Measurement-Based Analysis on Vehicle-to-Vehicle Connectivity in Tunnel Environment

Vehicular ad hoc network (VANET) brings an excellent solution to ensure road safety and transportation efficiency in critical environment like tunnel. Particularly, radio link connectivity of vehicle-to-vehicle (V2V) significantly influences the performance of VANETs. The communication range of the radio systems is a random variable in reality due to the channel fading effect. Therefore, the connectivity model between vehicles in realistic environment is a key for accurate evaluation of system performances. In this paper, we study the V2V connectivity performance in the presence of channel randomness for tunnel environment. Firstly, based on channel measurement campaign, empirical path loss (PL) and small-scale fading channel models are established. Secondly, we study the influence of large-scale fading parameters on V2V connectivity. Thirdly, based on real small-scale fading characteristics, we derive the V2V connectivity probability between any two vehicles under Nakagami fading channel for one-dimensional VANET, and give the closed-form of V2V connectivity probability. Finally, we study the influences of various parameters (i.e., Nakagami fading factor, vehicle density, and neighbor order) on V2V connectivity performance. Results show that with the Nakagami fading shape factor increases, the connectivity probability increases. The shadowing fading can improve connectivity in the VANET; the path loss exponent, transmission distance, and signal-to-noise ratio (SNR) threshold have a negative impact on connectivity probability. The transmit power, vehicle density, and path loss threshold value have a positive impact on connectivity

Preparation and enhanced properties of Fe3O4 nanoparticles reinforced polyimide nanocomposites

Polyimide (PI) nanocomposite reinforced with Fe3O4 nanoparticles (NPs) at various NPs loadings levels of 5.0, 10.0, 15.0, and 20.0 wt% were prepared. The chemical interactions of the Fe3O4 NPs/PI nanocomposites were characterized using Fourier Transform Infrared (FT-IR) spectroscopy. X-ray Diffraction (XRD) results revealed that the addition of NPs had a significant effect on the crystallization of PI. Scanning electron microscope (SEM) and the atomic force microscope (AFM) were used to characterize the dispersion and surface morphology of the Fe3O4 NPs and the PI nanocomposites. The obtained optical band gap of the nanocomposites characterized using Ultraviolet-Visible Diffuse Reflectance Spectroscopy (UV-Vis DRS) was decreased with increasing the Fe3O4 loading. Differential scanning calorimetry (DSC) results showed a continuous increase of Tg with increasing the Fe3O4 NPs loading. Some differences were observed in the onset decomposition temperature between the pure PI and nanocomposites since the NPs and the PI matrix were physically entangled together to form the nanocomposites. The contact angle of pure PI was larger than that of Fe3O4/PI nanocomposites films, and increased with increasing the loading of Fe3O4. The degree of swelling was increased with increasing the Fe3O4 loading and the swelling time. The dielectric properties of the nanocomposite were strongly related to the Fe3O4 loading levels. The Fe3O4/PI magnetic property also had been improved with increasing the loading of the magnetic nanoparticles

Evaluation of next-generation sequencing software in mapping and assembly

Next-generation high-throughput DNA sequencing technologies have advanced progressively in sequence-based genomic research and novel biological applications with the promise of sequencing DNA at unprecedented speed. These new non-Sanger-based technologies feature several advantages when compared with traditional sequencing methods in terms of higher sequencing speed, lower per run cost and higher accuracy. However, reads from next-generation sequencing (NGS) platforms, such as 454/Roche, ABI/SOLiD and Illumina/Solexa, are usually short, thereby restricting the applications of NGS platforms in genome assembly and annotation. We presented an overview of the challenges that these novel technologies meet and particularly illustrated various bioinformatics attempts on mapping and assembly for problem solving. We then compared the performance of several programs in these two fields, and further provided advices on selecting suitable tools for specific biological applications.published_or_final_versio

A Single-Site Vehicle Positioning Method in the Rectangular Tunnel Environment

Due to the satellite signals are blocked, it is difficult to obtain the vehicle position in the tunnels. We propose a single-site vehicle localization scheme for the rectangular tunnel environment, where most satellite-based positioning methods can not provide the required localization accuracy. In the non-line-of-sight (NLOS) scenarios, we make use of the reflection paths as assistants for vehicle positioning. Specifically, first, the virtual stations are established based on the actual geometrical structure of the tunnel. Second, we use the direction-of-arrival (DOA) and time-of-arrival (TOA) information of reflection paths from two tunnel walls to achieve vehicle positioning. Especially, the Cramer-Rao lower bound (CRLB) of the joint TOA and DOA localization for NLOS propagations in a two-dimensional (2D) space is derived. In addition, based on the localization algorithms with and without filters, we assess the localization performance. In the line-of-sight (LOS) scenarios, we use the LOS path and two reflection paths from the tunnel walls to estimate the vehicle location. First, virtual base stations are established. Second, based on the obtained TOA information, different positioning algorithms are used to estimate the vehicle location. Simulation results illustrate that the proposed positioning approach can provide a small root mean square error. The localization algorithms using filters improve the localization accuracy, compared with the positioning algorithm without using filters, namely, the two-stage weighted least squares (TSWLS) algorithm. Moreover, the Unscented Particle Filter (UPF) algorithm achieves better positioning accuracy than other methods (i.e., Unscented Kalman Filter (UKF), Extended Kalman Filter (EKF), TSWLS algorithms)

A Single-Site Vehicle Positioning Method in the Rectangular Tunnel Environment

Due to the satellite signals are blocked, it is difficult to obtain the vehicle position in the tunnels. We propose a single-site vehicle localization scheme for the rectangular tunnel environment, where most satellite-based positioning methods can not provide the required localization accuracy. In the non-line-of-sight (NLOS) scenarios, we make use of the reflection paths as assistants for vehicle positioning. Specifically, first, the virtual stations are established based on the actual geometrical structure of the tunnel. Second, we use the direction-of-arrival (DOA) and time-of-arrival (TOA) information of reflection paths from two tunnel walls to achieve vehicle positioning. Especially, the Cramer-Rao lower bound (CRLB) of the joint TOA and DOA localization for NLOS propagations in a two-dimensional (2D) space is derived. In addition, based on the localization algorithms with and without filters, we assess the localization performance. In the line-of-sight (LOS) scenarios, we use the LOS path and two reflection paths from the tunnel walls to estimate the vehicle location. First, virtual base stations are established. Second, based on the obtained TOA information, different positioning algorithms are used to estimate the vehicle location. Simulation results illustrate that the proposed positioning approach can provide a small root mean square error. The localization algorithms using filters improve the localization accuracy, compared with the positioning algorithm without using filters, namely, the two-stage weighted least squares (TSWLS) algorithm. Moreover, the Unscented Particle Filter (UPF) algorithm achieves better positioning accuracy than other methods (i.e., Unscented Kalman Filter (UKF), Extended Kalman Filter (EKF), TSWLS algorithms)

V2V Channel Modeling at 5.2 GHz for Highway Environment

To design and evaluate vehicle-to-vehicle (V2V) communication systems in intelligent transportation system (ITS), it is important to understand the propagation mechanisms and channel models of V2V channels. This paper aims to analyze the channel models at 5.2 GHz for the highway environment in obstructed line-of-sight (OLoS) and line-of-sight (LoS) scenarios, particularly the vehicle connectivity probability derivation based on the propagation model obtained from measurement. First, the path loss (PL), shadow fading (SF), narrowband K-factor, and small-scale amplitude fading are analyzed. Results showed that the received signal magnitude follows Rice and Weibull distribution in LoS and OLoS scenarios, respectively. Second, we develop simple and low-complexity tapped delay line (TDL) models with a 10 MHz bandwidth for LoS and OLoS scenarios; in addition, we investigate the wideband K-factor, the root mean square delay spread (RMS-DS), and delay-Doppler spectrum. Third, we derive the closed form connectivity probability between any two vehicles in the presence of Weibull fading channel, and analyze the effects of Weibull fading channel and traffic parameters on connectivity. It is found that Weibull fading parameter, transmit power and vehicle density have positive impact on connectivity probability, PL exponent has negative impact on connectivity probability

Non-Stationarity Analysis of Vehicle-to-Vulnerable Road Users Channel in Critical Scenarios

Direct vehicle-to-vulnerable road users (V2VRU) communication can prevent accidents by providing 360◦ awareness and improving detection, localization, and tracking of both vehicles and VRUs. Having a realistic channel is a prerequisite for developing a reliable V2VRU communication system. In order to parameterize a geometry-based stochastic channel model (GSCM), it is important to determine the length of local quasi-stationarity regions. Therefore, in this work, the non-stationarity of the V2VRU channel is analyzed by estimating the generalized local scattering function (GLSF) and its collinearity based on the channel measurement data. The estimated stationarity distance is presented for the three most critical accident scenarios in urban environment. We find that the observed rapid fluctuations of the stationarity distance are mainly caused by the sudden change in the Doppler domain at the collision point, strong multipath, and the blockage of the line of sight by parked vehicles

Growth, photosynthetic pigment proteins responses and transcriptome analysis provide insights into survival strategies against short-term cold stress in the blue-green algae, Arthrospira

Arthrospira species are widely cultivated due to their high nutritional value as a food supplement. The fluctuating temperature strongly influences the cultivation system for Arthrospira mass production. To reveal the underlying mechanisms of coping with temperature stress to adopt measures of harm reduction, we analyzed changes in growth, photosynthetic pigments and the transcriptome of Arthrospira sp. TJSD091 exposed to short-term cold stress. The photosynthetic pigments decreased significantly under cold temperature stress conditions, and so as the cells` dry weight. A total of 1294 genes were expressed differentially. Pathway analysis revealed 473 differentially expressed genes were identified in 32 KEGG pathways, of which 309 genes (65.33 %) are involved in the most affected metabolic pathway. The most sensitive metabolic pathways in response to cold stress involved energy metabolism, carbohydrate metabolism and photosynthesis proteins. The key hub regulatory genes were perceived as cyaA and genes related to two-component signal transduction systems. The genes regulated diverse metabolic functions to survive and grow. The increased respiration provided essential energy for basic motility maintenance under cold stress. The down-regulation of genes involved in photosynthesis, glycolysis, Calvin cycle and citrate cycle supported the low biomass production of the blue-green algae. The results provide a basis for revealing the survival mechanism of the blue-green algae to withstand cold stress at the gene transcription level