BACKGROUND: Ionotropic γ-aminobutyric acid (iGABA) receptors are involved in various physiological activities in insects, including sleep, olfactory memory, movement, and resistance to viruses. Ivermectin and fluralaner can disturb the insect nervous system by binding to iGABA receptors, and are therefore an effective means for controlling insect pests. However, the molecular mechanisms underlying the insecticidal effect of both the compounds on Aedes. aegypti remain unexplored.RESULTS: In this study, we investigated the spatiotemporal expression profile of Ae. aegypti RDL (Ae-RDL), a subunit of iGABA receptor. RDL dsRNA suppressed the expression of Ae-RDL mRNA in Ae. aegypti larvae and adult by 60% and 50.67%, resepectly. However, the physiology of Ae. aegypti larvae was not significantly affected. The mortality of Ae. aegypti larvae and adult females subjected to Ae-RDL knockdown significantly decreased after exposure to ivermectin and fluralaner. Additionally, Ae-RDL was cloned into Xenopus laevis oocytes and characterized using the two-electrode voltage-clamp method. The inward current was induced by GABA binding to the functional Ae-RDL homomeric receptors at a median effective concentration (EC 50 ) of 100.4 ± 59.95 ∼M (n > 3). The significant inhibitory effect of ivermectin and fluralaner on inward current indicated that both insecticides exerted a significant antagonistic effect on Ae-RDL. However, ivermectin also showed strong agonistic as well as weak activation effects on Ae-RDL. These contrasting effects of ivermectin on Ae-RDL depended on ivermectin concentration. CONCLUSION: Our study revealed that Ae-RDL subunit is a target of ivermectin and fluralaner, providing new insights into the insecticidal mechanism of both compounds in Ae. aegypti.

The intersection control and management can alleviate the traffic congestion caused by traffic incidents. Therefore, it becomes essential to develop a signal optimization method for intersections influenced by traffic incidents, which will be beneficial to prevent congestion spreading. In this paper, the proposed model is capable of maximizing the intersection throughput by comprehensively considering the queue length as the penalty value. The headway of leaving vehicles is assumed to follow the Cowan’s M3 headway distribution, where formulas for queue length can be derived based on gap acceptance theory. To satisfy the conditions for efficiently identifying feasible solutions in a short time, a heuristic algorithm (simulated annealing algorithm) is employed to solve the model. The numerical results can validate that the proposed method can solve the problem more efficiently and alleviate the intersection congestion caused by the incidents more desirably. When the incident occurs away from the intersection stop line, the impacts on intersection throughput will be gradually weakened. The proposed method is capable of improving the signalized intersection throughput while preventing the congestion from spreading to the upstream intersection.

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Adjacent closely spaced intersections with characteristics of short link distance and high pedestrian flow are primarily located in high-density urban areas. To address the problems of queue overflow, poor traffic operation, and high pedestrian travel delays, a pedestrian-motor vehicle signal optimization method for adjacent closely spaced intersections was proposed in this paper. First, the traffic flow entering the closely spaced intersections is divided into nonarterial and arterial flow categories to establish a delay model of pedestrian crossing. Then, a pedestrian crossing delay model based on pedestrian demand is constructed according to pedestrian crossing time and a space diagram. An optimization model for pedestrians and vehicles at adjacent closely spaced intersections is established, and an artificial intelligence algorithm is used to optimize this model. Finally, a selected case intersection is optimized. The results show that compared with a traditional single optimization method, vehicle delay decreased about 4%, 13.8%, 17.1%, and 25.9% and total pedestrian delay decreased by 3%, 15%, 25%, and 31%, respectively, for the four proposed scenarios.

The performance of intersections has been considered a key factor in measuring the efficiency of urban road systems. In this paper, a reliability model for a two-phase signalized intersection is proposed on the basis of presenting a concept of traffic function reliability (TFR). First, classic cumulative curves are created to derive delay formulas. Then, a model for traffic function reliability is proposed based on the quantitative relationship between the random traffic flows, signal timing, and queue lengths. Finally, the delay threshold of the intersection is determined by referring to the level of service. A numerical simulation has been created to clarify the proposed mechanism of TFR. The results show that the saturation and the green time ratio have a dramatical influence on TFR. Under different saturation levels, the sensitivity of TFR to changes in green time ratio gradually weakened. When the green signal ratio increases above a certain value, TFR remains nearly constant. A microscopic simulation verified the applicability of the proposed model. The results show that the accuracy of the model is close to 90% in the case of low saturation. This method provides road authorities useful insights to understand travel time variability.

Intersections are a vital component of the urban road network. Their use is essential for traffic efficiency and operational stability. In this paper, a dynamic control method for two-phase signal control intersection is proposed by using the intercycle flow standard deviation. This technique can dynamically assign weights to different control goals of traffic efficiency and operational stability. For intersections with large flow fluctuation amplitudes, greater weight is given to the control goal of operational stability to reduce the sensitivity of the signal control on flow fluctuation. For intersections with a small flow fluctuation amplitude, greater weight is given to the control goal of traffic efficiency to maximize the intersection throughput. Compared with the plan selection and pretimed control method, the numerical results can validate that this method has better control performance under different flow fluctuations amplitude. The fluctuation range length is significantly optimized, especially in the cases of the low and medium flow saturation conditions.