Investors usually require premiums to compensate those components of risk that cannot be diversified away. Investors＇ risk premiums is changing with the business cycles. In this paper we study the CCAPM allowing for ...Investors usually require premiums to compensate those components of risk that cannot be diversified away. Investors＇ risk premiums is changing with the business cycles. In this paper we study the CCAPM allowing for the time-varying beta. The timevarying betas are estimated from GARCH model. From the estimation results, we can see that the systematic risk coefficient betas of certain industry change when the volatility changes.展开更多
This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eli...This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.展开更多
The conversion of acetone derived from biomass to isobutene has attracted extensive attentions.In comparison with Brønsted acidic catalyst,Lewis acidic catalyst could exhibit a better catalytic performance with a...The conversion of acetone derived from biomass to isobutene has attracted extensive attentions.In comparison with Brønsted acidic catalyst,Lewis acidic catalyst could exhibit a better catalytic performance with a higher isobutene selectivity.However,the catalyst stability remains a key problem for the long-running acetone conversion and the reasons for catalyst deactivation are poorly understood up to now.Herein,the deactivation mechanism of Lewis acidic Y/Beta catalyst during the acetone to isobutene conversion was investigated by various characterization techniques,including acetone-temperature-programmed surface reaction,gas chromatography-mass spectrometry,in situ ultraviolet-visible,and ^(13)C cross polarization magic angle spinning nuclear magnetic resonance spectroscopy.A successive aldol condensation and cyclization were observed as the main side-reactions during the acetone conversion at Lewis acidic Y sites.In comparison with the low reaction temperature,a rapid formation and accumulation of the larger cyclic unsaturated aldehydes/ketones and aromatics could be observed,and which could strongly adsorb on the Lewis acidic sites,and thus cause the catalyst deactivation eventually.After a simple calcination,the coke deposits could be easily removed and the catalytic activity could be well restored.展开更多
Ce-encapsulated Beta zeolite was synthesized by a one-pot hydrothermal method with citric acid complexing Ce in the absence of Na species.Additional citric acid can effectively prevent the deposition of Ce species dur...Ce-encapsulated Beta zeolite was synthesized by a one-pot hydrothermal method with citric acid complexing Ce in the absence of Na species.Additional citric acid can effectively prevent the deposition of Ce species during the hydrothermal synthesis of zeolites,leading to uniform distribution of Ce cluster in the framework of Beta zeolites.Moreover,the sodium-free synthesis system resulted that the Brønsted acid sites were mainly located on the straight channels and external surface of Beta zeolites,improving the utilization of Brønsted acid sites.In addition,Ce encapsulated Beta zeolites showed enhanced activity and robust stability in the alkylation of benzene with 1-dodecene based on the synergistic effect between Ce species and Brønsted acid sites,which pave the way for its practical application in the production of alkylbenzene.展开更多
Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems,such as relatively ideal speed conditions and sample conditions.In engineering practice,the rotational speed of the mac...Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems,such as relatively ideal speed conditions and sample conditions.In engineering practice,the rotational speed of the machine is often transient and time-varying,which makes the sample annotation increasingly expensive.Meanwhile,the number of samples collected from different health states is often unbalanced.To deal with the above challenges,a complementary-label(CL)adversarial domain adaptation fault diagnosis network(CLADAN)is proposed under time-varying rotational speed and weakly-supervised conditions.In the weakly supervised learning condition,machine prior information is used for sample annotation via cost-friendly complementary label learning.A diagnosticmodel learning strategywith discretized category probabilities is designed to avoidmulti-peak distribution of prediction results.In adversarial training process,we developed virtual adversarial regularization(VAR)strategy,which further enhances the robustness of the model by adding adversarial perturbations in the target domain.Comparative experiments on two case studies validated the superior performance of the proposed method.展开更多
In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems...In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.展开更多
Hybrid precoding is considered as a promising low-cost technique for millimeter wave(mm-wave)massive Multi-Input Multi-Output(MIMO)systems.In this work,referring to the time-varying propagation circumstances,with semi...Hybrid precoding is considered as a promising low-cost technique for millimeter wave(mm-wave)massive Multi-Input Multi-Output(MIMO)systems.In this work,referring to the time-varying propagation circumstances,with semi-supervised Incremental Learning(IL),we propose an online hybrid beamforming scheme.Firstly,given the constraint of constant modulus on analog beamformer and combiner,we propose a new broadnetwork-based structure for the design model of hybrid beamforming.Compared with the existing network structure,the proposed network structure can achieve better transmission performance and lower complexity.Moreover,to enhance the efficiency of IL further,by combining the semi-supervised graph with IL,we propose a hybrid beamforming scheme based on chunk-by-chunk semi-supervised learning,where only few transmissions are required to calculate the label and all other unlabelled transmissions would also be put into a training data chunk.Unlike the existing single-by-single approach where transmissions during the model update are not taken into the consideration of model update,all transmissions,even the ones during the model update,would make contributions to model update in the proposed method.During the model update,the amount of unlabelled transmissions is very large and they also carry some information,the prediction performance can be enhanced to some extent by these unlabelled channel data.Simulation results demonstrate the spectral efficiency of the proposed method outperforms that of the existing single-by-single approach.Besides,we prove the general complexity of the proposed method is lower than that of the existing approach and give the condition under which its absolute complexity outperforms that of the existing approach.展开更多
Introduction: Enterobacteriaceae causing urinary tract infections (UTI) have developed resistance to the commonly used antibiotics due to emergence of Extended Spectrum Beta-Lactamases (ESBLs) and Carbapenamase produc...Introduction: Enterobacteriaceae causing urinary tract infections (UTI) have developed resistance to the commonly used antibiotics due to emergence of Extended Spectrum Beta-Lactamases (ESBLs) and Carbapenamase producing Enterobactericeae which are a public health problem worldwide. This study aims to determine the prevalence and characterize ESBLs and carbapenamase producing Enterobactericeae. Method: A cross-sectional study was carried out in Gertrude’s Children’s Hospital, Nairobi. 238 urine samples were collected from patients with urinary symptoms attending the outpatient department within the period 2020-2021. The urine were examined macroscopically and microscopically. Identification and antimicrobial susceptibility testing were done using VITEK® 2 Compact system (BioMérieux). Double disc synergy test and modified hodge tests were done as confirmatory tests for ESBLs and Carbapenamase phenotypes respectively. Polymerase Chain Reaction was used for the detection of blaCTX-M, blaTEM, blaSHV, blaKPC and blaOXA-48 genes. Results: From the 238 children sampled the prevalence of UTI caused by Enterobactericeae was 22.3%. The Enterobacteriaceae species isolated were Escherichia coli (84.9%), Klebsiella pneumoniae (5.66%), Proteus mirabillis (5.66%), Enterobacter aerogenes (1.89%) and Morganella morganii (1.89%). The isolated species were resistant to ampicillin. Meropenem had the highest susceptibility. Only E. coli species had the ESBLs (26.4%) and carbapenamase (1.9%) phenotypes. 100% had BlaCTX-M while 50% had blaTEM resistant gene. There was a significant association (p Conclusion: Ampicillin resistance resulted to use of alternative drugs and Meropenem was the drug of choice where increased resistance to the recommended drugs was noted. Further research on resistant genes is recommended.展开更多
文摘Investors usually require premiums to compensate those components of risk that cannot be diversified away. Investors＇ risk premiums is changing with the business cycles. In this paper we study the CCAPM allowing for the time-varying beta. The timevarying betas are estimated from GARCH model. From the estimation results, we can see that the systematic risk coefficient betas of certain industry change when the volatility changes.
基金the National Natural Science Foundation of China(62203356)Fundamental Research Funds for the Central Universities of China(31020210502002)。
文摘This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.
文摘The conversion of acetone derived from biomass to isobutene has attracted extensive attentions.In comparison with Brønsted acidic catalyst,Lewis acidic catalyst could exhibit a better catalytic performance with a higher isobutene selectivity.However,the catalyst stability remains a key problem for the long-running acetone conversion and the reasons for catalyst deactivation are poorly understood up to now.Herein,the deactivation mechanism of Lewis acidic Y/Beta catalyst during the acetone to isobutene conversion was investigated by various characterization techniques,including acetone-temperature-programmed surface reaction,gas chromatography-mass spectrometry,in situ ultraviolet-visible,and ^(13)C cross polarization magic angle spinning nuclear magnetic resonance spectroscopy.A successive aldol condensation and cyclization were observed as the main side-reactions during the acetone conversion at Lewis acidic Y sites.In comparison with the low reaction temperature,a rapid formation and accumulation of the larger cyclic unsaturated aldehydes/ketones and aromatics could be observed,and which could strongly adsorb on the Lewis acidic sites,and thus cause the catalyst deactivation eventually.After a simple calcination,the coke deposits could be easily removed and the catalytic activity could be well restored.
基金supported by the National Natural Science Foundation of China(22278090,21978055)Natural Science Foundation of Guangdong Province,China(2022A1515012088)the Science and Technology Planning Project of Guangdong Province,China(2022A0505030073,2022A0505030013).
文摘Ce-encapsulated Beta zeolite was synthesized by a one-pot hydrothermal method with citric acid complexing Ce in the absence of Na species.Additional citric acid can effectively prevent the deposition of Ce species during the hydrothermal synthesis of zeolites,leading to uniform distribution of Ce cluster in the framework of Beta zeolites.Moreover,the sodium-free synthesis system resulted that the Brønsted acid sites were mainly located on the straight channels and external surface of Beta zeolites,improving the utilization of Brønsted acid sites.In addition,Ce encapsulated Beta zeolites showed enhanced activity and robust stability in the alkylation of benzene with 1-dodecene based on the synergistic effect between Ce species and Brønsted acid sites,which pave the way for its practical application in the production of alkylbenzene.
基金Shanxi Scholarship Council of China(2022-141)Fundamental Research Program of Shanxi Province(202203021211096).
文摘Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems,such as relatively ideal speed conditions and sample conditions.In engineering practice,the rotational speed of the machine is often transient and time-varying,which makes the sample annotation increasingly expensive.Meanwhile,the number of samples collected from different health states is often unbalanced.To deal with the above challenges,a complementary-label(CL)adversarial domain adaptation fault diagnosis network(CLADAN)is proposed under time-varying rotational speed and weakly-supervised conditions.In the weakly supervised learning condition,machine prior information is used for sample annotation via cost-friendly complementary label learning.A diagnosticmodel learning strategywith discretized category probabilities is designed to avoidmulti-peak distribution of prediction results.In adversarial training process,we developed virtual adversarial regularization(VAR)strategy,which further enhances the robustness of the model by adding adversarial perturbations in the target domain.Comparative experiments on two case studies validated the superior performance of the proposed method.
基金partially supported by the National Natural Science Foundation of China(52375238)Science and Technology Program of Guangzhou(202201020213,202201020193,202201010399)GZHU-HKUST Joint Research Fund(YH202109).
文摘In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.
基金supported by the National Science Foundation of China under Grant No.62101467.
文摘Hybrid precoding is considered as a promising low-cost technique for millimeter wave(mm-wave)massive Multi-Input Multi-Output(MIMO)systems.In this work,referring to the time-varying propagation circumstances,with semi-supervised Incremental Learning(IL),we propose an online hybrid beamforming scheme.Firstly,given the constraint of constant modulus on analog beamformer and combiner,we propose a new broadnetwork-based structure for the design model of hybrid beamforming.Compared with the existing network structure,the proposed network structure can achieve better transmission performance and lower complexity.Moreover,to enhance the efficiency of IL further,by combining the semi-supervised graph with IL,we propose a hybrid beamforming scheme based on chunk-by-chunk semi-supervised learning,where only few transmissions are required to calculate the label and all other unlabelled transmissions would also be put into a training data chunk.Unlike the existing single-by-single approach where transmissions during the model update are not taken into the consideration of model update,all transmissions,even the ones during the model update,would make contributions to model update in the proposed method.During the model update,the amount of unlabelled transmissions is very large and they also carry some information,the prediction performance can be enhanced to some extent by these unlabelled channel data.Simulation results demonstrate the spectral efficiency of the proposed method outperforms that of the existing single-by-single approach.Besides,we prove the general complexity of the proposed method is lower than that of the existing approach and give the condition under which its absolute complexity outperforms that of the existing approach.
文摘Introduction: Enterobacteriaceae causing urinary tract infections (UTI) have developed resistance to the commonly used antibiotics due to emergence of Extended Spectrum Beta-Lactamases (ESBLs) and Carbapenamase producing Enterobactericeae which are a public health problem worldwide. This study aims to determine the prevalence and characterize ESBLs and carbapenamase producing Enterobactericeae. Method: A cross-sectional study was carried out in Gertrude’s Children’s Hospital, Nairobi. 238 urine samples were collected from patients with urinary symptoms attending the outpatient department within the period 2020-2021. The urine were examined macroscopically and microscopically. Identification and antimicrobial susceptibility testing were done using VITEK® 2 Compact system (BioMérieux). Double disc synergy test and modified hodge tests were done as confirmatory tests for ESBLs and Carbapenamase phenotypes respectively. Polymerase Chain Reaction was used for the detection of blaCTX-M, blaTEM, blaSHV, blaKPC and blaOXA-48 genes. Results: From the 238 children sampled the prevalence of UTI caused by Enterobactericeae was 22.3%. The Enterobacteriaceae species isolated were Escherichia coli (84.9%), Klebsiella pneumoniae (5.66%), Proteus mirabillis (5.66%), Enterobacter aerogenes (1.89%) and Morganella morganii (1.89%). The isolated species were resistant to ampicillin. Meropenem had the highest susceptibility. Only E. coli species had the ESBLs (26.4%) and carbapenamase (1.9%) phenotypes. 100% had BlaCTX-M while 50% had blaTEM resistant gene. There was a significant association (p Conclusion: Ampicillin resistance resulted to use of alternative drugs and Meropenem was the drug of choice where increased resistance to the recommended drugs was noted. Further research on resistant genes is recommended.
