Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the ...Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.展开更多
Ultrahigh-temperature-pressure experiments are crucial for understanding the physical and chemical properties of matter.The recent development of boron-doped diamond(BDD)heaters has made such melting experiments possi...Ultrahigh-temperature-pressure experiments are crucial for understanding the physical and chemical properties of matter.The recent development of boron-doped diamond(BDD)heaters has made such melting experiments possible in large-volume presses.However,estimates of temperatures above 2600 K and of the temperature distributions inside BDD heaters are not well constrained,owing to the lack of a suitable thermometer.Here,we establish a three-dimensional finite element model as a virtual thermometer to estimate the temperature and temperature field above 2600 K.The advantage of this virtual thermometer over those proposed in previous studies is that it considers both alternating and direct current heating modes,the actual sizes of cell assemblies after compression,the effects of the electrode,thermocouple and anvil,and the heat dissipation by the pressure-transmitting medium.The virtual thermometer reproduces the power-temperature relationships of ultrahigh-temperature-pressure experiments below 2600 K at press loads of 2.8-7.9 MN(~19 to 28 GPa)within experimental uncertainties.The temperatures above 2600 K predicted by our virtual thermometer are within the uncertainty of those extrapolated from power-temperature relationships below 2600 K.Furthermore,our model shows that the temperature distribution inside a BDD heater(19-26 K/mm along the radial direction and<83 K/mm along the longitudinal direction)is more homogeneous than those inside conventional heaters such as graphite or LaCrO_(3) heaters(100-200 K/mm).Our study thus provides a reliable virtual thermometer for ultrahigh-temperature experiments using BDD heaters in Earth and material sciences.展开更多
The air quality in China has improved significantly in the last decade and,correspondingly,the characteristics of PM_(2.5)have also changed.We studied the interannual variation of PM_(2.5)in Chengdu,one of the most he...The air quality in China has improved significantly in the last decade and,correspondingly,the characteristics of PM_(2.5)have also changed.We studied the interannual variation of PM_(2.5)in Chengdu,one of the most heavily polluted megacities in southwest China,during the most polluted season(winter).Our results show that the mass concentrations of PM_(2.5)decreased significantly year-by-year,from 195.8±91.0μg/m~3in winter 2016 to 96.1±39.3μg/m^(3)in winter 2020.The mass concentrations of organic matter(OM),SO_()4^(2-),NH_(4)^(+)and NO_(3)^(-)decreased by 49.6%,57.1%,49.7% and 28.7%,respectively.The differential reduction in the concentrations of chemical components increased the contributions from secondary organic carbon and NO_(3)^(-)and there was a larger contribution from mobile sources.The contribution of OM and NO_(3)^(-)not only increased with increasing levels of pollution,but also increased year-by-year at the same level of pollution.Four sources of PM_(2.5)were identified:combustion sources,vehicular emissions,dust and secondary aerosols.Secondary aerosols made the highest contribution and increased year-by-year,from 40.6%in winter 2016 to 46.3% in winter 2020.By contrast,the contribution from combustion sources decreased from 14.4% to 8.7%.Our results show the effectiveness of earlier pollution reduction policies and emphasizes that priority should be given to key pollutants(e.g.,OM and NO_(3)^(-))and sources(secondary aerosols and vehicular emissions)in future policies for the reduction of pollution in Chengdu during the winter months.展开更多
Single-particle aerosol mass spectrometry was used to study the characteristics of Fecontaining particles during winter in Chengdu,southwest China.The mass concentrations of PM_(2.5)and PM_(10)during the study period ...Single-particle aerosol mass spectrometry was used to study the characteristics of Fecontaining particles during winter in Chengdu,southwest China.The mass concentrations of PM_(2.5)and PM_(10)during the study period were 64±38 and 89±49μg/m~3,respectively,and NO_(2)and particulate matter were high compared with most other regions of China.The Fecontaining particles were divided into seven categories with different mass spectra,sources and aging characteristics.The highest contribution was from Fe mixed with carbonaceous components(Fe-C,23.1%)particles.Fe was more mixed with sulfate than nitrate and therefore the contribution of Fe mixed with sulfate(Fe-S,20.7%)particles was higher than that of Fe mixed with nitrate(Fe-N,12.5%)particles.The contributions from Fe-containing particles related to primary combustion were high in the small particle size range,whereas aged Fecontaining particles and dust-related particles were mostly found in the coarse particle size range.The air masses mainly originated from the west and east of Chengdu,and the corresponding PM_(2.5)concentrations were 79±36 and 55±36μg/m~3,respectively.The west and east air masses showed stronger contributions of Fe-containing particles related to biomass burning(Fe-B)and fossil fuel combustion(Fe-C and Fe-S)particles,respectively.The southwest area contributed the most Fe-containing particles.Future assessments of the effects of Fe-containing particles during heavy pollution period should pay more attention to Fe-C and Fe-S particles.Emission-reduction of Fe-containing particles should consider both local emissions and short-distance transmission from the surrounding areas.展开更多
The anti-counterfeiting of agricultural products plays an important role in protecting the rights and interests of consumers and maintaining the healthy development of the food market.Traditional anti-counterfeiting t...The anti-counterfeiting of agricultural products plays an important role in protecting the rights and interests of consumers and maintaining the healthy development of the food market.Traditional anti-counterfeiting technology mainly relies on anti-counterfeiting features of packaging or labeling,which has the risk of being copied and reused.Biological fingerprint anti-counterfeiting is a method of anti-counterfeiting that takes the biological fingerprint of agricultural products as the anti-counterfeiting feature.This paper aims to take the distribution of lenticels on the surface of mango as a biological fingerprint,and propose a mango biological fingerprint anti-counterfeiting method.As the mango ripens,the peel color of mango will change significantly,which will affect the accuracy of anti-counterfeiting identification.In this paper,the images of ripe mangoes are classified by Fuzzy C-means clustering,and appropriate image enhancement technology is used to highlight the features.The results show that the mango biological fingerprint anti-counterfeiting method based on Fuzzy C-means clustering has good accuracy and robustness,and effectively reduces the impact of peel color change on anti-counterfeiting identification during mango ripening.These results support that it is feasible to use the lenticels distribution of mango as a biological fingerprint.In this paper,a computer vision anti-counterfeiting method based on lenticels distribution is proposed.展开更多
COVID-19,caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),is a major public health threat.Edible plants are rich in bioactive components,with a variety of functions,such as enhancing immunity,anti...COVID-19,caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),is a major public health threat.Edible plants are rich in bioactive components,with a variety of functions,such as enhancing immunity,antiviral,anti-inflammatory and so on.Thus,the intake of edible plants to boost the body's resistance to COVID-19 is a promising and possibly affordable strategy.This review revisits the effects of functional components from edible plants(such as polyphenols,polysaccharides,lectin,alkaloids,polyunsaturated fatty acids,terpenoids,and saponins)on COVID-19.The inhibitory effects of bioactive components on the virus's entrance and replication,anti-inflammatory and immune enhancement are discussed.And finally,we present the prospects of using edible plant functional ingredients as vaccine adjuvants and the prospects and problems in the use of edible plant functional components for the prevention of COVID-19.Functional components of edible plants interacted with structural proteins of SARS-CoV-2 virus and key enzymes in virus recognition and replication,thereby inhibiting virus entry and replication in the host.Meanwhile,these bioactive components had anti-inflammatory effects and could inhibit cytokine storms.Therefore,we believe that functional components from edible plants can enhance human resistance to COVID-19 and can be applied in the development of new therapies.展开更多
The temperature dependence of the Al2O3 solubility in bridgmanite has been determined in the system MgSiO3–Al_(2)O_(3)at temperatures of 2750–3000 K under a constant pressure of 27 GPa using a multi-anvil apparatus....The temperature dependence of the Al2O3 solubility in bridgmanite has been determined in the system MgSiO3–Al_(2)O_(3)at temperatures of 2750–3000 K under a constant pressure of 27 GPa using a multi-anvil apparatus.Bridgmanite becomes more aluminous with increasing temperatures.A LiNbO3-type phase with a pyrope composition(Mg_(3)Al_(2)Si_(3)O_(12))forms at 2850 K,which is regarded as to be transformed from bridgmanite upon decompression.This phase contains 30 mol%Al_(2)O_(3)at 3000 K.The MgSiO3 solubility in corundum also increases with temperatures,reaching 52 mol%at 3000 K.Molar volumes of the hypothetical Al_(2)O_(3)bridgmanite and MgSiO_(3)corundum are constrained to be 25.950.05 and 26.24±0.06 cm^(3)/mol,respectively,and interaction parameters of non-ideality for these two phases are 5.6±0.5 and 2.2±0.5 KJ/mol,respectively.The increases in Al^(2)O^(3)and MgSiO^(3)contents,respectively,in bridgmanite and corundum are caused by a larger entropy of Al_(2)O_(3)bridgmanite plus MgSiO_(3)corundum than that of MgSiO_(3)bridgmanite plus Al_(2)O_(3)corundum with temperature,in addition to the configuration entropy.Our study may help explain dynamics of the top lower mantle and constrain pressure and temperature conditions of shocked meteorites.展开更多
To investigate the volatility of atmospheric particulates and the evolution of other particulate properties(chemical composition,particle size distribution and mixing state)with temperature,a thermodenuder coupled wit...To investigate the volatility of atmospheric particulates and the evolution of other particulate properties(chemical composition,particle size distribution and mixing state)with temperature,a thermodenuder coupled with a single particle aerosol mass spectrometer was used to conduct continuous observations of atmospheric fine particles in Chengdu,southwest China.Because of their complex sources and secondary reaction processes,the average mass spectra of single particles contained a variety of chemical components(including organic,inorganic and metal species).When the temperature rose from room temperature to280℃,the relative areas of volatile and semi-volatile components decreased,while the relative areas of less or non-volatile components increased.Most(>80%)nitrate and sulfate existed in the form of NH_(4)NO_(3)and(NH_(4))_(2)SO_(4),and their volatilization temperatures were50–100℃and 150–280℃,respectively.The contribution of biomass burning(BB)and vehicle emission(VE)particles increased significantly at 280℃,which emphasized the important role of regional biomass burning and local motor vehicle emissions to the core of particles.With the increase in temperature,the particle size of the particles coated with volatile or semi-volatile components was reduced,and their mixing with secondary inorganic components was significantly weakened.The formation of K-nitrate(KNO_(3))and K-sulfate(KSO_(4))particles was dominated by liquid-phase processes and photochemical reactions,respectively.Reducing KNO_(3)and BB particles is the key to improving visibility.These new results are helpful towards better understanding the initial sources,pollution formation mechanisms and climatic effects of fine particulate matter in this megacity in southwest China.展开更多
Motor timing is an important part of sensorimotor control. Previous studies have shown that beta oscillations embody the process of temporal perception in explicit timing tasks. In contrast, studies focusing on beta o...Motor timing is an important part of sensorimotor control. Previous studies have shown that beta oscillations embody the process of temporal perception in explicit timing tasks. In contrast, studies focusing on beta oscillations in implicit timing tasks are lacking. In this study, we set up an implicit motor timing task and found a modulation pattern of beta oscillations with temporal perception during movement preparation. We trained two macaques in a repetitive visually-guided reach-to-grasp task with different holding intervals. Spikes and local field potentials were recorded from microelectrode arrays in the primary motor cortex, primary somatosensory cortex, and posterior parietal cortex. We analyzed the association between beta oscillations and temporal interval in fixedduration experiments(500 ms as the Short Group and1500 ms as the Long Group) and random-duration experiments(500 ms to 1500 ms). The results showed that the peak beta frequencies in both experiments ranged from15 Hz to 25 Hz. The beta power was higher during the hold period than the movement(reach and grasp) period.Further, in the fixed-duration experiments, the mean poweras well as the maximum rate of change of beta power in the first 300 ms were higher in the Short Group than in the Long Group when aligned with the Center Hit event. In contrast, in the random-duration experiments, the corresponding values showed no statistical differences among groups. The peak latency of beta power was shorter in the Short Group than in the Long Group in the fixed-duration experiments, while no consistent modulation pattern was found in the random-duration experiments. These results indicate that beta oscillations can modulate with temporal interval in their power mode. The synchronization period of beta power could reflect the cognitive set maintaining working memory of the temporal structure and attention.展开更多
基金We acknowledge funding from NSFC Grant 62306283.
文摘Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.
基金supported financially by the National Key R&D Program of China(Grant No.2022YFB3706602)the National Natural Science Foundation of China(Grant Nos.42272041,41902034,and 12011530063)the Jilin University High-Level Innovation Team Foundation,China(Grant No.2021TD-05).
文摘Ultrahigh-temperature-pressure experiments are crucial for understanding the physical and chemical properties of matter.The recent development of boron-doped diamond(BDD)heaters has made such melting experiments possible in large-volume presses.However,estimates of temperatures above 2600 K and of the temperature distributions inside BDD heaters are not well constrained,owing to the lack of a suitable thermometer.Here,we establish a three-dimensional finite element model as a virtual thermometer to estimate the temperature and temperature field above 2600 K.The advantage of this virtual thermometer over those proposed in previous studies is that it considers both alternating and direct current heating modes,the actual sizes of cell assemblies after compression,the effects of the electrode,thermocouple and anvil,and the heat dissipation by the pressure-transmitting medium.The virtual thermometer reproduces the power-temperature relationships of ultrahigh-temperature-pressure experiments below 2600 K at press loads of 2.8-7.9 MN(~19 to 28 GPa)within experimental uncertainties.The temperatures above 2600 K predicted by our virtual thermometer are within the uncertainty of those extrapolated from power-temperature relationships below 2600 K.Furthermore,our model shows that the temperature distribution inside a BDD heater(19-26 K/mm along the radial direction and<83 K/mm along the longitudinal direction)is more homogeneous than those inside conventional heaters such as graphite or LaCrO_(3) heaters(100-200 K/mm).Our study thus provides a reliable virtual thermometer for ultrahigh-temperature experiments using BDD heaters in Earth and material sciences.
基金supported by the National Natural Science Foundation of China(Nos.42205100 and 41805095)the Sichuan Science and Technology Program(Nos.2019YFS0476and 2022NSFSC0982)support from the Sichuan comprehensive monitoring station for environmental air quality。
文摘The air quality in China has improved significantly in the last decade and,correspondingly,the characteristics of PM_(2.5)have also changed.We studied the interannual variation of PM_(2.5)in Chengdu,one of the most heavily polluted megacities in southwest China,during the most polluted season(winter).Our results show that the mass concentrations of PM_(2.5)decreased significantly year-by-year,from 195.8±91.0μg/m~3in winter 2016 to 96.1±39.3μg/m^(3)in winter 2020.The mass concentrations of organic matter(OM),SO_()4^(2-),NH_(4)^(+)and NO_(3)^(-)decreased by 49.6%,57.1%,49.7% and 28.7%,respectively.The differential reduction in the concentrations of chemical components increased the contributions from secondary organic carbon and NO_(3)^(-)and there was a larger contribution from mobile sources.The contribution of OM and NO_(3)^(-)not only increased with increasing levels of pollution,but also increased year-by-year at the same level of pollution.Four sources of PM_(2.5)were identified:combustion sources,vehicular emissions,dust and secondary aerosols.Secondary aerosols made the highest contribution and increased year-by-year,from 40.6%in winter 2016 to 46.3% in winter 2020.By contrast,the contribution from combustion sources decreased from 14.4% to 8.7%.Our results show the effectiveness of earlier pollution reduction policies and emphasizes that priority should be given to key pollutants(e.g.,OM and NO_(3)^(-))and sources(secondary aerosols and vehicular emissions)in future policies for the reduction of pollution in Chengdu during the winter months.
基金supported by the Scientific Research Project (No.17ZB0484)of Sichuan Provincial Department of EducationScientific Research Project (No.2021ZKQN004)of Southwest Medical University+1 种基金National Natural Science Foundation of China (No.41805095)Sichuan Science and Technology Program (No.2019YFS0476)。
文摘Single-particle aerosol mass spectrometry was used to study the characteristics of Fecontaining particles during winter in Chengdu,southwest China.The mass concentrations of PM_(2.5)and PM_(10)during the study period were 64±38 and 89±49μg/m~3,respectively,and NO_(2)and particulate matter were high compared with most other regions of China.The Fecontaining particles were divided into seven categories with different mass spectra,sources and aging characteristics.The highest contribution was from Fe mixed with carbonaceous components(Fe-C,23.1%)particles.Fe was more mixed with sulfate than nitrate and therefore the contribution of Fe mixed with sulfate(Fe-S,20.7%)particles was higher than that of Fe mixed with nitrate(Fe-N,12.5%)particles.The contributions from Fe-containing particles related to primary combustion were high in the small particle size range,whereas aged Fecontaining particles and dust-related particles were mostly found in the coarse particle size range.The air masses mainly originated from the west and east of Chengdu,and the corresponding PM_(2.5)concentrations were 79±36 and 55±36μg/m~3,respectively.The west and east air masses showed stronger contributions of Fe-containing particles related to biomass burning(Fe-B)and fossil fuel combustion(Fe-C and Fe-S)particles,respectively.The southwest area contributed the most Fe-containing particles.Future assessments of the effects of Fe-containing particles during heavy pollution period should pay more attention to Fe-C and Fe-S particles.Emission-reduction of Fe-containing particles should consider both local emissions and short-distance transmission from the surrounding areas.
基金supported by the National Natural Science Foundation of China(No.32172270).
文摘The anti-counterfeiting of agricultural products plays an important role in protecting the rights and interests of consumers and maintaining the healthy development of the food market.Traditional anti-counterfeiting technology mainly relies on anti-counterfeiting features of packaging or labeling,which has the risk of being copied and reused.Biological fingerprint anti-counterfeiting is a method of anti-counterfeiting that takes the biological fingerprint of agricultural products as the anti-counterfeiting feature.This paper aims to take the distribution of lenticels on the surface of mango as a biological fingerprint,and propose a mango biological fingerprint anti-counterfeiting method.As the mango ripens,the peel color of mango will change significantly,which will affect the accuracy of anti-counterfeiting identification.In this paper,the images of ripe mangoes are classified by Fuzzy C-means clustering,and appropriate image enhancement technology is used to highlight the features.The results show that the mango biological fingerprint anti-counterfeiting method based on Fuzzy C-means clustering has good accuracy and robustness,and effectively reduces the impact of peel color change on anti-counterfeiting identification during mango ripening.These results support that it is feasible to use the lenticels distribution of mango as a biological fingerprint.In this paper,a computer vision anti-counterfeiting method based on lenticels distribution is proposed.
基金supported by the National Natural Science Foundation of China(No.32172270).
文摘COVID-19,caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),is a major public health threat.Edible plants are rich in bioactive components,with a variety of functions,such as enhancing immunity,antiviral,anti-inflammatory and so on.Thus,the intake of edible plants to boost the body's resistance to COVID-19 is a promising and possibly affordable strategy.This review revisits the effects of functional components from edible plants(such as polyphenols,polysaccharides,lectin,alkaloids,polyunsaturated fatty acids,terpenoids,and saponins)on COVID-19.The inhibitory effects of bioactive components on the virus's entrance and replication,anti-inflammatory and immune enhancement are discussed.And finally,we present the prospects of using edible plant functional ingredients as vaccine adjuvants and the prospects and problems in the use of edible plant functional components for the prevention of COVID-19.Functional components of edible plants interacted with structural proteins of SARS-CoV-2 virus and key enzymes in virus recognition and replication,thereby inhibiting virus entry and replication in the host.Meanwhile,these bioactive components had anti-inflammatory effects and could inhibit cytokine storms.Therefore,we believe that functional components from edible plants can enhance human resistance to COVID-19 and can be applied in the development of new therapies.
基金Z.L.was financially supported by the Bayerisches Geoinstitut Visitor’s Program and the Fundamental Research Funds for the Central Universities of Ministry of Education of China(Grant No.45119031C037)This project has received funding from the European Research Council(ERC)under the European Union’s Horizon 2020 research and innovation programme(Proposal No.787527)+2 种基金It is also supported by research grants to T.K.(BMBF:05K13WC2,05K16 WC2DFG:KA3434/3–1,KA3434/7–1,KA3434/8–1,KA3434/9–1)Z.L.(the National Science Foundation of China Grant No.41902034).
文摘The temperature dependence of the Al2O3 solubility in bridgmanite has been determined in the system MgSiO3–Al_(2)O_(3)at temperatures of 2750–3000 K under a constant pressure of 27 GPa using a multi-anvil apparatus.Bridgmanite becomes more aluminous with increasing temperatures.A LiNbO3-type phase with a pyrope composition(Mg_(3)Al_(2)Si_(3)O_(12))forms at 2850 K,which is regarded as to be transformed from bridgmanite upon decompression.This phase contains 30 mol%Al_(2)O_(3)at 3000 K.The MgSiO3 solubility in corundum also increases with temperatures,reaching 52 mol%at 3000 K.Molar volumes of the hypothetical Al_(2)O_(3)bridgmanite and MgSiO_(3)corundum are constrained to be 25.950.05 and 26.24±0.06 cm^(3)/mol,respectively,and interaction parameters of non-ideality for these two phases are 5.6±0.5 and 2.2±0.5 KJ/mol,respectively.The increases in Al^(2)O^(3)and MgSiO^(3)contents,respectively,in bridgmanite and corundum are caused by a larger entropy of Al_(2)O_(3)bridgmanite plus MgSiO_(3)corundum than that of MgSiO_(3)bridgmanite plus Al_(2)O_(3)corundum with temperature,in addition to the configuration entropy.Our study may help explain dynamics of the top lower mantle and constrain pressure and temperature conditions of shocked meteorites.
基金supported by the Sichuan Natural Science Foundation (No.2022NSFSC0982)the Sichuan Science and Technology Program (No.2019YFS0476)the National Natural Science Foundation of China (No.41805095)。
文摘To investigate the volatility of atmospheric particulates and the evolution of other particulate properties(chemical composition,particle size distribution and mixing state)with temperature,a thermodenuder coupled with a single particle aerosol mass spectrometer was used to conduct continuous observations of atmospheric fine particles in Chengdu,southwest China.Because of their complex sources and secondary reaction processes,the average mass spectra of single particles contained a variety of chemical components(including organic,inorganic and metal species).When the temperature rose from room temperature to280℃,the relative areas of volatile and semi-volatile components decreased,while the relative areas of less or non-volatile components increased.Most(>80%)nitrate and sulfate existed in the form of NH_(4)NO_(3)and(NH_(4))_(2)SO_(4),and their volatilization temperatures were50–100℃and 150–280℃,respectively.The contribution of biomass burning(BB)and vehicle emission(VE)particles increased significantly at 280℃,which emphasized the important role of regional biomass burning and local motor vehicle emissions to the core of particles.With the increase in temperature,the particle size of the particles coated with volatile or semi-volatile components was reduced,and their mixing with secondary inorganic components was significantly weakened.The formation of K-nitrate(KNO_(3))and K-sulfate(KSO_(4))particles was dominated by liquid-phase processes and photochemical reactions,respectively.Reducing KNO_(3)and BB particles is the key to improving visibility.These new results are helpful towards better understanding the initial sources,pollution formation mechanisms and climatic effects of fine particulate matter in this megacity in southwest China.
基金the International Cooperation and Exchange of the National Natural Science Foundation of China (31320103914)the General Program of the National Natural Science Foundation of China (31370987)+2 种基金the National Natural Science Foundation of China for Outstanding Young Scholars (81622027)the Beijing Nova Program of China (2016B615)the National Basic Research Development Program of China (2017YFA0106100)
文摘Motor timing is an important part of sensorimotor control. Previous studies have shown that beta oscillations embody the process of temporal perception in explicit timing tasks. In contrast, studies focusing on beta oscillations in implicit timing tasks are lacking. In this study, we set up an implicit motor timing task and found a modulation pattern of beta oscillations with temporal perception during movement preparation. We trained two macaques in a repetitive visually-guided reach-to-grasp task with different holding intervals. Spikes and local field potentials were recorded from microelectrode arrays in the primary motor cortex, primary somatosensory cortex, and posterior parietal cortex. We analyzed the association between beta oscillations and temporal interval in fixedduration experiments(500 ms as the Short Group and1500 ms as the Long Group) and random-duration experiments(500 ms to 1500 ms). The results showed that the peak beta frequencies in both experiments ranged from15 Hz to 25 Hz. The beta power was higher during the hold period than the movement(reach and grasp) period.Further, in the fixed-duration experiments, the mean poweras well as the maximum rate of change of beta power in the first 300 ms were higher in the Short Group than in the Long Group when aligned with the Center Hit event. In contrast, in the random-duration experiments, the corresponding values showed no statistical differences among groups. The peak latency of beta power was shorter in the Short Group than in the Long Group in the fixed-duration experiments, while no consistent modulation pattern was found in the random-duration experiments. These results indicate that beta oscillations can modulate with temporal interval in their power mode. The synchronization period of beta power could reflect the cognitive set maintaining working memory of the temporal structure and attention.
