Train Mass Rapid Transit(MRT)was put into service in 1987,and has since been augmented by and linked to the Light Rapid Transit.Combined,you can often get you within walking distance of most destinations.The maps on t...Train Mass Rapid Transit(MRT)was put into service in 1987,and has since been augmented by and linked to the Light Rapid Transit.Combined,you can often get you within walking distance of most destinations.The maps on the metro system are easy to read,complete with English version.You can easily purchase an EZ-Link card or a NETS Flashpay Card(stored value cards)at all MRT stations and bus interchange.展开更多
Deep Learning-based systems for Finger vein recognition have gained rising attention in recent years due to improved efficiency and enhanced security.The performance of existing CNN-based methods is limited by the pun...Deep Learning-based systems for Finger vein recognition have gained rising attention in recent years due to improved efficiency and enhanced security.The performance of existing CNN-based methods is limited by the puny generalization of learned features and deficiency of the finger vein image training data.Considering the concerns of existing methods,in this work,a simplified deep transfer learning-based framework for finger-vein recognition is developed using an EfficientNet model of deep learning with a self-attention mechanism.Data augmentation using various geometrical methods is employed to address the problem of training data shortage required for a deep learning model.The proposed model is tested using K-fold cross-validation on three publicly available datasets:HKPU,FVUSM,and SDUMLA.Also,the developed network is compared with other modern deep nets to check its effectiveness.In addition,a comparison of the proposed method with other existing Finger vein recognition(FVR)methods is also done.The experimental results exhibited superior recognition accuracy of the proposed method compared to other existing methods.In addition,the developed method proves to be more effective and less sophisticated at extracting robust features.The proposed EffAttenNet achieves an accuracy of 98.14%on HKPU,99.03%on FVUSM,and 99.50%on SDUMLA databases.展开更多
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
AIM:To investigate the postnatal development of parvalbumin(PV)-positive gamma-aminobutyric acid(GABA)interneurons and the co-expression of perineuronal nets(PNNs)and PV in the visual cortex of rats,as well as the reg...AIM:To investigate the postnatal development of parvalbumin(PV)-positive gamma-aminobutyric acid(GABA)interneurons and the co-expression of perineuronal nets(PNNs)and PV in the visual cortex of rats,as well as the regulatory effects of fluoxetine(FLX)treatment and binocular form deprivation(BFD)on these indices.METHODS:Wistar rats were assigned to three experimental cohorts:1)Age-related groups:postnatal week(PW)1,PW3,PW5,PW7,and PW9;2)FLX treatment duration groups:FLX 0W,FLX 2W,FLX 4W,FLX 6W,and FLX 8W;3)Intervention groups:control(Cont),FLX,BFD,and BFD+FLX.The levels of PNNs,PV,and PNNs/PV coexpression in the visual cortex were detected and analyzed.RESULTS:The density of PV-positive cells and the coexpression of PNNs and PV increased gradually with the maturation of the visual cortex(b=0.960,P<0.01).The ratio of PV-positive cells surrounded by PNNs to total PV-positive cells(PNNs+/PV+/total PV+)was significantly decreased in the FLX 4W group(χ^(2)=9.03,P=0.003).There was no significant difference in the PNNs+/PV+/total PV+ratio between the FLX and BFD groups(χ^(2)=1.08,P=0.161),but a significant difference was observed between the BFD+FLX group and the BFD group(χ^(2)=5.82,P<0.01).CONCLUSION:The number of PV-positive neurons and PNNs-surrounded PV neurons in the rat visual cortex increases postnatally and reaches adult levels by postnatal week 7.Chronic FLX treatment downregulates these expressions.Combined 4-week FLX treatment and BFD exerts a more significant inhibitory effect on the PNNs+/PV+/total PV+ratio than either intervention alone.展开更多
South Africa strengthens its efforts in polar and ocean research Under the command of Ashley Johnson,the iron gate on the starboard side of the S.A.Agulhas II vessel opened slowly,and the paired bongo nets,supported b...South Africa strengthens its efforts in polar and ocean research Under the command of Ashley Johnson,the iron gate on the starboard side of the S.A.Agulhas II vessel opened slowly,and the paired bongo nets,supported by a mechanised framework,gradually sank 100 metres into the sea.After being towed for a while,they were retrieved,and scientists on board sampled the plankton collected for analysis.Simultaneously,the bongo nets also gathered data on temperature,salinity,conductivity,and depth.Following this,the scientists deployed Niskin bottles to collect water samples from various depths.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
The conventional Shear Stress Transport(SST)k–ωturbulence model often exhibits substantial inaccu-racies when applied to the prediction of flow behavior in complex regions within axial flow control valves.To enhance...The conventional Shear Stress Transport(SST)k–ωturbulence model often exhibits substantial inaccu-racies when applied to the prediction of flow behavior in complex regions within axial flow control valves.To enhance its predictive fidelity for internal flow fields,this study introduces a novel calibration framework that integrates an artificial neural network(ANN)surrogate model with a particle swarm optimization(PSO)algorithm.In particular,an optimal Latin hypercube sampling strategy was employed to generate representative sample points across the empirical parameter space.For each sample,numerical simulations using ANSYS Fluent were conducted to evaluate the flow characteristics,with empirical turbulence model parameters as inputs and flow rate as the target output.These data were used to construct the high-fidelity ANN surrogate model.The PSO algorithm was then applied to this surrogate to identify the optimal set of empirical parameters tailored specifically to axial flow control valve configurations.A revealed by the presented results,the calibrated SST k–ωmodel significantly improves prediction accuracy:deviations from large eddy simulation(LES)benchmarks at small valve openings were reduced from 7.6%to under 3%.Furthermore,the refined model maintains the computational efficiency characteristic of Reynolds-averaged Navier-Stokes(RANS)simulations while substantially enhancing the accuracy of both pressure and velocity field predictions.Overall,the proposed methodology effectively reconciles the trade-off between computational cost and predictive accuracy,offering a robust and scalable approach for turbulence model calibration in complex internal flow scenarios.展开更多
This paper summarized the technical regulations for protected production of netted melon in Yantai City,primarily including technical measures such as the environmental requirements of the production area,cultivation ...This paper summarized the technical regulations for protected production of netted melon in Yantai City,primarily including technical measures such as the environmental requirements of the production area,cultivation techniques,pest and disease control,harvesting,packaging,storage,waste management,and production records for netted melon grown in facilities.The technical regulations aim to standardize the protected production of netted melon and enhance the level of standardized and normative production technology.展开更多
文摘Train Mass Rapid Transit(MRT)was put into service in 1987,and has since been augmented by and linked to the Light Rapid Transit.Combined,you can often get you within walking distance of most destinations.The maps on the metro system are easy to read,complete with English version.You can easily purchase an EZ-Link card or a NETS Flashpay Card(stored value cards)at all MRT stations and bus interchange.
文摘Deep Learning-based systems for Finger vein recognition have gained rising attention in recent years due to improved efficiency and enhanced security.The performance of existing CNN-based methods is limited by the puny generalization of learned features and deficiency of the finger vein image training data.Considering the concerns of existing methods,in this work,a simplified deep transfer learning-based framework for finger-vein recognition is developed using an EfficientNet model of deep learning with a self-attention mechanism.Data augmentation using various geometrical methods is employed to address the problem of training data shortage required for a deep learning model.The proposed model is tested using K-fold cross-validation on three publicly available datasets:HKPU,FVUSM,and SDUMLA.Also,the developed network is compared with other modern deep nets to check its effectiveness.In addition,a comparison of the proposed method with other existing Finger vein recognition(FVR)methods is also done.The experimental results exhibited superior recognition accuracy of the proposed method compared to other existing methods.In addition,the developed method proves to be more effective and less sophisticated at extracting robust features.The proposed EffAttenNet achieves an accuracy of 98.14%on HKPU,99.03%on FVUSM,and 99.50%on SDUMLA databases.
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 Suzhou Science and Technology Bureau(No.SKY2023175)the Project of State Key Laboratory of Radiation Medicine and Protection+6 种基金Soochow University(No.GZK1202309)the Advantage Subject Lifting Project(No.XKTJ-XK202412)the Suzhou Science and Education for Strengthening Healthcare(No.MSXM2024010)the Suzhou Medical Key Supported Disciplines(No.SZFCXK202118)the Youth Scientific Research Fund Project of Kunshan Hospital of Traditional Chinese Medicine(No.2024QNJJ06)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX23_1673)the Undergraduate Training Program for Innovation and Entrepreneurship,Soochow University(No.202310285162Y).
文摘AIM:To investigate the postnatal development of parvalbumin(PV)-positive gamma-aminobutyric acid(GABA)interneurons and the co-expression of perineuronal nets(PNNs)and PV in the visual cortex of rats,as well as the regulatory effects of fluoxetine(FLX)treatment and binocular form deprivation(BFD)on these indices.METHODS:Wistar rats were assigned to three experimental cohorts:1)Age-related groups:postnatal week(PW)1,PW3,PW5,PW7,and PW9;2)FLX treatment duration groups:FLX 0W,FLX 2W,FLX 4W,FLX 6W,and FLX 8W;3)Intervention groups:control(Cont),FLX,BFD,and BFD+FLX.The levels of PNNs,PV,and PNNs/PV coexpression in the visual cortex were detected and analyzed.RESULTS:The density of PV-positive cells and the coexpression of PNNs and PV increased gradually with the maturation of the visual cortex(b=0.960,P<0.01).The ratio of PV-positive cells surrounded by PNNs to total PV-positive cells(PNNs+/PV+/total PV+)was significantly decreased in the FLX 4W group(χ^(2)=9.03,P=0.003).There was no significant difference in the PNNs+/PV+/total PV+ratio between the FLX and BFD groups(χ^(2)=1.08,P=0.161),but a significant difference was observed between the BFD+FLX group and the BFD group(χ^(2)=5.82,P<0.01).CONCLUSION:The number of PV-positive neurons and PNNs-surrounded PV neurons in the rat visual cortex increases postnatally and reaches adult levels by postnatal week 7.Chronic FLX treatment downregulates these expressions.Combined 4-week FLX treatment and BFD exerts a more significant inhibitory effect on the PNNs+/PV+/total PV+ratio than either intervention alone.
文摘South Africa strengthens its efforts in polar and ocean research Under the command of Ashley Johnson,the iron gate on the starboard side of the S.A.Agulhas II vessel opened slowly,and the paired bongo nets,supported by a mechanised framework,gradually sank 100 metres into the sea.After being towed for a while,they were retrieved,and scientists on board sampled the plankton collected for analysis.Simultaneously,the bongo nets also gathered data on temperature,salinity,conductivity,and depth.Following this,the scientists deployed Niskin bottles to collect water samples from various depths.
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funded by Gansu Provincial Department of Education(Industrial Support Plan Project:2025CYZC-048).
文摘The conventional Shear Stress Transport(SST)k–ωturbulence model often exhibits substantial inaccu-racies when applied to the prediction of flow behavior in complex regions within axial flow control valves.To enhance its predictive fidelity for internal flow fields,this study introduces a novel calibration framework that integrates an artificial neural network(ANN)surrogate model with a particle swarm optimization(PSO)algorithm.In particular,an optimal Latin hypercube sampling strategy was employed to generate representative sample points across the empirical parameter space.For each sample,numerical simulations using ANSYS Fluent were conducted to evaluate the flow characteristics,with empirical turbulence model parameters as inputs and flow rate as the target output.These data were used to construct the high-fidelity ANN surrogate model.The PSO algorithm was then applied to this surrogate to identify the optimal set of empirical parameters tailored specifically to axial flow control valve configurations.A revealed by the presented results,the calibrated SST k–ωmodel significantly improves prediction accuracy:deviations from large eddy simulation(LES)benchmarks at small valve openings were reduced from 7.6%to under 3%.Furthermore,the refined model maintains the computational efficiency characteristic of Reynolds-averaged Navier-Stokes(RANS)simulations while substantially enhancing the accuracy of both pressure and velocity field predictions.Overall,the proposed methodology effectively reconciles the trade-off between computational cost and predictive accuracy,offering a robust and scalable approach for turbulence model calibration in complex internal flow scenarios.
基金Supported by The Teaching Reform Research Project of Yantai Institute of China Agricultural University(202302Ks)Yantai Local Standard Revision Program(DB 3706/T 73-2021).
文摘This paper summarized the technical regulations for protected production of netted melon in Yantai City,primarily including technical measures such as the environmental requirements of the production area,cultivation techniques,pest and disease control,harvesting,packaging,storage,waste management,and production records for netted melon grown in facilities.The technical regulations aim to standardize the protected production of netted melon and enhance the level of standardized and normative production technology.
