Upland crop-rice cropping systems(UCR)facilitate sustainable agricultural intensification.Accurate UCR cultivation mapping is needed to ensure food security,sustainable water management,and rural revitalization.Howeve...Upland crop-rice cropping systems(UCR)facilitate sustainable agricultural intensification.Accurate UCR cultivation mapping is needed to ensure food security,sustainable water management,and rural revitalization.However,datasets describing cropping systems are limited in spatial coverage and crop types.Mapping UCR is more challenging than crop identification and most existing approaches rely heavily on accurate phenology calendars and representative training samples,which limits its applications over large regions.We describe a novel algorithm(RRSS)for automatic mapping of upland crop-rice cropping systems using Sentinel-1 Synthetic Aperture Radar(SAR)and Sentinel-2 Multispectral Instrument(MSI)data.One indicator,the VV backscatter range,was proposed to discriminate UCR and another two indicators were designed by coupling greenness and pigment indices to further discriminate tobacco or oilseed UCR.The RRSS algorithm was applied to South China characterized by complex smallholder rice cropping systems and diverse topographic conditions.This study developed 10-m UCR maps of a major rice bowl in South China,the Xiang-Gan-Min(XGM)region.The performance of the RRSS algorithm was validated based on 5197 ground-truth reference sites,with an overall accuracy of 91.92%.There were7348 km^(2) areas of UCR,roughly one-half of them located in plains.The UCR was represented mainly by oilseed-UCR and tobacco-UCR,which contributed respectively 69%and 15%of UCR area.UCR patterns accounted for only one-tenth of rice production,which can be tripled by intensification from single rice cropping.Application to complex and fragmented subtropical regions suggested the spatiotemporal robustness of the RRSS algorithm,which could be further applied to generate 10-m UCR datasets for application at national or global scales.展开更多
Cotton breeding for the development of early-maturing varieties is an effective way to improve multiple cropping indexes and alleviate the conflict between grains and cotton in the cultivated fields in China.In the pr...Cotton breeding for the development of early-maturing varieties is an effective way to improve multiple cropping indexes and alleviate the conflict between grains and cotton in the cultivated fields in China.In the present study,we aimed to identify upland cotton quantitative trait loci(QTLs)and candidate genes related to early-maturity traits,including whole growth period(WGP),flowering timing(FT),node of the first fruiting branch(NFFB),height of the node of the first fruiting branch(HNFFB),and plant height(PH).An early-maturing variety,CCRI50,and a latematuring variety,Guoxinmian 11,were crossed to obtain biparental populations.These populations were used to map QTLs for the early-maturity traits for two years(2020 and 2021).With BSA-seq analysis based on the data of population 2020,the candidate regions related to early maturity were found to be located on chromosome D03.We then developed 22 polymorphic insertions or deletions(InDel)markers to further narrow down the candidate regions,resulting in the detection of five and four QTLs in the 2020 and 2021 populations,respectively.According to the results of QTL mapping,two candidate regions(InDel_G286-InDel_G144 and InDel_G24-InDel_G43)were detected.In these regions,three genes(GH_D03G0451,GH_D03G0649,and GH_D03G1180)have nonsynonymous mutations in their exons and one gene(GH_D03G0450)has SNP variations in the upstream sequence between CCRI50 and Guoxinmian 11.These four genes also showed dominant expression in the floral organs.The expression levels of GH_D03G0451,GH_D03G0649 and GH_D03G1180 were significantly higher in CCRI50 than in Guoxinmian 11 during the bud differentiation stages,while GH_D03G0450 showed the opposite trend.Further functional verification of GH_D03G0451 indicated that the GH_D03G0451-silenced plants showed a delay in the flowering time.The results suggest that these are the candidate genes for cotton early maturity,and they may be used for breeding early-maturity cotton varieties.展开更多
Pressure and tilt data are jointly inverted to simultaneously map the orientation and dimensions of a hydraulic fracture.The deformation induced by a fracture under internal pressure is modeled using the distributed d...Pressure and tilt data are jointly inverted to simultaneously map the orientation and dimensions of a hydraulic fracture.The deformation induced by a fracture under internal pressure is modeled using the distributed dislocation technique.The planar fracture is represented by four quarter ellipses,joined at the center and sharing semi-axes.This configuration provides a straightforward model for characterizing asymmetric fracture geometry.The inverse problem of mapping the fracture geometry is formulated using the Bayesian probabilistic method,combining the a priori information on the fracture model with updated information from pressure and tilt data.Solving the nonlinear inverse problem is achieved by pseudo-randomly sampling the posterior probability distribution through the Markov chain Monte Carlo method.The resulting posterior probability distribution is then explored to assess uncertainty,resolution,and correlation between model parameters.Numerical experiments are conducted to verify the accuracy and validity of the proposed analysis method in mapping the fracture geometry using synthetic pressure and tilt data.展开更多
Unsupervised methods based on density representation have shown their abilities in anomaly detection,but detection performance still needs to be improved.Specifically,approaches using normalizing flows can accurately ...Unsupervised methods based on density representation have shown their abilities in anomaly detection,but detection performance still needs to be improved.Specifically,approaches using normalizing flows can accurately evaluate sample distributions,mapping normal features to the normal distribution and anomalous features outside it.Consequently,this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network(NF-BMR).It utilizes pre-trained Convolutional Neural Networks(CNN)and normalizing flows to construct discriminative source and target domain feature spaces.Additionally,to better learn feature information in both domain spaces,we propose the Bidirectional Mapping Residual Network(BMR),which maps sample features to these two spaces for anomaly detection.The two detection spaces effectively complement each other’s deficiencies and provide a comprehensive feature evaluation from two perspectives,which leads to the improvement of detection performance.Comparative experimental results on the MVTec AD and DAGM datasets against the Bidirectional Pre-trained Feature Mapping Network(B-PFM)and other state-of-the-art methods demonstrate that the proposed approach achieves superior performance.On the MVTec AD dataset,NF-BMR achieves an average AUROC of 98.7%for all 15 categories.Especially,it achieves 100%optimal detection performance in five categories.On the DAGM dataset,the average AUROC across ten categories is 98.7%,which is very close to supervised methods.展开更多
This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble lear...This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.展开更多
目的基于T2^(*)mapping定量分析业余马拉松运动员足踝部关节软骨的T2^(*)值,并分析其与性别、年龄、身体质量指数(body mass index,BMI)、跑龄、跑量之间的相关性。材料与方法于2023年7月份至2023年9月份招募重庆市长跑运动爱好者48名,...目的基于T2^(*)mapping定量分析业余马拉松运动员足踝部关节软骨的T2^(*)值,并分析其与性别、年龄、身体质量指数(body mass index,BMI)、跑龄、跑量之间的相关性。材料与方法于2023年7月份至2023年9月份招募重庆市长跑运动爱好者48名,其中跑量<300 km/月的36例(中低跑量组),跑量≥300 km/月的12例(高跑量组)。所有受试者均进行单侧无症状踝关节的MRI扫描,扫描序列包括T2^(*)mapping多回波自旋回波(spin echo,SE)序列矢状位、质子密度加权成像脂肪抑制(proton density-weighted imaging fat-saturated,PDWI-FS)序列矢状位、冠状位、横轴位以及T1加权脂肪抑制成像(T1-weighted imaging fat-saturated,T1WI-FS)序列横轴位。沿关节软骨轮廓边缘勾画距骨穹窿、跟骰关节跟骨面、骰骨面及后距下关节跟骨面、距骨面软骨作为感兴趣区(region of interest,ROI),获得相应的T2^(*)值。采用线性回归分析软骨T2^(*)值与年龄、BMI、跑龄的相关性,采用独立样本t检验分析不同跑量及不同性别间的软骨T2^(*)值差异。结果(1)距骨穹窿、跟骰关节跟骨面及骰骨面、后距下关节跟骨面及距骨面软骨T2^(*)值在性别上的差异均具有统计学意义(P=0.001、P<0.001、P=0.002、P=0.008、P=0.004);(2)高跑量组的距骨穹窿、后距下关节跟骨面软骨T2^(*)值高于中低跑量组(P=0.014、0.023),不同跑量的跟骰关节跟骨面及骰骨面、后距下关节距骨面软骨T2^(*)值的差异均无统计学意义(P=0.987、0.072、0.724);(3)距骨穹窿、跟骰关节跟骨面及骰骨面、后距下关节跟骨面、距骨面软骨T2^(*)值均与BMI呈正相关(r=0.376、0.384、0.300、0.422、0.455,P=0.005、0.004、0.019、0.001、0.001)。结论在业余马拉松运动员这一跑步群体中,与中低跑量相比,高跑量更有可能导致距骨穹窿、后距下关节跟骨面软骨损伤;而与较低的BMI相比,高BMI增加了距骨穹窿、跟骰关节跟骨面、骰骨面及后距下关节跟骨面、距骨面软骨损伤的风险。展开更多
Powdery mildew negatively impacts wheat yield and quality.Emmer wheat(Triticum dicoccum),an ancestral species of common wheat,is a gene donor for wheat improvement.Cultivated emmer accession H1-707 exhibited all-stage...Powdery mildew negatively impacts wheat yield and quality.Emmer wheat(Triticum dicoccum),an ancestral species of common wheat,is a gene donor for wheat improvement.Cultivated emmer accession H1-707 exhibited all-stage resistance to powdery mildew over consecutive years.Genetic analysis of H1-707 at the seedling stage revealed a dominant monogenic inheritance pattern,and the underlying gene was designated Pm71.By employing bulked segregant exome sequencing(BSE-Seq)and using 2000 F2:3 families,Pm71 was fine mapped to a 336-kb interval on chromosome arm 6AS by referencing to the durum cv.Svevo RefSeq 1.0.Collinearity analysis revealed high homology in the candidate interval between Svevo and six Triticum species.Among six high-confidence genes annotated within this interval,TRITD6Av1G005050 encoding a GDSL esterase/lipase was identified as a key candidate for Pm71.展开更多
In response to the problem of inter-carrier interference(ICI)and inter-subband interference(IBI)in the received signals of universal filtered multi-carrier(UFMC)systems,a novel interfer-ence suppression design scheme ...In response to the problem of inter-carrier interference(ICI)and inter-subband interference(IBI)in the received signals of universal filtered multi-carrier(UFMC)systems,a novel interfer-ence suppression design scheme applying the method of complex weighted matrix inter-leaving map-ping(CWMIM)is proposed on the basis of the existing suppression scheme of conjugate weighted butterfly interleaving mapping(CWBIM).The proposed scheme performs matrix interleaving map-ping on the transmitted signal,which not only improves the carrier interference ratio(CIR)of the received signal by combining the original IBI and ICI terms,but also further inhibits the probability of burst error in the received signal.Meanwhile,the scheme can further decrease the impact of phase rotation errors in the received signal by increasing the number of rotation factors.Theoretical analysis and simulation results demonstrate that compared with CWBIM-UFMC,the proposed CWMIM-UFMC can obtain more effective ICI and IBI suppression and better system bit error rate(BER)performance with only a little bit increase in computational complexity.展开更多
Objective:To evaluate the value of rehabilitation nursing based on mind mapping model combined with psychological intervention for patients with nephrotic syndrome(NS).Methods:A total of 60 patients with NS who visite...Objective:To evaluate the value of rehabilitation nursing based on mind mapping model combined with psychological intervention for patients with nephrotic syndrome(NS).Methods:A total of 60 patients with NS who visited our hospital from January 2024 to December 2024 were selected as samples and randomly divided into groups.The observation group received rehabilitation nursing based on the mind mapping model combined with psychological intervention,while the control group received routine intervention.The differences in emotional scores,self-care ability scores,compliance,and complications were compared between the two groups.Results:The anxiety(SAS)and depression(SDS)scores of the observation group were lower than those of the control group,while the self-care ability scale(ESCA)score was higher than that of the control group(P<0.05).The compliance rate of the observation group was higher than that of the control group(P<0.05).The complication rate of NS in the observation group was lower than that in the control group(P<0.05).Conclusion:Rehabilitation nursing based on the mind mapping model combined with psychological intervention can enhance self-care ability,reduce negative emotions,and reduce complications in NS nursing,which is efficient and feasible.展开更多
基金supported by the National Natural Science Foundation of China(42171325,41771468)the National Key Research and Development Program of China(2022YFD2001101)+1 种基金the Science Bureau of Fujian Province(2023Y0042)the Finance Department and the Digital Economy Alliance of Fujian Province。
文摘Upland crop-rice cropping systems(UCR)facilitate sustainable agricultural intensification.Accurate UCR cultivation mapping is needed to ensure food security,sustainable water management,and rural revitalization.However,datasets describing cropping systems are limited in spatial coverage and crop types.Mapping UCR is more challenging than crop identification and most existing approaches rely heavily on accurate phenology calendars and representative training samples,which limits its applications over large regions.We describe a novel algorithm(RRSS)for automatic mapping of upland crop-rice cropping systems using Sentinel-1 Synthetic Aperture Radar(SAR)and Sentinel-2 Multispectral Instrument(MSI)data.One indicator,the VV backscatter range,was proposed to discriminate UCR and another two indicators were designed by coupling greenness and pigment indices to further discriminate tobacco or oilseed UCR.The RRSS algorithm was applied to South China characterized by complex smallholder rice cropping systems and diverse topographic conditions.This study developed 10-m UCR maps of a major rice bowl in South China,the Xiang-Gan-Min(XGM)region.The performance of the RRSS algorithm was validated based on 5197 ground-truth reference sites,with an overall accuracy of 91.92%.There were7348 km^(2) areas of UCR,roughly one-half of them located in plains.The UCR was represented mainly by oilseed-UCR and tobacco-UCR,which contributed respectively 69%and 15%of UCR area.UCR patterns accounted for only one-tenth of rice production,which can be tripled by intensification from single rice cropping.Application to complex and fragmented subtropical regions suggested the spatiotemporal robustness of the RRSS algorithm,which could be further applied to generate 10-m UCR datasets for application at national or global scales.
基金funded by the Natural Science Foundation of Xinjiang Uygur Autonomous Region,China(2022D01B222)the China Agriculture Research System(CARS-15-06)the Key R&D Project of Eight Division of Xinjiang Production and Construction Corps,China(2021NY01)。
文摘Cotton breeding for the development of early-maturing varieties is an effective way to improve multiple cropping indexes and alleviate the conflict between grains and cotton in the cultivated fields in China.In the present study,we aimed to identify upland cotton quantitative trait loci(QTLs)and candidate genes related to early-maturity traits,including whole growth period(WGP),flowering timing(FT),node of the first fruiting branch(NFFB),height of the node of the first fruiting branch(HNFFB),and plant height(PH).An early-maturing variety,CCRI50,and a latematuring variety,Guoxinmian 11,were crossed to obtain biparental populations.These populations were used to map QTLs for the early-maturity traits for two years(2020 and 2021).With BSA-seq analysis based on the data of population 2020,the candidate regions related to early maturity were found to be located on chromosome D03.We then developed 22 polymorphic insertions or deletions(InDel)markers to further narrow down the candidate regions,resulting in the detection of five and four QTLs in the 2020 and 2021 populations,respectively.According to the results of QTL mapping,two candidate regions(InDel_G286-InDel_G144 and InDel_G24-InDel_G43)were detected.In these regions,three genes(GH_D03G0451,GH_D03G0649,and GH_D03G1180)have nonsynonymous mutations in their exons and one gene(GH_D03G0450)has SNP variations in the upstream sequence between CCRI50 and Guoxinmian 11.These four genes also showed dominant expression in the floral organs.The expression levels of GH_D03G0451,GH_D03G0649 and GH_D03G1180 were significantly higher in CCRI50 than in Guoxinmian 11 during the bud differentiation stages,while GH_D03G0450 showed the opposite trend.Further functional verification of GH_D03G0451 indicated that the GH_D03G0451-silenced plants showed a delay in the flowering time.The results suggest that these are the candidate genes for cotton early maturity,and they may be used for breeding early-maturity cotton varieties.
基金supported by the National Natural Science Foundation of China under Grant Nos.52374033 and U23A20596.
文摘Pressure and tilt data are jointly inverted to simultaneously map the orientation and dimensions of a hydraulic fracture.The deformation induced by a fracture under internal pressure is modeled using the distributed dislocation technique.The planar fracture is represented by four quarter ellipses,joined at the center and sharing semi-axes.This configuration provides a straightforward model for characterizing asymmetric fracture geometry.The inverse problem of mapping the fracture geometry is formulated using the Bayesian probabilistic method,combining the a priori information on the fracture model with updated information from pressure and tilt data.Solving the nonlinear inverse problem is achieved by pseudo-randomly sampling the posterior probability distribution through the Markov chain Monte Carlo method.The resulting posterior probability distribution is then explored to assess uncertainty,resolution,and correlation between model parameters.Numerical experiments are conducted to verify the accuracy and validity of the proposed analysis method in mapping the fracture geometry using synthetic pressure and tilt data.
基金This work was supported in part by the National Key R&D Program of China 2021YFE0110500in part by the National Natural Science Foundation of China under Grant 62062021in part by the Guiyang Scientific Plan Project[2023]48-11.
文摘Unsupervised methods based on density representation have shown their abilities in anomaly detection,but detection performance still needs to be improved.Specifically,approaches using normalizing flows can accurately evaluate sample distributions,mapping normal features to the normal distribution and anomalous features outside it.Consequently,this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network(NF-BMR).It utilizes pre-trained Convolutional Neural Networks(CNN)and normalizing flows to construct discriminative source and target domain feature spaces.Additionally,to better learn feature information in both domain spaces,we propose the Bidirectional Mapping Residual Network(BMR),which maps sample features to these two spaces for anomaly detection.The two detection spaces effectively complement each other’s deficiencies and provide a comprehensive feature evaluation from two perspectives,which leads to the improvement of detection performance.Comparative experimental results on the MVTec AD and DAGM datasets against the Bidirectional Pre-trained Feature Mapping Network(B-PFM)and other state-of-the-art methods demonstrate that the proposed approach achieves superior performance.On the MVTec AD dataset,NF-BMR achieves an average AUROC of 98.7%for all 15 categories.Especially,it achieves 100%optimal detection performance in five categories.On the DAGM dataset,the average AUROC across ten categories is 98.7%,which is very close to supervised methods.
基金the University of Transport Technology under the project entitled“Application of Machine Learning Algorithms in Landslide Susceptibility Mapping in Mountainous Areas”with grant number DTTD2022-16.
文摘This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.
基金financially supported by National Natural Science Foundation of China(32301800,32301923 and 32072053)Wheat Industrial Technology System of Shandong Province(SDAIT-01-01)Key Research and Development Project of Shandong Province(2022LZG002-4,2023LZGC009-4-4).
文摘Powdery mildew negatively impacts wheat yield and quality.Emmer wheat(Triticum dicoccum),an ancestral species of common wheat,is a gene donor for wheat improvement.Cultivated emmer accession H1-707 exhibited all-stage resistance to powdery mildew over consecutive years.Genetic analysis of H1-707 at the seedling stage revealed a dominant monogenic inheritance pattern,and the underlying gene was designated Pm71.By employing bulked segregant exome sequencing(BSE-Seq)and using 2000 F2:3 families,Pm71 was fine mapped to a 336-kb interval on chromosome arm 6AS by referencing to the durum cv.Svevo RefSeq 1.0.Collinearity analysis revealed high homology in the candidate interval between Svevo and six Triticum species.Among six high-confidence genes annotated within this interval,TRITD6Av1G005050 encoding a GDSL esterase/lipase was identified as a key candidate for Pm71.
基金Supported by the National Natural Science Foundation of China(No.61601296,61201244)the Science and Technology Innovation Action Plan Project of Shanghai Science and Technology Commission(No.20511103500)the Talent Program of Shanghai University of Engineer-ing Science(No.2018RC43).
文摘In response to the problem of inter-carrier interference(ICI)and inter-subband interference(IBI)in the received signals of universal filtered multi-carrier(UFMC)systems,a novel interfer-ence suppression design scheme applying the method of complex weighted matrix inter-leaving map-ping(CWMIM)is proposed on the basis of the existing suppression scheme of conjugate weighted butterfly interleaving mapping(CWBIM).The proposed scheme performs matrix interleaving map-ping on the transmitted signal,which not only improves the carrier interference ratio(CIR)of the received signal by combining the original IBI and ICI terms,but also further inhibits the probability of burst error in the received signal.Meanwhile,the scheme can further decrease the impact of phase rotation errors in the received signal by increasing the number of rotation factors.Theoretical analysis and simulation results demonstrate that compared with CWBIM-UFMC,the proposed CWMIM-UFMC can obtain more effective ICI and IBI suppression and better system bit error rate(BER)performance with only a little bit increase in computational complexity.
文摘Objective:To evaluate the value of rehabilitation nursing based on mind mapping model combined with psychological intervention for patients with nephrotic syndrome(NS).Methods:A total of 60 patients with NS who visited our hospital from January 2024 to December 2024 were selected as samples and randomly divided into groups.The observation group received rehabilitation nursing based on the mind mapping model combined with psychological intervention,while the control group received routine intervention.The differences in emotional scores,self-care ability scores,compliance,and complications were compared between the two groups.Results:The anxiety(SAS)and depression(SDS)scores of the observation group were lower than those of the control group,while the self-care ability scale(ESCA)score was higher than that of the control group(P<0.05).The compliance rate of the observation group was higher than that of the control group(P<0.05).The complication rate of NS in the observation group was lower than that in the control group(P<0.05).Conclusion:Rehabilitation nursing based on the mind mapping model combined with psychological intervention can enhance self-care ability,reduce negative emotions,and reduce complications in NS nursing,which is efficient and feasible.
