Dual-station direction finding location based on disturbance detection

The application of direction finding location technology in electronic warfare is becoming more and more extensive. Aiming at the problem that the traditional location method will greatly affect the location accuracy when the measurement information of each observation station is disturbed, a dual-station direction finding location algorithm based on disturbance detection is proposed. The algorithm uses the least squares method to obtain the target’s position information at each moment, then designs an improved Kalman filter algorithm with disturbance detection to improve the location accuracy. The simulation results show that the algorithm can still accurately track the target when the measurement information is disturbed, which has practical application value

An autonomous obstacle avoidance method based on artificial potential field and improved A* algorithm for UAV

The main purpose of autonomous obstacle avoidance path planning of unmanned aerial vehicles (UAVs) is to find a collision-free flight path from the starting point to the target point in the threatened airspace. This paper mainly studies and designs an autonomous obstacle avoidance algorithm for UAVs. Firstly, the research status of obstacle avoidance is reviewed. Secondly, the problem scene is set up, and the basic algorithm used is described. Furthermore, a modified algorithm is designed to solve the problems mentioned above. Finally, the effectiveness of the method is simulated and verified

Using a Hybrid Model to Forecast the Prevalence of Schistosomiasis in Humans

Background: We previously proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in forecasting schistosomiasis. Our purpose in the current study was to forecast the annual prevalence of human schistosomiasis in Yangxin County, using our ARIMA-NARNN model, thereby further certifying the reliability of our hybrid model. Methods: We used the ARIMA, NARNN and ARIMA-NARNN models to fit and forecast the annual prevalence of schistosomiasis. The modeling time range included was the annual prevalence from 1956 to 2008 while the testing time range included was from 2009 to 2012. The mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to measure the model performance. We reconstructed the hybrid model to forecast the annual prevalence from 2013 to 2016. Results: The modeling and testing errors generated by the ARIMA-NARNN model were lower than those obtained from either the single ARIMA or NARNN models. The predicted annual prevalence from 2013 to 2016 demonstrated an initial decreasing trend, followed by an increase. Conclusions: The ARIMA-NARNN model can be well applied to analyze surveillance data for early warning systems for the control and elimination of schistosomiasis

Escin Increases the Survival Rate of LPS-Induced Septic Mice Through Inhibition of HMGB1 Release from Macrophages

Background: Previous studies have described the effects of Escin on improving the survival rate of endotoxemic animals. The purpose of this study was to explore the molecular mechanisms of this potentially beneficial treatment. Methods: First, the survival rate of endotoxemic mice was monitored for up to 2 weeks after Escin pretreatment, Escin post-treatment, or Escin post-treatment + rHMGB1. The effects of Escin on the release of pro-inflammatory cytokines such as TNF-a, IL-1ß, IL-6 and HMGB1 in the serum of endotoxemic mice and LPS-induced macrophages were evaluated by ELISA. Furthermore, the mRNA and protein levels of HMGB1 in LPS-induced macrophages were measured by qRT-PCR and Western blot, respectively. Additionally, the release of pro-inflammatory cytokines such as TNF-a, IL-1ß, IL-6 was evaluated by ELISA in rHMGB1-induced macrophages. Finally, the protein levels and the activity of NF-κB in macrophages were checked by Western blot and ELISA, respectively. Results: Both pretreatment and post-treatment with Escin could improve the survival rate of endotoxemic mice, while exogenous rHMGB1 reversed this effect. In addition, Escin decreased the level of the pro-inflammatory cytokines TNF-a, IL-1ß, IL-6 and HMGB1 in endotoxemic mice and in LPS-induced macrophages. Escin could also inhibit the mRNA levels and activity of HMGB1. The release of the pro-inflammatory cytokines TNF-a, IL-1ß, IL-6 could be suppressed in rHMGB1-induced macrophages by Escin. Finally, Escin could suppress the activation of NF-κB in LPS-induced macrophages. Conclusion: Escin could improve the survival of mice with LPS-induced endotoxemia. This effect maybe meditated by reducing the release of HMGB1, resulting in the suppression of the release of pro-inflammatory cytokines

Genovariation Study of Hantavirus in Main Endemic Areas of Hemorrhagic Fever with Renal Syndrome in Hebei Province, China

<div><p>Background</p><p>Hemorrhagic fever with renal syndrome (HFRS) is an important infectious disease in Hebei Province. At present, cases from the northeast regions of the province account for >80% of the total incidences. However, studies that examine the region-specific genetic variations of the Hantavirus (HV), the causative pathogen for HFRS, have been lacking.</p><p>Methods</p><p>Rodents were collected in northeast Hebei Province from 2004 to 2013, and the HV strains used in this study were isolated in 1993. Lung tissues were isolated from the rodents and HV antigen was detected by indirect immunofluorescence. The M1 and M2 fragments of HV <i>M</i> region were amplified by reverse transcription polymerase chain reaction (RT-PCR), cloned into pMDl9-T vector, sequenced and compared with representative standard stains for homology and phylogenetic analysis.</p><p>Result</p><p>A total of 21 samples of HV antigen-positive were collected. Real-time PCR analysis revealed that the 19 rodent lungs and two HV strains were positive for the SEO virus. 11 samples were chosen to sequence, and they shared 95.8%–99.8% in nucleotide homology, and 83.6%–99.2% when compared to the standard strains of SEO virus. Phylogenetic analysis demonstrated that all strains were grouped into the same S3 subtype.</p><p>Conclusion</p><p>SEO was the major epidemic genotype of HV in the main HFRS endemic areas in Hebei Province, and S3 was the major subtype. There was minor genetic variation in HV over short term periods, while long term variations were higher.</p></div

Phylogenetic trees for hantavirus based on the complete sequences of <i>M</i> segments (1-3651nt).

<p>Phylogenetic trees for hantavirus based on the complete sequences of <i>M</i> segments (1-3651nt).</p

Comparison of the nucleotide and amino acid sequences of <i>M</i> segment (1–3651 nt).

<p>Comparison of the nucleotide and amino acid sequences of <i>M</i> segment (1–3651 nt).</p