buildings located at rock sites. Modelling wave propagation through soil medium helps to derive the primary and secondary wave velocities. Most of the time soil mediums are heterogeneous, layered and undergoes nonline...buildings located at rock sites. Modelling wave propagation through soil medium helps to derive the primary and secondary wave velocities. Most of the time soil mediums are heterogeneous, layered and undergoes nonlinear strains even under weak excitation. The equivalent linear approximation with one dimensional wave propagation is widely adopted for modeling earthquake excitation for layered soil. In this paper, importance of local soil effects, the process of wave propagation through three dimensional elastic medium, layered medium situated on rigid rock, attenuation of stress waves due to material damping, equivalent linear approximation, the concept of one dimensional wave propagation, and a case study of one dimensional wave propagation as a part of site-specific ground response analyses for Delhi region are included. The case study brings out the importance of carrying out site-specific ground response analyses of buildings considering the scenario earthquakes and actual soil conditions for Delhi region.展开更多
A methodology integrating correlation,regression(MLR),machine learning(ML),and pattern analysis of long-term weekly net ecosystem exchange(NEE)datasets are applied to four deciduous broadleaf forest(DBF)sites forming ...A methodology integrating correlation,regression(MLR),machine learning(ML),and pattern analysis of long-term weekly net ecosystem exchange(NEE)datasets are applied to four deciduous broadleaf forest(DBF)sites forming part of the AmeriFlux(FLUXNET2015)database.Such analysis effectively characterizes and distinguishes those DBF sites for which long-term NEE patterns can be accurately predicted using the recorded environmental variables,from those sites cannot be so delineated.Comparisons of twelve NEE prediction models(5 MLR;7 ML),using multi-fold cross-validation analysis,reveal that support vector regression generates the most accurate and reliable predictions for each site considered,based on fits involving between 16 and 24 available environmental variables.SVR can accurately predict NEE for datasets for DBF sites US-MMS and US-MOz,but fail to reliably do so for sites CA-Cbo and MX-Tes.For the latter two sites the predicted versus recorded NEE weekly data follow a Y≠X pattern and are characterized by rapid fluctuations between low and high NEE values across leaf-on seasonal periods.Variable influences on NEE,determined by their importance to MLR and ML model solutions,identify distinctive sets of the most and least influential variables for each site studied.Such information is valuable for monitoring and modelling the likely impacts of changing climate on the ability of these sites to serve as long-term carbon sinks.The periodically oscillating NEE weekly patterns distinguished for sites CA-Cbo and MX-Tes are not readily explained in terms of the currently recorded environmental variables.More detailed analysis of the biological processes at work in the forest understory and soil at these sites are recommended to determine additional suitable variables to measure that might better explain such fluctuations.展开更多
Dividing fields into a few relatively homogeneous management zones(MZs) is a practical and costeffective approach to precision agriculture. There are three basic approaches to MZ delineation using soil and/or landscap...Dividing fields into a few relatively homogeneous management zones(MZs) is a practical and costeffective approach to precision agriculture. There are three basic approaches to MZ delineation using soil and/or landscape properties, yield information, and both sources of information. The objective of this study is to propose an integrated approach to delineating site-specific MZ using relative elevation, organic matter, slope, electrical conductivity, yield spatial trend map, and yield temporal stability map(ROSE-YSTTS) and evaluate it against two other approaches using only soil and landscape information(ROSE) or clustering multiple year yield maps(CMYYM). The study was carried out on two no-till corn-soybean rotation fields in eastern Illinois, USA. Two years of nitrogen(N) rate experiments were conducted in Field B to evaluate the delineated MZs for site-specific N management. It was found that in general the ROSE approach was least effective in accounting for crop yield variability(8.0%–9.8%), while the CMYYM approach was least effective in accounting for soil and landscape(8.9%–38.1%), and soil nutrient and pH variability(9.4%–14.5%). The integrated ROSE-YSTTS approach was reasonably effective in accounting for the three sources of variability(38.6%–48.9%, 16.1%–17.3% and 13.2%–18.7% for soil and landscape, nutrient and pH, and yield variability, respectively), being either the best or second best approach. It was also found that the ROSE-YSTTS approach was effective in defining zones with high,medium and low economically optimum N rates. It is concluded that the integrated ROSE-YSTTS approach combining soil, landscape and yield spatial-temporal variability information can overcome the weaknesses of approaches using only soil, landscape or yield information,and is more robust for MZ delineation. It also has the potential for site-specific N management for improved economic returns. More studies are needed to further evaluate their appropriateness for precision N and crop management.展开更多
Increasing cases of human infections with the high pathogenic avian influenza virus H5N1 have raised great concern on potential human flu pandemics caused by H5N1. The two viral surface glycoproteins, the hemagglutini...Increasing cases of human infections with the high pathogenic avian influenza virus H5N1 have raised great concern on potential human flu pandemics caused by H5N1. The two viral surface glycoproteins, the hemagglutinin (HA) and the neuraminidase (NA) proteins, are major antigens o H5N1. Introducing new mutations on these two pro teins is the major strategy used by H5N1 to expand host range and to avoid the recognition of host im mune systems. We analyzed the two surface proteins of H5N1 from Asian human patients and identified many new mutation sites, including a few that were unique to certain lethal strains. We also analyzed the distribution of mutations on different epitopes of the two surface proteins. A receptor-binding site tha might involve in the determination of host specificity of H5N1 was also found. Results reported here pro vided information for better understanding of the evolution trend of H5N1 genome in human.展开更多
文摘buildings located at rock sites. Modelling wave propagation through soil medium helps to derive the primary and secondary wave velocities. Most of the time soil mediums are heterogeneous, layered and undergoes nonlinear strains even under weak excitation. The equivalent linear approximation with one dimensional wave propagation is widely adopted for modeling earthquake excitation for layered soil. In this paper, importance of local soil effects, the process of wave propagation through three dimensional elastic medium, layered medium situated on rigid rock, attenuation of stress waves due to material damping, equivalent linear approximation, the concept of one dimensional wave propagation, and a case study of one dimensional wave propagation as a part of site-specific ground response analyses for Delhi region are included. The case study brings out the importance of carrying out site-specific ground response analyses of buildings considering the scenario earthquakes and actual soil conditions for Delhi region.
文摘A methodology integrating correlation,regression(MLR),machine learning(ML),and pattern analysis of long-term weekly net ecosystem exchange(NEE)datasets are applied to four deciduous broadleaf forest(DBF)sites forming part of the AmeriFlux(FLUXNET2015)database.Such analysis effectively characterizes and distinguishes those DBF sites for which long-term NEE patterns can be accurately predicted using the recorded environmental variables,from those sites cannot be so delineated.Comparisons of twelve NEE prediction models(5 MLR;7 ML),using multi-fold cross-validation analysis,reveal that support vector regression generates the most accurate and reliable predictions for each site considered,based on fits involving between 16 and 24 available environmental variables.SVR can accurately predict NEE for datasets for DBF sites US-MMS and US-MOz,but fail to reliably do so for sites CA-Cbo and MX-Tes.For the latter two sites the predicted versus recorded NEE weekly data follow a Y≠X pattern and are characterized by rapid fluctuations between low and high NEE values across leaf-on seasonal periods.Variable influences on NEE,determined by their importance to MLR and ML model solutions,identify distinctive sets of the most and least influential variables for each site studied.Such information is valuable for monitoring and modelling the likely impacts of changing climate on the ability of these sites to serve as long-term carbon sinks.The periodically oscillating NEE weekly patterns distinguished for sites CA-Cbo and MX-Tes are not readily explained in terms of the currently recorded environmental variables.More detailed analysis of the biological processes at work in the forest understory and soil at these sites are recommended to determine additional suitable variables to measure that might better explain such fluctuations.
基金funded by Cargill Crop Nutrition (now Mosaic Company), Cargill Dry Corn Ingredients and Pioneer Hi-Bred International, Inc
文摘Dividing fields into a few relatively homogeneous management zones(MZs) is a practical and costeffective approach to precision agriculture. There are three basic approaches to MZ delineation using soil and/or landscape properties, yield information, and both sources of information. The objective of this study is to propose an integrated approach to delineating site-specific MZ using relative elevation, organic matter, slope, electrical conductivity, yield spatial trend map, and yield temporal stability map(ROSE-YSTTS) and evaluate it against two other approaches using only soil and landscape information(ROSE) or clustering multiple year yield maps(CMYYM). The study was carried out on two no-till corn-soybean rotation fields in eastern Illinois, USA. Two years of nitrogen(N) rate experiments were conducted in Field B to evaluate the delineated MZs for site-specific N management. It was found that in general the ROSE approach was least effective in accounting for crop yield variability(8.0%–9.8%), while the CMYYM approach was least effective in accounting for soil and landscape(8.9%–38.1%), and soil nutrient and pH variability(9.4%–14.5%). The integrated ROSE-YSTTS approach was reasonably effective in accounting for the three sources of variability(38.6%–48.9%, 16.1%–17.3% and 13.2%–18.7% for soil and landscape, nutrient and pH, and yield variability, respectively), being either the best or second best approach. It was also found that the ROSE-YSTTS approach was effective in defining zones with high,medium and low economically optimum N rates. It is concluded that the integrated ROSE-YSTTS approach combining soil, landscape and yield spatial-temporal variability information can overcome the weaknesses of approaches using only soil, landscape or yield information,and is more robust for MZ delineation. It also has the potential for site-specific N management for improved economic returns. More studies are needed to further evaluate their appropriateness for precision N and crop management.
文摘Increasing cases of human infections with the high pathogenic avian influenza virus H5N1 have raised great concern on potential human flu pandemics caused by H5N1. The two viral surface glycoproteins, the hemagglutinin (HA) and the neuraminidase (NA) proteins, are major antigens o H5N1. Introducing new mutations on these two pro teins is the major strategy used by H5N1 to expand host range and to avoid the recognition of host im mune systems. We analyzed the two surface proteins of H5N1 from Asian human patients and identified many new mutation sites, including a few that were unique to certain lethal strains. We also analyzed the distribution of mutations on different epitopes of the two surface proteins. A receptor-binding site tha might involve in the determination of host specificity of H5N1 was also found. Results reported here pro vided information for better understanding of the evolution trend of H5N1 genome in human.
