Basic surveying and mapping involves a lot of content, which is a systematic and complex work. In actual surveying and mapping, it is necessary not only to improve the accuracy of surveying and mapping, but also to fu...Basic surveying and mapping involves a lot of content, which is a systematic and complex work. In actual surveying and mapping, it is necessary not only to improve the accuracy of surveying and mapping, but also to further improve the efficiency of surveying and mapping. In recent years, UAV technology has developed rapidly, and UAV remote sensing mapping has also become a new surveying and mapping technology. It can use corresponding equipment to control UAVs and photographic equipment to obtain corresponding information. However, the UAV remote sensing mapping technology is still in the initial stage of development at this stage, and further research on practical problems needs to be enhanced when applied in basic surveying and mapping, so as to effectively promote the development of UAV remote sensing mapping technology.展开更多
The development and applications of low temperature plasma technology used in surface modification of materials are presented in this paper. Based on plasma sources and ion sources technology, multi-functions ion impl...The development and applications of low temperature plasma technology used in surface modification of materials are presented in this paper. Based on plasma sources and ion sources technology, multi-functions ion implantation and deposition technologies were developed and the related processes are also used to treat different products. The related technologies were translated into industrial productions supported by national research projects. Following the last development of international plasma researches, the standardization and internationalization processes of plasma technologies are executed in our center.展开更多
This study investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,...This study investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,China.Based on randomly generated 40 NTDs,the study developed models for the geologic hazard susceptibility assessment using the random forest algorithm and evaluated their performances using the area under the receiver operating characteristic curve(AUC).Specifically,the means and standard deviations of the AUC values from all models were then utilized to assess the overall spatial correlation between the conditioning factors and the susceptibility assessment,as well as the uncertainty introduced by the NTDs.A risk and return methodology was thus employed to quantify and mitigate the uncertainty,with log odds ratios used to characterize the susceptibility assessment levels.The risk and return values were calculated based on the standard deviations and means of the log odds ratios of various locations.After the mean log odds ratios were converted into probability values,the final susceptibility map was plotted,which accounts for the uncertainty induced by random NTDs.The results indicate that the AUC values of the models ranged from 0.810 to 0.963,with an average of 0.852 and a standard deviation of 0.035,indicating encouraging prediction effects and certain uncertainty.The risk and return analysis reveals that low-risk and high-return areas suggest lower standard deviations and higher means across multiple model-derived assessments.Overall,this study introduces a new framework for quantifying the uncertainty of multiple training and evaluation models,aimed at improving their robustness and reliability.Additionally,by identifying low-risk and high-return areas,resource allocation for geologic hazard prevention and control can be optimized,thus ensuring that limited resources are directed toward the most effective prevention and control measures.展开更多
Coal dependence and inefficient decentralized heating have significantly increased China’s energy consumption for winter heating,increasing air pollution and exacerbating the greenhouse effect.In 2017,China implement...Coal dependence and inefficient decentralized heating have significantly increased China’s energy consumption for winter heating,increasing air pollution and exacerbating the greenhouse effect.In 2017,China implemented the Pilot Policy on Clean Winter Heating in Northern China,aiming to achieve high central heating coverage and cleaner energy consumption.Studying the effects of this policy can help promote its implementation and serve as a reference for effective adjustment of the contents in the future.However,few studies have investigated this policy and its carbon reduction effects,and most focus on the provincial or city levels.Therefore,this paper considers the policy’s influence on air pollution and carbon emissions at the county level to provide a precise and comprehensive assessment of the policy effects.We use panel data from 1290 counties in 15 provinces in Northern China from 2014 to 2021,applying a multiperiod difference-in-differences model to quantify the impact of the policy on carbon emissions and air quality in the pilot area.We then conduct a series of tests to demonstrate the robustness of the results and analyze the mechanisms of the policy effects from two perspectives,namely,central heating and natural gas use,through a mediating effect model.Finally,we examine the heterogeneity of policy effects between counties based on geographic location and per capita income levels of rural residents through a moderating effect model.The results reveal that the policy significantly reduces air pollution and carbon emissions in the pilot area by increasing the central heating area and natural gas use.Compared with the central and western regions in the north and areas with low-income rural residents,the policy effects in the eastern regions in the north and areas with high-income rural residents are more pronounced.展开更多
It is difficult for solanum crops to grow continuously during winter in severe cold regions. Thus, a soil heating system for facility agriculture based on solar concentration technology was proposed, and a novel compo...It is difficult for solanum crops to grow continuously during winter in severe cold regions. Thus, a soil heating system for facility agriculture based on solar concentration technology was proposed, and a novel compound parabolic concentration photothermal and photoelectricity device(CTPV) equipped in the system was designed to address this problem. In accordance with the structure of the device, LightTools optical software was selected to analyze the variation trend of the light escape rate of the device with the diff erent incident angles. On the basis of the calculation results, an experimental test system was used to investigate the relationship of the air temperature of the inlet and the outlet, total output power of the solar cells, and photothermal and photoelectricity efficiency of the device with the operation time during a sunny day. Research results reveal that the light escape rate of the device is 5.36% at an incidence angle of 12°. At a velocity of 1.5 m/s, the maximum air temperature of the outlet can reach 55.6 ℃, and the total output power of the solar cells is 474.4 W. The variation of the total power of the solar cells is consistent with the simulation results. The maximum instantaneous heat collection and the maximum photothermal and photoelectricity efficiency of the device are 306 W and 60.4%, respectively, and the average efficiency is 44.9%. This study can serve as a reference for compound parabolic concentration technology applied for soil heating in facility agricultural soil heating systems.展开更多
Background The high rate of long-term relapse is a major cause of smoking cessation failure.Recently,neurofeedback training has been widely used in the treatment of nicotine addiction;however,approximately 30%of subje...Background The high rate of long-term relapse is a major cause of smoking cessation failure.Recently,neurofeedback training has been widely used in the treatment of nicotine addiction;however,approximately 30%of subjects fail to benefit from this intervention.Our previous randomised clinical trial(RCT)examined cognition-guided neurofeedback and demonstrated a significant decrease in daily cigarette consumption at the 4-month follow-up.However,significant individual differences were observed in the 4-month follow-up effects of decreased cigarette consumption.Therefore,it is critical to identify who will benefit from pre-neurofeedback.Aims We examined whether the resting-state electroencephalography(EEG)characteristics from pre-neurofeedback predicted the 4-month follow-up effects and explored the possible mechanisms.Methods This was a double-blind RCT.A total of 60 participants with nicotine dependence were randomly assigned to either the real-feedback or yoked-feedback group.They underwent 6 min closed-eye resting EEG recordings both before and after two neurofeedback sessions.A follow-up assessment was conducted after 4 months.Results The frontal resting-state theta power spectral density(PSD)was significantly altered in the real-feedback group after two neurofeedback visits.Higher theta PSD in the real-feedback group before neurofeedback was the only predictor of decreased cigarette consumption at the 4-month follow-up.Further reliability analysis revealed a significant positive correlation between theta PSD pre-neurofeedback and post-neurofeedback.A leave-one-out cross-validated linear regression of the theta PSD pre-neurofeedback demonstrated a significant correlation between the predicted and observed reductions in cigarette consumption at the 4-month follow-up.Finally,source analysis revealed that the brain mechanisms of the theta PSD predictor were located in the orbital frontal cortex.Conclusions Our study demonstrated changes in the resting-state theta PSD following neurofeedback training.Moreover,the resting-state theta PSD may serve as a prognostic marker of neurofeedback effects.A higher resting-state theta PSD predicts a better long-term response to neurofeedback treatment,which may facilitate the selection of individualised interventions.展开更多
Background Internet gaming disorder(IGD)is a mental health issue that affects individuals worldwide.However,the lack of knowledge about the biomarkers associated with the development of IGD has restricted the diagnosi...Background Internet gaming disorder(IGD)is a mental health issue that affects individuals worldwide.However,the lack of knowledge about the biomarkers associated with the development of IGD has restricted the diagnosis and treatment of this disorder.Aims We aimed to reveal the biomarkers associated with the development of IGD through resting-state brain network analysis and provide clues for the diagnosis and treatment of IGD.Methods Twenty-six patients with IGD,23 excessive internet game users(EIUs)who recurrently played internet games but were not diagnosed with IGD and 29 healthy controls(HCs)performed delay discounting task(DDT)and Iowa gambling task(IGT).Resting-state functional magnetic resonance imaging(fMRI)data were also collected.Results Patients with IGD exhibited significantly lower hubness in the right medial orbital part of the superior frontal gyrus(ORBsupmed)than both the EIU and the HC groups.Additionally,the hubness of the right ORBsupmed was found to be positively correlated with the highest excessive internet gaming degree during the past year in the EIU group but not the IGD group;this might be the protective mechanism that prevents EIUs from becoming addicted to internet games.Moreover,the hubness of the right ORBsupmed was found to be related to the treatment outcome of patients with IGD,with higher hubness of this region indicating better recovery when undergoing forced abstinence.Further modelling analysis of the DDT and IGT showed that patients with IGD displayed higher impulsivity during the decision-making process,and impulsivity-related parameters were negatively correlated with the hubness of right ORBsupmed.Conclusions Our findings revealed that the impulsivity-related right ORBsupmed hubness could serve as a potential biomarker of IGD and provide clues for the diagnosis and treatment of IGD.展开更多
The Yellow River Source National Park(YRSP)is one of the most sensitive and fragile ecological regions in the world.The historical intensive grazing and climate change have resulted in ecological degradation that thre...The Yellow River Source National Park(YRSP)is one of the most sensitive and fragile ecological regions in the world.The historical intensive grazing and climate change have resulted in ecological degradation that threatens the wildlife and livestock.Exploring the sustainable strategy is urgent for policy makers to meet the demands for wild ungulates and livestock.In our study,the grassland ecological carrying capability(GECC)was assessed based on the updated grass-livestock balance that considered the grass competition from wild ungulates.The balances between grass and livestock,and GECC and grassland pressure index(GPI)in the YRSP were measured through overlay analysis and geostatistic analysis.The results showed that:(1)the ratio of livestock to wild ungulates in the research area was approximately 4.56:1,in which the proportion of livestock was 81.75%and the actual number of livestock was 33.84×104 standard sheep units;(2)Under the scenario of minimum grazing utilisation rate,the theoretical grazing capacity and GECC were 37.83×104 standard sheep units and−0.13,respectively.Under the maximum grazing utilisation rate,the theoretical grazing capacity and GECC were 41.93×104 standard sheep units and−0.21,respectively.Since GECC in both scenarios were both less than 0,the grassland was considered to be in surplus and the livestock was not overloaded.However,GPI in the two scenarios were 0.87 and 0.79,respectively,both of which exceeded the warning line of 0.70.Based on GECC,we recommend that the sustainable strategy in YRSP is either to increase the supplementary feeding about 6.40×104 standard sheep units or reduce the grazing livestock by about 3.50×10^(4) standard sheep units.展开更多
In this paper, a new method of combination single layer wavelet transform and compressive sensing is proposed for image fusion. In which only measured the high-pass wavelet coefficients of the image but preserved the ...In this paper, a new method of combination single layer wavelet transform and compressive sensing is proposed for image fusion. In which only measured the high-pass wavelet coefficients of the image but preserved the low-pass wavelet coefficient. Then, fuse the low-pass wavelet coefficients and the measurements of high-pass wavelet coefficient with different schemes. For the reconstruction, by using the minimization of total variation algorithm (TV), high-pass wavelet coefficients could be recovered by the fused measurements. Finally, the fused image could be reconstructed by the inverse wavelet transform. The experiments show the proposed method provides promising fusion performance with a low computational complexity.展开更多
In the present study, newly design hybrid nanostructures were produced by growing long carbon nanofibers (CNF) on single- and multi-layer graphene oxide (GO) sheets in the presence of catalyst by chemical vapor deposi...In the present study, newly design hybrid nanostructures were produced by growing long carbon nanofibers (CNF) on single- and multi-layer graphene oxide (GO) sheets in the presence of catalyst by chemical vapor deposition (CVD). Chemical composition analysis indicated the formation of Fe-C bonds by the deposition of carbon atoms on catalyst surface of Fe2O3 and increasing in C/O atomic ratio confirming CNF growing. These hybrid additives were distributed homogeneously through polyamide 6.6 (PA6.6) chains by high shear thermokinetic mixer in melt phase. Spectroscopic studies showed that the differences in the number of graphene layer in hybrid structures directly affected the crystalline behavior and dispersion state in polymer matrix. Flexural strength and flexural modulus of PA6.6 nanocomposites were improved up to 14.7% and 14% by the integration of 0.5 wt% CNF grown on multi-layer GO, respectively, whereas there was a significant loss in flexural properties of single-layer GO based nanocomposites. Also, the integration of 0.5 wt% multi-layer GO hybrid reinforcement in PA6.6 provided a significant increase in tensile modulus about 24%. Therefore, multi-layer GO with CNF increased the degree of crystallinity in nanocomposites by forming intercalated structure and acted as a nucleating agent causing the improvement in mechanical properties.展开更多
Magnetic resonance imaging(MRI)plays an important role in precision medicine that is hampered by the lack of contrast agents with high efficiency and the ability to translate diagnostic accuracy into therapeutic inter...Magnetic resonance imaging(MRI)plays an important role in precision medicine that is hampered by the lack of contrast agents with high efficiency and the ability to translate diagnostic accuracy into therapeutic intervention.Herein,we demonstrate a DNA-based MRI probe that overcomes previous single-mode enhancement and provides a mechanism of action for aggregationinduced dual-modal MRI signal enhancement.A facile method is developed to produce aggregated T_(1)/T_(2)dual-modal NaGdF_(4):Dy@PDA-DNA(PDA=polydopamine)MRI probes.When aggregated,this probe can further amplify MRI signal intensity and exhibit improved geometrical and positional stability in vivo.The performance of the NaGdF_(4):Dy@PDA-DNA MRI probe toward MRI-guided preoperative planning and visualization-guided surgery is verified using an orthotopic tumor-bearing mouse model.The result shows that the rapid metabolism of the degraded probe leads to the mitigation of long-term toxic effects.Therefore,the developed high-performance MRI probe is of great significance for enhancing MRI diagnostic accuracy into precision medical therapeutic interventions.展开更多
As the key principle of precision farming,the distribution of fractional vegetation cover is the basis of crop management within the field serves.To estimate crop FVC rapidly at the farm scale,high temporal-spatial re...As the key principle of precision farming,the distribution of fractional vegetation cover is the basis of crop management within the field serves.To estimate crop FVC rapidly at the farm scale,high temporal-spatial resolution imagery obtained by unmanned aerial vehicle(UAV)was adopted.To verify the application potential of consumer-grade UAV RGB imagery in estimated FVC,blue-green characteristic vegetation index(TBVI)and red-green vegetation index(TRVI)were proposed in this study according to the differences of the gray value among cotton vegetation,soil and shadow in the field.First,two new constructed indices and several published indices were used to extract visible light images and generate greyscale images for each of the visible light vegetation indices.Then,the thresholds of cotton vegetation and non-vegetation pixels were established based on the vegetation index threshold method which combines support vector machine classification and vegetation index.Finally,the accuracy difference in vegetation information extraction between the newly constructed and several published indices was compared.The results show that the accuracy of the information extracted by TRVI is higher than that of subdivision index of other visible light(FVC extraction precision in the first bud stage of cotton:R2=0.832,RMSE=2.307,nRMSE=4.405%;FVC extraction precision in the bud stage of cotton:R2=0.981,RMSE=1.393,nRMSE=1.984%;FVC extraction precision in the flowering stage of cotton:R2=0.893,RMSE=2.101,nRMSE=2.422%;FVC extraction precision in the boll stage of cotton:R2=0.958,RMSE=1.850,nRMSE=2.050%).展开更多
文摘Basic surveying and mapping involves a lot of content, which is a systematic and complex work. In actual surveying and mapping, it is necessary not only to improve the accuracy of surveying and mapping, but also to further improve the efficiency of surveying and mapping. In recent years, UAV technology has developed rapidly, and UAV remote sensing mapping has also become a new surveying and mapping technology. It can use corresponding equipment to control UAVs and photographic equipment to obtain corresponding information. However, the UAV remote sensing mapping technology is still in the initial stage of development at this stage, and further research on practical problems needs to be enhanced when applied in basic surveying and mapping, so as to effectively promote the development of UAV remote sensing mapping technology.
文摘The development and applications of low temperature plasma technology used in surface modification of materials are presented in this paper. Based on plasma sources and ion sources technology, multi-functions ion implantation and deposition technologies were developed and the related processes are also used to treat different products. The related technologies were translated into industrial productions supported by national research projects. Following the last development of international plasma researches, the standardization and internationalization processes of plasma technologies are executed in our center.
基金supported by a project entitled Loess Plateau Region-Watershed-Slope Geological Hazard Multi-Scale Collaborative Intelligent Early Warning System of the National Key R&D Program of China(2022YFC3003404)a project of the Shaanxi Youth Science and Technology Star(2021KJXX-87)public welfare geological survey projects of Shaanxi Institute of Geologic Survey(20180301,201918,202103,and 202413).
文摘This study investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,China.Based on randomly generated 40 NTDs,the study developed models for the geologic hazard susceptibility assessment using the random forest algorithm and evaluated their performances using the area under the receiver operating characteristic curve(AUC).Specifically,the means and standard deviations of the AUC values from all models were then utilized to assess the overall spatial correlation between the conditioning factors and the susceptibility assessment,as well as the uncertainty introduced by the NTDs.A risk and return methodology was thus employed to quantify and mitigate the uncertainty,with log odds ratios used to characterize the susceptibility assessment levels.The risk and return values were calculated based on the standard deviations and means of the log odds ratios of various locations.After the mean log odds ratios were converted into probability values,the final susceptibility map was plotted,which accounts for the uncertainty induced by random NTDs.The results indicate that the AUC values of the models ranged from 0.810 to 0.963,with an average of 0.852 and a standard deviation of 0.035,indicating encouraging prediction effects and certain uncertainty.The risk and return analysis reveals that low-risk and high-return areas suggest lower standard deviations and higher means across multiple model-derived assessments.Overall,this study introduces a new framework for quantifying the uncertainty of multiple training and evaluation models,aimed at improving their robustness and reliability.Additionally,by identifying low-risk and high-return areas,resource allocation for geologic hazard prevention and control can be optimized,thus ensuring that limited resources are directed toward the most effective prevention and control measures.
基金supported by the National Social Science Fund of China[Grant No.21BGL181]to Yan Chen.
文摘Coal dependence and inefficient decentralized heating have significantly increased China’s energy consumption for winter heating,increasing air pollution and exacerbating the greenhouse effect.In 2017,China implemented the Pilot Policy on Clean Winter Heating in Northern China,aiming to achieve high central heating coverage and cleaner energy consumption.Studying the effects of this policy can help promote its implementation and serve as a reference for effective adjustment of the contents in the future.However,few studies have investigated this policy and its carbon reduction effects,and most focus on the provincial or city levels.Therefore,this paper considers the policy’s influence on air pollution and carbon emissions at the county level to provide a precise and comprehensive assessment of the policy effects.We use panel data from 1290 counties in 15 provinces in Northern China from 2014 to 2021,applying a multiperiod difference-in-differences model to quantify the impact of the policy on carbon emissions and air quality in the pilot area.We then conduct a series of tests to demonstrate the robustness of the results and analyze the mechanisms of the policy effects from two perspectives,namely,central heating and natural gas use,through a mediating effect model.Finally,we examine the heterogeneity of policy effects between counties based on geographic location and per capita income levels of rural residents through a moderating effect model.The results reveal that the policy significantly reduces air pollution and carbon emissions in the pilot area by increasing the central heating area and natural gas use.Compared with the central and western regions in the north and areas with low-income rural residents,the policy effects in the eastern regions in the north and areas with high-income rural residents are more pronounced.
基金the financial support for this research provided by the National Natural Science Foundation of China (No. 51966012) ProjectProgram for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region (No. NJYT-18-A12)+2 种基金Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region (No. NJZY17491)Major science and Technology Projects in Inner Mongolia (2018)Inner Mongolia Autonomous Region Graduate Research Innovation Project (No. S20201156Z)。
文摘It is difficult for solanum crops to grow continuously during winter in severe cold regions. Thus, a soil heating system for facility agriculture based on solar concentration technology was proposed, and a novel compound parabolic concentration photothermal and photoelectricity device(CTPV) equipped in the system was designed to address this problem. In accordance with the structure of the device, LightTools optical software was selected to analyze the variation trend of the light escape rate of the device with the diff erent incident angles. On the basis of the calculation results, an experimental test system was used to investigate the relationship of the air temperature of the inlet and the outlet, total output power of the solar cells, and photothermal and photoelectricity efficiency of the device with the operation time during a sunny day. Research results reveal that the light escape rate of the device is 5.36% at an incidence angle of 12°. At a velocity of 1.5 m/s, the maximum air temperature of the outlet can reach 55.6 ℃, and the total output power of the solar cells is 474.4 W. The variation of the total power of the solar cells is consistent with the simulation results. The maximum instantaneous heat collection and the maximum photothermal and photoelectricity efficiency of the device are 306 W and 60.4%, respectively, and the average efficiency is 44.9%. This study can serve as a reference for compound parabolic concentration technology applied for soil heating in facility agricultural soil heating systems.
基金This work was supported by the National Natural Science Foundation of China(32000750,32171080,71942003,and 32161143022)Grants for Scientific Research of BSKY(XJ201907)from Anhui Medical University+4 种基金Scientific Research Improvement Project of Anhui Medical University(2021xkjT018)Research Fund of Anhui Institute of Translational Medicine(2022zhyx-C02)Basic and Clinical Collaborative Research Improvement Project of Anhui Medical University(2020xkjT020)The Chinese National Programs for Brain Science and Brain-like Intelligence Technology(2021ZD0202101)CAS-VPST Silk Road Science Fund 2021(GLHZ202128).The numerical calculations in this paper have been done on the Medical Big Data Supercomputing Center System of Anhui Medical University and Bioinformatics Center of the University of Science and Technology of China.
文摘Background The high rate of long-term relapse is a major cause of smoking cessation failure.Recently,neurofeedback training has been widely used in the treatment of nicotine addiction;however,approximately 30%of subjects fail to benefit from this intervention.Our previous randomised clinical trial(RCT)examined cognition-guided neurofeedback and demonstrated a significant decrease in daily cigarette consumption at the 4-month follow-up.However,significant individual differences were observed in the 4-month follow-up effects of decreased cigarette consumption.Therefore,it is critical to identify who will benefit from pre-neurofeedback.Aims We examined whether the resting-state electroencephalography(EEG)characteristics from pre-neurofeedback predicted the 4-month follow-up effects and explored the possible mechanisms.Methods This was a double-blind RCT.A total of 60 participants with nicotine dependence were randomly assigned to either the real-feedback or yoked-feedback group.They underwent 6 min closed-eye resting EEG recordings both before and after two neurofeedback sessions.A follow-up assessment was conducted after 4 months.Results The frontal resting-state theta power spectral density(PSD)was significantly altered in the real-feedback group after two neurofeedback visits.Higher theta PSD in the real-feedback group before neurofeedback was the only predictor of decreased cigarette consumption at the 4-month follow-up.Further reliability analysis revealed a significant positive correlation between theta PSD pre-neurofeedback and post-neurofeedback.A leave-one-out cross-validated linear regression of the theta PSD pre-neurofeedback demonstrated a significant correlation between the predicted and observed reductions in cigarette consumption at the 4-month follow-up.Finally,source analysis revealed that the brain mechanisms of the theta PSD predictor were located in the orbital frontal cortex.Conclusions Our study demonstrated changes in the resting-state theta PSD following neurofeedback training.Moreover,the resting-state theta PSD may serve as a prognostic marker of neurofeedback effects.A higher resting-state theta PSD predicts a better long-term response to neurofeedback treatment,which may facilitate the selection of individualised interventions.
基金This work was supported by grants from The Chinese National Programs for Brain Science and Brain-like Intelligence Technology(2021ZD0202101)The National Natural Science Foundation of China(32171080,32161143022,71942003,31900766 and 71874170)+3 种基金the Major Project of Philosophy and Social Science Research,Ministry of Education of China(19JZD010)the CAS-VPST Silk Road Science Fund 2021(GLHZ202128)the Collaborative Innovation Program of Hefei Science Center,CAS(2020HSC-CIP001)the Anhui Provincial Key Research and Development Project(202004b11020013).
文摘Background Internet gaming disorder(IGD)is a mental health issue that affects individuals worldwide.However,the lack of knowledge about the biomarkers associated with the development of IGD has restricted the diagnosis and treatment of this disorder.Aims We aimed to reveal the biomarkers associated with the development of IGD through resting-state brain network analysis and provide clues for the diagnosis and treatment of IGD.Methods Twenty-six patients with IGD,23 excessive internet game users(EIUs)who recurrently played internet games but were not diagnosed with IGD and 29 healthy controls(HCs)performed delay discounting task(DDT)and Iowa gambling task(IGT).Resting-state functional magnetic resonance imaging(fMRI)data were also collected.Results Patients with IGD exhibited significantly lower hubness in the right medial orbital part of the superior frontal gyrus(ORBsupmed)than both the EIU and the HC groups.Additionally,the hubness of the right ORBsupmed was found to be positively correlated with the highest excessive internet gaming degree during the past year in the EIU group but not the IGD group;this might be the protective mechanism that prevents EIUs from becoming addicted to internet games.Moreover,the hubness of the right ORBsupmed was found to be related to the treatment outcome of patients with IGD,with higher hubness of this region indicating better recovery when undergoing forced abstinence.Further modelling analysis of the DDT and IGT showed that patients with IGD displayed higher impulsivity during the decision-making process,and impulsivity-related parameters were negatively correlated with the hubness of right ORBsupmed.Conclusions Our findings revealed that the impulsivity-related right ORBsupmed hubness could serve as a potential biomarker of IGD and provide clues for the diagnosis and treatment of IGD.
基金funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA23060601)National Natural Science Foundation of China (U20A2088)+2 种基金Monitoring and Warning Program for Resources and Environment Carrying Capability in Sichuan Province (Grant No. ZXGH201709)Land space planning of Sichuan Province (2019-2035)Ecological restoration planning of land space in Sichuan Province (20212035)
文摘The Yellow River Source National Park(YRSP)is one of the most sensitive and fragile ecological regions in the world.The historical intensive grazing and climate change have resulted in ecological degradation that threatens the wildlife and livestock.Exploring the sustainable strategy is urgent for policy makers to meet the demands for wild ungulates and livestock.In our study,the grassland ecological carrying capability(GECC)was assessed based on the updated grass-livestock balance that considered the grass competition from wild ungulates.The balances between grass and livestock,and GECC and grassland pressure index(GPI)in the YRSP were measured through overlay analysis and geostatistic analysis.The results showed that:(1)the ratio of livestock to wild ungulates in the research area was approximately 4.56:1,in which the proportion of livestock was 81.75%and the actual number of livestock was 33.84×104 standard sheep units;(2)Under the scenario of minimum grazing utilisation rate,the theoretical grazing capacity and GECC were 37.83×104 standard sheep units and−0.13,respectively.Under the maximum grazing utilisation rate,the theoretical grazing capacity and GECC were 41.93×104 standard sheep units and−0.21,respectively.Since GECC in both scenarios were both less than 0,the grassland was considered to be in surplus and the livestock was not overloaded.However,GPI in the two scenarios were 0.87 and 0.79,respectively,both of which exceeded the warning line of 0.70.Based on GECC,we recommend that the sustainable strategy in YRSP is either to increase the supplementary feeding about 6.40×104 standard sheep units or reduce the grazing livestock by about 3.50×10^(4) standard sheep units.
文摘In this paper, a new method of combination single layer wavelet transform and compressive sensing is proposed for image fusion. In which only measured the high-pass wavelet coefficients of the image but preserved the low-pass wavelet coefficient. Then, fuse the low-pass wavelet coefficients and the measurements of high-pass wavelet coefficient with different schemes. For the reconstruction, by using the minimization of total variation algorithm (TV), high-pass wavelet coefficients could be recovered by the fused measurements. Finally, the fused image could be reconstructed by the inverse wavelet transform. The experiments show the proposed method provides promising fusion performance with a low computational complexity.
基金ordsa Teknik Tekstil A.S.Company for providing financial support.
文摘In the present study, newly design hybrid nanostructures were produced by growing long carbon nanofibers (CNF) on single- and multi-layer graphene oxide (GO) sheets in the presence of catalyst by chemical vapor deposition (CVD). Chemical composition analysis indicated the formation of Fe-C bonds by the deposition of carbon atoms on catalyst surface of Fe2O3 and increasing in C/O atomic ratio confirming CNF growing. These hybrid additives were distributed homogeneously through polyamide 6.6 (PA6.6) chains by high shear thermokinetic mixer in melt phase. Spectroscopic studies showed that the differences in the number of graphene layer in hybrid structures directly affected the crystalline behavior and dispersion state in polymer matrix. Flexural strength and flexural modulus of PA6.6 nanocomposites were improved up to 14.7% and 14% by the integration of 0.5 wt% CNF grown on multi-layer GO, respectively, whereas there was a significant loss in flexural properties of single-layer GO based nanocomposites. Also, the integration of 0.5 wt% multi-layer GO hybrid reinforcement in PA6.6 provided a significant increase in tensile modulus about 24%. Therefore, multi-layer GO with CNF increased the degree of crystallinity in nanocomposites by forming intercalated structure and acted as a nucleating agent causing the improvement in mechanical properties.
基金supported by the National Natural Science Foundation of China(22134006,21721003,22204161,U2241287)the Natural Science Foundation of Shandong Province(ZR2020MB063)the Program of Science and Technology Development Plan of Jilin Province(20230101039JC)。
文摘Magnetic resonance imaging(MRI)plays an important role in precision medicine that is hampered by the lack of contrast agents with high efficiency and the ability to translate diagnostic accuracy into therapeutic intervention.Herein,we demonstrate a DNA-based MRI probe that overcomes previous single-mode enhancement and provides a mechanism of action for aggregationinduced dual-modal MRI signal enhancement.A facile method is developed to produce aggregated T_(1)/T_(2)dual-modal NaGdF_(4):Dy@PDA-DNA(PDA=polydopamine)MRI probes.When aggregated,this probe can further amplify MRI signal intensity and exhibit improved geometrical and positional stability in vivo.The performance of the NaGdF_(4):Dy@PDA-DNA MRI probe toward MRI-guided preoperative planning and visualization-guided surgery is verified using an orthotopic tumor-bearing mouse model.The result shows that the rapid metabolism of the degraded probe leads to the mitigation of long-term toxic effects.Therefore,the developed high-performance MRI probe is of great significance for enhancing MRI diagnostic accuracy into precision medical therapeutic interventions.
基金The authors gratefully acknowledge the financial support provided by Top Talents Program for One Case One Discussion of Shandong Province,China Agriculture Research System(Grant No.CARS-15-22)Natural Science Foundation of Shandong Province(Grant No.ZR2021MD091).
文摘As the key principle of precision farming,the distribution of fractional vegetation cover is the basis of crop management within the field serves.To estimate crop FVC rapidly at the farm scale,high temporal-spatial resolution imagery obtained by unmanned aerial vehicle(UAV)was adopted.To verify the application potential of consumer-grade UAV RGB imagery in estimated FVC,blue-green characteristic vegetation index(TBVI)and red-green vegetation index(TRVI)were proposed in this study according to the differences of the gray value among cotton vegetation,soil and shadow in the field.First,two new constructed indices and several published indices were used to extract visible light images and generate greyscale images for each of the visible light vegetation indices.Then,the thresholds of cotton vegetation and non-vegetation pixels were established based on the vegetation index threshold method which combines support vector machine classification and vegetation index.Finally,the accuracy difference in vegetation information extraction between the newly constructed and several published indices was compared.The results show that the accuracy of the information extracted by TRVI is higher than that of subdivision index of other visible light(FVC extraction precision in the first bud stage of cotton:R2=0.832,RMSE=2.307,nRMSE=4.405%;FVC extraction precision in the bud stage of cotton:R2=0.981,RMSE=1.393,nRMSE=1.984%;FVC extraction precision in the flowering stage of cotton:R2=0.893,RMSE=2.101,nRMSE=2.422%;FVC extraction precision in the boll stage of cotton:R2=0.958,RMSE=1.850,nRMSE=2.050%).
