[Spatiotemporal Differentiation of Carbon Emissions from Logistics Industry at Provincial Scale in China Under the Background of High-quality Economic Development].

Since 2010, the Chinese economy has transitioned from a high-speed growth model to a high-quality development model. During this period, the logistics industry has witnessed rapid growth, leading to significant carbon emissions and posing severe threats to the ecological environment. To investigate the spatiotemporal variations in carbon emissions in China's logistics industry, we conducted a correlation analysis using Moran's index and a bivariate spatial autocorrelation model from 2010 to 2021.

Analysis of influencing factors of traffic accidents on urban ring road based on the SVM model optimized by Bayesian method.

Based on small scale sample of accident data from specific scenarios, fully exploring the potential influencing factors of the severity of traffic accidents has become a key and effective research method. In order to analyze the factors mentioned above in the scenario of urban ring roads, this paper collected data records of 1250 traffic accidents involving different severity on urban ring road of a central city in northwest China in the past 3 years. Firstly, the Support Vector Machine (SVM) model of non-parametric method is utilized to analyze the data above, and three kernel functions of linear, inhomogeneous polynomial and Gaussian radial basis are constructed respectively.

Mechanical properties and acoustic emission characteristics of basalt fiber reinforced cemented silty sand subjected to freeze-thaw cycles.

Freeze-thaw (F-T) cycling poses a significant challenge in seasonally frozen zones, notably affecting the mechanical properties of soil, which is a critical consideration in subgrade engineering. Consequently, a series of unconfined compressive strength tests were conducted to evaluate the influence of various factors, including fiber content, fiber length, curing time, and F-T cycles on the unconfined compression strength (UCS) of fiber-reinforced cemented silty sand. In parallel, acoustic emission (AE) testing was conducted to assess the AE characteristic parameters (e.

MXene Based Flame Retardant and Electrically Conductive Polymer Coatings.

Modern polymer coatings possess tremendous multifunctionalities and have attracted immense research interest in recent decades. However, with the expeditious development of technologies and industries, there is a vast demand for the flame retardancy and electrical conductivity of engineered polymer coatings. Traditional functional materials that render the polymer coatings with these properties require a sophisticated fabrication process, and their high mass gains can be a critical issue for weight-sensitive applications.

Activation technology of steel slag for concrete exposed to plateau climate: a state-of-the-art review.

As a byproduct of steelmaking, steel slag occupies significant land resources and poses potential environmental and safety challenges due to its extensive accumulation. Recently, steel slag has shown promising applications in the field of concrete. However, considering the complexity of the plateau environment, the utilization of steel slag is relatively lacking, and its low reactivity and poor volume stability remain the main factors restricting its application in plateau concrete.

Surface settlement induced by frictional force of epb shield tunneling in sandy gravels.

The excavation of Earth Pressure Balance (EPB) shield can be divided into two distinct stages, i.e. advancing and lining installation.

Connectivity reliability evaluation and most reliable shipping route choice in a seaborne crude oil network.

The connectivity reliability of strait and canal nodes in seaborne crude oil networks is uncertain because of various risk factors. Existing studies have mainly focused on road networks and often ignored real-world factors by assuming fixed and identical values for the connectivity reliability of each node, leading to inaccurate estimations. Few studies have considered node reliability when identifying the most reliable routes for oil shipments in response to various external and changing risks.

Influence of NR/MWCNT Blending on Rotor Metal Friction and Wear during Mixing Process.

Mixing involves blending raw rubber or masticated rubber with additives using a rubber mixer, which is the most critical process in rubber production. The internal mixer, as the most important mixing equipment, experiences rotor wear during prolonged operation, affecting the gap between the mixer rotor and the chamber wall. This wear reduces mixing effectiveness, weakens filler dispersion, and ultimately impacts rubber performance.

Pollution Characteristics of Heavy Metals in PM and Source-Specific Health Risks in the Tianjin Airport Community, China.

The airport and its surrounding areas are home to a variety of pollution sources, and air pollution is a recognized health concern for local populated regions. Submicron particulate matter (PM with an aerodynamic diameter of <1 mm) is a typical pollutant at airports, and the enrichment of heavy metals (HMs) in PM poses a great threat to human health. To comprehensively assess the source-specific health effects of PM-bound HMs in an airport community, PM filter samples were collected around the Tianjin Binhai International Airport for 12 h during the daytime and nighttime, both in the spring and summer, and 10 selected HMs (V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd, and Pb) were analyzed.

A new strong convective precipitation forecasting method based on attention mechanism and spatio-temporal reasoning.

Radar observation variables reflect the precipitation amount of strong convective precipitation processes, which accurate forecast is an important difficulty in weather forecasting. Current forecasting methods are mostly based on radar echo extrapolation, which has the insufficiency of input information and the ineffectiveness of model architecture. This paper presents a Bidirectional Long Short-Term Memory forecasting method for strong convective precipitation based on the attention mechanism and residual neural network (ResNet-Attention-BiLSTM).

Analyzing resilience influencing factors in the prefabricated building supply chain based on SEM-SD methodology.

The supply chain for prefabricated buildings (PB) currently grapples with pressing challenges. In order to ensure the safe and stable development of the prefabricated building supply chains (PBSC), this study aims to identify the key factors and internal mechanisms affecting the PBSC, and propose a supply chain resilience enhancement mechanism, so as to promote the sustainable development of the PB industry. The study combined a literature review and survey data to identify key resilience factors in PBSC.

Injury severity analysis of e-bike riders in China based on the in-vehicle recording video crash data: a random parameter ordered logit model.

This study investigates the impacts of various factors on e-bike riders' injury severity in crashes with motor vehicles, based on the in-vehicle recording video crash data in China. Variables from human factors, vehicle characteristics, road conditions, and environmental attributes are extracted from the video, especially for drivers and riders' illegal and avoidance behaviour before the crash, and sun shade canopy use. Results of mixed logit models reveal that drivers' speeding, running red lights, slow-down and swerve behaviour, light trucks, heavy trucks, and buses have significantly varied impacts on riders' injury.

Laser Ablating Biomimetic Periodic Array Fish Scale Surface for Drag Reduction.

Reducing resistance to surface friction is challenging in the field of engineering. Natural biological systems have evolved unique functional surfaces or special physiological functions to adapt to their complex environments over centuries. Among these biological wonders, fish, one of the oldest in the vertebrate group, have garnered attention due to their exceptional fluid dynamics capabilities.

Aircraft turnaround time dynamic prediction based on Time Transition Petri Net.

Accurate aircraft turnaround time prediction is an important way to coordinate the operation time of airport ground service and improve the efficiency of airport operation. In this paper, by analyzing the aircraft turnaround operation process, a description model based on Time Transition Petri Net is proposed. The model describes the flight turnaround operation process and the logical relationship of the operation.

Research on a Recognition Algorithm for Traffic Signs in Foggy Environments Based on Image Defogging and Transformer.

The efficient and accurate identification of traffic signs is crucial to the safety and reliability of active driving assistance and driverless vehicles. However, the accurate detection of traffic signs under extreme cases remains challenging. Aiming at the problems of missing detection and false detection in traffic sign recognition in fog traffic scenes, this paper proposes a recognition algorithm for traffic signs based on pix2pixHD+YOLOv5-T.

Redox Stability Optimization in Anode-Supported Solid Oxide Fuel Cells.

For Ni-YSZ anode-supported solid oxide fuel cells (SOFCs), the main drawback is that they are susceptible to reducing and oxidizing atmosphere changes because of the Ni/NiO volume variation. The anode expansion upon oxidation can cause significant stresses in the cell, eventually leading to failure. In order to improve the redox stability, an analytical model is developed to study the effect of anode structure on redox stability.

Experimental Study on the Strength Deterioration and Mechanism of Stabilized River Silt Reinforced with Cement and Alginate Fibers.

River silt deposited by water in coastal areas is unsuitable for engineering construction. Thus, the in situ stabilization treatment of river silt as the bearing layer has been an important research area in geotechnical engineering. The strength degradation behavior and mechanism of stabilized river silt reinforced with cement and alginate fibers (AFCS) in different engineering environments are crucial for engineering applications.

RiskFormer: Exploring the temporal associations between multi-type aberrant driving events and crash occurrence.

With the development of driving behavior monitoring technologies, commercial transportation enterprises have leveraged aberrant driving event detection results for evaluating crash risk and triggering proactive interventions. The state-of-the-art applications were established based upon instant associations between events and crash occurrence, which assumed crash risk surged with aberrant events. Consequently, the generated crash risk monitoring results merely contain discrete abrupt changes, failing to depict the time-varying trend of crash risk and posing challenges for interventions.

Experimental Studies of the Machinability of SiCp/Al with Different Volume Fractions under Ultrasonic-Assisted Grinding.

High-volume fraction silicon carbide particle-reinforced aluminum (SiCp/Al) has a promising application for its high specific strength, wear resistance, and thermal conductivity. However, SiCp/Al components with a high-volume fraction are prone to poor surface quality and defects such as fractures, cracks, and micro-pits. It has been reported that ultrasonic-assisted grinding machining (UAG) helps to improve the quality of SiCp/Al machined surfaces.

[Construction and Analysis of Machine Learning Based Transportation Carbon Emission Prediction Model].

Addressing the issue of carbon emissions in the transportation sector, this research constructed various predictive models using multiple machine learning algorithms based on panel data from 30 provinces in China from 2005 to 2019. The study aimed to identify the optimal machine learning algorithm and key factors influencing the carbon emissions of transportation, providing potent references for policymakers and decision-makers to reduce carbon emissions and promote the sustainable development of the transportation sector. Initially, drawing from the concept of the fixed effects model, we included the heterogeneity differences among provinces as an important factor.

Study on the risk assessment of Pedestrian-Vehicle conflicts in channelized Right-Turn lanes based on the Hierarchical-Grey Entropy-Cloud model.

Channelized right-turn lanes (CRTLs) in urban areas have been effective in improving the efficiency of right-turning vehicles but have also presented negative impacts on pedestrian movement. Pedestrians experience confusion regarding the allocation of road space when crossing crosswalks within these areas, leading to frequent conflicts between pedestrians and motor vehicles. In this paper, considering the characteristics of pedestrian-vehicle conflicts at channelized right-turn lanes as well as the ambiguity and uncertainty of the causes, a comprehensive assignment combined with a cloud model is proposed as a risk evaluation model for pedestrian-vehicle conflicts.

Enhancing multi-scenario applicability of freeway variable speed limit control strategies using continual learning.

Variable speed limit (VSL) control benefits freeway operations through dynamic speed limit adjustment strategies for specific operation scenarios, such as traffic jams, secondary crash prevention, etc. To develop optimal strategies, deep reinforcement learning (DRL) has been employed to map the traffic operation status to speed limits with the corresponding control effects. Then, VSL control strategies were obtained based upon memories of these complex mapping relationships.