Improving the accuracy of fishing ground prediction for oceanic economic species has always been one of the most concerning issues in fisheries research.Recent studies have confirmed that deep learning has achieved su...Improving the accuracy of fishing ground prediction for oceanic economic species has always been one of the most concerning issues in fisheries research.Recent studies have confirmed that deep learning has achieved superior results over traditional methods in the era of big data.However,the deep learning-based fishing ground prediction model with a single environment suffers from the problem that the area of the fishing ground is too large and not concentrated.In this study,we developed a deep learning-based fishing ground prediction model with multiple environmental factors using neon flying squid(Ommastrephes bartramii)in Northwest Pacific Ocean as an example.Based on the modified U-Net model,the approach involves the sea surface temperature,sea surface height,sea surface salinity,and chlorophyll a as inputs,and the center fishing ground as the output.The model is trained with data from July to November in 2002-2019,and tested with data of 2020.We considered and compared five temporal scales(3,6,10,15,and 30 days)and seven multiple environmental factor combinations.By comparing different cases,we found that the optimal temporal scale is 30 days,and the optimal multiple environmental factor combination contained SST and Chl a.The inclusion of multiple factors in the model greatly improved the concentration of the center fishing ground.The selection of a suitable combination of multiple environmental factors is beneficial to the precise spatial distribution of fishing grounds.This study deepens the understanding of the mechanism of environmental field influence on fishing grounds from the perspective of artificial intelligence and fishery science.展开更多
Identity-based key agreement protocol affords a natural way to combine the participant＇s identity with its public key. However, most of them just consider the key agreement in a single private key generator （PKG） e...Identity-based key agreement protocol affords a natural way to combine the participant＇s identity with its public key. However, most of them just consider the key agreement in a single private key generator （PKG） environment. In addition, the existing key agreement protocols have a great computing overhead for mobile computing which is more and more popular today. This paper proposes a new identity based key agreement protocol. With the help of mathematical tools, we make our protocol applied in multiple PKG environment. It also satisfies all the security properties which is set for key agreement protocol. Moreover, some of its time-consuming operations can be delivered to untrusted public computation resources, so its computing complexity can be greatly reduced.展开更多
The χ^2 family of signal fluctuation distributions represents the main fluctuation models which most radar targets follow it in their reflections. This family can be categorized as fluctuation distribution with two d...The χ^2 family of signal fluctuation distributions represents the main fluctuation models which most radar targets follow it in their reflections. This family can be categorized as fluctuation distribution with two degrees of freedom and those with four degrees of freedom. The first category represents all important class of fluctuation models which when illuminated by a coherent pulse train, return a train of fully correlated pulses （Swerling Ⅰ model） or fully decorrelated pulses （Swerling Ⅱ model）. The detection of this type of fluctuating targets is therefore of great importance. This paper is devoted to the analysis of Cell-Averaging （CA） based detectors for the case where the radar receiver noncoherently integrates M square-law detected pulses and the signal fluctuation obeys 2 statistics with two degrees of freedom. These detectors include the Mean-Of （MO）, the Greatest-Of （GO） and the Smallest-Of（SO） schemes. In these processors, the estimation of the noise power levels from the leading and the trailing reference windows is based on the CA technique. Exact formulas for the detection probabilities are derived, in the absence as well as in the presence of spurious targets. The primary and the secondary interfering targets are assumed to be fluctuating in accordance with the χ^2 fluctuation model with two degrees of freedom （SWI ＆ SWII）. The numerical results show that the MO version has the best homogeneous performance, the SO scheme has the best multiple-target performance, while the GO procedure does not offer any merits, neither in the absence nor in the presence of outlying targets.展开更多
To mitigate the catastrophic impacts of climate change,many measures and strategies have been designed and implemented to encourage people to change their daily behaviors for a low-carbon society transition.However,mo...To mitigate the catastrophic impacts of climate change,many measures and strategies have been designed and implemented to encourage people to change their daily behaviors for a low-carbon society transition.However,most people generate carbon emissions through their daily activities in space and time.They are also exposed to multiple environmental factors(e.g.,air pollution,noise,and greenspace).Changing people’s behaviors to reduce carbon emissions can also influence their multiple environmental exposures and further influence their health outcomes.Thus,this study seeks to examine the associations between individuals’daily carbon footprints and their exposures to multiple environmental factors(i.e.,air pollution,noise,and greenspace)across different spa-tial and temporal contexts using individual-level data collected by portable real-time sensors,an activity-travel diary,and a questionnaire from four communities in Hong Kong.The results first indicated that individuals’car-bon footprints of daily activities varied across different spatial and temporal contexts,with home and nighttime having the highest estimated carbon footprints.We also found that activity carbon footprints have a positive asso-ciation with PM2.5,which is particularly strong at home and from morning to nighttime,and mixed associations with noise(positive at home and nighttime,while negative in other places and during travel,from morning to afternoon).Besides,carbon footprints also have consistent negative associations with shrubland and woodland across different spatial and temporal contexts.The findings can provide essential insights into effective measures for promoting the transition to a low-carbon society.展开更多
Multiple polluted environments accelerate the corrosion of metal coatings.Here,microcapsules of pretreated montmorillonite(MMT)and layered double hydrotalcite(LDH)encapsulated repair agents were prepared by a simple a...Multiple polluted environments accelerate the corrosion of metal coatings.Here,microcapsules of pretreated montmorillonite(MMT)and layered double hydrotalcite(LDH)encapsulated repair agents were prepared by a simple and effective method and applied to epoxy coatings.The microcapsules efficiently adsorbed Congo red(CR),copper ions(Cu^(2+)),and chloride ions(Cl^(-)).Moreover,the coating doped microcapsules demonstrated a remarkable 334.6%improvement in its self-healing capability.After 40 days of exposure to a multiple polluted environments,the composite coating maintained a corrosion resistance efficiency of 99.01%.The experimental and theoretical methods prove that MMT/LDH efficiently adsorbed corrosive pollutants through ion exchange,coordination complexation,and electrostatic interaction,while the self-healing product achieved microcrack closure through hydrogen bonding and van der Waals force between atoms.This work can provide new insights and assistance for the study of corrosion inhibition mechanisms under multiple polluted environments.展开更多
Indoor environment and health have drawn public attention worldwide.However,the joint health effects and mechanisms of exposure to different types of indoor environmental factors remain unclear.We established an explo...Indoor environment and health have drawn public attention worldwide.However,the joint health effects and mechanisms of exposure to different types of indoor environmental factors remain unclear.We established an exploratory panel study on indoor environment and health effects among young adults in China(the China IEHE Study)to comprehensively investigate 3M issues,including multiple indoor environmental factors,multiple health effects,and multiple omics methods for mechanism exploration.This protocol aims to systematically introduce the entire China IEHE Study.Eighty-one young adults aged 18−28 years from a university adjacent to traffic arteries in Beijing were recruited and followed up four times.Sham/real air purification intervention was simultaneously applied in a randomized crossover order.A broad range of indoor physical,chemical,and biological factors were characterized through real-time monitoring and external and internal exposure analyses.Subclinical health indices reflecting cardiopulmonary,sleep,and cognitive health were repeatedly measured in a prospective order.Various biosamples including fasting venous blood,morning urine,nasal mucosal lining fluid,and exhaled breath condensate were collected to explore the underlying biological mechanisms.The China IEHE Study comes up with an enlightening framework for future prospective studies associated with the exploration of multisystem health effects and underlying biological mechanisms of indoor exposure.展开更多
To mitigate the deleterious effects of clutter and jammer, modern radars have adopted adaptive processing techniques such as constant false alarm rate(CFAR) detectors which are widely used to prevent clutter and noise...To mitigate the deleterious effects of clutter and jammer, modern radars have adopted adaptive processing techniques such as constant false alarm rate(CFAR) detectors which are widely used to prevent clutter and noise interference from saturating the radar’s display and preventing targets from being obscured.This paper concerns with the detection analysis of the novel version of CFAR schemes(cell-averaging generalized trimmed-mean,CATM) in the presence of additional outlying targets other than the target under research. The spurious targets as well as the tested one are assumed to be fluctuating in accordance with the χ~2-model with two-degrees of freedom. In this situation, the processor performance is enclosed by the swerling models(SWI and SWII). Between these bounds, there is an important class of target fluctuation which is known as moderately fluctuating targets. The detection of this class has many practical applications. Structure of the CATM detector is described briefly. Detection performances for optimal, CAM, CA, trimmed-mean(TM) and ordered-statistic(OS) CFAR strategies have been analyzed and compared for desired probability of false alarm and determined size of the reference window. False alarm rate performance of these processors has been evaluated for different strengths of interfering signal and the effect of correlation among the target returns on the detection and false alarm performances has also been studied. Our numerical results show that, with a proper choice of trimming parameters,the novel model CAM presents an ideal detection performance outweighing that of the Neyman-Pearson detector on condition that the tested target obeys the SWII model in its fluctuation. Although the new models CAS and CAM can be treated as special cases of the CATM algorithm, their multi-target performance is modest even it has an enhancement relative to that of the classical CAcheme. Additionally, they fail to maintain the false alarm rate constant when the operating environment is of type target multiplicity. Moreover, the non-coherent integration of M pulses ameliorates the processor performance either it operates in homogeneous or multi-target environment.展开更多
Karst environment is very common in southwest China. Soil and vegetation are the most sensitive elements for the variation of karst environment. The weathering of carbonate is important soil formation mechanism in kar...Karst environment is very common in southwest China. Soil and vegetation are the most sensitive elements for the variation of karst environment. The weathering of carbonate is important soil formation mechanism in karst area, but its soil forming ability is so poor that the thickness of soil layer becomes thin by the water erosion, though the soil loss is insignificant but serious. The karst process, the ecology process, the hydrology process are three important circulation mechanisms in the karst multiple media environment. In the Chinese North and South karst area, the eco-environmental protection and restoration has already been the important part as the national territorial resources and the environmen- tal comprehensive development and management. The character of karst plants mainly depends on the environmental conditions, i.e. lack of water, richness of Ca, poor soil and shortage of organic matter. The plants have low growth pace and low life-form resource; it is vulnerable under the disturbance of irrational human activities. Therefore, the rocky desertification is the final result of karst ecosystem degradation. But ecological condition is severe in the North and South karst area, especially in the south karst stone mountainous area and the north arid karst area. There are many problems with the eco-environmental protection and restoration. This paper takes the karst multiple media environment as a core, comprehensively discusses the relations of the three processes – karst, hydrology, and ecology, and puts forward the direction of the research on karst ecology hydrology and the future.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 41876141 and Grant 42006159in part by the National Key R&D Programme of China under Grant 2019YFD0901404.
文摘Improving the accuracy of fishing ground prediction for oceanic economic species has always been one of the most concerning issues in fisheries research.Recent studies have confirmed that deep learning has achieved superior results over traditional methods in the era of big data.However,the deep learning-based fishing ground prediction model with a single environment suffers from the problem that the area of the fishing ground is too large and not concentrated.In this study,we developed a deep learning-based fishing ground prediction model with multiple environmental factors using neon flying squid(Ommastrephes bartramii)in Northwest Pacific Ocean as an example.Based on the modified U-Net model,the approach involves the sea surface temperature,sea surface height,sea surface salinity,and chlorophyll a as inputs,and the center fishing ground as the output.The model is trained with data from July to November in 2002-2019,and tested with data of 2020.We considered and compared five temporal scales(3,6,10,15,and 30 days)and seven multiple environmental factor combinations.By comparing different cases,we found that the optimal temporal scale is 30 days,and the optimal multiple environmental factor combination contained SST and Chl a.The inclusion of multiple factors in the model greatly improved the concentration of the center fishing ground.The selection of a suitable combination of multiple environmental factors is beneficial to the precise spatial distribution of fishing grounds.This study deepens the understanding of the mechanism of environmental field influence on fishing grounds from the perspective of artificial intelligence and fishery science.
基金Supported by the National Natural Science Foundation of China(61103194)
文摘Identity-based key agreement protocol affords a natural way to combine the participant＇s identity with its public key. However, most of them just consider the key agreement in a single private key generator （PKG） environment. In addition, the existing key agreement protocols have a great computing overhead for mobile computing which is more and more popular today. This paper proposes a new identity based key agreement protocol. With the help of mathematical tools, we make our protocol applied in multiple PKG environment. It also satisfies all the security properties which is set for key agreement protocol. Moreover, some of its time-consuming operations can be delivered to untrusted public computation resources, so its computing complexity can be greatly reduced.
文摘The χ^2 family of signal fluctuation distributions represents the main fluctuation models which most radar targets follow it in their reflections. This family can be categorized as fluctuation distribution with two degrees of freedom and those with four degrees of freedom. The first category represents all important class of fluctuation models which when illuminated by a coherent pulse train, return a train of fully correlated pulses （Swerling Ⅰ model） or fully decorrelated pulses （Swerling Ⅱ model）. The detection of this type of fluctuating targets is therefore of great importance. This paper is devoted to the analysis of Cell-Averaging （CA） based detectors for the case where the radar receiver noncoherently integrates M square-law detected pulses and the signal fluctuation obeys 2 statistics with two degrees of freedom. These detectors include the Mean-Of （MO）, the Greatest-Of （GO） and the Smallest-Of（SO） schemes. In these processors, the estimation of the noise power levels from the leading and the trailing reference windows is based on the CA technique. Exact formulas for the detection probabilities are derived, in the absence as well as in the presence of spurious targets. The primary and the secondary interfering targets are assumed to be fluctuating in accordance with the χ^2 fluctuation model with two degrees of freedom （SWI ＆ SWII）. The numerical results show that the MO version has the best homogeneous performance, the SO scheme has the best multiple-target performance, while the GO procedure does not offer any merits, neither in the absence nor in the presence of outlying targets.
基金supported by grants from the Hong Kong Re-search Grants Council(General Research Fund Grants No.14605920,14611621,14606922,14603724Collaborative Research Fund Grant No.C4023-20GF+3 种基金Research Matching Grants RMG 8601219,8601242,3110151)RGC Postdoctoral Fellowship No.PDFS2425-4H01)a grant from the Research Committee on Research Sustainability of Major Re-search Grants Council Funding Schemes(Grant No.3133235)of the Chinese University of Hong Kong(CUHK)grant from the Vice-Chancellor’s One-offDiscretionary Fund(Smart and Sustainable Cities:City of Commons)(4930787)of CUHK.
文摘To mitigate the catastrophic impacts of climate change,many measures and strategies have been designed and implemented to encourage people to change their daily behaviors for a low-carbon society transition.However,most people generate carbon emissions through their daily activities in space and time.They are also exposed to multiple environmental factors(e.g.,air pollution,noise,and greenspace).Changing people’s behaviors to reduce carbon emissions can also influence their multiple environmental exposures and further influence their health outcomes.Thus,this study seeks to examine the associations between individuals’daily carbon footprints and their exposures to multiple environmental factors(i.e.,air pollution,noise,and greenspace)across different spa-tial and temporal contexts using individual-level data collected by portable real-time sensors,an activity-travel diary,and a questionnaire from four communities in Hong Kong.The results first indicated that individuals’car-bon footprints of daily activities varied across different spatial and temporal contexts,with home and nighttime having the highest estimated carbon footprints.We also found that activity carbon footprints have a positive asso-ciation with PM2.5,which is particularly strong at home and from morning to nighttime,and mixed associations with noise(positive at home and nighttime,while negative in other places and during travel,from morning to afternoon).Besides,carbon footprints also have consistent negative associations with shrubland and woodland across different spatial and temporal contexts.The findings can provide essential insights into effective measures for promoting the transition to a low-carbon society.
基金sponsored by the National Natural Science Foundation of China(Nos.52472029 and 52062032)Jiangxi Provincial Key Laboratory of Advanced Civil Engineering Materials and Green Intelligent Construction(No.20242BCC32046)+1 种基金Jiangxi Provincial Natural Science Foundation(No.20212ACB204017)Innovation Fund Designated for Graduate Students of Jiangxi Province(No.YC2024-B003).
文摘Multiple polluted environments accelerate the corrosion of metal coatings.Here,microcapsules of pretreated montmorillonite(MMT)and layered double hydrotalcite(LDH)encapsulated repair agents were prepared by a simple and effective method and applied to epoxy coatings.The microcapsules efficiently adsorbed Congo red(CR),copper ions(Cu^(2+)),and chloride ions(Cl^(-)).Moreover,the coating doped microcapsules demonstrated a remarkable 334.6%improvement in its self-healing capability.After 40 days of exposure to a multiple polluted environments,the composite coating maintained a corrosion resistance efficiency of 99.01%.The experimental and theoretical methods prove that MMT/LDH efficiently adsorbed corrosive pollutants through ion exchange,coordination complexation,and electrostatic interaction,while the self-healing product achieved microcrack closure through hydrogen bonding and van der Waals force between atoms.This work can provide new insights and assistance for the study of corrosion inhibition mechanisms under multiple polluted environments.
基金supported by the National Key Research and Development Program of China[grants 2022YFC3702704 and 2017YFC0702700]the National Natural Science Foundation of China[grants 22076006 and 82073506].
文摘Indoor environment and health have drawn public attention worldwide.However,the joint health effects and mechanisms of exposure to different types of indoor environmental factors remain unclear.We established an exploratory panel study on indoor environment and health effects among young adults in China(the China IEHE Study)to comprehensively investigate 3M issues,including multiple indoor environmental factors,multiple health effects,and multiple omics methods for mechanism exploration.This protocol aims to systematically introduce the entire China IEHE Study.Eighty-one young adults aged 18−28 years from a university adjacent to traffic arteries in Beijing were recruited and followed up four times.Sham/real air purification intervention was simultaneously applied in a randomized crossover order.A broad range of indoor physical,chemical,and biological factors were characterized through real-time monitoring and external and internal exposure analyses.Subclinical health indices reflecting cardiopulmonary,sleep,and cognitive health were repeatedly measured in a prospective order.Various biosamples including fasting venous blood,morning urine,nasal mucosal lining fluid,and exhaled breath condensate were collected to explore the underlying biological mechanisms.The China IEHE Study comes up with an enlightening framework for future prospective studies associated with the exploration of multisystem health effects and underlying biological mechanisms of indoor exposure.
文摘To mitigate the deleterious effects of clutter and jammer, modern radars have adopted adaptive processing techniques such as constant false alarm rate(CFAR) detectors which are widely used to prevent clutter and noise interference from saturating the radar’s display and preventing targets from being obscured.This paper concerns with the detection analysis of the novel version of CFAR schemes(cell-averaging generalized trimmed-mean,CATM) in the presence of additional outlying targets other than the target under research. The spurious targets as well as the tested one are assumed to be fluctuating in accordance with the χ~2-model with two-degrees of freedom. In this situation, the processor performance is enclosed by the swerling models(SWI and SWII). Between these bounds, there is an important class of target fluctuation which is known as moderately fluctuating targets. The detection of this class has many practical applications. Structure of the CATM detector is described briefly. Detection performances for optimal, CAM, CA, trimmed-mean(TM) and ordered-statistic(OS) CFAR strategies have been analyzed and compared for desired probability of false alarm and determined size of the reference window. False alarm rate performance of these processors has been evaluated for different strengths of interfering signal and the effect of correlation among the target returns on the detection and false alarm performances has also been studied. Our numerical results show that, with a proper choice of trimming parameters,the novel model CAM presents an ideal detection performance outweighing that of the Neyman-Pearson detector on condition that the tested target obeys the SWII model in its fluctuation. Although the new models CAS and CAM can be treated as special cases of the CATM algorithm, their multi-target performance is modest even it has an enhancement relative to that of the classical CAcheme. Additionally, they fail to maintain the false alarm rate constant when the operating environment is of type target multiplicity. Moreover, the non-coherent integration of M pulses ameliorates the processor performance either it operates in homogeneous or multi-target environment.
文摘Karst environment is very common in southwest China. Soil and vegetation are the most sensitive elements for the variation of karst environment. The weathering of carbonate is important soil formation mechanism in karst area, but its soil forming ability is so poor that the thickness of soil layer becomes thin by the water erosion, though the soil loss is insignificant but serious. The karst process, the ecology process, the hydrology process are three important circulation mechanisms in the karst multiple media environment. In the Chinese North and South karst area, the eco-environmental protection and restoration has already been the important part as the national territorial resources and the environmen- tal comprehensive development and management. The character of karst plants mainly depends on the environmental conditions, i.e. lack of water, richness of Ca, poor soil and shortage of organic matter. The plants have low growth pace and low life-form resource; it is vulnerable under the disturbance of irrational human activities. Therefore, the rocky desertification is the final result of karst ecosystem degradation. But ecological condition is severe in the North and South karst area, especially in the south karst stone mountainous area and the north arid karst area. There are many problems with the eco-environmental protection and restoration. This paper takes the karst multiple media environment as a core, comprehensively discusses the relations of the three processes – karst, hydrology, and ecology, and puts forward the direction of the research on karst ecology hydrology and the future.
