Cooperative Spectrum Sensing Algorithm to Overcome Noise Fluctuations Based on Energy Detection in Sensing Systems

In sensing systems, nodes must be able to rapidly detect whether a signal from a primary transmitter is present in a certain spectrum. However, traditional energy-detection algorithms are poorly adapted to treating noisy signals. In this paper, we investigate how rapid energy detection and detection sensitivity are related to detection duration and average power fluctuation in noise. The results indicate that detection performance and detection sensitivity decrease quickly with increasing average power fluctuation in noise and are worse in situations with low signal-to-noise ratio. First, we present a dynamic threshold algorithm based on energy detection to suppress the influence of noise fluctuation and improve the sensing sensitivity. Then, we present a new energy-detection algorithm based on cooperation between nodes. Simulations show that the proposed scheme improves the resistance to average power fluctuation in noise for short detection timescales and provides sensitive detection that improves with increasing numbers of cooperative detectors. In other words, the proposed scheme enhances the ability to overcome noise and improves spectrum sensing performance

Interactive effects of increased temperature, elevated pCO2 and different nitrogen sources on the coccolithophore Gephyrocapsaoceanica.

As a widespread phytoplankton species, the coccolithophore Gephyrocapsaoceanica has a significant impact on the global biogeochemical cycle through calcium carbonate precipitation and photosynthesis. As global change continues, marine phytoplankton will experience alterations in multiple parameters, including temperature, pH, CO2, and nitrogen sources, and the interactive effects of these variables should be examined to understand how marine organisms will respond to global change. Here, we show that the specific growth rate of G. oceanica is reduced by elevated CO2 (1000 μatm) in [Formula: see text]-grown cells, while it is increased by high CO2 in [Formula: see text]-grown ones. This difference was related to intracellular metabolic regulation, with decreased cellular particulate organic carbon and particulate organic nitrogen (PON) content in the [Formula: see text] and high CO2 condition compared to the low CO2 condition. In contrast, no significant difference was found between the high and low CO2 levels in [Formula: see text] cultures (p > 0.05). The temperature increase from 20°C to 25°C increased the PON production rate, and the enhancement was more prominent in [Formula: see text] cultures. Enhanced or inhibited particulate inorganic carbon production rate in cells supplied with [Formula: see text] relative to [Formula: see text] was observed, depending on the temperature and CO2 condition. These results suggest that a greater disruption of the organic carbon pump can be expected in response to the combined effects of increased [Formula: see text]/[Formula: see text] ratio, temperature, and CO2 level in the oceans of the future. Additional experiments conducted under nutrient limitation conditions are needed before we can extrapolate our findings to the global oceans

Influence of Oil Viscosity on Alkaline Flooding for Enhanced Heavy Oil Recovery

Oil viscosity was studied as an important factor for alkaline flooding based on the mechanism of “water drops” flow. Alkaline flooding for two oil samples with different viscosities but similar acid numbers was compared. Besides, series flooding tests for the same oil sample were conducted at different temperatures and permeabilities. The results of flooding tests indicated that a high tertiary oil recovery could be achieved only in the low-permeability (approximately 500 mD) sandpacks for the low-viscosity heavy oil (Zhuangxi, 390 mPa·s); however, the high-viscosity heavy oil (Chenzhuang, 3450 mPa·s) performed well in both the low- and medium-permeability (approximately 1000 mD) sandpacks. In addition, the results of flooding tests for the same oil at different temperatures also indicated that the oil viscosity put a similar effect on alkaline flooding. Therefore, oil with a high-viscosity is favorable for alkaline flooding. The microscopic flooding test indicated that the water drops produced during alkaline flooding for oils with different viscosities differed significantly in their sizes, which might influence the flow behaviors and therefore the sweep efficiencies of alkaline fluids. This study provides an evidence for the feasibility of the development of high-viscosity heavy oil using alkaline flooding

Channel Estimation Performance Analysis of FBMC/OQAM Systems with Bayesian Approach for 5G-Enabled IoT Applications

A filter bank multicarrier (FBMC) with offset quadrature amplitude modulation (OQAM) (FBMC/OQAM) is considered to be one of the physical layer technologies in future communication systems, and it is also a wireless transmission technology that supports the applications of Internet of Things (IoT). However, efficient channel parameter estimation is one of the difficulties in realization of highly available FBMC systems. In this paper, the Bayesian compressive sensing (BCS) channel estimation approach for FBMC/OQAM systems is investigated and the performance in a multiple-input multiple-output (MIMO) scenario is also analyzed. An iterative fast Bayesian matching pursuit algorithm is proposed for high channel estimation. Bayesian channel estimation is first presented by exploring the prior statistical information of a sparse channel model. It is indicated that the BCS channel estimation scheme can effectively estimate the channel impulse response. Then, a modified FBMP algorithm is proposed by optimizing the iterative termination conditions. The simulation results indicate that the proposed method provides better mean square error (MSE) and bit error rate (BER) performance than conventional compressive sensing methods

Surface modelling of forest aboveground biomass based on remote sensing and forest inventory data

An accurate estimation of forest aboveground biomass (AGB) is important for carbon accounting. In this study, six methods, including partial least squares regression, regression kriging, k-nearest neighbour, support vector machines, random forest and high accuracy surface modelling (HASM), were used to simulate forest AGB. Forest AGB was mapped by combining Geoscience Laser Altimeter System data, optical imagery and field inventory data. The Normalized Difference Vegetation Index (NDVI) and Wide Dynamic Range Vegetation Index (WDRVI0.2) of September and October, which had a stronger correlation with forest AGB than that of the peak growing season, were selected as predictor variables, along with tree cover percentage and three GLAS-derived parameters. The results of the different methods were evaluated. The HASM model had the best modelling accuracy (small MAE, RMSE, NRMSE, RMSV and NMSE and large R2). A forest AGB map of the study area was generated using the optimal model

Two Nematicidal Compounds from <i>Lysinimonas</i> M4 against the Pine Wood Nematode, <i>Bursaphelenchus xylophilus</i>

A rich source of bioactive secondary metabolites from microorgannisms are widely used to control plant diseases in an eco-friendly way. To explore ideal candidates for prevention of pine wilt disease (PWD), a bacterial strain from rhizosphere of Pinus thunbergii, Lysinimonas M4, with nematicidal activity against pine wood nematode (PWN), Bursaphelenchus xylophilus, was isolated. Two nematicidal compounds were obtained from the culture of Lysinimonas M4 by silica gel chromatography based on bioactivity-guided fractionation and were subsequently identified as 2-coumaranone and cyclo-(Phe-Pro) by nuclear magnetic resonance (NMR) and mass spectrometry (MS). The 2-coumaranone and cyclo-(Phe-Pro) showed significant nematicidal activity against PWN, with LC50 values at 24 h of 0.196 mM and 0.425 mM, respectively. Both compounds had significant inhibitory effects on egg hatching, feeding, and reproduction. The study on nematicidal mechanisms revealed that 2-coumaranone and cyclo-(Phe-Pro) caused the accumulation of reactive oxygen species (ROS) in nematodes, along with a notable decrease in CAT and POS activity and an increase in SOD activity in nematodes, which might contribute to the death of pine wood nematodes. Bioassay tests demonstrated that the two compounds could reduce the incidence of wilting in Japanese black pine seedlings. This research offers a new bacterial strain and two metabolites for biocontrol against PWN

Two nematicidal furocoumarins from <i>Ficus carica</i> L. leaves and their physiological effects on pine wood nematode (<i>Bursaphelenchus xylophilus</i>)

<p>The ethanol extract of the <i>Ficus carica</i> L. leaves was tested to show strong nematicidal activity against pine wood nematode (PWN), <i>Bursaphelenchus xylophilus</i>, causing 90.93% corrected mortality within 72 h at 1.0 mg/mL. From the ethyl acetate soluble fraction of the <i>F. carica</i> L. leaves extract, the main nematicidal constituents were obtained by bioassay-guided isolation and identified as linear furocoumarins bergapten <b>(1)</b> and psoralen <b>(2)</b> by mass and NMR spectral data analysis. Bergapten and psoralen had significant nematicidal activity against PWN with the LC₅₀ values of 97.08 aKSnd 115.03 μg/mL within 72 h, respectively. The two furocoumarins could inhibit the activities of amylase, cellulase and acetylcholinesterase (AchE) from PWN. The morphologies of PWNs changed much after they were treated by bergapten and psoralen. The physiological effects of bergapten and psoralen on PWN might provide helpful clues to elucidate their nematicidal mechanisms.</p