Developing and exploring organic-inorganic hybrid multi-lanthanide(Ln)implanted heteropolyoxometalates(HPOMs)has bloomed into an emerging research fieId.In this article,two neoteric Dgluconic acids(H_(6)GA)concatenati...Developing and exploring organic-inorganic hybrid multi-lanthanide(Ln)implanted heteropolyoxometalates(HPOMs)has bloomed into an emerging research fieId.In this article,two neoteric Dgluconic acids(H_(6)GA)concatenating multi-Ln^(Ⅲ) implanted heteropoly tungstates K_(14)H_(10)[Ln_(4)(H_(2)O)_(4)W_(6)(H_(2)-GA)_(4) O_(12)(B-α-TeW_(9)O_(33))_(4)]·60 H_(2)O(Ln=La^(3+)(1),Pr^(3+)(2))were obtained in acidic aqueous system.Attractively,in the polyanion structure of 1 and 2,six WⅥand four LnⅢcenters are connected by four flexible H_(2)GA^(4-) ligands via carboxyl and hydroxyl groups,resulting in the heterometallic[Ln_(4)(H_(2)O)_(4)W_(6)H_(2)GA)_(4)O_(12)]^(8+)cluster and then the heterometallic cluster is surrounded by four[B-α-TeW_(9)O_(33)]^(8-)segments.Electrochemical measurements for the 1@CFMCN/GCE sensor(CFMCN=carboxylfunctionalized multiwalled carbon nanotube;GCE=glass carbon electrode)demonstrate that 1@CFMCN/GCE shows benign recognition response to detecting noradrenaline(NDA).This research expands the structural diversity of Ln-implanted HPOMs and presents an electrochemical platform of recognizing NDA in the field of biosensors.展开更多
The drive to reduce carbon emissions and meet climate change targets set by governments worldwide has led to the growth of renewable energy sources and electric vehicles in recent years.Resulting intermittent generati...The drive to reduce carbon emissions and meet climate change targets set by governments worldwide has led to the growth of renewable energy sources and electric vehicles in recent years.Resulting intermittent generation and centralised demand require increased transmission capacities when operating associated power systems.Existing transmission lines are not capable of meeting planned needs.In many countries,obtaining a new right of way to build an overhead line(OHL)is increasingly difficult.There is therefore an urgent need to study techniques for transmission line uprating.Simply increasing voltages is not feasible because elevated surface potential gradient at conductor surfaces increases audible noise(AN)levels unacceptably.The feasibility of high phase order,especially six-phase,transmission techniques has been previously demonstrated,and it has been proved to be an effective way to uprate existing three-phase double circuit OHLs with increased voltages.This study analyses two typical overhead line structures,whose conductor surface potential gradient and AN level are calculated.The average and maximum surface potential gradient of the six-phase OHL are 18.5%and 18.6%lower than that of the three-phase ones.The AN of the six-phase single circuit OHL is predicted to be 6.33 and 6.45 dBA lower than that of the three-phase double circuit OHL after the voltage is increased by 45%and 50%for the lines considered.It is shown that six-phase OHLs can increase capacity by allowing elevating phase voltages without increasing acoustic noise levels.展开更多
Computer vision is a field that involves making a machine “see”.This technology uses a camera and computer instead of the human eye to identify,track and measure targets for further image processing.With the develop...Computer vision is a field that involves making a machine “see”.This technology uses a camera and computer instead of the human eye to identify,track and measure targets for further image processing.With the development of computer vision,such technology has been widely used in the field of agricultural automation and plays a key role in its development.This review systematically summarizes and analyzes the technologies and challenges over the past three years and explores future opportunities and prospects to form the latest reference for researchers.Through the analyses,it is found that the existing technology can help the development of agricultural automation for small field farming to achieve the advantages of low cost,high efficiency and high precision.However,there are still major challenges.First,the technology will continue to expand into new application areas in the future,and there will be more technological issues that need to be overcome.It is essential to build large-scale data sets.Second,with the rapid development of agricultural automation,the demand for professionals will continue to grow.Finally,the robust performance of related technologies in various complex environments will also face challenges.Through analysis and discussion,we believe that in the future,computer vision technology will be combined with intelligent technology such as deep learning technology,be applied to every aspect of agricultural production management based on large-scale datasets,be more widely used to solve the current agricultural problems,and better improve the economic,general and robust performance of agricultural automation systems,thus promoting the development of agricultural automation equipment and systems in a more intelligent direction.展开更多
基金Project supported by the National Natural Science Foundation of China(21871077,21671054,21771052,22071042,22001058,22171070)the Program for Innovation Teams in Science and Technology in Universities of Henan Province(20IRTSTHN004)。
文摘Developing and exploring organic-inorganic hybrid multi-lanthanide(Ln)implanted heteropolyoxometalates(HPOMs)has bloomed into an emerging research fieId.In this article,two neoteric Dgluconic acids(H_(6)GA)concatenating multi-Ln^(Ⅲ) implanted heteropoly tungstates K_(14)H_(10)[Ln_(4)(H_(2)O)_(4)W_(6)(H_(2)-GA)_(4) O_(12)(B-α-TeW_(9)O_(33))_(4)]·60 H_(2)O(Ln=La^(3+)(1),Pr^(3+)(2))were obtained in acidic aqueous system.Attractively,in the polyanion structure of 1 and 2,six WⅥand four LnⅢcenters are connected by four flexible H_(2)GA^(4-) ligands via carboxyl and hydroxyl groups,resulting in the heterometallic[Ln_(4)(H_(2)O)_(4)W_(6)H_(2)GA)_(4)O_(12)]^(8+)cluster and then the heterometallic cluster is surrounded by four[B-α-TeW_(9)O_(33)]^(8-)segments.Electrochemical measurements for the 1@CFMCN/GCE sensor(CFMCN=carboxylfunctionalized multiwalled carbon nanotube;GCE=glass carbon electrode)demonstrate that 1@CFMCN/GCE shows benign recognition response to detecting noradrenaline(NDA).This research expands the structural diversity of Ln-implanted HPOMs and presents an electrochemical platform of recognizing NDA in the field of biosensors.
文摘The drive to reduce carbon emissions and meet climate change targets set by governments worldwide has led to the growth of renewable energy sources and electric vehicles in recent years.Resulting intermittent generation and centralised demand require increased transmission capacities when operating associated power systems.Existing transmission lines are not capable of meeting planned needs.In many countries,obtaining a new right of way to build an overhead line(OHL)is increasingly difficult.There is therefore an urgent need to study techniques for transmission line uprating.Simply increasing voltages is not feasible because elevated surface potential gradient at conductor surfaces increases audible noise(AN)levels unacceptably.The feasibility of high phase order,especially six-phase,transmission techniques has been previously demonstrated,and it has been proved to be an effective way to uprate existing three-phase double circuit OHLs with increased voltages.This study analyses two typical overhead line structures,whose conductor surface potential gradient and AN level are calculated.The average and maximum surface potential gradient of the six-phase OHL are 18.5%and 18.6%lower than that of the three-phase ones.The AN of the six-phase single circuit OHL is predicted to be 6.33 and 6.45 dBA lower than that of the three-phase double circuit OHL after the voltage is increased by 45%and 50%for the lines considered.It is shown that six-phase OHLs can increase capacity by allowing elevating phase voltages without increasing acoustic noise levels.
基金The work in this paperwas supported by the National Natural Science Foundation for Young Scientists of China(31801804)the Guangxi Innovation-Driven Development Special Fund Project(GuikeAA18242011)+1 种基金the Key Research and Development Program of Nanning(20192065)the Fund Project of the Key Laboratory of Integrated Pest Management on Crops in South China,Ministry of Agriculture and Rural Area,P.R.China(SCIPM2018-05).
文摘Computer vision is a field that involves making a machine “see”.This technology uses a camera and computer instead of the human eye to identify,track and measure targets for further image processing.With the development of computer vision,such technology has been widely used in the field of agricultural automation and plays a key role in its development.This review systematically summarizes and analyzes the technologies and challenges over the past three years and explores future opportunities and prospects to form the latest reference for researchers.Through the analyses,it is found that the existing technology can help the development of agricultural automation for small field farming to achieve the advantages of low cost,high efficiency and high precision.However,there are still major challenges.First,the technology will continue to expand into new application areas in the future,and there will be more technological issues that need to be overcome.It is essential to build large-scale data sets.Second,with the rapid development of agricultural automation,the demand for professionals will continue to grow.Finally,the robust performance of related technologies in various complex environments will also face challenges.Through analysis and discussion,we believe that in the future,computer vision technology will be combined with intelligent technology such as deep learning technology,be applied to every aspect of agricultural production management based on large-scale datasets,be more widely used to solve the current agricultural problems,and better improve the economic,general and robust performance of agricultural automation systems,thus promoting the development of agricultural automation equipment and systems in a more intelligent direction.
基金financially supported by the National Natural Science Foundation of China (21731002, 21975104, 22071141 and 21471094)Guangdong Major Project of Basic and Applied Research (2019B030302009)Guangdong Basic and Applied Basic Research Foundation (2019A1515012162)