Malaria is a significant global health challenge.This devastating disease continues to affect millions,especially in tropical regions.It is caused by Plasmodium parasites transmitted by female Anopheles mosquitoes.Thi...Malaria is a significant global health challenge.This devastating disease continues to affect millions,especially in tropical regions.It is caused by Plasmodium parasites transmitted by female Anopheles mosquitoes.This study introduces a nonlinear mathematical model for examining the transmission dynamics of malaria,incorporating both human and mosquito populations.We aim to identify the key factors driving the endemic spread of malaria,determine feasible solutions,and provide insights that lead to the development of effective prevention and management strategies.We derive the basic reproductive number employing the next-generation matrix approach and identify the disease-free and endemic equilibrium points.Stability analyses indicate that the disease-free equilibrium is locally and globally stable when the reproductive number is below one,whereas an endemic equilibrium persists when this threshold is exceeded.Sensitivity analysis identifies the most influential mosquito-related parameters,particularly the bite rate and mosquito mortality,in controlling the spread of malaria.Furthermore,we extend our model to include a treatment compartment and three disease-preventive control variables such as antimalaria drug treatments,use of larvicides,and the use of insecticide-treated mosquito nets for optimal control analysis.The results show that optimal use of mosquito nets,use of larvicides for mosquito population control,and treatment can lower the basic reproduction number and control malaria transmission with minimal intervention costs.The analysis of disease control strategies and findings offers valuable information for policymakers in designing cost-effective strategies to combat malaria.展开更多
The paper primarily focuses on social safety nets and their effectiveness in poverty alleviation.Social Safety Net(SSN)programs pertain to social service initiatives aimed at providing temporary assistance to individu...The paper primarily focuses on social safety nets and their effectiveness in poverty alleviation.Social Safety Net(SSN)programs pertain to social service initiatives aimed at providing temporary assistance to individuals or groups facing vulnerabilities or unexpected hardships,such as those with lower incomes.Poverty poses a significant obstacle to the progress of social development,and its impacts are worsened by various factors including insecurity,frequent flooding,and droughts in Somalia.A total of 342 households in the Banadir region of Somalia were interviewed for the social safety nets(SSN)study.Data collection in the study was facilitated through the utilization of Kobo Toolbox,while the data analysis was conducted using EViews v.12.The results obtained from the ADP and PP tests indicated that all variables exhibited stationarity at the level.The Impact Assessment(IA)reveals a positive correlation with Household Income and Poverty Indices(HIPI),suggesting a risk of dependency without a strategic exit strategy,potentially leading to a 26%increase in poverty levels.A well-executed Program Implementation and Design(PID)can result in a 33%increase in income and poverty indices.Recipients perceive the Social Safety Net(PSSN)as reducing poverty and increasing income by 11%.Therefore,the study recommends integrating beneficiaries into the urban economy through sustainable livelihood options.Finally,the Somali government should prioritize the implementation of sustainable livelihood programs to mitigate dependency and alleviate poverty among SSN beneficiaries.展开更多
Global Navigation Satellite System(GNSS)-based continuous and accurate train positioning is one of the key technologies for advanced train operations such as train virtual coupling.However,GNSS-based train positioning...Global Navigation Satellite System(GNSS)-based continuous and accurate train positioning is one of the key technologies for advanced train operations such as train virtual coupling.However,GNSS-based train positioning faces significant challenges in real-world scenarios due to environmental complexities and signal interferences.Considering this issue,this paper presents an approach for modeling and performance analysis of GNSS-based train positioning systems using Colored Petri Nets(CPNs).By systematically modeling the GNSS signal reception and processing process,the performance of the positioning system under various environment scenarios is evaluated.The system model integrates three types of interference signals(i.e.,Amplitude Modulation(AM)signals,Frequency Modulation(FM)signals,and pulse signals)while incorporating environmental factors such as terrain obstructions and tunnel shielding.Additionally,the Extended Kalman Filter(EKF)algorithm is employed to process GNSS observation data,providing accurate train position estimations.The simulation results demonstrate that signal interferences and complex environmental conditions significantly affect the GNSS-based positioning accuracy.This study offers a comprehensive framework for evaluating the performance of GNSS-based train positioning systems in different scenarios,highlighting critical factors that influence positioning accuracy and stability.展开更多
Acute lung injury(ALI)linked to sepsis has a high mortality rate,with limited treatment options available.In recent studies,medical ozone has shown the potential to alleviate inflammation and infection.Here,we aimed t...Acute lung injury(ALI)linked to sepsis has a high mortality rate,with limited treatment options available.In recent studies,medical ozone has shown the potential to alleviate inflammation and infection.Here,we aimed to evaluate therapeutic potential of medical ozone in a mouse model of the sepsis-induced ALI by measuring behavioral assessments,lung function,and blood flow.Protein levels were quantified by Western blotting.In vitro,we performed experiments on bone marrow-derived macrophages(BMDMs)to investigate the effect of adenosine monophosphate(AMP)-activated protein kinase(AMPK)inhibitors and agonists on their phagocytic activity.The results showed that medical ozone significantly improved the survival rate,ameliorated lung injury,and enhanced lung function and limb microcirculation in mice with ALI.Notably,medical ozone inhibited the formation of neutrophil extracellular traps(NETs),a crucial factor in the ALI development.Additionally,medical ozone counteracted the elevated levels of tissue factor,matrix metalloproteinase-9,and interleukin-1β.In the ALI mice,the effects of ozone were abolished,and BMDMs showed an impaired capacity to engulf NETs following the Sr-a1 knockout.Under normal physiological conditions,the administration of an AMPK antagonist showed similar effects on the Sr-a1 knockout,significantly inhibiting the phagocytosis of NETs by BMDMs.In contrast,AMPK agonists enhanced this phagocytic process.In conclusion,medical ozone may alleviate the sepsis-induced lung injury through the AMPK/SR-A1 pathway,thereby enhancing the phagocytosis of NETs by macrophages.展开更多
This paper focuses on the intrusion classification of huge amounts of data in a network intrusion detection system. An intrusion detection model based on deep belief nets （DBN） is proposed to conduct intrusion detec...This paper focuses on the intrusion classification of huge amounts of data in a network intrusion detection system. An intrusion detection model based on deep belief nets （DBN） is proposed to conduct intrusion detection,and the principles regarding DBN are discussed.The DBN is composed of a multiple unsupervised restricted Boltzmann machine （RBM） and a supervised back propagation （BP）network.First,the DBN in the proposed model is pre-trained in a fast and greedy way,and each RBM is trained by the contrastive divergence algorithm.Secondly,the whole network is fine-tuned by the supervised BP algorithm,which is employed for classifying the low-dimensional features of the intrusion data generated by the last RBM layer simultaneously.The experimental results on the KDD CUP 1999 dataset demonstrate that the DBN using the RBM network with three or more layers outperforms the self-organizing maps （SOM）and neural network （NN）in intrusion classification.Therefore,the DBN is an efficient approach for intrusion detection in high-dimensional space.展开更多
Traditional models for project management have not adequately incorporated a number of factors that are important for resource allocation. This paper proposed a unified timed Petri net model in which scheduling and pl...Traditional models for project management have not adequately incorporated a number of factors that are important for resource allocation. This paper proposed a unified timed Petri net model in which scheduling and planning were collectively carried out to take full advantages of the flexibility of the FMS. Through the lens of system theory, two types of resources were distinguished: major role and auxiliary role, and the major role was used to construct the FMS' Petri net. The method simplified the Petri net's construction and gave a clear flow chart for scheduling. Hence, the auxiliary resource allocation could be easily carried out according to the schedule, which was proposed by heuristic search algorithm. At last, the efficacy of the Petri net model for online scheduling in a resource constrained environment was discussed.展开更多
Aim To present a quantitative method for structural complexity analysis and evaluation of information systems. Methods Based on Petri net modeling and analysis techniques and with the aid of mathematical tools in ge...Aim To present a quantitative method for structural complexity analysis and evaluation of information systems. Methods Based on Petri net modeling and analysis techniques and with the aid of mathematical tools in general net theory(GNT), a quantitative method for structure description and analysis of information systems was introduced. Results The structural complexity index and two related factors, i.e. element complexity factor and connection complexity factor were defined, and the relations between them and the parameters of the Petri net based model of the system were derived. Application example was presented. Conclusion The proposed method provides a theoretical basis for quantitative analysis and evaluation of the structural complexity and can be applied in the general planning and design processes of the information systems.展开更多
基金supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia[Grant No.KFU252959].
文摘Malaria is a significant global health challenge.This devastating disease continues to affect millions,especially in tropical regions.It is caused by Plasmodium parasites transmitted by female Anopheles mosquitoes.This study introduces a nonlinear mathematical model for examining the transmission dynamics of malaria,incorporating both human and mosquito populations.We aim to identify the key factors driving the endemic spread of malaria,determine feasible solutions,and provide insights that lead to the development of effective prevention and management strategies.We derive the basic reproductive number employing the next-generation matrix approach and identify the disease-free and endemic equilibrium points.Stability analyses indicate that the disease-free equilibrium is locally and globally stable when the reproductive number is below one,whereas an endemic equilibrium persists when this threshold is exceeded.Sensitivity analysis identifies the most influential mosquito-related parameters,particularly the bite rate and mosquito mortality,in controlling the spread of malaria.Furthermore,we extend our model to include a treatment compartment and three disease-preventive control variables such as antimalaria drug treatments,use of larvicides,and the use of insecticide-treated mosquito nets for optimal control analysis.The results show that optimal use of mosquito nets,use of larvicides for mosquito population control,and treatment can lower the basic reproduction number and control malaria transmission with minimal intervention costs.The analysis of disease control strategies and findings offers valuable information for policymakers in designing cost-effective strategies to combat malaria.
文摘The paper primarily focuses on social safety nets and their effectiveness in poverty alleviation.Social Safety Net(SSN)programs pertain to social service initiatives aimed at providing temporary assistance to individuals or groups facing vulnerabilities or unexpected hardships,such as those with lower incomes.Poverty poses a significant obstacle to the progress of social development,and its impacts are worsened by various factors including insecurity,frequent flooding,and droughts in Somalia.A total of 342 households in the Banadir region of Somalia were interviewed for the social safety nets(SSN)study.Data collection in the study was facilitated through the utilization of Kobo Toolbox,while the data analysis was conducted using EViews v.12.The results obtained from the ADP and PP tests indicated that all variables exhibited stationarity at the level.The Impact Assessment(IA)reveals a positive correlation with Household Income and Poverty Indices(HIPI),suggesting a risk of dependency without a strategic exit strategy,potentially leading to a 26%increase in poverty levels.A well-executed Program Implementation and Design(PID)can result in a 33%increase in income and poverty indices.Recipients perceive the Social Safety Net(PSSN)as reducing poverty and increasing income by 11%.Therefore,the study recommends integrating beneficiaries into the urban economy through sustainable livelihood options.Finally,the Somali government should prioritize the implementation of sustainable livelihood programs to mitigate dependency and alleviate poverty among SSN beneficiaries.
基金supported by the National Key Research and Development Program of China(2023YFB3907300)the Fundamental Research Funds for the Central Universities(2024JBMC002)the National Natural Science Foundation of China(T2222015,U2268206).
文摘Global Navigation Satellite System(GNSS)-based continuous and accurate train positioning is one of the key technologies for advanced train operations such as train virtual coupling.However,GNSS-based train positioning faces significant challenges in real-world scenarios due to environmental complexities and signal interferences.Considering this issue,this paper presents an approach for modeling and performance analysis of GNSS-based train positioning systems using Colored Petri Nets(CPNs).By systematically modeling the GNSS signal reception and processing process,the performance of the positioning system under various environment scenarios is evaluated.The system model integrates three types of interference signals(i.e.,Amplitude Modulation(AM)signals,Frequency Modulation(FM)signals,and pulse signals)while incorporating environmental factors such as terrain obstructions and tunnel shielding.Additionally,the Extended Kalman Filter(EKF)algorithm is employed to process GNSS observation data,providing accurate train position estimations.The simulation results demonstrate that signal interferences and complex environmental conditions significantly affect the GNSS-based positioning accuracy.This study offers a comprehensive framework for evaluating the performance of GNSS-based train positioning systems in different scenarios,highlighting critical factors that influence positioning accuracy and stability.
基金supported by the National Natural Science Foundation of China(Grant Nos.82271252,82204542,and 81971047)the Lianyungang Science and Technology Program Project(Grant Nos.SF2122 and SF2214)+2 种基金the Scientific Research Project of Jiangsu Provincial Health Commission(Grant No.Z2021066)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Grant No.21KJB310019)the Open Project of Jiangsu Province Key Laboratory of Anesthesiology,Xuzhou Medical University(Grant No.XZSYSKF2021014).
文摘Acute lung injury(ALI)linked to sepsis has a high mortality rate,with limited treatment options available.In recent studies,medical ozone has shown the potential to alleviate inflammation and infection.Here,we aimed to evaluate therapeutic potential of medical ozone in a mouse model of the sepsis-induced ALI by measuring behavioral assessments,lung function,and blood flow.Protein levels were quantified by Western blotting.In vitro,we performed experiments on bone marrow-derived macrophages(BMDMs)to investigate the effect of adenosine monophosphate(AMP)-activated protein kinase(AMPK)inhibitors and agonists on their phagocytic activity.The results showed that medical ozone significantly improved the survival rate,ameliorated lung injury,and enhanced lung function and limb microcirculation in mice with ALI.Notably,medical ozone inhibited the formation of neutrophil extracellular traps(NETs),a crucial factor in the ALI development.Additionally,medical ozone counteracted the elevated levels of tissue factor,matrix metalloproteinase-9,and interleukin-1β.In the ALI mice,the effects of ozone were abolished,and BMDMs showed an impaired capacity to engulf NETs following the Sr-a1 knockout.Under normal physiological conditions,the administration of an AMPK antagonist showed similar effects on the Sr-a1 knockout,significantly inhibiting the phagocytosis of NETs by BMDMs.In contrast,AMPK agonists enhanced this phagocytic process.In conclusion,medical ozone may alleviate the sepsis-induced lung injury through the AMPK/SR-A1 pathway,thereby enhancing the phagocytosis of NETs by macrophages.
基金The National Key Technology R&D Program during the 12th Five-Year Plan Period(No.2013BAK01B02)the National Natural Science Foundation of China(No.61373176)the Scientific Research Projects of Shaanxi Educational Committee(No.14JK1693)
文摘This paper focuses on the intrusion classification of huge amounts of data in a network intrusion detection system. An intrusion detection model based on deep belief nets （DBN） is proposed to conduct intrusion detection,and the principles regarding DBN are discussed.The DBN is composed of a multiple unsupervised restricted Boltzmann machine （RBM） and a supervised back propagation （BP）network.First,the DBN in the proposed model is pre-trained in a fast and greedy way,and each RBM is trained by the contrastive divergence algorithm.Secondly,the whole network is fine-tuned by the supervised BP algorithm,which is employed for classifying the low-dimensional features of the intrusion data generated by the last RBM layer simultaneously.The experimental results on the KDD CUP 1999 dataset demonstrate that the DBN using the RBM network with three or more layers outperforms the self-organizing maps （SOM）and neural network （NN）in intrusion classification.Therefore,the DBN is an efficient approach for intrusion detection in high-dimensional space.
文摘Traditional models for project management have not adequately incorporated a number of factors that are important for resource allocation. This paper proposed a unified timed Petri net model in which scheduling and planning were collectively carried out to take full advantages of the flexibility of the FMS. Through the lens of system theory, two types of resources were distinguished: major role and auxiliary role, and the major role was used to construct the FMS' Petri net. The method simplified the Petri net's construction and gave a clear flow chart for scheduling. Hence, the auxiliary resource allocation could be easily carried out according to the schedule, which was proposed by heuristic search algorithm. At last, the efficacy of the Petri net model for online scheduling in a resource constrained environment was discussed.
文摘Aim To present a quantitative method for structural complexity analysis and evaluation of information systems. Methods Based on Petri net modeling and analysis techniques and with the aid of mathematical tools in general net theory(GNT), a quantitative method for structure description and analysis of information systems was introduced. Results The structural complexity index and two related factors, i.e. element complexity factor and connection complexity factor were defined, and the relations between them and the parameters of the Petri net based model of the system were derived. Application example was presented. Conclusion The proposed method provides a theoretical basis for quantitative analysis and evaluation of the structural complexity and can be applied in the general planning and design processes of the information systems.
