Spatio-Temporal Patterns and Climate Variables Controlling of Biomass Carbon Stock of Global Grassland Ecosystems from 1982 to 2006

Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management

A Biodegradable Polyethylenimine-Based Vector Modified by Trifunctional Peptide R18 for Enhancing Gene Transfection Efficiency In Vivo

Lack of capacity to cross the nucleus membrane seems to be one of the main reasons for the lower transfection efficiency of gene vectors observed in vivo study than in vitro. To solve this problem, a new non-viral gene vector was designed. First, a degradable polyethylenimine (PEI) derivate was synthesized by crosslinking low-molecular-weight (LMW) PEI with N-octyl-N-quaternary chitosan (OTMCS), and then adopting a designed trifunctional peptide (RGDC- TAT-NLS) with good tumor targeting, cell uptake and nucleus transport capabilities to modify OTMCS-PEI. The new gene vector was termed as OTMCS- PEI-R18 and characterized in terms of its chemical structure and biophysical parameters. Gene transfection efficiency and nucleus transport mechanism of this vector were also evaluated. The polymer showed controlled degradation and remarkable buffer capabilities with the particle size around 100–300 nm and the zeta potential ranged from 5 mV to 40 mV. Agraose gel electrophoresis showed that OTMCS-PEI-R18 could effectively condensed plasmid DNA at a ratio of 1.0. Besides, the polymer was stable in the presence of sodium heparin and could resist digestion by DNase I at a concentration of 63U DNase I/DNA. OTMCS-PEI-R18 also showed much lower cytotoxicity and better transfection rates compared to polymers OTMCS-PEI-R13, OTMCS-PEI and PEI 25 KDa in vitro and in vivo. Furthermore, OTMCS-PEI-R18/DNA complexes could accumulate in the nucleus well soon and not rely on mitosis absolutely due to the newly incorporated ligand peptide NLS with the specific nuclear delivery pathway indicating that the gene delivery system OTMCS-PEI-R18 could reinforce gene transfection efficiency in vivo

New Signal and Algorithms for 5G/6G High Precision Train Positioning in Tunnel with Leaky Coaxial Cable

High precision train positioning is a crucial component of intelligent transportation systems. Tunnels are commonly encountered in subways and mountainous regions. As part of the communication system infrastructure, Leaky CoaXial (LCX) Cable is widely equipped as antenna in tunnels with many advantages. LCX positioning holds great promise as a technology for rail applications in the upcoming B5G (beyond-5G) and 6G eras. This paper focuses on the LCX positioning methodology and proposes two novel algorithms along with a novel communication-positioning integration signal. Firstly, a novel algorithm called Multiple Slot Distinction (MSD) LCX positioning algorithm is proposed. The algorithm utilizes a generated pseudo spectrum to fully utilize the coupled signals radiated from different slots of LCX. This approach offers higher time resolution compared to traditional methods. To further improve the positioning accuracy to centimeter-level and increase the measuring frequency for fast trains, a novel communication-positioning integration signal is designed. It consists of traditional Positioning Reference Signal (PRS) and a significantly low power Fine Ranging Signal (FRS). FRS is configured to be continuous and superposed onto the cellular signal using Non-Orthogonal Multiple Access (NOMA) principle to minimize its interference to communication. A two-stage LCX positioning method is then executed: At the first stage, the closest slot between the receiver and LCX is estimated by the proposed MSD algorithm using PRS; At the second stage, centimeter-level positioning is achieved by tracking the carrier phase of the continuous FRS. This process is assisted by the closest slot estimation, which helps mitigate interference between neighboring slots and eliminate the integer ambiguities. Simulation results show our proposed LCX position methodology outperforms the existing ones and offer great potentials for future implementations