The emergence of smart grids in India is propelled by an intricate interaction of market dynamics,regulatory structures,and stakeholder obligations.This study analyzes the primary factors that are driving the widespre...The emergence of smart grids in India is propelled by an intricate interaction of market dynamics,regulatory structures,and stakeholder obligations.This study analyzes the primary factors that are driving the widespread use of smart grid technologies and outlines the specific roles and obligations of different stakeholders,such as government entities,utility companies,technology suppliers,and consumers.Government activities and regulations are crucial in facilitating the implementation of smart grid technology by offering financial incentives,regulatory assistance,and strategic guidance.Utility firms have the responsibility of implementing and integrating smart grid infrastructure,with an emphasis on improving the dependability of the grid,minimizing losses in transmission and distribution,and integrating renewable energy sources.Technology companies offer the essential hardware and software solutions,which stimulate creativity and enhance efficiency.Consumers actively engage in the energy ecosystem by participating in demand response,implementing energy saving measures,and adopting distributed energy resources like solar panels and electric vehicles.This study examines the difficulties and possibilities in India’s smart grid industry,highlighting the importance of cooperation among stakeholders to build a strong,effective,and environmentally friendly energy future.展开更多
As drivers age, roadway conditions may become more challenging, particularly when normal aging is coupled with cognitive decline. Driving during lower visibility conditions, such as inclement weather, is especially ch...As drivers age, roadway conditions may become more challenging, particularly when normal aging is coupled with cognitive decline. Driving during lower visibility conditions, such as inclement weather, is especially challenging for older drivers due to their sensitivity to glare and reduced visibility. As a result, older drivers may adjust their behavior during adverse weather. This paper explores the differential impacts of weather on older drivers with cognitive decline compared to older drivers with normal cognitive function. Data were from a naturalistic driving study of older drivers in Omaha, Nebraska. Driver speed and weather data were extracted and the correlation between speed compliance, road weather conditions, and the cognitive/neurological status of the drivers was examined. Speed compliance was used as the surrogate safety measure since driving at lower speeds can indicate that the driver is challenged by roadway or environmental conditions and can therefore indicate a risk. The percentage of time during a trip when drivers were 16.1 kph under the speed limit was modeled as the dependent variable using beta regression. The variables that resulted in the best fit model were mild cognitive impairment (MCI), age group, traffic density, and weather. Results indicated that the youngest group of older drivers (young-old) spent less time driving at impeding speeds and had the least variability compared to the other two age groups. The middle group of older drivers (middle-old) had the highest amount of time driving at impeding speeds and had more variability than young-old drivers. The oldest group of older drivers (old-old) were the most likely to drive at impeding speeds and had the most variability. In general, older drivers were more likely to drive at impeding speeds during peak hours than during non-peak hours. Additionally, in most cases, older drivers spent less time below the speed limit when the weather was clear than in adverse conditions. Results indicate that older drivers are impacted by weather conditions, and distinct patterns were noted between older drivers who were cognitively impaired compared to drivers with normal cognition.展开更多
Osyris lanceolata is heavily and illegally exploited in East Africa for its essential oils, yet little is known about its population status and ecological requirements. This study examined its population structure and...Osyris lanceolata is heavily and illegally exploited in East Africa for its essential oils, yet little is known about its population status and ecological requirements. This study examined its population structure and environmental factors influencing its distribution in the semi-arid Karamoja sub-region, Uganda. We surveyed 388 plots (5 m radius) at different altitudes, recording life stages, stem diameters, and regeneration patterns, and analyzed soil samples. Multivariate analyses, including Canonical Correspondence Analysis (CCA), Detrended Correspondence Analysis (DCA), Non-metric Multidimensional Scaling (NMDS), and Multiple Regression Modeling (MRM), identified key environmental factors affecting its distribution. Findings show that O. lanceolata populations in Moroto, Nakapiripirit, and Amudat districts are severely degraded due to overexploitation. The species is primarily regenerating through coppicing rather than seedlings, with an exploitation intensity of 56.6%. Population densities are low, distribution is irregular, and sustainable harvesting is not viable. Soil properties, particularly Ca2+, N, P, K+, Na+, and organic matter, significantly influence its abundance. Conservation efforts should focus on identifying suitable provenances for genetic preservation and plantation establishment. Areas with at least 9 trees per hectare in Moroto, Nakapiripirit, and Amudat could serve as potential sites for ex-situ plantations. Further research should explore how biotic interactions, genetic diversity, and morphology affect oil yield and quality to support restoration, breeding, and domestication initiatives.展开更多
In recent years,soil acidification has been expanding in many areas of Asia due to increasing reactive nitrogen inputs and industrial activities,which may seriously affect the performance of various ecosystem function...In recent years,soil acidification has been expanding in many areas of Asia due to increasing reactive nitrogen inputs and industrial activities,which may seriously affect the performance of various ecosystem functions.However,the underlying patterns and processes of ecosystem multifunctionality(EMF)are largely unknown at different levels of pH,limiting our understanding of how EMF respond to drivers.This study aims to explore threshold of pH on changes in EMF and differences in the drivers for the changes in EMF on either side of each of the determined pH thresholds.We collected nutrient and environmental databases for raster-level sampling data,totaling 4,000 sampling points.Averaging and cluster-multiple-threshold approach were used to calculate EMF,then quadratic and generalized additive models and Mann-Whitney U were used to determine and test the pH thresholds for changes in EMF,structural equation modellings and variance partitioning analysis were used to explore the main drivers on changes in EMF.The pH threshold for EMF changes in Chinese terrestrial ecosystems is 6.0.When pH<6.0,climate was consistently more important in controlling the variation of EMF than other variables;when pH≥6.0,soil was consistently more important in controlling the variation of EMF than other variables.Specifically,when pH<6.0,mean annual temperature was the main factor in regulating the EMF variation;when pH≥6.0,soil moisture was the main factor in regulating the EMF variation.Our study provides important scientific value for the mechanism of maintaining EMF under global change.For example,with further increases in global nitrogen deposition,leading to increased soil acidification,there are different impacts on EMF in different regions.It may lead to a decrease in EMF in acidic soils and an increase in EMF in alkaline soils.This suggests different management strategies for different regions to maintain EMF stability in the context of future global changes.In the future,more attention should be paid to the biological mechanisms regulating EMF.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
Drought events have become more frequent and intense over East Asia in recent decades,leading to huge socioeconomic impacts.Although the droughts have been studied extensively by cases or for individual regions,their ...Drought events have become more frequent and intense over East Asia in recent decades,leading to huge socioeconomic impacts.Although the droughts have been studied extensively by cases or for individual regions,their leading variability and associated causes remain unclear.Based on the Standardized Precipitation Evapotranspiration Index(SPEI)and ERA5 reanalysis product from 1979 to 2020,this study evealuates the severity of spring droughts in East Asia and investigates their variations and associated drivers.The results indicate that North China and Mongolia have experienced remarkable trends toward dryness during spring in recent decades,while southwestern China has witnessed an opposite trend toward wetness.The first Empirical Orthogonal Function mode of SPEI variability reveals a similar seesawing pattern,with more severe dryness in northwestern China,Mongolia,North China,South Korea,and Japan but increased wetness in Southwestern China and southeast Asia.Further investigation reveals that the anomalously dry(wet)surface in North(Southwestern)China is significantly associated with anomalously high(low)temperature,less(more)precipitation,and reduced(increased)soil moisture during the previous winter and early spring,regulated by an anomalous anticyclone(cyclone)and thus reduced(increased)water vapor convergence.The spring dry-wet pattern in East Asia is also linked to cold sea surface temperature anomalies in the central-eastern Pacific.The findings of this study have important implications for improving the prediction of spring drought events in East Asia.展开更多
The prevalence of human immunodeficiency virus (AIDS) and hepatitis B virus among heavy truck drivers and their assistants has been well documented globally in correlation with their behavioral characteristics. The pr...The prevalence of human immunodeficiency virus (AIDS) and hepatitis B virus among heavy truck drivers and their assistants has been well documented globally in correlation with their behavioral characteristics. The present study aimed to screen for human immunodeficiency virus (HIV), hepatitis B virus (HBV), and behavioral characteristics among heavy truck drivers in Port Sudan. A cross-sectional study was conducted on 274 heavy truck drivers and their assistants who used the highway Port Sudan-Khartoum in Port Sudan city during 2019-2021. Data on behavioral characteristics and substance use habits were collected using a structured questionnaire, and an ELISA test was used to screen for HIV and HBV infections in the study participants. The chi-square test, odds ratio, and confidence intervals were used to find the association between behavioral characteristics and seropositive HIV/HBV. Of the 274 enrolled participants, the seroprevalence rates of HIV were 2.7% and HBV was 23.7%. Ninety-four (34.3%) of them had a history of high-risk sexual behavior outside of marriage;only two (0.7%) used condoms;14.2% of participants reported alcohol use;and 1.1% reported drug use. Univariate analysis revealed that having a sex history outside of marriage with ≥1 sex partner and never using a condom with a spouse or casual partner were significant risk factors for HIV and HBV among drivers. Fortunately, we found that most of the drivers reported low alcohol and drug use. Concerning this study, the seroprevalence of HIV and HBV is highly associated with a history of having sex outside of marriage and sexual behavior among truck drivers and assistances. Additional studies are needed to further investigate other STIs and behavioral characteristics associated with factors in truck drivers/assistance in different truck stop regions in Sudan.展开更多
Speeding is one of the most common aberrant driving behaviors among the driving population.Although research on speeding behavior among drivers has increased over the decades,little is known about the motivating facto...Speeding is one of the most common aberrant driving behaviors among the driving population.Although research on speeding behavior among drivers has increased over the decades,little is known about the motivating factors associated with speeding behavior among long-haul truck drivers(LHTDs),especially in developing nations like India.This study aims to develop a prediction model for speeding behavior and to identify the contributory factors and their influential patterns underlying speeding behavior among LHTDs in India.A cross-sectional study was conducted among LHTDs in Salem City,Tamil Nadu,India.The data were collected through face-to-face interviews using a questionnaire encompassing socio-demographic,work,vehicle,health-related lifestyle,and speeding-related characteristics.A total of 756 valid samples were collected and utilized for analysis purposes.While conventional statistical methods like binary logit technique lacked prediction capabilities,machine learning(ML)algorithms including decision tree(DT),random forest(RF),adaptive boosting(AdaBoost),and extreme gradient boosting(XGBoost)were employed to model speeding behavior among LHTDs.The analysis results showed that RF demonstrated superior performance in predicting speeding behavior over other competing algorithms with accuracy(0.80),F1 score(0.77),and AUROC(0.81).From the befitting RF model,the importance of factors contributing to speeding behavior among LHTDs was determined through the variable importance plot.Pressured delivery of goods,sleeping duration per day,age of truck,size of truck,monthly income,driving experience,driving duration per day,and age of the driver were identified as the eight topmost critical factors contributing to speeding behavior among LHTDs.Based on the developed RF model,the hidden relationships behind identified critical factors in relation to the speeding behavior were investigated using partial dependence plots(PDPs).The outcomes of this research will be useful for road safety authorities and Indian trucking industries to frame suitable policies and to introduce effective strategies for mitigating speeding behavior among LHTDs to promote road safety.展开更多
A mathematical model describing the risks of road accidents has been built on the basis of statistical data of drivers’ accident rate. It has been revealed that drivers can be divided by the degree of their accident ...A mathematical model describing the risks of road accidents has been built on the basis of statistical data of drivers’ accident rate. It has been revealed that drivers can be divided by the degree of their accident proneness into four categories with sharply differing probabilities of road accidents. It has been shown that there is a possibility of classification of drivers in accordance with specified categories.展开更多
Risky driving behaviors,such as driving fatigue and distraction have recently received more attention.There is also much research about driving styles,driving emotions,older drivers,drugged driving,DUI(driving under t...Risky driving behaviors,such as driving fatigue and distraction have recently received more attention.There is also much research about driving styles,driving emotions,older drivers,drugged driving,DUI(driving under the influence),and DWI(driving while intoxicated).Road hypnosis is a special behavior significantly impacting traffic safety.However,there is little research on this phenomenon.Road hypnosis,as an unconscious state,is can frequently occur while driving,particularly in highly predictable,monotonous,and familiar environments.In this paper,vehicle and virtual driving experiments are designed to collect the biological characteristics including eye movement and bioelectric parameters.Typical scenes in tunnels and highways are used as experimental scenes.LSTM(Long Short-Term Memory)and KNN(K-Nearest Neighbor)are employed as the base learners,while SVM(Support Vector Machine)serves as the meta-learner.A road hypnosis identification model is proposed based on ensemble learning,which integrates bioelectric and eye movement characteristics.The proposed model has good identification performance,as seen from the experimental results.In this study,alternative methods and technical support are provided for real-time and accurate identification of road hypnosis.展开更多
Most previous studies on the market efficiency of cryptocurrencies consider time evolution but do not provide insights into the potential driving factors.This study addresses this limitation by examining the time-vary...Most previous studies on the market efficiency of cryptocurrencies consider time evolution but do not provide insights into the potential driving factors.This study addresses this limitation by examining the time-varying efficiency of the two largest cryptocurrencies,Bitcoin and Ethereum,and the factors that drive efficiency.It uses daily data from August 7,2016,to February 15,2023,the adjusted market inefficiency magnitude(AMIMs)measure,and quantile regression.The results show evidence of time variation in the levels of market(in)efficiency for Bitcoin and Ethereum.Interestingly,the quantile regressions indicate that global financial stress negatively affects the AMIMs measures across all quantiles.Notably,cryptocurrency liquidity positively and significantly affects AMIMs irrespective of the level of(in)efficiency,whereas the positive effect of money flow is significant when the markets of both cryptocurrencies are efficient.Finally,the COVID-19 pandemic positively and significantly affected cryptocurrency market inefficiencies across most quantiles.展开更多
Familiar and unfamiliar drivers may exhibit different behaviours in response to the road environment.Overall familiarity with the road environment is a human factor believed to play a role in road crash injury severit...Familiar and unfamiliar drivers may exhibit different behaviours in response to the road environment.Overall familiarity with the road environment is a human factor believed to play a role in road crash injury severity due to its effect on a driver’s decision-making process,reaction time,etc.Hence,there is a need to separately analyse familiar and unfa miliar drivers regarding the injury severity of crashes.Using a six-year database of 30,481 rural two-vehicle crashes in Guilan province,Iran,this research first defined four categories of crashes,reflecting various levels of the involved drivers’familiarity with the environ ment(72%of drivers were from the same vs.28%from a different province).Next,the injury severity of crashes in each familiarity crash category was analysed using both non-parametric(classification and regression trees)and parametric(logistic regression)methods.When both crash parties were unfamiliar,several results are different compared to whenboth parties were familiar or when ignoring driver familiarity.For instance,young at-fault drivers increased the injury severity of crashes if they were unfamiliar,while they decreased the crash severity if they were familiar.Also,crashes in winter tended to be more severe when one or especially both crash parties were unfamiliar,but winter crashes were less severe when both drivers were familiar or when driver familiarity was ignored.Overall,when both drivers were familiar,63%of crashes were injury/fatal;however,when both drivers were unfamiliar,only 31%of crashes involved an injury or fatality.展开更多
Motor vehicle crashes are the leading cause of the death of teenagers in the United States.Young drivers have shown a higher propensity to get involved in crashes due to using a cellphone while driving,breaking the sp...Motor vehicle crashes are the leading cause of the death of teenagers in the United States.Young drivers have shown a higher propensity to get involved in crashes due to using a cellphone while driving,breaking the speed limit,and reckless driving.This study analyzed motor vehicle crashes involving young drivers using New Jersey crash data.Specifically,four years of crash data(2016-2019)were gathered and analyzed.Different machine learning(ML)methods,such as Random Forest,Light GBM,Catboost,and XGBoost,were used to predict the injury severity.The performance of the models was evaluated using accuracy,precision,and recall scores.In addition,interpretable ML techniques like sensitivity analysis and Shapley values were conducted to assess the most influential factors’impacts on young driver-related crashes.The results revealed that XGBoost performed better than Random Forest,CatBoost,and LightGBM models in crash severity prediction.Results from the sensitivity analysis showed that multi-vehicle crashes,angular crashes,crashes at intersections,and dark-not-lit conditions had increased crash severity.A partial dependence plot of SHAP values revealed that speeding in clear weather had a higher likelihood of injury crashes,and multi-vehicle crashes at the intersection had more injury crashes.We expect that the results obtained from this study will help policymakers and practitioners take appropriate countermeasures to improve the safety of young drivers in New Jersey.展开更多
Understory plants are important components of forest ecosystems and play a crucial role in regulating community structures,function realization,and community succession.However,little is known about how abiotic and bi...Understory plants are important components of forest ecosystems and play a crucial role in regulating community structures,function realization,and community succession.However,little is known about how abiotic and biotic drivers affect the diversity of understory species in cold temperate coniferous forests in the semiarid climate region of North China.We hypothesized that(1)topographic factors are important environmental factors affecting the distribution and variation of understory strata,and(2)different understory strata respond differently to environmental factors;shrubs may be significantly affected by the overstory stratum,and herbs may be more affected by surface soil conditions.To test these hypotheses,we used the boosted regression tree method to analyze abiotic and biotic environmental factors that influence understory species diversity,using data from 280 subplots across 56 sites in cold temperate coniferous forests of North China.Elevation and slope aspect were the dominant and indirect abiotic drivers affecting understory species diversity,and individual tree size inequality(DBH variation)was the dominant biotic driver of understory species diversity;soil water content was the main edaphic factors affecting herb layers.Elevation,slope aspect,and DBH variation accounted for 36.4,14.5,and 12.1%,respectively,of shrub stratum diversity.Shrub diversity decreased with elevation within the range of altitude of this study,but increased with DBH variation;shrub diversity was highest on north-oriented slopes.The strongest factor affecting herb stratum species diversity was slope aspect,accounting for 25.9%of the diversity,followed by elevation(15.7%),slope(12.2%),and soil water content(10.3%).The highest herb diversity was found on southeast-oriented slopes and the lowest on northeast-oriented slopes;herb diversity decreased with elevation and soil water content,but increased with slope.The results of the study provide a reference for scientific management and biodiversity protection in cold temperate coniferous forests of North China.展开更多
文摘The emergence of smart grids in India is propelled by an intricate interaction of market dynamics,regulatory structures,and stakeholder obligations.This study analyzes the primary factors that are driving the widespread use of smart grid technologies and outlines the specific roles and obligations of different stakeholders,such as government entities,utility companies,technology suppliers,and consumers.Government activities and regulations are crucial in facilitating the implementation of smart grid technology by offering financial incentives,regulatory assistance,and strategic guidance.Utility firms have the responsibility of implementing and integrating smart grid infrastructure,with an emphasis on improving the dependability of the grid,minimizing losses in transmission and distribution,and integrating renewable energy sources.Technology companies offer the essential hardware and software solutions,which stimulate creativity and enhance efficiency.Consumers actively engage in the energy ecosystem by participating in demand response,implementing energy saving measures,and adopting distributed energy resources like solar panels and electric vehicles.This study examines the difficulties and possibilities in India’s smart grid industry,highlighting the importance of cooperation among stakeholders to build a strong,effective,and environmentally friendly energy future.
文摘As drivers age, roadway conditions may become more challenging, particularly when normal aging is coupled with cognitive decline. Driving during lower visibility conditions, such as inclement weather, is especially challenging for older drivers due to their sensitivity to glare and reduced visibility. As a result, older drivers may adjust their behavior during adverse weather. This paper explores the differential impacts of weather on older drivers with cognitive decline compared to older drivers with normal cognitive function. Data were from a naturalistic driving study of older drivers in Omaha, Nebraska. Driver speed and weather data were extracted and the correlation between speed compliance, road weather conditions, and the cognitive/neurological status of the drivers was examined. Speed compliance was used as the surrogate safety measure since driving at lower speeds can indicate that the driver is challenged by roadway or environmental conditions and can therefore indicate a risk. The percentage of time during a trip when drivers were 16.1 kph under the speed limit was modeled as the dependent variable using beta regression. The variables that resulted in the best fit model were mild cognitive impairment (MCI), age group, traffic density, and weather. Results indicated that the youngest group of older drivers (young-old) spent less time driving at impeding speeds and had the least variability compared to the other two age groups. The middle group of older drivers (middle-old) had the highest amount of time driving at impeding speeds and had more variability than young-old drivers. The oldest group of older drivers (old-old) were the most likely to drive at impeding speeds and had the most variability. In general, older drivers were more likely to drive at impeding speeds during peak hours than during non-peak hours. Additionally, in most cases, older drivers spent less time below the speed limit when the weather was clear than in adverse conditions. Results indicate that older drivers are impacted by weather conditions, and distinct patterns were noted between older drivers who were cognitively impaired compared to drivers with normal cognition.
文摘Osyris lanceolata is heavily and illegally exploited in East Africa for its essential oils, yet little is known about its population status and ecological requirements. This study examined its population structure and environmental factors influencing its distribution in the semi-arid Karamoja sub-region, Uganda. We surveyed 388 plots (5 m radius) at different altitudes, recording life stages, stem diameters, and regeneration patterns, and analyzed soil samples. Multivariate analyses, including Canonical Correspondence Analysis (CCA), Detrended Correspondence Analysis (DCA), Non-metric Multidimensional Scaling (NMDS), and Multiple Regression Modeling (MRM), identified key environmental factors affecting its distribution. Findings show that O. lanceolata populations in Moroto, Nakapiripirit, and Amudat districts are severely degraded due to overexploitation. The species is primarily regenerating through coppicing rather than seedlings, with an exploitation intensity of 56.6%. Population densities are low, distribution is irregular, and sustainable harvesting is not viable. Soil properties, particularly Ca2+, N, P, K+, Na+, and organic matter, significantly influence its abundance. Conservation efforts should focus on identifying suitable provenances for genetic preservation and plantation establishment. Areas with at least 9 trees per hectare in Moroto, Nakapiripirit, and Amudat could serve as potential sites for ex-situ plantations. Further research should explore how biotic interactions, genetic diversity, and morphology affect oil yield and quality to support restoration, breeding, and domestication initiatives.
基金This work was supported by the Tianshan Programme of Excellence(2022TSYCCX0001)the National Key Program for Basic Research and Development(973 Program)(2012CB417101)。
文摘In recent years,soil acidification has been expanding in many areas of Asia due to increasing reactive nitrogen inputs and industrial activities,which may seriously affect the performance of various ecosystem functions.However,the underlying patterns and processes of ecosystem multifunctionality(EMF)are largely unknown at different levels of pH,limiting our understanding of how EMF respond to drivers.This study aims to explore threshold of pH on changes in EMF and differences in the drivers for the changes in EMF on either side of each of the determined pH thresholds.We collected nutrient and environmental databases for raster-level sampling data,totaling 4,000 sampling points.Averaging and cluster-multiple-threshold approach were used to calculate EMF,then quadratic and generalized additive models and Mann-Whitney U were used to determine and test the pH thresholds for changes in EMF,structural equation modellings and variance partitioning analysis were used to explore the main drivers on changes in EMF.The pH threshold for EMF changes in Chinese terrestrial ecosystems is 6.0.When pH<6.0,climate was consistently more important in controlling the variation of EMF than other variables;when pH≥6.0,soil was consistently more important in controlling the variation of EMF than other variables.Specifically,when pH<6.0,mean annual temperature was the main factor in regulating the EMF variation;when pH≥6.0,soil moisture was the main factor in regulating the EMF variation.Our study provides important scientific value for the mechanism of maintaining EMF under global change.For example,with further increases in global nitrogen deposition,leading to increased soil acidification,there are different impacts on EMF in different regions.It may lead to a decrease in EMF in acidic soils and an increase in EMF in alkaline soils.This suggests different management strategies for different regions to maintain EMF stability in the context of future global changes.In the future,more attention should be paid to the biological mechanisms regulating EMF.
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National Natural Science Foundation of China(42230603,42275020)Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)+3 种基金Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies(2020B1212060025)Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021001)Open Fund of State Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,MNR(QNHX2310)Future Earth Early-Career Fellowship of the Future Earth Global Secretariat Hub China。
文摘Drought events have become more frequent and intense over East Asia in recent decades,leading to huge socioeconomic impacts.Although the droughts have been studied extensively by cases or for individual regions,their leading variability and associated causes remain unclear.Based on the Standardized Precipitation Evapotranspiration Index(SPEI)and ERA5 reanalysis product from 1979 to 2020,this study evealuates the severity of spring droughts in East Asia and investigates their variations and associated drivers.The results indicate that North China and Mongolia have experienced remarkable trends toward dryness during spring in recent decades,while southwestern China has witnessed an opposite trend toward wetness.The first Empirical Orthogonal Function mode of SPEI variability reveals a similar seesawing pattern,with more severe dryness in northwestern China,Mongolia,North China,South Korea,and Japan but increased wetness in Southwestern China and southeast Asia.Further investigation reveals that the anomalously dry(wet)surface in North(Southwestern)China is significantly associated with anomalously high(low)temperature,less(more)precipitation,and reduced(increased)soil moisture during the previous winter and early spring,regulated by an anomalous anticyclone(cyclone)and thus reduced(increased)water vapor convergence.The spring dry-wet pattern in East Asia is also linked to cold sea surface temperature anomalies in the central-eastern Pacific.The findings of this study have important implications for improving the prediction of spring drought events in East Asia.
文摘The prevalence of human immunodeficiency virus (AIDS) and hepatitis B virus among heavy truck drivers and their assistants has been well documented globally in correlation with their behavioral characteristics. The present study aimed to screen for human immunodeficiency virus (HIV), hepatitis B virus (HBV), and behavioral characteristics among heavy truck drivers in Port Sudan. A cross-sectional study was conducted on 274 heavy truck drivers and their assistants who used the highway Port Sudan-Khartoum in Port Sudan city during 2019-2021. Data on behavioral characteristics and substance use habits were collected using a structured questionnaire, and an ELISA test was used to screen for HIV and HBV infections in the study participants. The chi-square test, odds ratio, and confidence intervals were used to find the association between behavioral characteristics and seropositive HIV/HBV. Of the 274 enrolled participants, the seroprevalence rates of HIV were 2.7% and HBV was 23.7%. Ninety-four (34.3%) of them had a history of high-risk sexual behavior outside of marriage;only two (0.7%) used condoms;14.2% of participants reported alcohol use;and 1.1% reported drug use. Univariate analysis revealed that having a sex history outside of marriage with ≥1 sex partner and never using a condom with a spouse or casual partner were significant risk factors for HIV and HBV among drivers. Fortunately, we found that most of the drivers reported low alcohol and drug use. Concerning this study, the seroprevalence of HIV and HBV is highly associated with a history of having sex outside of marriage and sexual behavior among truck drivers and assistances. Additional studies are needed to further investigate other STIs and behavioral characteristics associated with factors in truck drivers/assistance in different truck stop regions in Sudan.
文摘Speeding is one of the most common aberrant driving behaviors among the driving population.Although research on speeding behavior among drivers has increased over the decades,little is known about the motivating factors associated with speeding behavior among long-haul truck drivers(LHTDs),especially in developing nations like India.This study aims to develop a prediction model for speeding behavior and to identify the contributory factors and their influential patterns underlying speeding behavior among LHTDs in India.A cross-sectional study was conducted among LHTDs in Salem City,Tamil Nadu,India.The data were collected through face-to-face interviews using a questionnaire encompassing socio-demographic,work,vehicle,health-related lifestyle,and speeding-related characteristics.A total of 756 valid samples were collected and utilized for analysis purposes.While conventional statistical methods like binary logit technique lacked prediction capabilities,machine learning(ML)algorithms including decision tree(DT),random forest(RF),adaptive boosting(AdaBoost),and extreme gradient boosting(XGBoost)were employed to model speeding behavior among LHTDs.The analysis results showed that RF demonstrated superior performance in predicting speeding behavior over other competing algorithms with accuracy(0.80),F1 score(0.77),and AUROC(0.81).From the befitting RF model,the importance of factors contributing to speeding behavior among LHTDs was determined through the variable importance plot.Pressured delivery of goods,sleeping duration per day,age of truck,size of truck,monthly income,driving experience,driving duration per day,and age of the driver were identified as the eight topmost critical factors contributing to speeding behavior among LHTDs.Based on the developed RF model,the hidden relationships behind identified critical factors in relation to the speeding behavior were investigated using partial dependence plots(PDPs).The outcomes of this research will be useful for road safety authorities and Indian trucking industries to frame suitable policies and to introduce effective strategies for mitigating speeding behavior among LHTDs to promote road safety.
文摘A mathematical model describing the risks of road accidents has been built on the basis of statistical data of drivers’ accident rate. It has been revealed that drivers can be divided by the degree of their accident proneness into four categories with sharply differing probabilities of road accidents. It has been shown that there is a possibility of classification of drivers in accordance with specified categories.
基金supported by the New Generation of Information Technology Innovation Project of China University Innovation Fund of Ministry of Education(Grant No.2022IT191)the Qingdao Top Talent Program of Innovation and Entrepreneurship(Grant No.19-3-2-8-zhc)+2 种基金the project'Research and Development of Key Technologies and Systems for Unmanned Navigation of Coastal Ships'of the National Key Research and Development Program(Grant No.2018YFB1601500)the General Project of Natural Science Foundation of Shandong Province of China(Grant No.ZR2020MF082)Shandong Intelligent Green Manufacturing Technology and Equipment Collaborative Innovation Center(Grant No.IGSD-2020-012).
文摘Risky driving behaviors,such as driving fatigue and distraction have recently received more attention.There is also much research about driving styles,driving emotions,older drivers,drugged driving,DUI(driving under the influence),and DWI(driving while intoxicated).Road hypnosis is a special behavior significantly impacting traffic safety.However,there is little research on this phenomenon.Road hypnosis,as an unconscious state,is can frequently occur while driving,particularly in highly predictable,monotonous,and familiar environments.In this paper,vehicle and virtual driving experiments are designed to collect the biological characteristics including eye movement and bioelectric parameters.Typical scenes in tunnels and highways are used as experimental scenes.LSTM(Long Short-Term Memory)and KNN(K-Nearest Neighbor)are employed as the base learners,while SVM(Support Vector Machine)serves as the meta-learner.A road hypnosis identification model is proposed based on ensemble learning,which integrates bioelectric and eye movement characteristics.The proposed model has good identification performance,as seen from the experimental results.In this study,alternative methods and technical support are provided for real-time and accurate identification of road hypnosis.
文摘Most previous studies on the market efficiency of cryptocurrencies consider time evolution but do not provide insights into the potential driving factors.This study addresses this limitation by examining the time-varying efficiency of the two largest cryptocurrencies,Bitcoin and Ethereum,and the factors that drive efficiency.It uses daily data from August 7,2016,to February 15,2023,the adjusted market inefficiency magnitude(AMIMs)measure,and quantile regression.The results show evidence of time variation in the levels of market(in)efficiency for Bitcoin and Ethereum.Interestingly,the quantile regressions indicate that global financial stress negatively affects the AMIMs measures across all quantiles.Notably,cryptocurrency liquidity positively and significantly affects AMIMs irrespective of the level of(in)efficiency,whereas the positive effect of money flow is significant when the markets of both cryptocurrencies are efficient.Finally,the COVID-19 pandemic positively and significantly affected cryptocurrency market inefficiencies across most quantiles.
文摘Familiar and unfamiliar drivers may exhibit different behaviours in response to the road environment.Overall familiarity with the road environment is a human factor believed to play a role in road crash injury severity due to its effect on a driver’s decision-making process,reaction time,etc.Hence,there is a need to separately analyse familiar and unfa miliar drivers regarding the injury severity of crashes.Using a six-year database of 30,481 rural two-vehicle crashes in Guilan province,Iran,this research first defined four categories of crashes,reflecting various levels of the involved drivers’familiarity with the environ ment(72%of drivers were from the same vs.28%from a different province).Next,the injury severity of crashes in each familiarity crash category was analysed using both non-parametric(classification and regression trees)and parametric(logistic regression)methods.When both crash parties were unfamiliar,several results are different compared to whenboth parties were familiar or when ignoring driver familiarity.For instance,young at-fault drivers increased the injury severity of crashes if they were unfamiliar,while they decreased the crash severity if they were familiar.Also,crashes in winter tended to be more severe when one or especially both crash parties were unfamiliar,but winter crashes were less severe when both drivers were familiar or when driver familiarity was ignored.Overall,when both drivers were familiar,63%of crashes were injury/fatal;however,when both drivers were unfamiliar,only 31%of crashes involved an injury or fatality.
文摘Motor vehicle crashes are the leading cause of the death of teenagers in the United States.Young drivers have shown a higher propensity to get involved in crashes due to using a cellphone while driving,breaking the speed limit,and reckless driving.This study analyzed motor vehicle crashes involving young drivers using New Jersey crash data.Specifically,four years of crash data(2016-2019)were gathered and analyzed.Different machine learning(ML)methods,such as Random Forest,Light GBM,Catboost,and XGBoost,were used to predict the injury severity.The performance of the models was evaluated using accuracy,precision,and recall scores.In addition,interpretable ML techniques like sensitivity analysis and Shapley values were conducted to assess the most influential factors’impacts on young driver-related crashes.The results revealed that XGBoost performed better than Random Forest,CatBoost,and LightGBM models in crash severity prediction.Results from the sensitivity analysis showed that multi-vehicle crashes,angular crashes,crashes at intersections,and dark-not-lit conditions had increased crash severity.A partial dependence plot of SHAP values revealed that speeding in clear weather had a higher likelihood of injury crashes,and multi-vehicle crashes at the intersection had more injury crashes.We expect that the results obtained from this study will help policymakers and practitioners take appropriate countermeasures to improve the safety of young drivers in New Jersey.
基金supported by the National Natural Science Foundation of China(Grant No.31470630)Shanxi Forestry Science and Technology Innovation Project
文摘Understory plants are important components of forest ecosystems and play a crucial role in regulating community structures,function realization,and community succession.However,little is known about how abiotic and biotic drivers affect the diversity of understory species in cold temperate coniferous forests in the semiarid climate region of North China.We hypothesized that(1)topographic factors are important environmental factors affecting the distribution and variation of understory strata,and(2)different understory strata respond differently to environmental factors;shrubs may be significantly affected by the overstory stratum,and herbs may be more affected by surface soil conditions.To test these hypotheses,we used the boosted regression tree method to analyze abiotic and biotic environmental factors that influence understory species diversity,using data from 280 subplots across 56 sites in cold temperate coniferous forests of North China.Elevation and slope aspect were the dominant and indirect abiotic drivers affecting understory species diversity,and individual tree size inequality(DBH variation)was the dominant biotic driver of understory species diversity;soil water content was the main edaphic factors affecting herb layers.Elevation,slope aspect,and DBH variation accounted for 36.4,14.5,and 12.1%,respectively,of shrub stratum diversity.Shrub diversity decreased with elevation within the range of altitude of this study,but increased with DBH variation;shrub diversity was highest on north-oriented slopes.The strongest factor affecting herb stratum species diversity was slope aspect,accounting for 25.9%of the diversity,followed by elevation(15.7%),slope(12.2%),and soil water content(10.3%).The highest herb diversity was found on southeast-oriented slopes and the lowest on northeast-oriented slopes;herb diversity decreased with elevation and soil water content,but increased with slope.The results of the study provide a reference for scientific management and biodiversity protection in cold temperate coniferous forests of North China.
