Sheng Jin

Effects of nitrogen deficiency on gas exchange, chlorophyll fluorescence, and antioxidant enzymes in leaves of rice plants

Gas exchange, chlorophyll (Chl) fluorescence, and contents of photosynthetic pigments, soluble proteins (ribulose-1,5-bisphosphate carboxylase/oxygenase, RuBPCO), and antioxidant enzymes were characterized in the fully expanded 6th leaves in rice seedlings grown on either complete (CK) or on nitrogen-deficient nutrient (N-deficiency) solutions during a 20-chase period. Compared with the control plants, the lower photosynthetic capacity at saturation irradiance (Pmax) was accompanied by an increase in intercellular CO2 concentration (Ci), indicating that in N-deficient plants the decline in Pmax was not due to stomatal limitation but due to the reduced carboxylation efficiency. The fluorescence parameters ΦPS2, Fv′/Fm′, electron transport rate (ETR), and qP showed the same tendency as Pmax in N-deficient plants. Correspondingly, a higher qN paralleled the rise of the ratio of carotenoid (Car) to Chl contents. However, Fv/Fm was still diminished, suggesting that photoinhibition did occur in the photosystem 2 (PS2) reaction centres. In addition, the activities of antioxidant enzymes on a fresh mass basis were gradually lowered, leading to the aggravation of membrane lipid peroxidation with the proceeding N-deficiency. The accumulation of malonyldialdehyde resulted in the lessening of Chl and soluble protein content. Analyses of regression showed PS2 excitation pressure (1 - qP) was linearly correlated with the content of Chl and inversely with soluble protein (particularly RuBPCO) content. There was a lag phase in the increase of PS2 excitation pressure compared to the decrease of RuBPCO content. Therefore, the increased excitation pressure under N-deficiency is probably the result of saturation of the electron transport chain due to the limitation of the use of reductants by the Calvin cycle. Rice plants responded to N-deficiency and high irradiance by decreasing light-harvesting capacity and by increasing thermal dissipation of absorbed energy.

Non-Lane-Based Car-Following Model with Visual Angle Information

Car-following theory is of significance in microscopic traffic flow theory. The key assumption of current car-following theory is that vehicles travel in the middle of a single lane. However, this assumption is unrealistic and cannot describe driving behavior in a complex traffic environment. When the lateral separation characteristics between the follower and the leader are taken into account, the time-to-collision equation is modified with visual angle information and introduced into the General Motors model. A non-lane-based model of car following was developed; it uses time to collision and is based on the stimulus–response framework. The proposed model was investigated with simulations conducted under several driving scenarios. The model could describe local and asymptotic stabilities, lateral movement, and the effect of neighboring vehicles. Results implied that this staggered car-following model incorporating lateral separation greatly enhanced the realism of car-following behavior.

Safety evaluation for expressways: A comparative study for macroscopic and microscopic indicators

Objective: This article is to assess the performance of 3 macroscopic safety indicators (speed, speed dispersion, and volume) and two microscopic potential crash risks (time to collision and deceleration rate to avoid crash) on safety evaluation for expressways. Methods: Field data were collected at 3 locations for 4 different time periods on an expressway in Beijing, China. The speed of each vehicle, headway time, and vehicle length were recorded by a traffic management system. The 5 safety indicators were thus calibrated on the basis of the collected data. Further, consistency and comparative analyses were applied to assess the performance of indicators. Results: According to the analyses, speed dispersion was a better predictor of the two microscopic potential risks compared to the two macroscopic indicators. Conclusions: Speed dispersion is recommended to proactively assess road safety because (1) it provides consistent risk evaluation with microscopic potential risks and (2) it makes data collection easier.

On the Impact of Cooperative Autonomous Vehicles in Improving Freeway Merging: A Modified Intelligent Driver Model-Based Approach

Transport researchers and practitioners have long been seeking capable solutions to deal with the traffic oscillations caused by freeway merging. Although existing approaches based on ramp metering have improved the overall efficiency of on-ramps, their performance is still far below the theoretical capacity. The recently proposed detecting technology of autonomous vehicles (AVs) provides an alternative for maximizing the merging efficiency by developing and using appropriate controllers for AVs. In this paper, we develop a cooperative intelligent driver model in order to examine the system performance under different proportions of AVs. The results show that, with a proper vehicle-to-vehicle controlling mechanism, an increasing percentage of AVs will reduce the total travel time and smooth traffic oscillations.

Up-regulation of cyclic electron flow and down-regulation of linear electron flow in antisense- rca mutant rice

To investigate how excess excitation energy is dissipated in a ribulose-1,5-bisphospate carboxylase/oxygenase activase antisense transgenic rice with net photosynthetic rate (PN) half of that of wild type parent, we measured the response curve of PN to intercellular CO2 concentration (Ci), electron transport rate (ETR), quantum yield of open photosystem 2 (PS2) reaction centres under irradiation (Fv′/Fm′), efficiency of total PS2 centres (ΦPS2), photochemical (qP) and non-photochemical quenching (NPQ), post-irradiation transient increase in chlorophyll (Chl) fluorescence (PITICF), and P700+ re-reduction. Carboxylation efficiency dependence on Ci, ETR at saturation irradiance, and Fv′/Fm′, ΦPS2, and qP under the irradiation were significantly lower in the mutant. However, NPQ, energy-dependent quenching (qE), PITICF, and P700+ re-reduction were significantly higher in the mutant. Hence the mutant down-regulates linear ETR and stimulates cyclic electron flow around PS1, which may generate the ΔpH to support NPQ and qE for dissipation of excess excitation energy.

Potential risk and its influencing factors for separated bicycle paths

In this paper, we propose two potential risk indicators to define and evaluate the safety of bicycle path at the microscopic level. Field bicycle data were collected from three survey sites under different traffic conditions. These two risk indicators based on speed dispersion were proposed and calculated during each 5-min interval. The risk influences of various widths of bicycle path and traffic conditions were analyzed by using one-way ANOVA. We further proposed a generalized linear model (GLM) for modeling and analyzing the relationships between bicycle risks and v/c ratio and percentages of electric bicycles, male cyclists, young cyclists, and loaded cyclists. The stepwise regression models were applied for determination of coefficients. The results show that the influences of gender and age of cyclists on potential risks are not significant. The risks increase with the width of bicycle path and percentage of electric bicycles, while only for wider bicycle path (4-lane case in this study), the risks are associated with whether or not cyclists are loaded. The findings could contribute for analysis and evaluation of the safety for bicycle path.

Analysis of the relationship between aggregated traffic volume and traffic conflicts on expressways

Numerous efforts have been made to examine the relationship between aggregated traffic volume and conflicts and some inconsistent findings (linear vs. non-linear) have been observed. In this study, we explore the causes of this inconsistency. It is found that traffic conflicts are very similar for all uncongested traffic states, which supports the proportional linear assumptions in many research. By contrast, the conflicts for congested traffic states are significantly higher, which results in a non-linear feature for combined traffic states.

A Method for Queue Length Estimation in an Urban Street Network Based on Roll Time Occupancy Data

A method estimating the queue length in city street networks was proposed using the data of roll time occupancy. The key idea of this paper is that when the queue length in front of the queue detector becomes longer, the speeds of the following vehicles to pass through the detector will become smaller, resulting in higher occupancy with constant traffic intensity. Considering the relationship between queue lengths and roll time occupancy affected by many factors, such as link length, lane width, lane number, and bus ratio, twelve different conditions were designed, and the traffic data under different conditions was obtained using VISSIM simulation. Based on the analysis of simulation data, an S-type logistic model was decided to develop for the relationship between queue lengths and roll time occupancy, and the fitting equations were obtained under the twelve simulation situations. The average model for the relationship between queue lengths and roll time occupancy was presented by successive multiple linear regression with the fitting equation parameters and simulation parameters, and the estimation model for queue length was presented through analyzing the equation of the average relation model.

Lane-Based Saturation Degree Estimation for Signalized Intersections Using Travel Time Data

Saturation degree estimation is a vital problem of signal timing optimization. However, classic loop-detector-based algorithms are not capable to capture the severity of oversaturation, since detectors are located in front of stop lines, and also cannot distinguish the saturated degree in different lane groups if detectors are located at an upstream position. In this paper, we present a new method to estimate the lane-based saturation degree using travel times. The method is simple and mainly depends on the parameters of signal cycles and the corresponding virtual cycles. The virtual cycle parameters are extracted by analyzing the data on travel times using the K-mean cluster analysis. Then, two models for the traffic demand saturated degree (TDSD) and the effectively used green time saturation degree (EUGTSD) are presented based on the traffic flow conservation during one signal cycle and the corresponding virtual cycle. The new method can overcome the defects of loop-detector-based algorithms, and it can be used to optimize the TDSD and the EUGTSD simultaneously. Finally, the precision of the two types of models is evaluated using field survey data. The results show that the new method has a higher precision for the TDSD and the same accuracy level for the EUGTSD compared to the existing methods. The findings of this paper have potential applicability to signal control systems.

Modeling Mixed Bicycle Traffic Flow: A Comparative Study on the Cellular Automata Approach

Simulation, as a powerful tool for evaluating transportation systems, has been widely used in transportation planning, management, and operations. Most of the simulation models are focused on motorized vehicles, and the modeling of nonmotorized vehicles is ignored. The cellular automata (CA) model is a very important simulation approach and is widely used for motorized vehicle traffic. The Nagel-Schreckenberg (NS) CA model and the multivalue CA (M-CA) model are two categories of CA model that have been used in previous studies on bicycle traffic flow. This paper improves on these two CA models and also compares their characteristics. It introduces a two-lane NS CA model and M-CA model for both regular bicycles (RBs) and electric bicycles (EBs). In the research for this paper, many cases, featuring different values for the slowing down probability, lane-changing probability, and proportion of EBs, were simulated, while the fundamental diagrams and capacities of the proposed models were analyzed and compared between the two models. Field data were collected for the evaluation of the two models. The results show that the M-CA model exhibits more stable performance than the two-lane NS model and provides results that are closer to real bicycle traffic.