted.The results demonstrate that the proposed hybrid SVR-based models consistently provided accurate DCS predictions.Among these models,the SVR model optimized with the chameleon swarm algorithm exhibited the best performance,with metrics indicating its effectiveness,including root mean square error(RMSE)﹦3.9675,mean absolute error(MAE)﹦2.9673,coefficient of determination(R^(2))﹦0.98631,and variance accounted for(VAF)﹦98.634.This suggests that the chameleon swarm algorithm yielded the most optimal results for enhancing SVR models.Notably,impact pressure and characteristic impedance emerged as the two most influential parameters in DCS prediction.This research is anticipated to serve as a reliable reference for estimating the DCS of rocks subjected to freeze-thaw weathering.展开更多
The denoising of microseismic signals is a prerequisite for subsequent analysis and research.In this research,a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm(BWOA)optimized ...The denoising of microseismic signals is a prerequisite for subsequent analysis and research.In this research,a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm(BWOA)optimized VariationalMode Decomposition(VMD)jointWavelet Threshold Denoising(WTD)algorithm(BVW)is proposed.The BVW algorithm integrates VMD and WTD,both of which are optimized by BWOA.Specifically,this algorithm utilizes VMD to decompose the microseismic signal to be denoised into several Band-Limited IntrinsicMode Functions(BLIMFs).Subsequently,these BLIMFs whose correlation coefficients with the microseismic signal to be denoised are higher than a threshold are selected as the effective mode functions,and the effective mode functions are denoised using WTD to filter out the residual low-and intermediate-frequency noise.Finally,the denoised microseismic signal is obtained through reconstruction.The ideal values of VMD parameters and WTD parameters are acquired by searching with BWOA to achieve the best VMD decomposition performance and solve the problem of relying on experience and requiring a large workload in the application of the WTD algorithm.The outcomes of simulated experiments indicate that this algorithm is capable of achieving good denoising performance under noise of different intensities,and the denoising performance is significantly better than the commonly used VMD and Empirical Mode Decomposition(EMD)algorithms.The BVW algorithm is more efficient in filtering noise,the waveform after denoising is smoother,the amplitude of the waveform is the closest to the original signal,and the signal-to-noise ratio(SNR)and the root mean square error after denoising are more satisfying.The case based on Fankou Lead-Zinc Mine shows that for microseismic signals with different intensities of noise monitored on-site,compared with VMD and EMD,the BVW algorithm ismore efficient in filtering noise,and the SNR after denoising is higher.展开更多
In recent decades, tokamak discharges with zero total toroidal current have been reported in tokamak experiments, and this is one of the key problems in alternating current(AC) operations.An efficient free-boundary eq...In recent decades, tokamak discharges with zero total toroidal current have been reported in tokamak experiments, and this is one of the key problems in alternating current(AC) operations.An efficient free-boundary equilibrium code is developed to investigate such advanced tokamak discharges with current reversal equilibrium configuration. The calculation results show that the reversal current equilibrium can maintain finite pressure and also has considerable effects on the position of the X-point and the magnetic separatrix shape, and hence also on the position of the strike point on the divertor plates, which is extremely useful for magnetic design, MHD stability analysis, and experimental data analysis etc. for the AC plasma current operation on tokamaks.展开更多
Type 2 diabetes mellitus(T2DM)is a chronic metabolic disorder characterized by hyperglycemia and insulin resistance.The global prevalence of T2DM has reached epidemic proportions,affecting approximately 463 million ad...Type 2 diabetes mellitus(T2DM)is a chronic metabolic disorder characterized by hyperglycemia and insulin resistance.The global prevalence of T2DM has reached epidemic proportions,affecting approximately 463 million adults worldwide in 2019.Current treatments for T2DM include lifestyle modifications,oral antidiabetic agents,and insulin therapy.However,these therapies may carry side effects and fail to achieve optimal glycemic control in some patients.Therefore,there is a growing interest in the role of gut microbiota and more gut-targeted therapies in the management of T2DM.The gut microbiota,which refers to the community of microorganisms that inhabit the human gut,has been shown to play a crucial role in the regulation of glucose metabolism and insulin sensitivity.Alterations in gut microbiota composition and diversity have been observed in T2DM patients,with a reduction in beneficial bacteria and an increase in pathogenic bacteria.This dysbiosis may contribute to the pathogenesis of the disease by promoting inflammation and impairing gut barrier function.Several gut-targeted therapies have been developed to modulate the gut microbiota and improve glycemic control in T2DM.One potential approach is the use of probio-tics,which are live microorganisms that confer health benefits to the host when administered in adequate amounts.Several randomized controlled trials have demonstrated that certain probiotics,such as Lactobacillus and Bifidobacterium species,can improve glycemic control and insulin sensitivity in T2DM patients.Mechanisms may include the production of short-chain fatty acids,the improvement of gut barrier function,and the reduction of inflammation.Another gut-targeted therapy is fecal microbiota transplantation(FMT),which involves the transfer of fecal material from a healthy donor to a recipient.FMT has been used successfully in the treatment of Clostridioides difficile infection and is now being investigated as a potential therapy for T2DM.A recent randomized controlled trial showed that FMT from lean donors improved glucose metabolism and insulin sensitivity in T2DM patients with obesity.However,FMT carries potential risks,including transmission of infectious agents and alterations in the recipient's gut microbiota that may be undesirable.In addition to probiotics and FMT,other gut-targeted therapies are being investigated for the management of T2DM,such as prebiotics,synbiotics,and postbiotics.Prebiotics are dietary fibers that promote the growth of beneficial gut bacteria,while synbiotics combine probiotics and prebiotics.Postbiotics refer to the metabolic products of probiotics that may have beneficial effects on the host.The NIH SPARC program,or the Stimulating Peripheral Activity to Relieve Conditions,is a research initiative aimed at developing new therapies for a variety of health conditions,including T2DM.The SPARC program focuses on using electrical stimulation to activate peripheral nerves and organs,in order to regulate glucose levels in the body.The goal of this approach is to develop targeted,non-invasive therapies that can help patients better manage their diabetes.One promising area of research within the SPARC program is the use of electrical stimulation to activate the vagus nerve,which plays an important role in regulating glucose metabolism.Studies have shown that vagus nerve stimulation can improve insulin sensitivity and lower blood glucose levels in patients with T2DM.Gut-targeted therapies,such as probiotics and FMT,have shown potential for improving glycemic control and insulin sensitivity in T2DM patients.However,further research is needed to determine the optimal dose,duration,and safety of these therapies.展开更多
Objective: Obstructive sleep apnea-hypopnea syndrome (OSA) is a disease of obstructive apnea or hypopnea caused by a repeated partial or complete collapse of the upper airway during sleep. The inspiratory part of the ...Objective: Obstructive sleep apnea-hypopnea syndrome (OSA) is a disease of obstructive apnea or hypopnea caused by a repeated partial or complete collapse of the upper airway during sleep. The inspiratory part of the flow-volume curve (F-V curve) can be used as an auxiliary means to evaluate upper airway obstruction in adults. This study is to evaluate the ability of the F-V curve to predict the OSA and explore inspiratory indicators related to airway obstruction during sleep. Methods: There were 332 patients included in this cross-sectional study, who were accompanied by snoring, daytime sleepiness and other symptoms, with suspicion of OSA. According to the nocturnal polysomnography, the subjects were distributed into mild to moderate OSA group, severe OSA group and non-OSA group. A pulmonary function test was used to collect the subjects’ spirometry and F-V curves. Results: There was no significant difference in a variety of indices derived from the F-V curve between OSA and normal subjects, including 25% inspiratory flow rate, middle inspiratory flow rate, 75% inspiratory flow rate, peak flow rate, and forced inspiratory flow rate in the first second. The pulmonary function parameters were significantly correlated with the weight, age and sex of the subjects. Conclusion: These findings suggest that the inspiratory curve of pulmonary function cannot evaluate the upper airway abnormalities in patients with obstructive apnea-hypopnea syndrome.展开更多
Surface ground motion produced by underground blasts is significantly influenced by near-surface geological conditions.However,near-surface low-propagation velocity layers were always ignored in past analyses of groun...Surface ground motion produced by underground blasts is significantly influenced by near-surface geological conditions.However,near-surface low-propagation velocity layers were always ignored in past analyses of ground motions due to their thin thickness.With the rising concern about surface ground motions produced by the ascendant scale and frequentness of underground excavation and mining,close attention is gradually paid to ground blast vibrations.Therefore,systemic experiments were conducted and took seven months in an underground mine to clarify the variation of motion from underground rock to surface ground.The attenuation of surface ground peak particle velocities(PPVs)is compared to that in underground rock,and horizontal amplitudes are compared to vertical amplitudes.Differences between bedrock and surface ground vibrations are analyzed to illustrate the site effect of near-surface lower-propagation velocity layers.One-dimensional site response analysis is employed to quantify the influence of different geological profiles on surface ground vibrations.The experimental data and site response analysis allowed the following conclusions:(1)geological site effects mainly produce decreasing dominant frequency(DF)of surface ground vibrations;(2)the site amplification effect of blast vibration needs to be characterized by peak particle displacement(PPD);(3)shear waves(S-waves)begin to dominate and surface Rayleigh waves(R-waves)develop as blast-induced ground vibrations travel upward through rock and lower-velocity layers to the surface.The comparison of response relative displacement to a critical value is best to assess the potential for cracking on surface structures.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.42072309)the Knowledge Innovation Program of Wuhan-Basic Research(Grant No.2022020801010199)the Fundamental Research Funds for National University,China University of Geosciences(Wuhan)(Grant No.CUGDCJJ202217).
文摘In cold regions,the dynamic compressive strength(DCS)of rock damaged by freeze-thaw weathering significantly influences the stability of rock engineering.Nevertheless,testing the dynamic strength under freeze-thaw weathering conditions is often both time-consuming and expensive.Therefore,this study considers the effect of characteristic impedance on DCS and aims to quickly determine the DCS of frozen-thawed rocks through the application of machine-learning techniques.Initially,a database of DCS for frozen-thawed rocks,comprising 216 rock specimens,was compiled.Three external load parameters(freeze-thaw cycle number,confining pressure,and impact pressure)and two rock parameters(characteristic impedance and porosity)were selected as input variables,with DCS as the predicted target.This research optimized the kernel scale,penalty factor,and insensitive loss coefficient of the support vector regression(SVR)model using five swarm intelligent optimization algorithms,leading to the development of five hybrid models.In addition,a statistical DCS prediction equation using multiple linear regression techniques was developed.The performance of the prediction models was comprehensively evaluated using two error indexes and two trend indexes.A sensitivity analysis based on the cosine amplitude method has also been conducted.The results demonstrate that the proposed hybrid SVR-based models consistently provided accurate DCS predictions.Among these models,the SVR model optimized with the chameleon swarm algorithm exhibited the best performance,with metrics indicating its effectiveness,including root mean square error(RMSE)﹦3.9675,mean absolute error(MAE)﹦2.9673,coefficient of determination(R^(2))﹦0.98631,and variance accounted for(VAF)﹦98.634.This suggests that the chameleon swarm algorithm yielded the most optimal results for enhancing SVR models.Notably,impact pressure and characteristic impedance emerged as the two most influential parameters in DCS prediction.This research is anticipated to serve as a reliable reference for estimating the DCS of rocks subjected to freeze-thaw weathering.
基金funded by the National Natural Science Foundation of China(Grant No.51874350)the National Natural Science Foundation of China(Grant No.52304127)+2 种基金the Fundamental Research Funds for the Central Universities of Central South University(Grant No.2020zzts200)the Science Foundation of the Fuzhou University(Grant No.511229)Fuzhou University Testing Fund of Precious Apparatus(Grant No.2024T040).
文摘The denoising of microseismic signals is a prerequisite for subsequent analysis and research.In this research,a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm(BWOA)optimized VariationalMode Decomposition(VMD)jointWavelet Threshold Denoising(WTD)algorithm(BVW)is proposed.The BVW algorithm integrates VMD and WTD,both of which are optimized by BWOA.Specifically,this algorithm utilizes VMD to decompose the microseismic signal to be denoised into several Band-Limited IntrinsicMode Functions(BLIMFs).Subsequently,these BLIMFs whose correlation coefficients with the microseismic signal to be denoised are higher than a threshold are selected as the effective mode functions,and the effective mode functions are denoised using WTD to filter out the residual low-and intermediate-frequency noise.Finally,the denoised microseismic signal is obtained through reconstruction.The ideal values of VMD parameters and WTD parameters are acquired by searching with BWOA to achieve the best VMD decomposition performance and solve the problem of relying on experience and requiring a large workload in the application of the WTD algorithm.The outcomes of simulated experiments indicate that this algorithm is capable of achieving good denoising performance under noise of different intensities,and the denoising performance is significantly better than the commonly used VMD and Empirical Mode Decomposition(EMD)algorithms.The BVW algorithm is more efficient in filtering noise,the waveform after denoising is smoother,the amplitude of the waveform is the closest to the original signal,and the signal-to-noise ratio(SNR)and the root mean square error after denoising are more satisfying.The case based on Fankou Lead-Zinc Mine shows that for microseismic signals with different intensities of noise monitored on-site,compared with VMD and EMD,the BVW algorithm ismore efficient in filtering noise,and the SNR after denoising is higher.
基金supported by National Natural Science Foundation of China (No. 12075276)partly by the Comprehensive Research Facility for Fusion Technology Program of China (No. 2018000052-73-01-001228)。
文摘In recent decades, tokamak discharges with zero total toroidal current have been reported in tokamak experiments, and this is one of the key problems in alternating current(AC) operations.An efficient free-boundary equilibrium code is developed to investigate such advanced tokamak discharges with current reversal equilibrium configuration. The calculation results show that the reversal current equilibrium can maintain finite pressure and also has considerable effects on the position of the X-point and the magnetic separatrix shape, and hence also on the position of the strike point on the divertor plates, which is extremely useful for magnetic design, MHD stability analysis, and experimental data analysis etc. for the AC plasma current operation on tokamaks.
基金Supported by the National Natural Science Foundation of China,No.82074532,No.82305376,and No.81873238the Open Projects of the Discipline of Chinese Medicine of Nanjing University of Chinese Medicine supported by the Subject of Academic Priority Discipline of Jiangsu Higher Education Institutions,No.ZYX03KF012the Postgraduate Research&Practice Innovation Program of Jiangsu Province,No.KYCX22_1963.
文摘Type 2 diabetes mellitus(T2DM)is a chronic metabolic disorder characterized by hyperglycemia and insulin resistance.The global prevalence of T2DM has reached epidemic proportions,affecting approximately 463 million adults worldwide in 2019.Current treatments for T2DM include lifestyle modifications,oral antidiabetic agents,and insulin therapy.However,these therapies may carry side effects and fail to achieve optimal glycemic control in some patients.Therefore,there is a growing interest in the role of gut microbiota and more gut-targeted therapies in the management of T2DM.The gut microbiota,which refers to the community of microorganisms that inhabit the human gut,has been shown to play a crucial role in the regulation of glucose metabolism and insulin sensitivity.Alterations in gut microbiota composition and diversity have been observed in T2DM patients,with a reduction in beneficial bacteria and an increase in pathogenic bacteria.This dysbiosis may contribute to the pathogenesis of the disease by promoting inflammation and impairing gut barrier function.Several gut-targeted therapies have been developed to modulate the gut microbiota and improve glycemic control in T2DM.One potential approach is the use of probio-tics,which are live microorganisms that confer health benefits to the host when administered in adequate amounts.Several randomized controlled trials have demonstrated that certain probiotics,such as Lactobacillus and Bifidobacterium species,can improve glycemic control and insulin sensitivity in T2DM patients.Mechanisms may include the production of short-chain fatty acids,the improvement of gut barrier function,and the reduction of inflammation.Another gut-targeted therapy is fecal microbiota transplantation(FMT),which involves the transfer of fecal material from a healthy donor to a recipient.FMT has been used successfully in the treatment of Clostridioides difficile infection and is now being investigated as a potential therapy for T2DM.A recent randomized controlled trial showed that FMT from lean donors improved glucose metabolism and insulin sensitivity in T2DM patients with obesity.However,FMT carries potential risks,including transmission of infectious agents and alterations in the recipient's gut microbiota that may be undesirable.In addition to probiotics and FMT,other gut-targeted therapies are being investigated for the management of T2DM,such as prebiotics,synbiotics,and postbiotics.Prebiotics are dietary fibers that promote the growth of beneficial gut bacteria,while synbiotics combine probiotics and prebiotics.Postbiotics refer to the metabolic products of probiotics that may have beneficial effects on the host.The NIH SPARC program,or the Stimulating Peripheral Activity to Relieve Conditions,is a research initiative aimed at developing new therapies for a variety of health conditions,including T2DM.The SPARC program focuses on using electrical stimulation to activate peripheral nerves and organs,in order to regulate glucose levels in the body.The goal of this approach is to develop targeted,non-invasive therapies that can help patients better manage their diabetes.One promising area of research within the SPARC program is the use of electrical stimulation to activate the vagus nerve,which plays an important role in regulating glucose metabolism.Studies have shown that vagus nerve stimulation can improve insulin sensitivity and lower blood glucose levels in patients with T2DM.Gut-targeted therapies,such as probiotics and FMT,have shown potential for improving glycemic control and insulin sensitivity in T2DM patients.However,further research is needed to determine the optimal dose,duration,and safety of these therapies.
文摘Objective: Obstructive sleep apnea-hypopnea syndrome (OSA) is a disease of obstructive apnea or hypopnea caused by a repeated partial or complete collapse of the upper airway during sleep. The inspiratory part of the flow-volume curve (F-V curve) can be used as an auxiliary means to evaluate upper airway obstruction in adults. This study is to evaluate the ability of the F-V curve to predict the OSA and explore inspiratory indicators related to airway obstruction during sleep. Methods: There were 332 patients included in this cross-sectional study, who were accompanied by snoring, daytime sleepiness and other symptoms, with suspicion of OSA. According to the nocturnal polysomnography, the subjects were distributed into mild to moderate OSA group, severe OSA group and non-OSA group. A pulmonary function test was used to collect the subjects’ spirometry and F-V curves. Results: There was no significant difference in a variety of indices derived from the F-V curve between OSA and normal subjects, including 25% inspiratory flow rate, middle inspiratory flow rate, 75% inspiratory flow rate, peak flow rate, and forced inspiratory flow rate in the first second. The pulmonary function parameters were significantly correlated with the weight, age and sex of the subjects. Conclusion: These findings suggest that the inspiratory curve of pulmonary function cannot evaluate the upper airway abnormalities in patients with obstructive apnea-hypopnea syndrome.
基金supported by Natural Science Foundation of Jiangsu Province,China(Grant No.BK20220975)the National Natural Science Foundation of China(Grant Nos.51874350 and 41807259).
文摘Surface ground motion produced by underground blasts is significantly influenced by near-surface geological conditions.However,near-surface low-propagation velocity layers were always ignored in past analyses of ground motions due to their thin thickness.With the rising concern about surface ground motions produced by the ascendant scale and frequentness of underground excavation and mining,close attention is gradually paid to ground blast vibrations.Therefore,systemic experiments were conducted and took seven months in an underground mine to clarify the variation of motion from underground rock to surface ground.The attenuation of surface ground peak particle velocities(PPVs)is compared to that in underground rock,and horizontal amplitudes are compared to vertical amplitudes.Differences between bedrock and surface ground vibrations are analyzed to illustrate the site effect of near-surface lower-propagation velocity layers.One-dimensional site response analysis is employed to quantify the influence of different geological profiles on surface ground vibrations.The experimental data and site response analysis allowed the following conclusions:(1)geological site effects mainly produce decreasing dominant frequency(DF)of surface ground vibrations;(2)the site amplification effect of blast vibration needs to be characterized by peak particle displacement(PPD);(3)shear waves(S-waves)begin to dominate and surface Rayleigh waves(R-waves)develop as blast-induced ground vibrations travel upward through rock and lower-velocity layers to the surface.The comparison of response relative displacement to a critical value is best to assess the potential for cracking on surface structures.
