The gut microbiota plays a pivotal role in the maintenance of health for amphibians,and it has been fully recognized,but the effectiveness of various influencing factors has not yet been fully clarified.Although this ...The gut microbiota plays a pivotal role in the maintenance of health for amphibians,and it has been fully recognized,but the effectiveness of various influencing factors has not yet been fully clarified.Although this association should be considered while the amphibian order Caudata is facing a severe situation of population decline and extinction,there is little understanding of the association between diets and the diversity of gut microbiota in the amphibian order Caudata.Here,we conducted an extensive analysis of the gut microbiota of Cynops orientalis fed different diets using functional prediction and 16S rRNA amplicon sequencing techniques.First,we found that wild individuals had greater gut microbial diversity and richness in comparison to captive individuals.Second,we identified the bacterial taxa associated with diets and observed differences in the relative abundance of gut microbiota among people on various diets.Finally,we have a predictive comprehension of the selection and adaptative significance of shared core ASVs in the gut microbiota in maintaining the healthy survival of C.orientalis in a large-scale spatiotemporal map.Our study emphasizes how diets alter the gut microbiota of Caudata and offers fresh perspectives on the conservation and captive management of species in Caudata.展开更多
Fireworks burning releases massive fine particles and gaseous pollutants, significantly deteriorating air quality during Chinese Lunar New Year （LNY） period. To investigate the impact of the fireworks burning on the...Fireworks burning releases massive fine particles and gaseous pollutants, significantly deteriorating air quality during Chinese Lunar New Year （LNY） period. To investigate the impact of the fireworks burning on the atmospheric aerosol chemistry, 1-hr time resolution of PM2.5 samples in Xi＇an during the winter of 2016 including the LNY were collected and detected for inorganic ions, acidity and liquid water content （LWC） of the fine aerosols. PM2.5 during the LNY was 167 ± 87 μg/m^3, two times higher than the China National Ambient Air Quality Standard （75 μg/m^3）. K^＋ （28 wt.% of the total ion mass） was the most abundant ion in the LNY period, followed by SO^2-4 （25 wt.%） and C1^- （18 wt.%）. In contrast, NO^-3 （34 wt.%） was the most abundant species in the haze periods （hourly PM2.5 〉 75 μg/m^3）, followed by SO^2-4 （29.2 wt.%） and NH^＋4 （16.3 wt.%）, while SC94 （35 wt.%） was the most abundant species in the clean periods （hourly PM2.5 〈 75 μg/m^3）, followed by NO^-3 （23.1 wt.%） and NH^＋4 （11 wt.%）. Being different from the acidic nature in the non-LNY periods, aerosol in the LNY period presented an alkaline nature with a pH value of 7.8 ± 1.3. LWC during the LNY period showed a robust linear correlation with K2SO4 and KC1, suggesting that aerosol hygroscopicity was dominated by inorganic salts derived from fireworks burning. Analysis of correlations between the ratios of NO^-3/SO^2-4 and NH^＋4/SO^2-4 indicated that heterogeneous reaction of HNO3 with NH3 was an important formation pathway of particulate nitrate and ammonium during the LNY period.展开更多
Although the development of the robot picking vision system is widely applied,it is very challenging for fruit detection in orchards with complex light and environment,especially for fruit colors similar to the backgr...Although the development of the robot picking vision system is widely applied,it is very challenging for fruit detection in orchards with complex light and environment,especially for fruit colors similar to the background.In recent,there are few studies on pecan fruit detection and location based on machine vision.In this study,an accurate and efficient pecan fruit detection method was proposed based on machine vision under natural pecan orchards.In order to solve the illumination problem,a light compensation algorithm was first utilized to process the collected samples,and then an improved Faster Region Convolutional Neural Network(Faster RCNN)with the Feature Pyramid Networks(FPN)was established to train the samples.Finally,the pecan number counting method was introduced to count the number of pecan.A total of 241 pecan images were tested,and comparison experiments were carried out.The mean average precision(mAP)of the proposed detection method was 95.932%,compared with the result without uneven illumination correction(UIC),which was increased by 0.849%,while the mAP of the Single Shot Detector(SSD)+FPN was 92.991%.In addition,the number of clusters was counted using the proposed method with an accuracy rate of 93.539%compared with the actual clusters.The results demonstrate that the proposed network has good robustness for pecan fruit detection in different illumination and various unstructured environments,and the experimental achievement has great potential for robot-picking visual systems.展开更多
Airborne bacteria play key roles in terrestrial and marine ecosystems and human health,yet our understanding of bacterial communities and their response to the environmental variables lags significantly behind that of...Airborne bacteria play key roles in terrestrial and marine ecosystems and human health,yet our understanding of bacterial communities and their response to the environmental variables lags significantly behind that of other components of PM_(2.5).Here,atmospheric fine particles obtained from urban and suburb Shanghai were analyzed by using the qPCR and Illumina Miseq sequencing.The bacteria with an average concentration of 2.12× 10^(3 )cells/m^(3),were dominated by Sphingomonas,Curvibacter,Acinetobacter,Bradyrhizobium,Methylobacterium,Halomonas,Aliihoeflea,and Phyllobacterium,which were related to the nitrogen,carbon,sulfur cycling and human health risk.Our results provide a global survey of bacterial community across urban,suburb,and high-altitude sites.In Shanghai(China),urban PM2.5 harbour more diverse and dynamic bacterial populations than that in the suburb.The structural equation model explained about 27%,41%,and 20%^78%of the variance found in bacteria diversity,concentration,and discrepant genera among urban and suburb sites.This work furthered the knowledge of diverse bacteria in a coastal Megacity in the Yangtze river delta and emphasized the potential impact of environmental variables on bacterial community structure.展开更多
基金funded by the National Natural Science Foundation of China(31901120 and 31700320)China Postdoctoral Science Foundation(2022M723135)+2 种基金Beijing Natural Science Foundation(5192016)Anhui Provincial Key Laboratory of the Conservation and Exploitation of Biological Resources(swzy202006)Innovation and Entrepreneurship Training Program for college students of Anhui Normal University.
文摘The gut microbiota plays a pivotal role in the maintenance of health for amphibians,and it has been fully recognized,but the effectiveness of various influencing factors has not yet been fully clarified.Although this association should be considered while the amphibian order Caudata is facing a severe situation of population decline and extinction,there is little understanding of the association between diets and the diversity of gut microbiota in the amphibian order Caudata.Here,we conducted an extensive analysis of the gut microbiota of Cynops orientalis fed different diets using functional prediction and 16S rRNA amplicon sequencing techniques.First,we found that wild individuals had greater gut microbial diversity and richness in comparison to captive individuals.Second,we identified the bacterial taxa associated with diets and observed differences in the relative abundance of gut microbiota among people on various diets.Finally,we have a predictive comprehension of the selection and adaptative significance of shared core ASVs in the gut microbiota in maintaining the healthy survival of C.orientalis in a large-scale spatiotemporal map.Our study emphasizes how diets alter the gut microbiota of Caudata and offers fresh perspectives on the conservation and captive management of species in Caudata.
基金supported by the National Key R&D Program of China (No. 2017YFC0210000)the National Natural Science Funds of China for Distinguished Young Scholars (No. 41325014)the National Nature Science Foundation of China (No. 41773117)
文摘Fireworks burning releases massive fine particles and gaseous pollutants, significantly deteriorating air quality during Chinese Lunar New Year （LNY） period. To investigate the impact of the fireworks burning on the atmospheric aerosol chemistry, 1-hr time resolution of PM2.5 samples in Xi＇an during the winter of 2016 including the LNY were collected and detected for inorganic ions, acidity and liquid water content （LWC） of the fine aerosols. PM2.5 during the LNY was 167 ± 87 μg/m^3, two times higher than the China National Ambient Air Quality Standard （75 μg/m^3）. K^＋ （28 wt.% of the total ion mass） was the most abundant ion in the LNY period, followed by SO^2-4 （25 wt.%） and C1^- （18 wt.%）. In contrast, NO^-3 （34 wt.%） was the most abundant species in the haze periods （hourly PM2.5 〉 75 μg/m^3）, followed by SO^2-4 （29.2 wt.%） and NH^＋4 （16.3 wt.%）, while SC94 （35 wt.%） was the most abundant species in the clean periods （hourly PM2.5 〈 75 μg/m^3）, followed by NO^-3 （23.1 wt.%） and NH^＋4 （11 wt.%）. Being different from the acidic nature in the non-LNY periods, aerosol in the LNY period presented an alkaline nature with a pH value of 7.8 ± 1.3. LWC during the LNY period showed a robust linear correlation with K2SO4 and KC1, suggesting that aerosol hygroscopicity was dominated by inorganic salts derived from fireworks burning. Analysis of correlations between the ratios of NO^-3/SO^2-4 and NH^＋4/SO^2-4 indicated that heterogeneous reaction of HNO3 with NH3 was an important formation pathway of particulate nitrate and ammonium during the LNY period.
基金funded by the Forestry Science and Technology Innovation Fund Project of Hunan Province(Grant No.XLK202108-4)and the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘Although the development of the robot picking vision system is widely applied,it is very challenging for fruit detection in orchards with complex light and environment,especially for fruit colors similar to the background.In recent,there are few studies on pecan fruit detection and location based on machine vision.In this study,an accurate and efficient pecan fruit detection method was proposed based on machine vision under natural pecan orchards.In order to solve the illumination problem,a light compensation algorithm was first utilized to process the collected samples,and then an improved Faster Region Convolutional Neural Network(Faster RCNN)with the Feature Pyramid Networks(FPN)was established to train the samples.Finally,the pecan number counting method was introduced to count the number of pecan.A total of 241 pecan images were tested,and comparison experiments were carried out.The mean average precision(mAP)of the proposed detection method was 95.932%,compared with the result without uneven illumination correction(UIC),which was increased by 0.849%,while the mAP of the Single Shot Detector(SSD)+FPN was 92.991%.In addition,the number of clusters was counted using the proposed method with an accuracy rate of 93.539%compared with the actual clusters.The results demonstrate that the proposed network has good robustness for pecan fruit detection in different illumination and various unstructured environments,and the experimental achievement has great potential for robot-picking visual systems.
基金by the Shanghai Sailing Program(19YF1403200)National Natural Science Foundation of China(Grant Nos.21906023,91843301,91743202,21527814)+2 种基金Ministry of Science and Technology of China(No.2016YFC0202700)Marie Skto-dowska-Curie Actions(690958-MARSU-RISE-2015)China Postdoctoral Science Foundation(No.2018M640331).
文摘Airborne bacteria play key roles in terrestrial and marine ecosystems and human health,yet our understanding of bacterial communities and their response to the environmental variables lags significantly behind that of other components of PM_(2.5).Here,atmospheric fine particles obtained from urban and suburb Shanghai were analyzed by using the qPCR and Illumina Miseq sequencing.The bacteria with an average concentration of 2.12× 10^(3 )cells/m^(3),were dominated by Sphingomonas,Curvibacter,Acinetobacter,Bradyrhizobium,Methylobacterium,Halomonas,Aliihoeflea,and Phyllobacterium,which were related to the nitrogen,carbon,sulfur cycling and human health risk.Our results provide a global survey of bacterial community across urban,suburb,and high-altitude sites.In Shanghai(China),urban PM2.5 harbour more diverse and dynamic bacterial populations than that in the suburb.The structural equation model explained about 27%,41%,and 20%^78%of the variance found in bacteria diversity,concentration,and discrepant genera among urban and suburb sites.This work furthered the knowledge of diverse bacteria in a coastal Megacity in the Yangtze river delta and emphasized the potential impact of environmental variables on bacterial community structure.
