The Sb^(3+) doping strategy has been proven to be an effective way to regulate the band gap and improve the photophysical properties of organic-inorganic hybrid metal halides(OIHMHs).However,the emission of Sb^(3+) io...The Sb^(3+) doping strategy has been proven to be an effective way to regulate the band gap and improve the photophysical properties of organic-inorganic hybrid metal halides(OIHMHs).However,the emission of Sb^(3+) ions in OIHMHs is primarily confined to the low energy region,resulting in yellow or red emissions.To date,there are few reports about green emission of Sb^(3+)-doped OIHMHs.Here,we present a novel approach for regulating the luminescence of Sb^(3+) ions in 0D C_(10)H_(2)_(2)N_(6)InCl_(7)·H_(2)O via hydrogen bond network,in which water molecules act as agents for hydrogen bonding.Sb^(3+)-doped C_(10)H_(2)2N_(6)InCl_(7)·H_(2)O shows a broadband green emission peaking at 540 nm and a high photoluminescence quantum yield(PLQY)of 80%.It is found that the intense green emission stems from the radiative recombination of the self-trapped excitons(STEs).Upon removal of water molecules with heat,C_(10)H_(2)_(2)N_(6)In_(1-x)Sb_(x)Cl_(7) generates yellow emis-sion,attributed to the breaking of the hydrogen bond network and large structural distortions of excited state.Once water molecules are adsorbed by C_(10)H_(2)_(2)N_(6)In_(1-x)Sb_(x)Cl_(7),it can subsequently emit green light.This water-induced reversible emission switching is successfully used for optical security and information encryption.Our findings expand the under-standing of how the local coordination structure influences the photophysical mechanism in Sb^(3+)-doped metal halides and provide a novel method to control the STEs emission.展开更多
Counterfeiting of modern banknotes poses a significant challenge,prompting the use of various preventive measures.One such measure is the magnetic anti-counterfeiting strip.However,due to its inherent weak magnetic pr...Counterfeiting of modern banknotes poses a significant challenge,prompting the use of various preventive measures.One such measure is the magnetic anti-counterfeiting strip.However,due to its inherent weak magnetic properties,visualizing its magnetic distribution has been a longstanding challenge.In this work,we introduce an innovative method by using a fiber optic diamond probe,a highly sensitive quantum sensor designed specifically for detecting extremely weak magnetic fields.We employ this probe to achieve high-resolution imaging of the magnetic fields associated with the RMB 50denomination anti-counterfeiting strip.Additionally,we conduct computer simulations by using COMSOL Multiphysics software to deduce the potential geometric characteristics and material composition of the magnetic region within the anti-counterfeiting strip.The findings and method presented in this study hold broader significance,extending the RMB 50 denomination to various denominations of the Chinese currency and other items that employ magnetic anti-counterfeiting strips.These advances have the potential to significantly improve and promote security measures in order to prevent the banknotes from being counterfeited.展开更多
The authenticity identification of anti-counterfeiting codes based on mobile phone platforms is affected by lighting environment,photographing habits,camera resolution and other factors,resulting in poor collection qu...The authenticity identification of anti-counterfeiting codes based on mobile phone platforms is affected by lighting environment,photographing habits,camera resolution and other factors,resulting in poor collection quality of anti-counterfeiting codes and weak differentiation of anti-counterfeiting codes for high-quality counterfeits.Developing an anticounterfeiting code authentication algorithm based on mobile phones is of great commercial value.Although the existing algorithms developed based on special equipment can effectively identify forged anti-counterfeiting codes,the anti-counterfeiting code identification scheme based on mobile phones is still in its infancy.To address the small differences in texture features,low response speed and excessively large deep learning models used in mobile phone anti-counterfeiting and identification scenarios,we propose a feature-guided double pool attention network(FG-DPANet)to solve the reprinting forgery problem of printing anti-counterfeiting codes.To address the slight differences in texture features in high-quality reprinted anti-counterfeiting codes,we propose a feature guidance algorithm that creatively combines the texture features and the inherent noise feature of the scanner and printer introduced in the reprinting process to identify anti-counterfeiting code authenticity.The introduction of noise features effectively makes up for the small texture difference of high-quality anti-counterfeiting codes.The double pool attention network(DPANet)is a lightweight double pool attention residual network.Under the condition of ensuring detection accuracy,DPANet can simplify the network structure as much as possible,improve the network reasoning speed,and run better on mobile devices with low computing power.We conducted a series of experiments to evaluate the FG-DPANet proposed in this paper.Experimental results show that the proposed FG-DPANet can resist highquality and small-size anti-counterfeiting code reprint forgery.By comparing with the existing algorithm based on texture,it is shown that the proposed method has a higher authentication accuracy.Last but not least,the proposed scheme has been evaluated in the anti-counterfeiting code blurring scene,and the results show that our proposed method can well resist slight blurring of anti-counterfeiting images.展开更多
Background and Objective: HIV infection is a major global Public Health threat worldwide, particularly in Sub-Saharan Africa of which Benin. The level of knowledge determines the attitudes and behaviors of the populat...Background and Objective: HIV infection is a major global Public Health threat worldwide, particularly in Sub-Saharan Africa of which Benin. The level of knowledge determines the attitudes and behaviors of the populations towards this infection. The study objective was to assess knowledge, attitudes and practices related to HIV infection among motorbike taxi drivers (MTD) in Parakou in 2021. Methods: This was a descriptive cross-sectional study targeting MTD in Parakou in 2021. Participants were selected by cluster sampling. Pretested Digitized questionnaire using KoboCollect<sup>@</sup> applicationserved as a data collection tool. Knowledge, attitudes and practices variable were treated on a score scale. A knowledge score was considered to reflect a good knowledge of HIV if at least two-thirds of the knowledge statements had been correctly answered provided the subject recognized the sexual route as one of modes of HIV transmission, identified at least one preventive measure and meant the incurability of the disease. Quantitative and qualitative variables were appropriately described using the EPI Info 7.1.3.3 software. The participant was classified at positive attitude/practice for HIV prevention, when it has a score of at least 80% and suggests a good preventive measure face a risk of exposure to HIV. Results: A total of 374 subjects were recruited into the study. The mean age was 31.51 ± 7.76 years. Most participants (86.06%) had good knowledge of condom use as an HIV prevention method. The sources of information mentioned were mainly the media (77.07%), relatives or friends (63.38%), and field-workers from non-governmental organizations (37.26%). Routine HIV testing was 50.53%. Among participants, 76.10% reported at least two different sexual partners. Condom use was 59.18 % during the casual sexual intercourse. Within the client-provider relationship with female sex workers, 33.17% had had sexual intercourse with them. The sexual route was the most cited (92.99%), and 90.23% stated that HIV infection can be stabilized by medication in a health structure. Conclusion: The level of knowledge of motorbike taxi drivers in Parakou does not match their behavior with regard to HIV prevention. Appropriate strategies are needed to develop prevention skills in this population. To effectively comb at HIV, it will be necessary to strengthen the targeted HIV preventive interventions at key and bridge populations including motorbike taxi drivers in Benin.展开更多
This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.Th...This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.The model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel demand.The CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and frequencies.Based on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction efficiency.On this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban taxis.The combined prediction model is tested on a taxi travel demand dataset in a certain area of Beijing.The results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 metrics.Notably,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed model.These results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.展开更多
The developme nt of high-level an ti-co un terfeiti ng tech niq ues is of great sig nifica nee in econo mics and security issues.However,i ntricate read ing methods are required to obta in multi-level info rmati on st...The developme nt of high-level an ti-co un terfeiti ng tech niq ues is of great sig nifica nee in econo mics and security issues.However,i ntricate read ing methods are required to obta in multi-level info rmati on stored in differe nt colors,which greatly limits the applicati on of an ti-co un terfeit ing tech no logy on sol ving real world problems.Here in,we realize multicolor information anti-counterfeiting under simply external stimulation by utilizing the functional groups and multiple emission centers of lanthanide metal organic framework(Ln-MOFs)to tune luminescence color.Water responsive multicolor luminescence represented by both the tunable color from red to blue within the visible region and high sensitive responsivity has bee n achieved,owing to the in creased nonr adiative decay pathways and enhan ced Eu3+-to-liga nd en ergy back tra nsfer.Remarkably,i nfo rmatio n hidde n in differe nt colors n eeds to be read with a specific water content,which can be used as an en crypti on key to en sure the security of the info rmati on for high-level an ti-co un terfeiti ng.展开更多
Counterfeiting is one of the most serious problems in the consumer market. One promising approach for anti-counterfeiting is to attach a low-cost Radio-frequency Identification (RFID) tag to the product authentication...Counterfeiting is one of the most serious problems in the consumer market. One promising approach for anti-counterfeiting is to attach a low-cost Radio-frequency Identification (RFID) tag to the product authentication. In this paper, we propose an RFID system for detecting counterfeiting products. This RFID system consists of the tag authentication protocol and the database correction protocol. We use the tag authentication protocol for authenticating tags without revealing their sensitive information. This protocol also allows the customer to freely inquire the tag. To prevent the widespread of the counterfeit products, we use the tag status information along with tag identity information. Meanwhile, the database correction protocol guarantees the correctness of the tag status. Our anti-counterfeiting system is the first work considering the seller who plays an important role in the consumer product supply chain. Finally, we show that anti-counterfeiting system is quite secure against counterfeiting and the tag authentication protocol is lightweight enough to be implemented in RFID-based applications.展开更多
Taxi demand prediction is a crucial component of intelligent transportation system research.Compared to region-based demand prediction,origin-destination(OD)demand prediction has a wide range of potential applications...Taxi demand prediction is a crucial component of intelligent transportation system research.Compared to region-based demand prediction,origin-destination(OD)demand prediction has a wide range of potential applications,including real-time matching,idle vehicle allocation,ridesharing services,and dynamic pricing,among others.However,because OD demand involves complex spatiotemporal dependence,research in this area has been limited thus far.In this paper,we first review existing research from four perspectives:topology construction,temporal and spatial feature processing,and other relevant factors.We then elaborate on the advantages and limitations of OD prediction methods based on deep learning architecture theory.Next,we discuss ongoing challenges in OD prediction,such as dynamics,spatiotemporal dependence,semantic differentiation,time window selection,and data sparsity problems,and summarize and compare potential solutions to each challenge.These findings offer valuable insights for model selection in OD demand prediction.Finally,we provide public datasets and open-source code,along with suggestions for future research directions.展开更多
Hypertension, obesity, smoking, dyslipidemia, and type 2 diabetes (T2D) are the major risk factors for developing cardiovascular diseases (CVD). Recent studies revealed that taxi-motorbike drivers (TMDs) in Cotonou ha...Hypertension, obesity, smoking, dyslipidemia, and type 2 diabetes (T2D) are the major risk factors for developing cardiovascular diseases (CVD). Recent studies revealed that taxi-motorbike drivers (TMDs) in Cotonou had higher rates of CVD risk factors, but their impacts on cardiovascular events have rarely been studied. The Framingham risk score (FRS) is an algorithm that considers CVD risk factors and estimates the risk of developing CVD in the next 10 years. Our objectives were to assess the 10-year CVD risk predicted by the FRS, and to examine the relationships of 10-year CVD risk with plasma iron and potassium levels among TMDs. We included 134 TMDs (22 - 59 years old) who had no prior diagnosis of CVD or T2D, and not taking medications affecting iron and potassium homeostasis. Conventional cardiovascular risk factors were used to calculate the 10-year CVD risk, which was categorized as low (20%). FRS > 2%, which corresponded to the 75th percentile of FRS distribution in our study population, was used as a cut-off value to classify participants into two groups. Plasma iron and potassium levels were segregated into tertiles and their associations with 10-year CVD risk were quantified by multivariate-adjusted logistic regression to calculate the odd ratios (ORs) to being above the 75<sup>th</sup> percentile of 10-year CVD risk with the corresponding 95% confidence intervals (CIs). We found that 62.0% of participants had at least one of cardiovascular risk factors. Approximately 97.8% of TMDs had 10-year CVD risk 4.8 mmol/L led to an 83% risk reduction of having 10-year CVD risk > 2% (OR = 0.17, 95% CI: 0.04 - 0.82, P = 0.027). In conclusion, our findings showed that high plasma potassium levels associate with reduced 10-year CVD risk among TMDs. Interventions focused on monitoring of plasma potassium, particularly in those with existing cardiovascular risk factors, may help prevent CVD.展开更多
基金National Natural Science Foundation of China(11974063)Graduate research innovation project,School of Optoelectronic Engineering,Chongqing University(GDYKC2023002)+1 种基金Fundamental Research Funds for the Central Universities(2022CDJQY-010)The authors extend their appreciation to the Deputyship for Research and Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project no.(IFKSUOR3-073-9).
文摘The Sb^(3+) doping strategy has been proven to be an effective way to regulate the band gap and improve the photophysical properties of organic-inorganic hybrid metal halides(OIHMHs).However,the emission of Sb^(3+) ions in OIHMHs is primarily confined to the low energy region,resulting in yellow or red emissions.To date,there are few reports about green emission of Sb^(3+)-doped OIHMHs.Here,we present a novel approach for regulating the luminescence of Sb^(3+) ions in 0D C_(10)H_(2)_(2)N_(6)InCl_(7)·H_(2)O via hydrogen bond network,in which water molecules act as agents for hydrogen bonding.Sb^(3+)-doped C_(10)H_(2)2N_(6)InCl_(7)·H_(2)O shows a broadband green emission peaking at 540 nm and a high photoluminescence quantum yield(PLQY)of 80%.It is found that the intense green emission stems from the radiative recombination of the self-trapped excitons(STEs).Upon removal of water molecules with heat,C_(10)H_(2)_(2)N_(6)In_(1-x)Sb_(x)Cl_(7) generates yellow emis-sion,attributed to the breaking of the hydrogen bond network and large structural distortions of excited state.Once water molecules are adsorbed by C_(10)H_(2)_(2)N_(6)In_(1-x)Sb_(x)Cl_(7),it can subsequently emit green light.This water-induced reversible emission switching is successfully used for optical security and information encryption.Our findings expand the under-standing of how the local coordination structure influences the photophysical mechanism in Sb^(3+)-doped metal halides and provide a novel method to control the STEs emission.
基金Project supported by the National Key Research and Development Program of China (Grant No.2021YFB2012600)the Shanghai Aerospace Science and Technology Innovation Fund,China (Grant No.SAST-2022-102)。
文摘Counterfeiting of modern banknotes poses a significant challenge,prompting the use of various preventive measures.One such measure is the magnetic anti-counterfeiting strip.However,due to its inherent weak magnetic properties,visualizing its magnetic distribution has been a longstanding challenge.In this work,we introduce an innovative method by using a fiber optic diamond probe,a highly sensitive quantum sensor designed specifically for detecting extremely weak magnetic fields.We employ this probe to achieve high-resolution imaging of the magnetic fields associated with the RMB 50denomination anti-counterfeiting strip.Additionally,we conduct computer simulations by using COMSOL Multiphysics software to deduce the potential geometric characteristics and material composition of the magnetic region within the anti-counterfeiting strip.The findings and method presented in this study hold broader significance,extending the RMB 50 denomination to various denominations of the Chinese currency and other items that employ magnetic anti-counterfeiting strips.These advances have the potential to significantly improve and promote security measures in order to prevent the banknotes from being counterfeited.
基金This work is supported by Supported by the National Key Research and Development Program of China under Grant No.2020YFF0304902the Science and Technology Research Project of Jiangxi Provincial Department of Education under Grant No.GJJ202511。
文摘The authenticity identification of anti-counterfeiting codes based on mobile phone platforms is affected by lighting environment,photographing habits,camera resolution and other factors,resulting in poor collection quality of anti-counterfeiting codes and weak differentiation of anti-counterfeiting codes for high-quality counterfeits.Developing an anticounterfeiting code authentication algorithm based on mobile phones is of great commercial value.Although the existing algorithms developed based on special equipment can effectively identify forged anti-counterfeiting codes,the anti-counterfeiting code identification scheme based on mobile phones is still in its infancy.To address the small differences in texture features,low response speed and excessively large deep learning models used in mobile phone anti-counterfeiting and identification scenarios,we propose a feature-guided double pool attention network(FG-DPANet)to solve the reprinting forgery problem of printing anti-counterfeiting codes.To address the slight differences in texture features in high-quality reprinted anti-counterfeiting codes,we propose a feature guidance algorithm that creatively combines the texture features and the inherent noise feature of the scanner and printer introduced in the reprinting process to identify anti-counterfeiting code authenticity.The introduction of noise features effectively makes up for the small texture difference of high-quality anti-counterfeiting codes.The double pool attention network(DPANet)is a lightweight double pool attention residual network.Under the condition of ensuring detection accuracy,DPANet can simplify the network structure as much as possible,improve the network reasoning speed,and run better on mobile devices with low computing power.We conducted a series of experiments to evaluate the FG-DPANet proposed in this paper.Experimental results show that the proposed FG-DPANet can resist highquality and small-size anti-counterfeiting code reprint forgery.By comparing with the existing algorithm based on texture,it is shown that the proposed method has a higher authentication accuracy.Last but not least,the proposed scheme has been evaluated in the anti-counterfeiting code blurring scene,and the results show that our proposed method can well resist slight blurring of anti-counterfeiting images.
文摘Background and Objective: HIV infection is a major global Public Health threat worldwide, particularly in Sub-Saharan Africa of which Benin. The level of knowledge determines the attitudes and behaviors of the populations towards this infection. The study objective was to assess knowledge, attitudes and practices related to HIV infection among motorbike taxi drivers (MTD) in Parakou in 2021. Methods: This was a descriptive cross-sectional study targeting MTD in Parakou in 2021. Participants were selected by cluster sampling. Pretested Digitized questionnaire using KoboCollect<sup>@</sup> applicationserved as a data collection tool. Knowledge, attitudes and practices variable were treated on a score scale. A knowledge score was considered to reflect a good knowledge of HIV if at least two-thirds of the knowledge statements had been correctly answered provided the subject recognized the sexual route as one of modes of HIV transmission, identified at least one preventive measure and meant the incurability of the disease. Quantitative and qualitative variables were appropriately described using the EPI Info 7.1.3.3 software. The participant was classified at positive attitude/practice for HIV prevention, when it has a score of at least 80% and suggests a good preventive measure face a risk of exposure to HIV. Results: A total of 374 subjects were recruited into the study. The mean age was 31.51 ± 7.76 years. Most participants (86.06%) had good knowledge of condom use as an HIV prevention method. The sources of information mentioned were mainly the media (77.07%), relatives or friends (63.38%), and field-workers from non-governmental organizations (37.26%). Routine HIV testing was 50.53%. Among participants, 76.10% reported at least two different sexual partners. Condom use was 59.18 % during the casual sexual intercourse. Within the client-provider relationship with female sex workers, 33.17% had had sexual intercourse with them. The sexual route was the most cited (92.99%), and 90.23% stated that HIV infection can be stabilized by medication in a health structure. Conclusion: The level of knowledge of motorbike taxi drivers in Parakou does not match their behavior with regard to HIV prevention. Appropriate strategies are needed to develop prevention skills in this population. To effectively comb at HIV, it will be necessary to strengthen the targeted HIV preventive interventions at key and bridge populations including motorbike taxi drivers in Benin.
基金supported by the Surface Project of the National Natural Science Foundation of China(No.71273024)the Fundamental Research Funds for the Central Universities of China(2021YJS080).
文摘This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.The model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel demand.The CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and frequencies.Based on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction efficiency.On this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban taxis.The combined prediction model is tested on a taxi travel demand dataset in a certain area of Beijing.The results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 metrics.Notably,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed model.These results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.
基金This work was supported by the National Natural Science Foundation of China(Nos.52025131,51632008,51772268,and 61721005)Zhejiang Provincial Natural Science Foundation of China(No.LD18E020001).
文摘The developme nt of high-level an ti-co un terfeiti ng tech niq ues is of great sig nifica nee in econo mics and security issues.However,i ntricate read ing methods are required to obta in multi-level info rmati on stored in differe nt colors,which greatly limits the applicati on of an ti-co un terfeit ing tech no logy on sol ving real world problems.Here in,we realize multicolor information anti-counterfeiting under simply external stimulation by utilizing the functional groups and multiple emission centers of lanthanide metal organic framework(Ln-MOFs)to tune luminescence color.Water responsive multicolor luminescence represented by both the tunable color from red to blue within the visible region and high sensitive responsivity has bee n achieved,owing to the in creased nonr adiative decay pathways and enhan ced Eu3+-to-liga nd en ergy back tra nsfer.Remarkably,i nfo rmatio n hidde n in differe nt colors n eeds to be read with a specific water content,which can be used as an en crypti on key to en sure the security of the info rmati on for high-level an ti-co un terfeiti ng.
文摘Counterfeiting is one of the most serious problems in the consumer market. One promising approach for anti-counterfeiting is to attach a low-cost Radio-frequency Identification (RFID) tag to the product authentication. In this paper, we propose an RFID system for detecting counterfeiting products. This RFID system consists of the tag authentication protocol and the database correction protocol. We use the tag authentication protocol for authenticating tags without revealing their sensitive information. This protocol also allows the customer to freely inquire the tag. To prevent the widespread of the counterfeit products, we use the tag status information along with tag identity information. Meanwhile, the database correction protocol guarantees the correctness of the tag status. Our anti-counterfeiting system is the first work considering the seller who plays an important role in the consumer product supply chain. Finally, we show that anti-counterfeiting system is quite secure against counterfeiting and the tag authentication protocol is lightweight enough to be implemented in RFID-based applications.
基金supported by 2022 Shenyang Philosophy and Social Science Planning under grant SY202201Z,Liaoning Provincial Department of Education Project under grant LJKZ0588.
文摘Taxi demand prediction is a crucial component of intelligent transportation system research.Compared to region-based demand prediction,origin-destination(OD)demand prediction has a wide range of potential applications,including real-time matching,idle vehicle allocation,ridesharing services,and dynamic pricing,among others.However,because OD demand involves complex spatiotemporal dependence,research in this area has been limited thus far.In this paper,we first review existing research from four perspectives:topology construction,temporal and spatial feature processing,and other relevant factors.We then elaborate on the advantages and limitations of OD prediction methods based on deep learning architecture theory.Next,we discuss ongoing challenges in OD prediction,such as dynamics,spatiotemporal dependence,semantic differentiation,time window selection,and data sparsity problems,and summarize and compare potential solutions to each challenge.These findings offer valuable insights for model selection in OD demand prediction.Finally,we provide public datasets and open-source code,along with suggestions for future research directions.
文摘Hypertension, obesity, smoking, dyslipidemia, and type 2 diabetes (T2D) are the major risk factors for developing cardiovascular diseases (CVD). Recent studies revealed that taxi-motorbike drivers (TMDs) in Cotonou had higher rates of CVD risk factors, but their impacts on cardiovascular events have rarely been studied. The Framingham risk score (FRS) is an algorithm that considers CVD risk factors and estimates the risk of developing CVD in the next 10 years. Our objectives were to assess the 10-year CVD risk predicted by the FRS, and to examine the relationships of 10-year CVD risk with plasma iron and potassium levels among TMDs. We included 134 TMDs (22 - 59 years old) who had no prior diagnosis of CVD or T2D, and not taking medications affecting iron and potassium homeostasis. Conventional cardiovascular risk factors were used to calculate the 10-year CVD risk, which was categorized as low (20%). FRS > 2%, which corresponded to the 75th percentile of FRS distribution in our study population, was used as a cut-off value to classify participants into two groups. Plasma iron and potassium levels were segregated into tertiles and their associations with 10-year CVD risk were quantified by multivariate-adjusted logistic regression to calculate the odd ratios (ORs) to being above the 75<sup>th</sup> percentile of 10-year CVD risk with the corresponding 95% confidence intervals (CIs). We found that 62.0% of participants had at least one of cardiovascular risk factors. Approximately 97.8% of TMDs had 10-year CVD risk 4.8 mmol/L led to an 83% risk reduction of having 10-year CVD risk > 2% (OR = 0.17, 95% CI: 0.04 - 0.82, P = 0.027). In conclusion, our findings showed that high plasma potassium levels associate with reduced 10-year CVD risk among TMDs. Interventions focused on monitoring of plasma potassium, particularly in those with existing cardiovascular risk factors, may help prevent CVD.