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Deploying the dynamic wireless power transfer (DWPT) equipment at intersections can improve the transportation efficiency and decrease the energy consumption. It can easily turn the disadvantages of waiting time for red phase into the advantages of charging benefits for electric vehicles (EVs). This study develops a multiobjective speed planning model with differentiated charging strategy to optimize the EV’s trajectory at signalized intersections with DWPT. To mitigate the negative impact of DWPT, the proposed model is divided into charging priority driving (C-eco-driving) mode and time priority driving (T-eco-driving) mode for connected and automated electric vehicles (CAEVs) to apply different scenarios. Meanwhile, a widely applied car-following model, i.e., the Intelligent Driver Model (IDM), has been calibrated with the ground-truth dataset to meet the intersection characteristic for EVs in mixed traffic. The efficiency and robustness of two eco-driving modes were validated in single-vehicle and mixed traffic based on MATLAB simulation. For single vehicle, the electricity benefits of the C-eco-driving mode and T-eco-driving mode increase about 0.0867 kWh and 0.0532 kWh, respectively. T-eco-driving mode reduces 2.5 s of travel time. For mixed traffic, the C-eco-driving mode provides more charging benefits about 51~73% than no-control strategy. In contrast, the T-eco-driving mode provides significant time benefits of 2.6 s and slight electricity benefits of 12~30% than no-control strategy. The increment of market penetration rate and wireless charging length can significantly improve the charging benefits. When charging length has the same value, the closer the DWPT facilities to the intersection, the more obvious the charging benefits.

Many studies have simulated traffic behavior at signalized intersections using various Car-Following (CF) models. However, the performance of which CF Model is superior at signalized intersections has not been thoroughly analyzed and evaluated. In this study, two novel Artificial Neural Network (ANN) CF models, the Convolutional Neural Network—Long Short-term Memory (CNN-LSTM) and the Convolution-LSTM (Conv-LSTM)—are first applied to predict CF behaviors at signalized intersections. Both models can extract spatial and temporal information to address the long-term dependency problem more effectively. Based on the filtered NGSIM dataset, we conduct a comparative empirical study of three conventional CF models and five ANN CF models. The dataset is divided into two categories based on the characteristics of CF behavior at signalized intersections: continuous and discontinuous. The experiments demonstrated that ANN CF models outperformed conventional CF models when the output was the velocity in two categories of traffic flow but only failed to do so when the output was acceleration in discontinuous traffic flow. The proposed models were capable of accurately predicting acceleration, but the traffic fluctuations also existed as time passed. Additionally, it was discovered that while the ANN CF model is preferable for traffic flow simulation, the conventional CF model still cannot be ignored for discontinuous traffic flow simulation, particularly when acceleration is required.

Here, we report the draft genome of Paraburkholderia sp. XV. This strain was isolated from the rhizosphere of mango (Mangifera indica L.). Its genome consists of 9,189 coding DNA sequences, 60 tRNAs, a single copy of the 16S rRNA, 5S rRNA, and 23S rRNA gene, and 1 tmRNA. The GC content is 62.6%.

Extremely high porosities and permeabilities are commonly discovered in the sandstones of the Xishanyao Formation in the central Junggar Basin with the burial depth greater than 5500 m, from which hydrocarbons are currently being produced. High content of carbonate cements (up to 20%) is also observed in a similar depth range. Our study aimed to improve our understanding on the origin of carbonate cements in the Xishanyao Formation, in order to provide insights into the existence of high porosity sandstones at greater depths. Integrated analyses including petrographic analysis, isotopic analysis, fluid-inclusion, and core analysis were applied to investigate the distribution and origin of carbonate cements and the influence of high fluid pressure on reservoir quality. Textural evidences demonstrate that there are two generations of carbonate cements, precipitated at the temperature of 90°C and 120°C, respectively. The carbonate cements with low δCPDB13 ranging from −19.07 to -8.95‰ dominantly occurred near the overpressure surface and especially accumulated at approximately 100 m below the surface. Our interpretation is that high content of carbonate cements is significantly influenced by early carbonate cements dissolution and migration under overpressure. Dissolution of plagioclase resulted in the development of internal pores and porosities of as much as 10% at 6500 m depth presumably.

Polyyne bridges have attracted extensive interest as molecular wires due to their shallow distance dependence during charge transfer. Here, we investigate whether triplet energy transfer from cadmium selenide (CdSe) quantum dots (QDs) to anthracene acceptors benefits from the high conductance associated with polyyne bridges, especially from the potential cumulene character in their excited states. Introducing π-electron rich oligoyne bridges between the surface-bound anthracene-based transmitter ligands, we explore the triplet energy transfer rate between the CdSe QDs and anthracene core. Our femtosecond transient absorption results reveal that a rate constant damping coefficient of β is 0.118 ± 0.011 Å−1, attributed to a through-bond coupling mechanism facilitated by conjugation among the anthracene core, the oligoyne bridges, and the COO⊖ anchoring group. In addition, oligoyne bridges lower the T1 energy level of the anthracene-based transmitters, enabling efficient triplet energy transfer from trapped excitons in CdSe QDs. Density-functional theory calculations suggest a slight cumulene character in these oligoyne bridges during triplet energy transfer, with diminished bond length alternation. This work demonstrates the potential of oligoyne bridges in mediating long-distance energy transfer. [ABSTRACT FROM AUTHOR]

Based on theory of Lemaitre’s equivalent strain of the damage and with the damage of bars of the block reticulated spherical shell, the nonlinear bending problem of the block reticulated shells considering damage with rectangular bottom was studied under the boundary condition of moved fixed-edges based on the nonlinear deformation fundamental equations. The trigonometric series solution satisfies boundary condition of the deflection was derived firstly. The stress function was solved by substitution of the solution into the nonlinear compatibility equation and the nonlinear characteristic formula of the loads and the deflection was obtained by the energy equation. Then the critical point was given. The critical load was given by the characteristic curves. The nonlinear characteristic formula in the paper can be reference by the engineering designers. The effect of the damage of the structure can be considered.