Accurate traffic speed forecasting not only can help traffic management departments make better judgments and improve the efficacy of road monitoring but also can help drivers plan their driving routes and arrive safely and smoothly at their destination. This paper focuses on the lack of traffic speed data and proposes a method for traffic speed forecasting based on the multitemporal traffic flow volume of the previous and later moment states. First, according to traffic flow volume data, the different traffic patterns of previous and later moment states were extracted. Second, the performance of five forecasting models, namely, long short-term memory (LSTM), backpropagation (BP), classification and regression trees, k-nearest neighbor, and support vector regression, were compared. Finally, the model with the best prediction results was used to conduct sensitivity analysis experiments for different traffic patterns. Through a real-data case study, we found that the LSTM model has the highest prediction accuracy compared to other models in both time and space. This traffic pattern “previous = 3 and later = 3” can forecast traffic speed more accurately, and its forecasting ability is robust across a range of scenarios.

Supported Pd_xCu_y bimetallic catalysts were prepared and characterized to illustrate the active-site isolation effect on controlling the reactivity and reaction pathway of acetylene hydrogenation.

The synergistic effects involving surface adsorption and photocatalytic degradation commonly play significant roles in the removal of persistent synthetic organics from wastewater in the case of porous semiconductors. Inspired by the visible-light harvesting advantages of porphyrin-based MOFs, a capsule-like bimetallic porphyrin-based MOF (PCN-222(Ni/Hf)) has been successfully constructed through a facile hydrothermal method. In which, the Hf (IV) ions were exactly bonded to the carboxyl groups substituted on the porphyrin rings, meanwhile the Ni (II) ions were finely bonded to the −N inside the porphyrin rings. The adsorption/photocatalytic performances were assessed by using four persistent dyes including rhodamine B (RhB), basic violet 14 (BV14), crystal violet, and acid black 210 (AB210) as the target substances, and enhanced total removal efficiency was obtained by the bimetallic PCN-222(Ni/Hf) in comparison with that of single PCN-222(Hf). The electrochemical analyses and the sacrificial agent capture experiments were carried out to elucidate the photocatalytic mechanism, and the adsorption/photocatalytic stability of PCN-222(Ni/Hf) is also investigated. The work has broadened the applications of porphyrin-based MOFs in the removal of organics by combining their excellent surface adsorption capacity and photocatalytic activities.

An insufficient functional relationship between adjustment factors and saturation flow rate (SFR) in the U.S. Highway Capacity Manual (HCM) method increases an additional prediction bias. The error of SFR predictions can reach 8–10%. To solve this problem, this paper proposes a comprehensive adjusted method that considers the effects of interactions between factors. Based on the data from 35 through lanes in Beijing and 25 shared through and left-turn lanes in Washington, DC, the interactions between lane width and percentage of heavy vehicles and proportion of left-turning vehicles were analyzed. Two comprehensive adjustment factor models were established and tested. The mean absolute percentage error (MAPE) of model 1 (considering the interaction between lane width and percentage of heavy vehicles) was 4.89% smaller than the MAPE of Chinese National Standard method (Standard Number is GB50647) at 13.64%. The MAPE of model 2 (considering the interaction between lane width and proportion of left-turning vehicles was 33.16% smaller than the MAPE of HCM method at 14.56%. This method could improve the accuracy of SFR prediction, provide support for traffic operation measures, alleviate the traffic congestion, and improve sustainable development of cities.

Understanding how land use affects urban rail transit (URT) ridership is essential for facilitating URT usage. While previous studies have explored the way that land use impacts URT ridership, few have figured out how this impact evolves over time. Utilizing URT turnstile and land use data in Beijing, we employed panel data analysis methods to verify the existence of the temporal heterogeneity of the impact and capture this temporal heterogeneity. The results identified time-varying impacts of land use on the URT boarding and alighting trips on weekdays and non-weekdays and also demonstrated the rationality of the mixed effects time-varying coefficient panel data (TVC-P) model in capturing this temporal heterogeneity accurately. The TVC-P model revealed how land use density appealed to URT commuting during weekday morning peak times, and how it triggered the generation of URT commutes during the weekday evening rush hours. The land use diversity promoted URT trips over an extended period on non-weekdays. Additionally, the study identified the time-varying impacts of specific land use on URT ridership. These insights provide both theoretical and empirical support for developing policies and actions that improve the efficiency of transportation systems and foster alignment between land use and transport.

Effective investment in transportation infrastructure ensures sustainable urban development and high-quality economic development. Understanding transportation and socioeconomic relationships is crucial for developing investment strategies. Existing research focuses on analyzing the contribution of transportation to the economy or the contribution of economic development to transportation, neglecting the identification of transportation infrastructure weaknesses to initiate targeted investment and construction. In this study, we propose an assessment framework based on the node–place model to identify the shortcomings in transportation infrastructure. The framework encompasses the adaptability of the current transportation infrastructure and the stage of economic development, evaluating whether the current transportation infrastructure is ahead of or lagging behind the level of economic development. We conduct a case study on three kinds of transportation infrastructure, including railways, highways, and civil aviation, in Zhejiang Province, China. The results show that Zhejiang Province’s transportation infrastructure generally meets economic development requirements, and most cities have relatively advanced transportation systems. However, significant gaps in transportation facilities in certain areas still need to be targeted and supplemented. These findings help to explore the theoretical relationship between transportation and socioeconomics, providing a basis for economic investment decisions on transportation infrastructure.