ALBERT

Description: The file includes both field measured and satellite derived high resolution LAI data obtained over the Honghe farm and Hailun site in northeastern China. The Honghe farm (centered at 47°39′N, 133°31′E) is located in the east of the Heilongjiang province, northeast China. Five plots in 400 m × 600 m were selected in the Honghe farm in 2012 and 2013. Within each plot, about 50 - 60 elementary sampling units (ESUs) about 20 m ×20 m in size were selected in different weeks with a moving sampling strategy to avoid the sampling disturbance. Field LAI measurements were performed weekly from June 11 to September 17, 2012, and from June 22 to August 27, 2013. All ESU measurements made with LAI-2200 within a plot were averaged to represent the plot LAI. The Hailun site (47°24′- 47°26′N, 126°47′- 126°51′E) is located in the western part of the Heilongjiang province. The main crop types are maize, soybean, and sorghum. Five crop plots in 100 m × 500 m were chosen for continuous LAI measurements. The plots cover an areas of about 30 km2 and an elevation of approximately 200-240 m above sea level with quite homogeneous surroundings. Three representative ESUs of approximately 20 m × 20 m were selected in each plot. Field LAI measurements were continuously carried out with LAI-2200 weekly at each plot from June 20 to September 22, 2016. The high-resolution LAI data were estimated with a look-up table (LUT) method from the HJ-1, Landsat 7 ETM+, and Sentinel-2A MSI reflectance data. The high resolution LAI data are consistent with the field measured LAI characterized by a slope close to the 1:1 line. The statistical results show R2 of 0.81 and 0.86, and RMSE of 0.62 and 0.70 for paddy rice and broadleaf crops, respectively. The scale factor is 0.01.

Description: The dataset includes global specific vegetation cover (SVC), base clumping index (BCI), full clumping index (FCI), and leaf projection function (G) derived from clumping index (CI), leaf area index (LAI), and fractional vegetation cover (FVC) remote sensing products. The SVC, defined as the ratio of FVC to LAI, was proposed to characterize the ability of vegetation to cover the ground and has great potential for vegetation characterization and phenology studies. In this dataset, the global monthly SVC was generated with FVC and LAI products from 2003–2017. Theoretically, SVC varies from 0 to 1. SVC 〉1.0 reveals inconsistent retrievals for FVC and LAI. Therefore, we also map the spatial distribution and frequency of SVC outying pixels based on above monthly SVC product. The BCI refers to the hypothetical minimum CI during leaf emergence when both the FVC and LAI are close to zero. The FCI represents the CI when the ground is completely covered by vegetation (FVC=1.0) or the pixel LAI reaches its maximum (assumed to be 7.0). The BCI and FCI values indicate the seasonal CI variations and would greatly facilitate canopy modeling and parameter retrieval studies. The global BCI and FCI with a spatial resolution of 0.05° were both estimated using the exponential relationships between CI and FVC or between CI and LAI, respectively. The nadir leaf projection function (G(0)) is defined as the average projection of the unit leaf area in the nadir direction. The global monthly G(0) maps at 0.05° spatial resolution were generated for the first time from the global CI, FVC, and LAI products based on the Beer-Lambert equation under the assumption that the whole CI can be approximated as nadir CI. It can be used as a benchmark for biophysical parameter retrieval and land surface modeling studies. The remote sensing products used for generating this dataset include the CAS-CI V1.1 (Wei et al., 2019), the GEOV2 FVC (Verger, A., 2019; https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS1_ATBD_LAI1km-V2_I1.41.pdf), and the MODIS LAI C6 (Myneni et al., 2015). In order to facilitate further analysis by users, the global monthly average CI, FVC, and LAI data at 0.05° are also provided in this dataset. Moreover, we share the statistical results about the variations of CI, FVC, LAI, and SVC with seasonal, latitude, and altitude. For more details about this dataset, please refer to (Fang et al. (2021) do:10.1016/j.srs.2021.100027).

Description: Langmuir DOI: 10.1021/la200156m

Description: Background: The invasion of red blood cells (RBCs) by malarial parasites is an essential step in the life cycle of Plasmodium falciparum. Human-parasite surface protein interactions play a critical role in this process. Although several interactions between human and parasite proteins have been discovered, the mechanism related to invasion remains poorly understood because numerous human-parasite protein interactions have not yet been identified. High-throughput screening experiments are not feasible for malarial parasites due to difficulty in expressing the parasite proteins. Here, we performed computational prediction of the PPIs involved in malaria parasite invasion to elucidate the mechanism by which invasion occurs. Results: In this study, an expectation maximization algorithm was used to estimate the probabilities of domain-domain interactions (DDIs). Estimates of DDI probabilities were then used to infer PPI probabilities. We found that our prediction performance was better than that based on the information of D. melanogaster alone when information related to the six species was used. Prediction performance was assessed using protein interaction data from S. cerevisiae, indicating that the predicted results were reliable. We then used the estimates of DDI probabilities to infer interactions between 490 parasite and 3,787 human membrane proteins. A small-scale dataset was used to illustrate the usability of our method in predicting interactions between human and parasite proteins. The positive predictive value (PPV) was lower than that observed in S. cerevisiae. We integrated gene expression data to improve prediction accuracy and to reduce false positives. We identified 80 membrane proteins highly expressed in the schizont stage by fast Fourier transform method. Approximately 221 erythrocyte membrane proteins were identified using published mass spectral datasets. A network consisting of 205 interactions was predicted. Results of network analysis suggest that SNARE proteins of parasites and APP of humans may function in the invasion of RBCs by parasites. Conclusions: We predicted a small-scale PPI network that may be involved in parasite invasion of RBCs by integrating DDI information and expression profiles. Experimental studies should be conducted to validate the predicted interactions. The predicted PPIs help elucidate the mechanism of parasite invasion and provide directions for future experimental investigations.

Description: The comprehensive land carrying capacities of seven cities in the Shandong Peninsula Blue Economic Zone between 2007–2014 were assessed using a multi-criterion comprehensive evaluation approach and an index of 27 indicators, and cluster analysis was conducted to identify the spatial-temporal variations of the cities’ comprehensive land carrying capacities. The results showed that the carrying capacity of the water and soil resources of the cities had declined except Dongying City; in contrast, the carrying capacities of the eco-environment, the social resources and the economy and technology of the seven cities had all arisen. The carrying capacities of social resources of Dongying and Weihai were markedly higher than the other five cities. The carrying capacities of economy and technology of Qingdao and Dongying were high, the capacities of Weihai and Yantai were moderate, and the capacities of Weifang, Rizhao, and Binzhou were low. In general, the comprehensive land carrying capacities of the eastern cities were higher than those of the western cities, which was similar to the spatial pattern of the economy development of those cities. In addition, positive correlations were identified between the comprehensive land carrying capacity and the per capita land for construction, areal proportion of wetland to total land, percentage of green space to build up area, per capita public green space, comprehensive utilization rate of industrial solid waste residues, urbanization rate, area of per capita urban road, per capita GDP, economy density, fixed-assets investment per area, etc. However negative correlations were discovered between the comprehensive land carrying capacity and the discharge of industrial waste water per 10,000 Yuan RMB GDP, as well as the proportion of added value of the primary industry to total GDP. Finally, we discussed measures to improve the comprehensive land carrying capacities of the cities, such as elevating the intensive land utilization and economic development, decreasing the proportion of added value of the primary industry to total GDP, promoting energy saving and emission reduction, etc.

Description: The Community Radiative Transfer Model (CRTM) presently uses one lookup table (LUT) of cloud and precipitation single-scattering properties at microwave frequencies, with which any particle size distribution may interface via effective radius. This may produce scattering properties insufficiently representative of the model output if the microphysics parameterization scheme particle size distribution mismatches that assumed in constructing the LUT, such as one being exponential and the other monodisperse, or assuming different particle bulk densities. The CRTM also assigns a 5-μm effective radius to all non-precipitating clouds, an additional inconsistency. Brightness temperatures are calculated from 3-hour convection-permitting simulations of Hurricane Karl (2010) by the Weather Research and Forecasting model; each simulation uses one of three different microphysics schemes. For each microphysics scheme, a consistent cloud scattering LUT is constructed; the use of these LUTs produces differences in brightness temperature fields that would be better for analyzing and constraining microphysics schemes than using the CRTM LUT as-released. Other LUTs are constructed which contain one of the known microphysics-inconsistencies with the CRTM LUT as-released, such as the bulk density of graupel, but are otherwise microphysics-consistent; differences in brightness temperature to using an entirely microphysics-consistent LUT further indicate the significance of that inconsistency. The CRTM LUT as-released produces higher brightness temperature than using microphysics-consistent LUTs. None of the LUTs can produce brightness temperatures that can match well to observations at all frequencies, which is likely due in part to the use of spherical particle scattering.