An extended car following model is proposed by incorporating an intelligent transportation system in traffic. The stability condition of this model is obtained by using the linear stability theory. The results show that anticipating the behavior of more vehicles ahead leads to the stabilization of traffic systems. The modified Korteweg-de Vries equation (the mKdV equation, for short) near the critical point is derived by applying the reductive perturbation method. The traffic jam could be thus described by the kink-antikink soliton solution for the mKdV equation. From the simulation of space-time evolution of the vehicle headway, it is shown that the traffic jam is suppressed efficiently with taking into account the information about the motion of more vehicles in front, and the analytical result is consonant with the simulation one.

Two lattice traffic models are proposed by incorporating a cooperative driving system. The lattice versions of the hydrodynamic model of traffic flow are described by the differential-difference equation and difference-difference equation, respectively. The stability conditions for the two models are obtained using the linear stability theory. The results show that considering more than one site ahead in vehicle motion leads to the stabilization of the system. The modified Korteweg-de Vries equation (the mKdV equation, for short) near the critical point is derived by using the reductive perturbation method to show the traffic jam which is proved to be described by kink-anti-kink soliton solutions obtained from the mKdV equations.

This paper presents a continuum traffic model. The derivation of this model is based upon the assumption that the stream velocity u reaches the equilibrium velocity u(e) within the relaxation time T, while the equilibrium velocity u(e) is adjusted to be attained through the driver's reaction time t(r). It is also assumed that the former delay time scale is greater than the latter. A motion equation with nonconstant propagation velocity of a disturbance in traffic flow is derived that can reflect the anisotropy of disturbance propagation in real traffic, unlike some other higher-order continuum models. It indicates that in our model the undesirable "wrong-way travel" phenomenon and gas-like behavior have been eliminated. The formation and diffusion of traffic shock can be better simulated.

The soliton interaction is investigated based on solving the higher-order nonlinear Schrödinger equation with the effects of third-order dispersion, self-steepening, and stimulated Raman scattering. By using Hirota's bilinear method, the analytic one-, two-, and three-soliton solutions of this model are obtained. According to those solutions, the relevant properties and features of physical and optical interest are illustrated. The results of this paper will be valuable to the study of signal amplification and pulse compression.

We studied the spatial and temporal distribution patterns of Chlorinated Volatile Organic Compounds (CVOCs) in the karst aquifers in northern Puerto Rico (1982-2013). Seventeen CVOCs were widely detected across the study area, with the most detected and persistent contaminated CVOCs including trichloroethylene (TCE), tetrachloroethylene (PCE), carbon tetrachloride (CT), chloroform (TCM), and methylene chloride (DCM). Historically, 471 (76%) and 319 (52%) of the 615 sampling sites have CVOC concentrations above the detection limit and maximum contamination level (MCL), respectively. The spatiotemporal patterns of the CVOC concentrations showed two clusters of contaminated areas, one near the Superfund site “Upjohn” and another near “Vega Alta Public Supply Wells.” Despite a decreasing trend in concentrations, there is a general northward movement and spreading of contaminants even beyond the extent of known sources of the Superfund and landfill sites. Our analyses suggest that, besides the source conditions, karst characteristics (high heterogeneity, complex hydraulic and biochemical environment) are linked to the long-term spatiotemporal patterns of CVOCs in groundwater.

SUMMARY We studied the fractal scaling behavior of groundwater level fluctuation for various types of aquifers in Puerto Rico using the methods of (1) detrended fluctuation analysis (DFA) to examine the monofractality and (2) wavelet transform maximum modulus (WTMM) to analyze the multifractality. The DFA results show that fractals exist in groundwater fluctuations of all the aquifers with scaling patterns that are anti-persistent (1 < β < 1.5; 1.32 ± 0.12, 18 wells) or persistent (β > 1.5; 1.62 ± 0.07, 4 wells). The multi-fractal analysis confirmed the need to characterize these highly complex processes with multifractality, which originated from the stochastic distribution of the irregularly-shaped fluctuations. The singularity spectra of the fluctuation processes in each well were site specific. We found a general elevational effect with smaller fractal scaling coefficients in the shallower wells, except for the Northern Karst Aquifer Upper System. High spatial variability of fractal scaling of groundwater level fluctuations in the karst aquifer is due to the coupled effects of anthropogenic perturbations, precipitation, elevation and particularly the high heterogeneous hydrogeological conditions.

This study investigates the occurrence of six phthalates and distribution of the three most-detected phthalates in the karst region of northern Puerto Rico (KRNPR) using data from historical records and current field measurements. Statistical data analyses, including ANOVA, Chi-Square, and logistic regression models are used to examine the major factors affecting the presence and concentrations of phthalates in the KRNPR. The most detected phthalates include DEHP, DBP, and DEP. At least one phthalate specie is detected above DL in 7% of the samples and 24% of the sampling sites. Concentrations of total phthalates average 5.08 ± 1.37 μg L, and range from 0.093 to 58.4 μg L. The analysis shows extensive spatial and temporal presence of phthalates resulting from dispersed phthalate sources throughout the karst aquifers. Hydrogeological factors are significantly more important in predicting the presence and concentrations of phthalates in eogenetic karst aquifers than anthropogenic factors. Among the hydrogeological factors, time of detection and hydraulic conductivities larger than 300 m d are the most influential factors. Persistent presence through time reflects continuous sources of phthalates entering the aquifers and a high capacity of the karst aquifers to store and slowly release contaminants for long periods of time. The influence of hydraulic conductivity reveals the importance of contaminant fate and transport mechanisms from contamination sources. This study improves the understanding of factors affecting the spatial variability and fate of phthalates in karst aquifers, and allows us to better predict their occurrence based on these factors.

The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was initially reported in Wuhan, China since December, 2019. Here, we reported a timely and comprehensive resource named iCTCF to archive 256,356 chest computed tomography (CT) images, 127 types of clinical features (CFs), and laboratory-confirmed SARS-CoV-2 clinical status from 1170 patients, reaching a data volume of 38.2 GB. To facilitate COVID-19 diagnosis, we integrated the heterogeneous CT and CF datasets, and developed a novel framework of Hybrid-learning for UnbiaSed predicTion of COVID-19 patients (HUST-19) to predict negative cases, mild/regular and severe/critically ill patients, respectively. Although both CT images and CFs are informative in predicting patients with or without COVID-19 pneumonia, the integration of CT and CF datasets achieved a striking accuracy with an area under the curve (AUC) value of 0.978, much higher than that when exclusively using either CT (0.919) or CF data (0.882). Together with HUST- 19, iCTCF can serve as a fundamental resource for improving the diagnosis and management of COVID-19 patients.Authors Wanshan Ning, Shijun Lei, Jingjing Yang, and Yukun Cao contributed equally to this work.