Interpreting core-level spectra of oxidizing phosphorene: Theory and experiment

We combine ab initio density functional theory calculations with the equivalent cores approximation to determine core-level binding-energy shifts at phosphorus sites caused by oxidation of phosphorene. We find that presence of oxygen increases the core-level binding energies of P atoms and expect binding-energy shifts of up to 6 eV in highly defective geometries. We have identified likely binding geometries of oxygen that help to interpret the observed core-level photoemission spectra in samples at different stages of oxidation and allow us to determine the fractions of specific local geometries

Research Status and Prospects on Plant Canopy Structure Measurement Using Visual Sensors Based on Three-Dimensional Reconstruction

Three-dimensional (3D) plant canopy structure analysis is an important part of plant phenotype studies. To promote the development of plant canopy structure measurement based on 3D reconstruction, we reviewed the latest research progress achieved using visual sensors to measure the 3D plant canopy structure from four aspects, including the principles of 3D plant measurement technologies, the corresponding instruments and specifications of different visual sensors, the methods of plant canopy structure extraction based on 3D reconstruction, and the conclusion and promise of plant canopy measurement technology. In the current research phase on 3D structural plant canopy measurement techniques, the leading algorithms of every step for plant canopy structure measurement based on 3D reconstruction are introduced. Finally, future prospects for a standard phenotypical analytical method, rapid reconstruction, and precision optimization are described

Propagation Characteristics of Radio Wave in Plastic Greenhouse

International audienceIn order to realize the deployment of wireless sensor network in large areas of plastic greenhouses. The propagation characteristics of radio wave in plastic greenhouse were studied. The Received Signal Strength Index (RSSI) in greenhouse and between greenhouses were studied, and the logarithmic path loss model for RSSI was established. The results show that the radio wave attenuation parameters A and n between greenhouses were 30.785 and 2.89. The attenuation index was larger than the index of free space. In the plastic greenhouse planted with tomatoes, the radio wave attenuation parameters A and n in the ground were 34.99 and 3.64, and in the top of canopy were 35.14 and 2.85, its show that the radio wave transmission has been significantly affected by the crop in the plastic greenhouse

A More Reliable Orbit Initialization Method for LEO Precise Orbit Determination Using GNSS

Precise orbit determination (POD) using GNSS has been rapidly developed and is the mainstream technology for the navigation of low Earth orbit (LEO) satellites. The initialization of orbit parameters is a key prerequisite for LEO POD processing. For a LEO satellite equipped with a GNSS receiver, sufficient discrete kinematic positions can be obtained easily by processing space-borne GNSS data, and its orbit parameters can thus be estimated directly in iterative manner. This method of direct iterative estimation is called as the direct approach, which is generally considered highly reliable, but in practical applications it has risk of failure. Stability analyses demonstrate that the direct approach is sensitive to oversized errors in the starting velocity vector at the reference time, which may lead to large errors in design matrix because the reference orbit may be significantly distorted, and eventually cause the divergence of the orbit parameter estimation. In view of this, a more reliable method, termed the progressive approach, is presented in this paper. Instead of estimating the orbit parameters directly, it first fits the discrete kinematic positions to a reference ephemeris in the form of the GNSS broadcast ephemeris, which construct a reference orbit that is smooth and close to the true orbit. Based on the reference orbit, the starting orbit parameters are computed in sufficient accuracy, and then the final orbit parameters are estimated with a high accuracy by using discrete kinematic positions as measurements. The stability analyses show that the design matrix errors are reduced in the progressive approach, which would assure more robust orbit parameter estimation than the direct estimation approach. Various orbit initialization experiments are performed on the KOMPSAT-5 and FY3C satellites. The results have fully verified the high reliability of the proposed progressive approach

Effects of Light Intensity and Temperature on the Photosynthesis Characteristics and Yield of Lettuce

Lettuce is an important vegetable in horticulture, but information about the interactive effects of light and temperature on its photosynthetic characteristics was inadequate. This work investigated the effects of three temperatures (15/10 (T15), 23/18 (T23), and 30/23 °C (T30)) and five light treatments (100 (P100), 200 (P200), 350 (P350), 500 (P500), and 600 μmol·m−2·s−1 (P600)) on the light–response curves, chlorophyll content, and yield of lettuce. The results showed that the maximum photosynthetic rate, light saturation point, chlorophyll content, and yield of lettuce were all the highest at T23 compared with T15 and T30 under different light intensities. Under the same temperature conditions, the photosynthesis capacity and yield of lettuce in the P350 and P500 treatments at T15, P350, P500, and P600 treatments at T23 and P500, and P600 treatments at T30 were larger than other light treatments. The results suggested that temperature play had a more pronounced influence on photosynthesis and yield in lettuce, but the appropriate levels of light intensity improved its potential photosynthetic capacity and yield under different temperature conditions

A Novel Method for Precise Onboard Real-Time Orbit Determination with a Standalone GPS Receiver

Satellite remote sensing systems require accurate, autonomous and real-time orbit determinations (RTOD) for geo-referencing. Onboard Global Positioning System (GPS) has widely been used to undertake such tasks. In this paper, a novel RTOD method achieving decimeter precision using GPS carrier phases, required by China’s HY2A and ZY3 missions, is presented. A key to the algorithm success is the introduction of a new parameter, termed pseudo-ambiguity. This parameter combines the phase ambiguity, the orbit, and clock offset errors of the GPS broadcast ephemeris together to absorb a large part of the combined error. Based on the analysis of the characteristics of the orbit and clock offset errors, the pseudo-ambiguity can be modeled as a random walk, and estimated in an extended Kalman filter. Experiments of processing real data from HY2A and ZY3, simulating onboard operational scenarios of these two missions, are performed using the developed software SATODS. Results have demonstrated that the position and velocity accuracy (3D RMS) of 0.2–0.4 m and 0.2–0.4 mm/s, respectively, are achieved using dual-frequency carrier phases for HY2A, and slightly worse results for ZY3. These results show it is feasible to obtain orbit accuracy at decimeter level of 3–5 dm for position and 0.3–0.5 mm/s for velocity with this RTOD method

A Machine Learning-Based Approach for Improved Orbit Predictions of LEO Space Debris With Sparse Tracking Data From a Single Station

Accurate orbit prediction (OP) of space debris is vital in space situation awareness (SSA) related tasks, such as space collision warnings. However, owing to the sparse and low precision observations, unknown geometrical and physical features of debris, and effects of incomplete force models, OP based on the orbital mechanics theory or physics-based OP of space debris suffers from rapid error growth over a long duration, limiting the period of validity of debris OP for precise space applications. Considering that the tracking arcs of a debris object over a single station often share a similar temporal and spatial distribution in the inertial space, the resultant OP errors possibly have a coherent relationship with the temporal and spatial distribution of tracking arcs. This article proposes a machine learning (ML)-based approach to model the underlying pattern of debris OP errors from historical observations and apply it to modify the future physics-based OP results. The approach includes three steps: constructing a historical OP error set, training an ML model to fit the historical OP error set, and correcting the future physics-based OP with ML-predicted orbital errors. The ensemble learning algorithm of boosting tree is studied as the primary ML method for the error modeling and predicting process. Experiments with three low-Earth-orbit objects, tracked by a single radar station, demonstrate that the trained ML models can capture more than 80% of the underlying pattern of the historical OP errors. More importantly, the errors of physics-based OP over the future seven days reduce from thousands of meters to hundreds or even tens of meters through the error correction with the learned error pattern, achieving at least 50% accuracy improvement. Such dramatic OP improvements show the promising potential of ML for enhanced SSA capability

Manage system for internet of things of greenhouse based on GWT

In order to fit the different demands for the internet of things system of greenhouse environment monitoring and control, the greenhouse environment monitoring and control management system based on Google Web Toolkit (GWT) was developed. Using remote method call (RPC) AJAX as the communication method between browser and web server, the system realized the functions such as: configuration of acquisition and control parameters, the adaptive match of database between gateway and server, the adaptive diagnosis of monitoring parameters, the warning of monitoring parameters, the adaptive generation of interface, and so on. The functions of the system was tested the results shows that the WEB browser application and Android App can adaptively realize the greenhouse environment monitoring and control according to the information configuration. Keywords: Greenhouse, Internet of things, Monitoring and control system, Softwar