Developing an anthropogenic carbon dioxides(CO_(2))emissions monitoring and verification support(MVS)capacity is essential to support the Global Stocktake(GST)and ratchet up Nationally Determined Contributions(NDCs).T...
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Developing an anthropogenic carbon dioxides(CO_(2))emissions monitoring and verification support(MVS)capacity is essential to support the Global Stocktake(GST)and ratchet up Nationally Determined Contributions(NDCs).The 2019 IPCC refinement proposes top-down inversed CO_(2)emissions,primarily from fossil fuel(FFCO_(2)),as a viable emission *** substantial progress in directly inferring FFCO_(2)emissions from CO_(2)observations,substantial challenges remain,particularly in distinguishing local CO_(2)enhancements from the high background due to the long atmospheric ***,using short-lived and co-emitted nitrogen dioxide(NO_(2))as a proxy in FFCO_(2)emission inversion has gained *** methodology is broadly categorized into plume-based and emission ratios(ERs)-based inversion *** the plume-based methods,NO_(2)observations act as locators,constraints,and validators for deciphering CO_(2)plumes downwind of sources,typically at point source and city *** ERs-based inversion approach typically consists of two steps:inferring NO_(2)-based nitrogen oxides(NO_(x))emissions and converting NO_(x)to CO_(2)emissions using CO_(2)-to-NO_(x)*** integrating NO_(2)observations into FFCO_(2)emission inversion offers advantages over the direct CO_(2)-based methods,uncertainties persist,including both structural and data-related *** these uncertainties is a primary focus for future research,which includes deploying nextgeneration satellites and developing advanced inversion ***,data caveats are necessary when releasing data to users to prevent potential *** NO_(2)-based CO_(2)emission inversion requires interdisciplinary collaboration across multiple communities of remote sensing,emission inventory,transport model improvement,and atmospheric inversion algorithm development.
This letter aims to learn a global representation for each point in a random cluster using only purely local geometric or topological information. Based on this, distributed tags for indoor positioning break the atomi...
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This letter aims to learn a global representation for each point in a random cluster using only purely local geometric or topological information. Based on this, distributed tags for indoor positioning break the atomicity of tags and make deployment more arbitrary. It also allows NP-hard matches to be quickly estimated with only one local observation. The novel self-supervised topological representation learning method only takes local point clusters as input and utilizes the proposed cluster-based sampling, training, and loss functions to form global self-comparison. The training samples are generated in real-time virtually, and there are few matching errors after being transferred to practice. The compact backbone network directly processes the coordinates of points and abandons the iterative optimization commonly used in matching. Moreover, it uses the representation to measure similarity directly, and the inference speed reaches the millisecond level. In the actual and virtual experiments, the local point clusters are surprisingly accurately matched to the random global ones. The localization based on this is also verified, and the relevant results prove the effectiveness of the proposed method.
INSPIRED by the insight from American political scientist Lasswell, who summarized the environmental role in societal surveillance [1], Schramm coined the term “social radar” [2] as it resembles the activities of ra...
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INSPIRED by the insight from American political scientist Lasswell, who summarized the environmental role in societal surveillance [1], Schramm coined the term “social radar” [2] as it resembles the activities of radar in collecting and processing information, playing a crucial role in helping humans perceive changes in the internal and external environment and promptly adjusting adaptive behaviors.
Recent increases in emissions from freight transport have caused strong concerns about air quality in Pakistan,following the rapid development of projects related to the China-Pakistan Economic Corridor(CPEC).This stu...
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Recent increases in emissions from freight transport have caused strong concerns about air quality in Pakistan,following the rapid development of projects related to the China-Pakistan Economic Corridor(CPEC).This study reported the first measurements of on-road truck emissions in Pakistan and investigated their dependence on altitude along CPEC *** from 70 trucks were measured on CPEC highways located in Islamabad(540 m above sea level),Sost(2800 m above sea level),and at the Khunjerab Pass(4693 m above sea level).Calculated emission factors for carbon monoxide,hydrocarbons,and nitrogen oxides from heavy-duty trucks in Islamabad were 12.94±1.46,15.21±1.67,and 10.69±1.34 g km^(-1)(95%confidence level),respectively,for pre-Pak-II trucks,and 12.75±2.80,14.24±3.53,and 10.24±2.34 g km^(-1)(95%confidence level),respectively,for Pak-II trucks,representing 2e20 times higher values than the emission standards in Pakistan and *** altitude increase of approximately 4000 m,with the associated changes in meteorology and fleet characteristics,induced an average increase of 103.6%,86.3%,124.5%,and 133.6%in the emission factors of carbon monoxide,hydrocarbons,nitrogen oxides,and carbon dioxide,***,on-road emissions along the CPEC were mainly influenced by truck *** study will support the budget evaluation of transport emissions from the CPEC trade fleet.
The broad and powerful pectoral fins of manta rays are crucial to their efficient and maneuverable swimming. However, very little is currently known about the pectoral-fin-driven 3-D locomotion of manta-inspired robot...
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The broad and powerful pectoral fins of manta rays are crucial to their efficient and maneuverable swimming. However, very little is currently known about the pectoral-fin-driven 3-D locomotion of manta-inspired robots. This study is focused on the development and 3-D path-following control of an agile robotic manta. First, a novel robotic manta with 3-D mobility is constructed, of which the distinctive pectoral fins provide the only propulsion. Specifically, the unique pitching mechanism is detailed in which the time-coupled coordination movement of the pectoral fins is applied. Second, based on a 6-axis force measuring platform, the propulsion characteristics of the flexible pectoral fins are analyzed. Then, the force-data-driven 3-D dynamic model is further established. Third, a control scheme combined with a line-of-sight (LOS) guidance system and a sliding-mode fuzzy controller is conceived, addressing the 3-D path-following task. Finally, various simulated and aquatic experiments are conducted, demonstrating the superior performance of our prototype and the effectiveness of the proposed path-following scheme. This study will hopefully generate fresh insights into the updated design and control of agile bioinspired robots performing underwater tasks in dynamic environments.
POWERED by the rapid development of Internet,the penetration of the Internet of Things,the emergence of big data,and the rise of social media,more and more complex systems are exhibiting the characteristics of social,...
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POWERED by the rapid development of Internet,the penetration of the Internet of Things,the emergence of big data,and the rise of social media,more and more complex systems are exhibiting the characteristics of social,physical,and information *** systems are known as cyber-physicalsocial systems(CPSS)[1],[2].These CPSS face unprecedented challenges in design,analysis,management,control and integration due to their involvement with human and social factors[3],[4].To cope with this challenge,there are two main approaches to CPSS research.
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