Formaldehyde(HCHO)is a high-yield product of the oxidation of volatile organic compounds(VOCs)released by anthropogenic activities,fires,and vegetations.Hence,we examined the spatiotemporal variation trends in HCHO co...Formaldehyde(HCHO)is a high-yield product of the oxidation of volatile organic compounds(VOCs)released by anthropogenic activities,fires,and vegetations.Hence,we examined the spatiotemporal variation trends in HCHO columns observed using the Ozone Monitoring Instrument(OMI)during 2005–2021 across the Fenwei Plain(FWP)and analysed the source and variability of HCHO using multi-source data,such as thermal anomalies.The spatial distribution of the annualmean HCHO in the FWP increased from northwest to southeast during 2005–2021,and the high-value aggregation areas contracted and gradually clustered,forming a belt-shaped distribution area from Xi’an to Baoji,north of the Qinling Mountains.The annual mean HCHO concentration generally showed a two-step increase over the 17 years.Fires showed a single-peak trend in March and a double-peak M-shaped trend in March and October,whereas urban thermal anomalies(UTAs)showed an inverted U-shaped trend over 17 years,with peaks occurring in May.The HCHO peaks are mainly caused by the alternating contributions of fires and UTAs.The fires and UTAs(predominantly industrial heat sources)played a role in controlling the background level of HCHO in the FWP.Precipitation and temperature were also important influencing variables for seasonal variations,and the influence of plant sources on HCHO concentrations had significant regional characteristics and contributions.In addition,the FWP has poor dispersion conditions and is an aggregated area for the long-range transport of air pollutants.展开更多
The convergence of large language models(LLMs)and virtual reality(VR)technologies has led to significant breakthroughs across multiple domains,particularly in healthcare and medicine.Owing to its immersive and interac...The convergence of large language models(LLMs)and virtual reality(VR)technologies has led to significant breakthroughs across multiple domains,particularly in healthcare and medicine.Owing to its immersive and interactive capabilities,VR technology has demonstrated exceptional utility in surgical simulation,rehabilitation,physical therapy,mental health,and psychological treatment.By creating highly realistic and precisely controlled environments,VR not only enhances the efficiency of medical training but also enables personalized therapeutic approaches for patients.The convergence of LLMs and VR extends the potential of both technologies.LLM-empowered VR can transform medical education through interactive learning platforms and address complex healthcare challenges using comprehensive solutions.This convergence enhances the quality of training,decision-making,and patient engagement,paving the way for innovative healthcare delivery.This study aims to comprehensively review the current applications,research advancements,and challenges associated with these two technologies in healthcare and medicine.The rapid evolution of these technologies is driving the healthcare industry toward greater intelligence and precision,establishing them as critical forces in the transformation of modern medicine.展开更多
Vanadium oxide cathode materials with stable crystal structure and fast Zn^(2+) storage capabilities are extremely important to achieving outstanding electrochemical performance in aqueous zinc‐ion batteries.In this ...Vanadium oxide cathode materials with stable crystal structure and fast Zn^(2+) storage capabilities are extremely important to achieving outstanding electrochemical performance in aqueous zinc‐ion batteries.In this work,a one‐step hydrothermal method was used to manipulate the bimetallic ion intercalation into the interlayer of vanadium oxide.The pre‐intercalated Cu ions act as pillars to pin the vanadium oxide(V‐O)layers,establishing stabilized two‐dimensional channels for fast Zn^(2+) diffusion.The occupation of Mn ions between V‐O interlayer further expands the layer spacing and increases the concentration of oxygen defects(Od),which boosts the Zn^(2+) diffusion kinetics.As a result,as‐prepared Cu_(0.17)Mn_(0.03)V_(2)O_(5−□)·2.16H_(2)O cathode shows outstanding Zn‐storage capabilities under room‐and lowtemperature environments(e.g.,440.3 mAh g^(−1) at room temperature and 294.3 mAh g^(−1)at−60°C).Importantly,it shows a long cycling life and high capacity retention of 93.4%over 2500 cycles at 2 A g^(−1) at−60°C.Furthermore,the reversible intercalation chemistry mechanisms during discharging/charging processes were revealed via operando X‐ray powder diffraction and ex situ Raman characterizations.The strategy of a couple of 3d transition metal doping provides a solution for the development of superior room‐/lowtemperature vanadium‐based cathode materials.展开更多
Annual mass balance is an important factor that reflects glacier change and glacier meltwater resources.In this study,we analyzed the changes in glacier area,snow line altitude(SLA)and surface elevation in theány...Annual mass balance is an important factor that reflects glacier change and glacier meltwater resources.In this study,we analyzed the changes in glacier area,snow line altitude(SLA)and surface elevation in theányêmaqên Mountain region using multisource remote sensing data.Then,the annual mass balance of two glaciers was reconstructed by using SLA-mass-balance gradient method.The results showed that the glacier area in theányêmaqên Mountains decreased by 29.4 km2from 1985 to 2017.The average SLAs of the Halong Glacier and Yehelong Glacier were approximately 5290 m and 5188 m,respectively.The glacier mass balance for the two glaciers from 1990 to 2020 was-0.71 m w.e.a^(-1) and-0.63 m w.e.a^(-1),respectively.Our results indicate that SLA is an important indicator of glacier changes,and a long sequence of SLAs can more accurately reconstruct the glacier mass balance of the glacier.The mean annual glacial meltwater-fed streamflow is 1.45×10^(7)m^(3) and 1.12×10^(7)m^(3),respectively.Sensitivity analysis indicates that summer air temperature plays a leading role in regard to the influential climatic factors of glacial retreat in theányêmaqên Mountains.This highlights the potential of the methodology for application on reconstructing annual glacier surface mass balance at larger scales without direct measurements.展开更多
From 2008 to 2010, a total of 15 snow pit samples were collected from 13 mountain glaciers in western China. In this study these samples are used to determine the spatial distribution of insoluble particle concentrati...From 2008 to 2010, a total of 15 snow pit samples were collected from 13 mountain glaciers in western China. In this study these samples are used to determine the spatial distribution of insoluble particle concentrations and dust deposition fluxes in western China. The results show that the mass concentrations of insoluble particles exhibit high spatial variation and strongly decrease （by a factor of approximately 50） from the north （Tienshan Mountains） to the south （Himalayas）. However, the insoluble particles concentrations at the southeastern Tibetan Plateau （TP） sites are also high and ap- proximately 30 times greater than those in the Himalayas. The spatial distribution of the dust flux is similar to that of the mass concentrations; however, the high dust deposition rate in the southeastern TP is very significant as a result of the extensive snow accumulation （precipitation） in this region. The average sizes of the insoluble particles at each site generally exhibit bimodal distributions with peaks at approximately 5 μm and 10 μm, which can be explained as re- sulting from dust emissions from regional and local sources, respectively. The enrichment factors for most of the elements measured in insoluble particles are less than 10 at all of the study sites, indicating primarily crustal sources. However, the sites located in the peripheral mountains of western China, such as the Tienshan Mountains and the Himalayas, are characterized by high levels of certain enrichment elements （e.g., Cu, Zn, Cr, and V） indicative of sources related to the long-range transport of pollutants.展开更多
Though being considered strategically important in matters of national defense based on its abundance of natural resources,Northwest China is one of the most ecologically vulnerable areas in the country. As one of the...Though being considered strategically important in matters of national defense based on its abundance of natural resources,Northwest China is one of the most ecologically vulnerable areas in the country. As one of the region's important water sources,glaciers have gone through major changes due to climate change. An analysis of research results over the past 60 years reveals that the glaciers have been retreating in general to some degree in large river basins in Northwest China,but the rate of retreating varied largely among different regions,ranging from 0. 01% ·a^(-1) to 0. 75% ·a^(-1). Specifically,glaciers around the Lantsang River Basin and the Altay Mountains have been retreating fastest. The retreat of glaciers has already caused an increase in runoff in mountainous areas of Northwest China. Meanwhile,increases in the frequency of glacial flash floods and in the flood discharge will further enhance the probability of glacial lake outburst floods and ensuing disasters.展开更多
Learning and inferring underlying motion patterns of captured 2D scenes and then re-creating dynamic evolution consistent with the real-world natural phenomena have high appeal for graphics and animation.To bridge the...Learning and inferring underlying motion patterns of captured 2D scenes and then re-creating dynamic evolution consistent with the real-world natural phenomena have high appeal for graphics and animation.To bridge the technical gap between virtual and real environments,we focus on the inverse modeling and reconstruction of visually consistent and property-verifiable oceans,taking advantage of deep learning and differentiable physics to learn geometry and constitute waves in a self-supervised manner.First,we infer hierarchical geometry using two networks,which are optimized via the differentiable renderer.We extract wave components from the sequence of inferred geometry through a network equipped with a differentiable ocean model.Then,ocean dynamics can be evolved using the reconstructed wave components.Through extensive experiments,we verify that our new method yields satisfactory results for both geometry reconstruction and wave estimation.Moreover,the new framework has the inverse modeling potential to facilitate a host of graphics applications,such as the rapid production of physically accurate scene animation and editing guided by real ocean scenes.展开更多
Erratum to Xueguang Xie,Yang Gao,Fei Hou,Aimin Hao&Hong Qin.Dynamic ocean inverse modeling based on differentiable rendering.Computational Visual Media Vol.10,No.2,279–294,2024.https://doi10.1007/s41095-023-0338-...Erratum to Xueguang Xie,Yang Gao,Fei Hou,Aimin Hao&Hong Qin.Dynamic ocean inverse modeling based on differentiable rendering.Computational Visual Media Vol.10,No.2,279–294,2024.https://doi10.1007/s41095-023-0338-4 The authors apologize for a hidden error in the article.It is that the images in Figs.14(a)and 14(d)were mistakenly presented as left–right mirror images.The authors have flipped them to ensure that the figures now correspond correctly with others in the subfigures(b,c,e,f).The accurate version of Fig.14 is provided as below.展开更多
Deep learning has achieved impressive success in a variety of tasks and is developing rapidly in recent years.The problem of understanding the deep learning models has become an issue for the development of deep learn...Deep learning has achieved impressive success in a variety of tasks and is developing rapidly in recent years.The problem of understanding the deep learning models has become an issue for the development of deep learning,for example,in domains like medicine and finance which require interpretable models.While it is challenging to analyze and interpret complicated deep neural networks,visualization is good at bridging between abstract data and intuitive representations.Visual analytics for deep learning is a rapidly growing research field.To help users better understand this field,we present a mini-survey including a user-based taxonomy that covers state-of-the-art works of the field.Regarding the requirements of different types of users(beginners,practitioners,developers,and experts),we categorize the methods and tools by four visualization goals respectively focusing on teaching deep learning concepts,architecture assessment,tools for debugging and improving models,and visual explanation.Notably,we present a table consisting of the name of the method or tool,the year,the visualization goal,and the types of networks to which the method or tool can be applied,to assist users in finding available tools and methods quickly.To emphasize the importance of visual explanation for deep learning,we introduce the studies in this research field in detail.展开更多
基金supported by the National Natural Science Foundation of China(No.41571062)the Fundamental Research Funds for the Central Universities(No.2021TS014)the Natural Science Basic Research Plan in Shaanxi Province of China(No.2023-JC-YB-259).
文摘Formaldehyde(HCHO)is a high-yield product of the oxidation of volatile organic compounds(VOCs)released by anthropogenic activities,fires,and vegetations.Hence,we examined the spatiotemporal variation trends in HCHO columns observed using the Ozone Monitoring Instrument(OMI)during 2005–2021 across the Fenwei Plain(FWP)and analysed the source and variability of HCHO using multi-source data,such as thermal anomalies.The spatial distribution of the annualmean HCHO in the FWP increased from northwest to southeast during 2005–2021,and the high-value aggregation areas contracted and gradually clustered,forming a belt-shaped distribution area from Xi’an to Baoji,north of the Qinling Mountains.The annual mean HCHO concentration generally showed a two-step increase over the 17 years.Fires showed a single-peak trend in March and a double-peak M-shaped trend in March and October,whereas urban thermal anomalies(UTAs)showed an inverted U-shaped trend over 17 years,with peaks occurring in May.The HCHO peaks are mainly caused by the alternating contributions of fires and UTAs.The fires and UTAs(predominantly industrial heat sources)played a role in controlling the background level of HCHO in the FWP.Precipitation and temperature were also important influencing variables for seasonal variations,and the influence of plant sources on HCHO concentrations had significant regional characteristics and contributions.In addition,the FWP has poor dispersion conditions and is an aggregated area for the long-range transport of air pollutants.
基金Supported by Noncommunicable Chronic Diseases-National Science and Technology Major Project(2024ZD0523200)National Natural Science Foundation of China(62301330,62101346).
文摘The convergence of large language models(LLMs)and virtual reality(VR)technologies has led to significant breakthroughs across multiple domains,particularly in healthcare and medicine.Owing to its immersive and interactive capabilities,VR technology has demonstrated exceptional utility in surgical simulation,rehabilitation,physical therapy,mental health,and psychological treatment.By creating highly realistic and precisely controlled environments,VR not only enhances the efficiency of medical training but also enables personalized therapeutic approaches for patients.The convergence of LLMs and VR extends the potential of both technologies.LLM-empowered VR can transform medical education through interactive learning platforms and address complex healthcare challenges using comprehensive solutions.This convergence enhances the quality of training,decision-making,and patient engagement,paving the way for innovative healthcare delivery.This study aims to comprehensively review the current applications,research advancements,and challenges associated with these two technologies in healthcare and medicine.The rapid evolution of these technologies is driving the healthcare industry toward greater intelligence and precision,establishing them as critical forces in the transformation of modern medicine.
基金National Natural Science Foundation of China,Grant/Award Numbers:52372188,51902090,51922008,520721142023 Introduction of studying abroad talent program,the China Postdoctoral Science Foundation,Grant/Award Number:2019 M652546+3 种基金Xinxiang Major Science and Technology Projects,Grant/Award Number:21ZD001Henan Province Postdoctoral Start‐Up Foundation,Grant/Award Number:1901017Henan Center for Outstanding Overseas Scientists,Grant/Award Number:GZS2018003Overseas Expertise Introduction Project for Discipline Innovation,Grant/Award Number:D17007。
文摘Vanadium oxide cathode materials with stable crystal structure and fast Zn^(2+) storage capabilities are extremely important to achieving outstanding electrochemical performance in aqueous zinc‐ion batteries.In this work,a one‐step hydrothermal method was used to manipulate the bimetallic ion intercalation into the interlayer of vanadium oxide.The pre‐intercalated Cu ions act as pillars to pin the vanadium oxide(V‐O)layers,establishing stabilized two‐dimensional channels for fast Zn^(2+) diffusion.The occupation of Mn ions between V‐O interlayer further expands the layer spacing and increases the concentration of oxygen defects(Od),which boosts the Zn^(2+) diffusion kinetics.As a result,as‐prepared Cu_(0.17)Mn_(0.03)V_(2)O_(5−□)·2.16H_(2)O cathode shows outstanding Zn‐storage capabilities under room‐and lowtemperature environments(e.g.,440.3 mAh g^(−1) at room temperature and 294.3 mAh g^(−1)at−60°C).Importantly,it shows a long cycling life and high capacity retention of 93.4%over 2500 cycles at 2 A g^(−1) at−60°C.Furthermore,the reversible intercalation chemistry mechanisms during discharging/charging processes were revealed via operando X‐ray powder diffraction and ex situ Raman characterizations.The strategy of a couple of 3d transition metal doping provides a solution for the development of superior room‐/lowtemperature vanadium‐based cathode materials.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research Program(STEP,Grant No.2019QZKK0205)the National Natural Science Foundation of China(grant No.42071077,42171148)the Fundamental Research Funds for the Central Universities(lzujbky-2021-sp11)。
文摘Annual mass balance is an important factor that reflects glacier change and glacier meltwater resources.In this study,we analyzed the changes in glacier area,snow line altitude(SLA)and surface elevation in theányêmaqên Mountain region using multisource remote sensing data.Then,the annual mass balance of two glaciers was reconstructed by using SLA-mass-balance gradient method.The results showed that the glacier area in theányêmaqên Mountains decreased by 29.4 km2from 1985 to 2017.The average SLAs of the Halong Glacier and Yehelong Glacier were approximately 5290 m and 5188 m,respectively.The glacier mass balance for the two glaciers from 1990 to 2020 was-0.71 m w.e.a^(-1) and-0.63 m w.e.a^(-1),respectively.Our results indicate that SLA is an important indicator of glacier changes,and a long sequence of SLAs can more accurately reconstruct the glacier mass balance of the glacier.The mean annual glacial meltwater-fed streamflow is 1.45×10^(7)m^(3) and 1.12×10^(7)m^(3),respectively.Sensitivity analysis indicates that summer air temperature plays a leading role in regard to the influential climatic factors of glacial retreat in theányêmaqên Mountains.This highlights the potential of the methodology for application on reconstructing annual glacier surface mass balance at larger scales without direct measurements.
基金supported by grants from the Hundred Talents Program of Chinese Academy of Sciencesthe Science Fund for Creative Research Groups of the National Natural Science Foundation of China(NSFC)(41121001,ISIS584763SN:5609773)the Scientific Research Foundation of the Key Laboratory of Cryospheric Sciences(SKLCS-ZZ-2014-01-04)
文摘From 2008 to 2010, a total of 15 snow pit samples were collected from 13 mountain glaciers in western China. In this study these samples are used to determine the spatial distribution of insoluble particle concentrations and dust deposition fluxes in western China. The results show that the mass concentrations of insoluble particles exhibit high spatial variation and strongly decrease （by a factor of approximately 50） from the north （Tienshan Mountains） to the south （Himalayas）. However, the insoluble particles concentrations at the southeastern Tibetan Plateau （TP） sites are also high and ap- proximately 30 times greater than those in the Himalayas. The spatial distribution of the dust flux is similar to that of the mass concentrations; however, the high dust deposition rate in the southeastern TP is very significant as a result of the extensive snow accumulation （precipitation） in this region. The average sizes of the insoluble particles at each site generally exhibit bimodal distributions with peaks at approximately 5 μm and 10 μm, which can be explained as re- sulting from dust emissions from regional and local sources, respectively. The enrichment factors for most of the elements measured in insoluble particles are less than 10 at all of the study sites, indicating primarily crustal sources. However, the sites located in the peripheral mountains of western China, such as the Tienshan Mountains and the Himalayas, are characterized by high levels of certain enrichment elements （e.g., Cu, Zn, Cr, and V） indicative of sources related to the long-range transport of pollutants.
基金Supported by the China National Natural Science Foundation(41401084,41471060)the International Partnership Program of Chinese Academy of Sciences(131C11KYSB20160061)
文摘Though being considered strategically important in matters of national defense based on its abundance of natural resources,Northwest China is one of the most ecologically vulnerable areas in the country. As one of the region's important water sources,glaciers have gone through major changes due to climate change. An analysis of research results over the past 60 years reveals that the glaciers have been retreating in general to some degree in large river basins in Northwest China,but the rate of retreating varied largely among different regions,ranging from 0. 01% ·a^(-1) to 0. 75% ·a^(-1). Specifically,glaciers around the Lantsang River Basin and the Altay Mountains have been retreating fastest. The retreat of glaciers has already caused an increase in runoff in mountainous areas of Northwest China. Meanwhile,increases in the frequency of glacial flash floods and in the flood discharge will further enhance the probability of glacial lake outburst floods and ensuing disasters.
基金sponsored by grants from the National Natural Science Foundation of China(62002010,61872347)the CAMS Innovation Fund for Medical Sciences(2019-I2M5-016)the Special Plan for the Development of Distinguished Young Scientists of ISCAS(Y8RC535018).
文摘Learning and inferring underlying motion patterns of captured 2D scenes and then re-creating dynamic evolution consistent with the real-world natural phenomena have high appeal for graphics and animation.To bridge the technical gap between virtual and real environments,we focus on the inverse modeling and reconstruction of visually consistent and property-verifiable oceans,taking advantage of deep learning and differentiable physics to learn geometry and constitute waves in a self-supervised manner.First,we infer hierarchical geometry using two networks,which are optimized via the differentiable renderer.We extract wave components from the sequence of inferred geometry through a network equipped with a differentiable ocean model.Then,ocean dynamics can be evolved using the reconstructed wave components.Through extensive experiments,we verify that our new method yields satisfactory results for both geometry reconstruction and wave estimation.Moreover,the new framework has the inverse modeling potential to facilitate a host of graphics applications,such as the rapid production of physically accurate scene animation and editing guided by real ocean scenes.
文摘Erratum to Xueguang Xie,Yang Gao,Fei Hou,Aimin Hao&Hong Qin.Dynamic ocean inverse modeling based on differentiable rendering.Computational Visual Media Vol.10,No.2,279–294,2024.https://doi10.1007/s41095-023-0338-4 The authors apologize for a hidden error in the article.It is that the images in Figs.14(a)and 14(d)were mistakenly presented as left–right mirror images.The authors have flipped them to ensure that the figures now correspond correctly with others in the subfigures(b,c,e,f).The accurate version of Fig.14 is provided as below.
基金Rulei Yu and Lei Shi are supported by China National 973 Project 2014CB340301NSFC Grant 61772504。
文摘Deep learning has achieved impressive success in a variety of tasks and is developing rapidly in recent years.The problem of understanding the deep learning models has become an issue for the development of deep learning,for example,in domains like medicine and finance which require interpretable models.While it is challenging to analyze and interpret complicated deep neural networks,visualization is good at bridging between abstract data and intuitive representations.Visual analytics for deep learning is a rapidly growing research field.To help users better understand this field,we present a mini-survey including a user-based taxonomy that covers state-of-the-art works of the field.Regarding the requirements of different types of users(beginners,practitioners,developers,and experts),we categorize the methods and tools by four visualization goals respectively focusing on teaching deep learning concepts,architecture assessment,tools for debugging and improving models,and visual explanation.Notably,we present a table consisting of the name of the method or tool,the year,the visualization goal,and the types of networks to which the method or tool can be applied,to assist users in finding available tools and methods quickly.To emphasize the importance of visual explanation for deep learning,we introduce the studies in this research field in detail.
