Construction and Accuracy Analysis of a BDS/GPS-Integrated Positioning Algorithm for Forests

The objective of this study was to construct a BeiDou navigation satellite system (BDS)/ global positioning system (GPS)-integrated positioning algorithm that meets the accuracy requirement of forest surveys and to analyze its accuracy to provide theoretical and technical support for accurate positioning and navigation in forests. The Quercus variabilis broad-leaved forest in Jiufeng National Forest Park and the Sabina Coniferous forest in Dongsheng Bajia forest farm were selected as the study area. A Sanding T-23 multi-frequency three-constellation receiver and a u-blox NEO-M8T multi-constellation receiving module were used for continuous observation under the forest canopy. Compared with T-23, the u-blox NEO-M8T is much lighter and more flexible in the forest. The BDS/GPS-integrated positioning algorithm for forests was constructed by temporally and spatially unifying the satellite systems and using a reasonable observed value weighting method. Additionally, the algorithm is also written into the RTKLIB software to calculate the three-dimensional (3D) coordinates of the forest observation point in the World Geodetic System 1984 (WGS-84) coordinate system. Finally, the results were compared with the positioning results obtained using GPS alone. The experimental results indicated that, compared with GPS positioning, there were 13–27 visible satellites available for the BDS/GPS-integrated positioning algorithm for forests, far more than the satellites available for the GPS positioning algorithm alone. The Position Dilution of Precision (PDOP) values for the BDS/GPS-integrated positioning ranged from 0.5 to 1.9, lower than those for GPS positioning. The signal noise ratio (SNR) of the BDS/GPS-integrated satellite signals and GPS satellite signals were both in the range of 10–50 dB-Hz. However, because there were more visible satellites for the BDS/GPS-integrated positioning, the signals from the BDS/GPS-integrated satellites were stronger and had a more stable SNR than those from the GPS satellites alone. The results obtained using the BDS/GPS-integrated positioning algorithm for forests had significantly higher theoretical and actual accuracies in the X, Y and Z directions than those obtained using the GPS positioning algorithm. This suggests that the BDS/GPS-integrated positioning algorithm can obtain more accurate positioning results for complex forest environments

Effect of Nitric Oxide Treatment on Storage Quality of Glorious Oranges

AbstractEffect of nitric oxide (NO) treatment on storage quality and disease resistance of Glorious oranges was investigated in the experiment. The results showed that NO treatment could effectively reduce disease incidence inoculated with Collletotichum goeosporioides Penz and inhibit the increase of lesion diameter of Glorious oranges during storage. Compared with the control, NO treatment kept higher level of titritable acidity (TA), soluble protein, ascorbic acid (ASA) and reducing sugar, and lower level of weight lose rate and soluble solid concentration (SSC), retarding ripening of fruits

Monolithic quantum-dot distributed feedback laser array on silicon

Electrically-pumped lasers directly grown on silicon are key devices interfacing silicon microelectronics and photonics. We report here, for the first time, an electrically-pumped, room-temperature, continuous-wave (CW) and single-mode distributed feedback (DFB) laser array fabricated in InAs/GaAs quantum-dot (QD) gain material epitaxially grown on silicon. CW threshold currents as low as 12 mA and single-mode side mode suppression ratios (SMSRs) as high as 50 dB have been achieved from individual devices in the array. The laser array, compatible with state-of-the-art coarse wavelength division multiplexing (CWDM) systems, has a well-aligned channel spacing of 20 0.2 nm and exhibits a record wavelength coverage range of 100 nm, the full span of the O-band. These results indicate that, for the first time, the performance of lasers epitaxially grown on silicon is elevated to a point approaching real-world CWDM applications, demonstrating the great potential of this technology

A Drive to Driven Model of Mapping Intraspecific Interaction Networks.

Community ecology theory suggests that an individual\u27s phenotype is determined by the phenotypes of its coexisting members to the extent at which this process can shape community evolution. Here, we develop a mapping theory to identify interaction quantitative trait loci (QTL) governing inter-individual dependence. We mathematically formulate the decision-making strategy of interacting individuals. We integrate these mathematical descriptors into a statistical procedure, enabling the joint characterization of how QTL drive the strengths of ecological interactions and how the genetic architecture of QTL is driven by ecological networks. In three fish full-sib mapping experiments, we identify a set of genome-wide QTL that control a range of societal behaviors, including mutualism, altruism, aggression, and antagonism, and find that these intraspecific interactions increase the genetic variation of body mass by about 50%. We showcase how the interaction QTL can be used as editors to reconstruct and engineer new social networks for ecological communities

Computational Identification of Gene Networks as a Biomarker of Neuroblastoma Risk

Neuroblastoma is a common cancer in children, affected by a number of genes that interact with each other through intricate but coordinated networks. Traditional approaches can only reconstruct a single regulatory network that is topologically not informative enough to explain the complexity of neuroblastoma risk. We implemented and modified an advanced model for recovering informative, omnidirectional, dynamic, and personalized networks (idopNetworks) from static gene expression data for neuroblastoma risk. We analyzed 3439 immune genes of neuroblastoma for 217 high-risk patients and 30 low-risk patients by which to reconstruct large patient-specific idopNetworks. By converting these networks into risk-specific representations, we found that the shift in patients from a low to high risk or from a high to low risk might be due to the reciprocal change of hub regulators. By altering the directions of regulation exerted by these hubs, it may be possible to reduce a high risk to a low risk. Results from a holistic, systems-oriented paradigm through idopNetworks can potentially enable oncologists to experimentally identify the biomarkers of neuroblastoma and other cancers