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Transportation agencies build statistical models and predict the average crash frequency to identify hazardous road sections and make informed decisions to reduce crashes. In this paper, safety performance models (SPFs) were built and evaluated considering various pavement and roadway characteristics, including pavement friction, which is seldom available for analysis. Four count data models--Poisson model, negative binomial (NB) model, hurdle-NB model (HNB), and zero-inflated NB (ZINB) model--were built based on roadway characteristics and crash data provided by the Oklahoma Department of Transportation (ODOT). Pavement friction, roadway geometry, surface condition characteristics, and traffic exposure were considered the contributing factors to traffic crashes. Established models were compared in terms of the goodness-of-fit, zero inflation, and statistical significance of factors. The HNB model exhibited promising fitting performance with a manageable number of influencing variables. Coefficients in the HNB model suggest that adequate pavement friction and the presence of shoulders can significantly reduce the crash frequency and thus improve roadway safety performance. Potential issues of the statistical models, such as unobserved heterogeneity and multicollinearity, were also discussed. The relation between roadway infrastructure characteristics (including pavement friction) and roadway safety revealed in this study could assist in choosing the proper statistical model for better decision-making and selecting appropriate preventive treatments for improved roadway safety., Author(s): Joshua Q. Li (corresponding author) [1]; Wenyao Liu [1]; Xue Yang [1]; Pan Lu [2]; Kelvin C. P. Wang [1] 1. Introduction Transportation systems play crucial roles in providing [...]

Traditional contact and water-based testing devices exhibit some limitations in evaluating pavement skid resistance. This study demonstrates the viability of deep learning (DL) based non-contact pavement skid resistance evaluation using 3D laser imaging technology. Pavement 3D images and friction numbers were collected from 28 field sites in 10 states in the U.S. to cover pavement sections with various texture and friction characteristics. A total number of 28,000 pairs of 3D images and friction numbers were prepared as the database to train and validate the friction prediction model, named as FrictionNet-V, using the convolutional neural network. The input of FrictionNet-V is the 3D pavement image from the left wheel path, and the output is the corresponding friction number ranging from 0.2 to 0.9. Based on the experimental results on 5,600 testing images, FrictionNet-V achieved better performance than other DL models in terms of speed and accuracy. The result demonstrates the potential of highway speed non-contact pavement skid resistance evaluation using high resolution 3D texture images and DL methods at the network level in the future. [ABSTRACT FROM AUTHOR]

High silicon dioxide content enables as a cement substitute. This study explored recycling RHA and RAP in cement stabilised macadam (CSM) to produce a pavement base material. Laboratory experiments covering strength, flexibility, shrinkage, and resistance to temperature variation were conducted on CSM with RAP (40% by weight of natural aggregates) and RHA at 0%, 20%, 40%, 60%, and 80% weight of cement. The results indicated that the compressive strength, resilient modulus, and tensile strength of CSM increased with curing time while the increasing rate and strength after curing decreased with the addition of RHA. The resistance to thermal changes, moisture loss, and the freeze-thaw cycle could be maintained by replacing 20 wt.% (or lower content) cement with RHA. These findings suggest that replacing 20 wt.% of cement with RHA and 40 wt.% of natural aggregates with RAP can generate qualified and environmental pavement base material. [ABSTRACT FROM AUTHOR]

In atmosphere free-space optical communication (FSO) systems, the scintillation effect produced by turbulence effects increases the bit error rate (BER) of the communication system and reduces the system's performance. However, a high correlation of turbulent noise occurs in the two transmission channels when a signal transmitted in the bidirectional atmospheric channel with channel reciprocity. The performance of the FSO system can be increased by extracting channel state information (CSI) in forward transmission and using adaptive power technology to reduce turbulence in inverse transmission. In this research, we propose a bidirectional atmospheric channel reciprocity-based adaptive power transmission (CR-APT) technique that lowers the bit error rate of the transmitted signal by using the CSI of the relevant channel. To verify the effectiveness of the technique, a bidirectional atmospheric channel with various turbulence intensities is built in the simulation program, along with various background sounds to vary the channel reciprocity, and the impact of reciprocity on signal transmission is examined. The simulation findings demonstrate that adaptive power transmission with high reciprocity is excellent under the weak turbulence condition, and its future development is promising. [ABSTRACT FROM AUTHOR]

Acoustic sensors with ultrahigh sensitivity, broadband response, and high resolution are essential for high-precision nondestructive weak signal detection technology. In this paper, based on the size effect of an ultrahigh-quality (Q) calcium fluoride (CaF2) resonator, a weak acoustic signal is detected by the dispersive response regime in which an acoustic, elastic wave modulates the geometry and is converted to a resonance frequency shift. Through the structural design of the resonator, the sensitivity reaches 11.54 V/Pa at 10 kHz in the experiment. To our knowledge, the result is higher than that of other optical resonator acoustic sensors. We further detected a weak signal as low as 9.4 µPa/Hz1/2, which greatly improved the detection resolution. With a good directionality of 36.4 dB and a broadband frequency response range of 20 Hz–20 kHz, the CaF2 resonator acoustic sensing system can not only acquire and reconstruct speech signals over a long distance but also accurately identify and separate multiple voices in noisy environments. This system shows high performance in weak sound detection, sound source localization, sleep monitoring, and many other voice interaction applications. [ABSTRACT FROM AUTHOR]

Aiming at achieving the concurrent performances of high loading, well controlled release and active targeted delivery, folate (FA) modified dual pH/reduction-responsive mixed polymeric micelles were rationally assembled using FA-PEG-PDEAEMA and PEG-SS-PCL by dissipative particle dynamics (DPD) simulations. The optimized polymers PEG112-PDEAEMA40, FA-PEG112-PDEAEMA40, and PEG112-SS-PCL70 were synthesized and characterized using 1H NMR, FT-IR and GPC, and their mixed micelles were applied for doxorubicin (DOX) delivery. The drug loading capacity (LC) and encapsulation efficiency (EE) values of the MIX1 (FA-PEG112-PDEAEMA40/PEG112-SS-PCL70) at a DOX/polymer feeding ratio of 15 mg/30 mg were 20.22% and 50.69%, which were higher than those of single polymer micelles and MIX2 (PEG112-PDEAEMA40/PEG112-SS-PCL70). Particle size distributions, mesoscopic morphologies, DPD simulations and in vitro drug release profiles all confirmed the well-controlled release performance of the DOX-loaded micelles formed by MIX1: slow DOX release with a cumulative release of 20.46% in the neutral environment and accelerated release with a cumulative release of 74.20% at pH 5.0 + 10 mM DTT within 120 h, which were similar to those of MIX2. Cytotoxicity assay found that both MIX1 and MIX2 blank micelles were biocompatible, and a superior inhibitory effect of the FA-modified DOX-loaded micelles MIX1 on HepG2 cells was found compared to that of free DOX and non-FA-modified DOX-loaded micelles MIX2. All of these confirmed the superiority of MIX1 micelles with high loading capacity, well controlled release, and enhanced inhibitory effects on HepG2 cells, which might be a prospective candidate for anticancer drug delivery. [ABSTRACT FROM AUTHOR]