The energy demand in Australia is increasing with the industrialization and rapid economic growth.This study analyzed the relationships among the economic growth,Foreign Direct Investment(FDI),trade openness,urbanizat...The energy demand in Australia is increasing with the industrialization and rapid economic growth.This study analyzed the relationships among the economic growth,Foreign Direct Investment(FDI),trade openness,urbanization,and energy usage in Australia based on the data from World Development Indicators(WDI)from 1972 to 2021.The results indicates that there is a cointegration among economic growth,FDI,trade openness,urbanization,and energy usage,which was traced through the autoregressivedistributed lag(ARDL).The Zivot-Andrews unit root test reveals that energy usage,economic growth,FDI,urbanization,and trade openness show significant structural breaks in 1993,1996,1982,2008,and 1994,respectively.The ARDL model shows that economic growth has a positive and significant effect on energy usage in the long-run(0.814)and short-run(0.809).Moreover,the results also show that FDI(0.028)and trade openness(0.043)have positive impacts on energy usage in the long-run.However,urbanization shows a negative and significant influence on energy usage in the long-run(–0.965).Then,the research demonstrates a unidirectional causation between energy usage and trade openness,with energy usage significantly causing trade openness.The current study endorses energy consumption policies and investment strategies for a paradigm shifting from a reliance on fossil fuels as the primary energy source to renewable energy sources.These findings have profound implications for sustainable energy usage.展开更多
The present study has been carried out on a total of 50 available plant species to assess their dust-capturing capacity and biochemical performances in and around open cast granite mine areas of Jhansi district and Bu...The present study has been carried out on a total of 50 available plant species to assess their dust-capturing capacity and biochemical performances in and around open cast granite mine areas of Jhansi district and Bundelkhand University campus treated as control site. Plant species existing under a polluted environment for a long time may be considered as potentially resistant species and recommended for green belt design in mining areas, especially to cope with dust pollution. Results showed the pollution level, especially of mining-originated dust particles holding capacity of leaves and effects of different biochemical parameters (Total Chlorophyll, Protein and Carotenoid) of existing plant species both from mining areas as well as from Bundelkhand University campus. Based on their performances, Tectona grandis L., Ficus hispida L., Calotropis procera Aiton., Butea monosperma Lam. and Ficus benghalensis L., etc. are highly tolerant species while Ficus infectoria L., Artocarpus heterophyllus Lam., Ipomoea purpurea L., Allianthus excelsa Roxb. and Bauhinia variegata L. are intermediate tolerant species. T. grandis had shown the highest dust-holding capacity (2.566 ± 0.0004 mg/cm2) whereas Albizia procera (0.018 ± 0.0002 mg/cm2) was found to be the lowest dust-holding capacity. Our findings also showed that the T. grandis and F. hispida have significant dust deposition with minimal effect of dust on their leaf chlorophyll (17.447 ± 0.019 mg/g and 14.703 ± 0.201 mg/g), protein (0.699 ± 0.001 mg/g and 0.604 ± 0.002 mg/g) and carotenoid (0.372 ± 0.003 mg/g and 0.354 ± 0.003 mg/g) content respectively among all selected plant species. Therefore, in the present investigation, plant species with high tolerance to high dust-holding capacity on their leaf surfaces are preferable for green corridors as open cast granite mines and their adjacent areas.展开更多
Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,auton...Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,autonomous vehicles(AVs)are expected to have exceptional perception systems to capture instantaneously their driving environments for predicting lane changes.By exploring the Waymo open motion dataset,this study proposes a framework to explore autonomous driving data and investigate lane change behaviors.In the framework,this study develops a Long Short-Term Memory(LSTM)model to predict lane changing behaviors.The concept of Vehicle Operating Space(VOS)is introduced to quantify a vehicle's instantaneous driving environment as an important indicator used to predict vehicle lane changes.To examine the robustness of the model,a series of sensitivity analysis are conducted by varying the feature selection,prediction horizon,and training data balancing ratios.The test results show that including VOS into modeling can speed up the loss decay in the training process and lead to higher accuracy and recall for predicting lane-change behaviors.This study offers an example along with a methodological framework for transportation researchers to use emerging autonomous driving data to investigate driving behaviors and traffic environments.展开更多
In 2023,Baishideng Publishing Group(Baishideng)routinely published 47 openaccess journals,including 46 English-language journals and 1 Chinese-language journal.Our successes were accomplished through the collective de...In 2023,Baishideng Publishing Group(Baishideng)routinely published 47 openaccess journals,including 46 English-language journals and 1 Chinese-language journal.Our successes were accomplished through the collective dedicated efforts of Baishideng staffs,Editorial Board Members,and Peer Reviewers.Among these 47 Baishideng journals,7 are included in the Science Citation Index Expanded(SCIE)and 6 in the Emerging Sources Citation Index(ESCI).With the support of Baishideng authors,company staffs,Editorial Board Members,and Peer Reviewers,the publication work of 2023 is about to be successfully completed.This editorial summarizes the 2023 activities and accomplishments of the 13 SCIEand ESCI-indexed Baishideng journals,outlines the Baishideng publishing policy changes and additions made this year,and highlights the unique advantages of Baishideng journals.展开更多
文摘The energy demand in Australia is increasing with the industrialization and rapid economic growth.This study analyzed the relationships among the economic growth,Foreign Direct Investment(FDI),trade openness,urbanization,and energy usage in Australia based on the data from World Development Indicators(WDI)from 1972 to 2021.The results indicates that there is a cointegration among economic growth,FDI,trade openness,urbanization,and energy usage,which was traced through the autoregressivedistributed lag(ARDL).The Zivot-Andrews unit root test reveals that energy usage,economic growth,FDI,urbanization,and trade openness show significant structural breaks in 1993,1996,1982,2008,and 1994,respectively.The ARDL model shows that economic growth has a positive and significant effect on energy usage in the long-run(0.814)and short-run(0.809).Moreover,the results also show that FDI(0.028)and trade openness(0.043)have positive impacts on energy usage in the long-run.However,urbanization shows a negative and significant influence on energy usage in the long-run(–0.965).Then,the research demonstrates a unidirectional causation between energy usage and trade openness,with energy usage significantly causing trade openness.The current study endorses energy consumption policies and investment strategies for a paradigm shifting from a reliance on fossil fuels as the primary energy source to renewable energy sources.These findings have profound implications for sustainable energy usage.
文摘The present study has been carried out on a total of 50 available plant species to assess their dust-capturing capacity and biochemical performances in and around open cast granite mine areas of Jhansi district and Bundelkhand University campus treated as control site. Plant species existing under a polluted environment for a long time may be considered as potentially resistant species and recommended for green belt design in mining areas, especially to cope with dust pollution. Results showed the pollution level, especially of mining-originated dust particles holding capacity of leaves and effects of different biochemical parameters (Total Chlorophyll, Protein and Carotenoid) of existing plant species both from mining areas as well as from Bundelkhand University campus. Based on their performances, Tectona grandis L., Ficus hispida L., Calotropis procera Aiton., Butea monosperma Lam. and Ficus benghalensis L., etc. are highly tolerant species while Ficus infectoria L., Artocarpus heterophyllus Lam., Ipomoea purpurea L., Allianthus excelsa Roxb. and Bauhinia variegata L. are intermediate tolerant species. T. grandis had shown the highest dust-holding capacity (2.566 ± 0.0004 mg/cm2) whereas Albizia procera (0.018 ± 0.0002 mg/cm2) was found to be the lowest dust-holding capacity. Our findings also showed that the T. grandis and F. hispida have significant dust deposition with minimal effect of dust on their leaf chlorophyll (17.447 ± 0.019 mg/g and 14.703 ± 0.201 mg/g), protein (0.699 ± 0.001 mg/g and 0.604 ± 0.002 mg/g) and carotenoid (0.372 ± 0.003 mg/g and 0.354 ± 0.003 mg/g) content respectively among all selected plant species. Therefore, in the present investigation, plant species with high tolerance to high dust-holding capacity on their leaf surfaces are preferable for green corridors as open cast granite mines and their adjacent areas.
文摘Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,autonomous vehicles(AVs)are expected to have exceptional perception systems to capture instantaneously their driving environments for predicting lane changes.By exploring the Waymo open motion dataset,this study proposes a framework to explore autonomous driving data and investigate lane change behaviors.In the framework,this study develops a Long Short-Term Memory(LSTM)model to predict lane changing behaviors.The concept of Vehicle Operating Space(VOS)is introduced to quantify a vehicle's instantaneous driving environment as an important indicator used to predict vehicle lane changes.To examine the robustness of the model,a series of sensitivity analysis are conducted by varying the feature selection,prediction horizon,and training data balancing ratios.The test results show that including VOS into modeling can speed up the loss decay in the training process and lead to higher accuracy and recall for predicting lane-change behaviors.This study offers an example along with a methodological framework for transportation researchers to use emerging autonomous driving data to investigate driving behaviors and traffic environments.
文摘In 2023,Baishideng Publishing Group(Baishideng)routinely published 47 openaccess journals,including 46 English-language journals and 1 Chinese-language journal.Our successes were accomplished through the collective dedicated efforts of Baishideng staffs,Editorial Board Members,and Peer Reviewers.Among these 47 Baishideng journals,7 are included in the Science Citation Index Expanded(SCIE)and 6 in the Emerging Sources Citation Index(ESCI).With the support of Baishideng authors,company staffs,Editorial Board Members,and Peer Reviewers,the publication work of 2023 is about to be successfully completed.This editorial summarizes the 2023 activities and accomplishments of the 13 SCIEand ESCI-indexed Baishideng journals,outlines the Baishideng publishing policy changes and additions made this year,and highlights the unique advantages of Baishideng journals.
