Southwest Jiaotong University Hope College

Abstract Several developing markets, such as Brazil, Russia, India, China, and South Africa (BRICS), are facing challenges in attaining the targets set with regard to the Sustainable Development Goals (SDGs). While previous studies have extensively examined the Environmental Kuznets Curve in BRICS nations, focusing on other proxy of environmental degradation like CO 2 emissions and ecological footprint, little attention has been given to the Load Capacity Curve (LCC) hypothesis specifically in relation to emerging economies. Consequently, there exists a gap in the literature regarding the validation of the LCC hypothesis for these economies. To bridge this gap, our research intends to assess the validity of the LCC hypothesis in the context of the BRICS countries. Specifically, we investigate the impact of biomass energy and social globalization on the load capacity factor (a proxy for ecological quality) in the BRICS countries from 1990 to 2018, while considering the roles of economic growth and natural resources. Additionally, we explore the development of an SDG framework tailored for the BRICS nations, which can serve as a blueprint for other emerging economies. To analyze the data, we employ the Method of Moments‐Quantile‐Regression (MMQR) approach along with long‐run estimators. The findings of the MMQR analysis reveal that natural resources, social globalization, and gross domestic product have adverse effects on ecological quality, while biomass energy exhibits a positive influence on ecological quality. Furthermore, our research validates the LCC hypothesis for the BRICS economies. We also observe evidence of causality between the load capacity factor and its determinants. Based on our investigation, we recommend a transition in energy policies from hydrocarbon energy to sustainable energy options by implementing innovative approaches to biomass technology that can enhance conversion efficiency. Implementing these policy changes will not only enhance ecological quality but also align the SDG targets.

The study of rock crack propagation by multi-scale method is of great significance to comprehensively and accurately understand the law of rock crack evolution. In this paper, the theoretical, experimental and numerical methods from macroscale, mesoscale and microscale used for crack propagation in recent years are summarized and analyzed. Firstly, the evolution mechanism of the crack and the related research status are analyzed from a single scale. Secondly, multi-scale theory, modeling, meshing algorithm and macro-mesoscopic parameters are reviewed in the multi-scale coupling method. Through the analysis of the results published in recent years, it is considered that the following aspects need to be further studied: the characteristic parameters of the rock are different at different scales, so the extraction of the characteristic parameters under different scales is essential to modeling and coupling; the heterogeneity of rock and the prefabrication of cracks are greatly affected by human factors, so that 3D printing will be a good breakthrough to build the model of crack owing to its accurate control on the distribution and the size of cracks. The internal stress field of the rock is complex and varied, and the generation and expansion of the microcracks in the process of crack propagation are closely related to the surrounding environment. Therefore, it is of great importance to combine theoretical, experimental and numerical research with practical engineering.

The rapid urbanization in China urges scholars to investigate the impacts of built environment on the level of travel satisfaction of rural residents to improve their quality of life and make planning exercises more human-centric. This study samples six villages out of the 25 top rural areas in Chengdu, Sichuan, China, as the research object and constructs a structural equation model to explore the direct and indirect impacts of the built environment on daily travel satisfaction of rural residents. The research finds that building density (0.609), road density (0.569), the number of accessible markets (0.314), and private car ownership (0.02) have significant positive impacts on travel satisfaction. Public transport (−0.063) has a direct negative impact on travel satisfaction. Consequently, in order to further improve travel satisfaction, construction departments and rural planners should improve the building and road densities of new rural areas and increase the number of accessible markets. The convenience of rural public transport services also needs improvement.

In recent years, while the scale of the used car market has been expanding, the price evaluation system of my country's second-hand car market has exposed the problem that it does not meet the market demand. Accurate used car price prediction can help people make correct decisions and avoid the wanton price tag of used cars in the market as much as possible. This paper uses the random forest and LightGBM algorithms to predict the price of used cars and compares and analyzes the prediction results. The experiments found that the relevant evaluation indicators of the random forest and LightGBM models are as follows: MSE is 0.0373 and 0.0385 respectively; MAE is 0.125 and 0.117 respectively; The R square of prediction is 0.936 and 0.933 respectively. Among the two prediction models, the prediction error of the LightGBM model is smaller, and it can be considered to be applied to other fields in future research.

Adaptive traffic signal control can alleviate traffic congestion and improve throughput. A decentralized multi-agent reinforcement learning (MARL) is a promising data-driven method for learning a cooperative traffic signal policy for dynamic traffic networks. Although most existing MARL algorithms employ neural networks, e.g., convolutional neural network (CNN), to capture the low-dimensional feature embedding from the high-dimensional state space, the features of dynamic traffic network states cannot be effectively exacted by CNN s due to some features of objects ignored, e.g., the directions of vehicles. Based on the above observations, we propose a decentralized graph-based multi-agent advantage actor-critic method, referred to as GraphLight, to implement traffic signal control at multiple intersections. In the proposed GraphLight, the graph convolutional network is employed to extract features of dynamic traffic networks, the states of neighbor agents are used to learn cooperative control policies. We numerically evaluate the proposed GraphLight in an environment with 25 intersections. The experimental results show that the proposed method outperforms the state-of-the-art methods in terms of multiple metrics, and can adapt better the dynamic traffic networks.

Shield excavation and tail grouting are the main causes of ground deformation in tunnel construction, especially in the case of new tunnels undercrossing existing tunnels, which have stricter requirements for settlement control. This paper investigates the equivalent layer method, which is used to simulate ground deformation induced by shield construction and tail grouting via numerical analysis. The research is based on a case study of Beijing’s newly built Metro Line 12 undercrossing the existing Metro Line 10, which is constructed in soft soil. Three-dimensional finite simulation via Plaxis 3D is performed, incorporating the equivalent layer method. Parametric analysis is carried out to explore the influence of the thickness (δ) and elastic modulus (E) of the equivalent layer on surface settlement. It is shown that the surface settlement increases almost linearly with the increase in δ, and it is insensitive to changes in E. The δ is the dominating factor affecting the surface settlement. Based on the Beijing Metro Lines project, the predicted surface settlement is analyzed and compared with monitoring data. Based on a case study of Beijing Metro, the applicability of the equivalent layer method is verified, and the empirical values for δ and E are summarized. δ = 1.8 Gp and E = 2 MPa are suitable values for analysis, which could be references for other shield tunnel constructions in soft soil. With the obtained empirical values of the equivalent layer method, the deformation caused by grouting and undercrossing tunnels could be accurately predicted, which is benefit for reducing budget and environmental protection.

Physical activity is highly correlated with social media dependence in adolescence, but the underlying mechanisms between these variables require further investigation. This study suggests two potential psychological pathways linking physical activity and social media dependence in adolescence, with depression potentially serving as a mediating factor and difficulty describing feelings acting as a moderating factor. A self-reported survey was conducted with 3,247 Chinese adolescents, including measures of physical activity, social media dependence, depression, and difficulty describing feelings. Descriptive statistics and correlation analyses were performed on these variables, and a mediation-moderation model was developed. Physical activity showed a significant negative correlation with social media dependence, depression, and difficulty describing feelings. Additionally, depression was positively correlated with both social media dependence and difficulty describing feelings, and difficulty describing feelings was positively correlated with social media dependence. Furthermore, difficulty describing feelings moderated the relationship between depression and social media dependence in adolescence. This study provides further insights into the psychological mechanisms underlying the relationship between physical activity and social media dependence in adolescence. Depression serves as a mediating factor, while difficulty describing feelings acts as a moderating factor in the relationship between depression and social media dependence. These findings enhance our understanding of the role of depression and difficulty describing feelings in the relationship between physical activity and social media dependence, offering valuable implications for more comprehensive and targeted interventions aimed at reducing social media dependence among adolescents.

This letter concentrates on the spectrum sensing (SS) problem for noncircular (NC) signal in multiantenna cognitive radio networks. A novel detection method called NC local average variance (NC-LAV) is developed to exploit the NC characteristic of the primary signals for SS. The distribution of the NC-LAV statistic in the absence of primary user is first derived. Then, based on the derived distribution, we present an asymptotic threshold determination of the proposed NC-LAV method. Compared to the peer methods, the proposed NC-LAV method exhibits much lower complexity. Meanwhile, the simulation results reveal that the proposed method achieves better performance than several state-of-the-art methods.

With the booming of Positive Psychology, a growing scholarly interest has emerged in language learners' psychological well-being. However, limited research has been conducted on the emotions of Chinese EFL learners. Therefore, this study aimed to quantitatively examine the burnout, enjoyment, and engagement levels among 387 junior high school EFL learners. The findings revealed that the students experienced low levels of burnout but high levels of enjoyment and engagement in learning. Furthermore, significant gender and grade differences were observed in these variables. The study also found strong negative associations between burnout and both enjoyment and engagement, along with significant positive correlations between enjoyment and engagement. Additionally, it was discovered that enjoyment, rather than burnout, significantly predicted English learning engagement. Interestingly, the study also revealed that enjoyment fully mediated the relationship between engagement and burnout. These findings highlight the importance of promoting enjoyment in order to reduce burnout and foster increased engagement among language learners. This article concludes with the theoretical and pedagogical implications for EFL instruction.

The sustainable third-party reverse logistics provider (3PRLP) selection, as the core of sustainable supply chain management, has become paramount in research nowadays. In the actual evaluation process, the decision makers may hesitate in a few linguistic terms and have different partiality towards each term, hence the possibility distribution based hesitant fuzzy linguistic term sets (PDHFLTSs), as expressed by a consecutive or non-consecutive linguistic term set, is suitable for such an evaluation. The purpose of this paper is to solve sustainable 3PRLP selection problems with linguistic information by developing an effective and robust method. We firstly redefine the covariance-based correlation coefficient that can simplify the computation to calculate the consensus degree, and then introduce the hesitant degree in context of possibility distribution information, in order to enrich measures of PDHFLTSs. On this basis, the weights of experts are computed for expression aggregation. Secondly, to overcome attributes’ weights staying constant, the combination of group utility function and variable weight approach is introduced to give the weights of attributes. Most importantly, a decision method, called MULTIMOORA, is optimized by improving the ranking position method, and then, through the combination with PDHFLTS, we proposed a possibility distribution based hesitant fuzzy linguistic MULTIMOORA method with great robustness. At last, the presented method is applied to the field of sustainable third-party reverse logistics provider selection in the e-commerce express industry and the effectiveness is verified by several comparative analyses.

Understanding the impact of climate change on runoff and its extremes is of great significance for water resource assessment and adaptation strategies, especially in water-scarce regions. This study aims to analyze the impact of future climate change on runoff and its extremes in the upper reaches of the Heihe River basin in northwest China. The projected runoff was derived using the Soil Water Assessment Tool with climate data from the CSIRO-MK-3-6-0 model under the scenario of RCP4.5, and a frequency analysis of runoff was performed by generalized extreme value distribution. The results indicate that, compared with the baseline period of 1961 to 2000, the minimum and maximum temperatures in the period 2031 to 2070 were predicted to increase by 2.5 °C on average. The precipitation in most months was also predicted to increase, with an average rise of 16.5%. The multi-year average runoff was projected to increase by 8%. The annual mean and extreme flows were also expected to rise under future climate change at different return periods, and the low flow was expected to increase the most.

In order to improve the deformation energy consumption and self-centering ability of reinforced concrete (RC) frame beam-column joints for main buildings of conventional islands in nuclear power plants, a new type of self-centering joint equipped with super-elastic shape memory alloy (SMA) bars and a steel plate as kernel components in the core area of the joint is proposed in this study. Four 1/5-scale frame joints were designed and manufactured, including two contrast joints (a normal reinforced concrete joint and a concrete joint that replaces steel bars with SMA bars) and two new model joints with different SMA reinforcement ratios. Subsequently, the residual deformation, energy dissipation capacity, stiffness degradation and self-centering performance of the novel frame joints were studied through a low-frequency cyclic loading test. Finally, based on the OpenSees finite element software platform, an effective numerical model of the new joint was established and verified. On this basis, varying two main parameters, the SMA reinforcement ratio and the axial compression ratio, a simulation was systematically conducted to demonstrate the effectiveness of the proposed joint in seismic performance. The results show that replacing ordinary steel bars in the beam with SMA bars not only greatly reduces the bearing capacity and stiffness of the joint, but also makes the failure mode of the joint brittle. The construction of a new type of joint with consideration of the SMA reinforcement and the steel plate can improve the bearing capacity, delay the stiffness degradation and improve the ductility and self-centering capability of the joints. Within a certain range, increasing the ratio of the SMA bars can further improve the ultimate bearing capacity and energy dissipation capacity of the new joint. Increasing or decreasing the axial compression ratio of column ends has little effect on the overall seismic performance of new joints.

In an era of intense brand competition, a successful logo can effectively boost consumer awareness of a company. However, existing research has not thoroughly examined the aspect of symmetry in logo design. Addressing this gap, the present study investigates the impact of logo symmetry on consumers' perceived product quality. Through three online experiments, the results revealed that symmetrical logos significantly enhance perceived product quality compared to asymmetrical logos, with perceived stability mediating this effect. Furthermore, the study confirmed the moderating role of cognitive load, showing that symmetrical logos positively affect perceived product quality only under low cognitive load, while this effect vanishes under high cognitive load. This study contributes to the field of visual logo design and provides practical insights for companies in product promotion and logo design.

Although there is a great demand for machine translation (MT) among language learners, its potentials as a computer-assisted language learning aid remain under-explored. Against this backdrop, this study adopted a mixed research method and conducted a semester-long empirical investigation into how EFL learners in mainland China used MT to assist their writing, whether MT helped improve their writing competence and how they perceived MT in EFL writing instruction. The major findings comprise: 1) By using MT students made more lexical and grammatical changes in essay revision; 2) MT helped improve the learners’ overall writing competence, and particularly had a greater effect on writing accuracy and lexical complexity than on other dimensions; 3) Students generally held a positive attitude towards incorporating MT into EFL writing instruction.

Computer Assisted Language Learning (CALL) has been a burgeoning industry in China, one case in point being the extensive employment of Automated Writing Evaluation (AWE) systems in college English writing instruction to reduce teachers’ workload. Nonetheless, what warrants a special mention is that most teachers include automatic scores in the formative evaluation of relevant courses with scant attention to the scoring efficacy of these systems (Bai & Wang, 2018; Wang & Zhang, 2020). To have a clearer picture of the scoring validity of two commercially available Chinese AWE systems (Pigai and iWrite), the present study sampled 486 timed CET-4 (College English Test Band-4) essays produced by second-year non-English majors from 8 intact classes. Data comprising the maximum score difference, agreement rate, Pearson’s correlation coefficient and Cohen’s Kappa were collected to showcase human-machine and machine-machine congruence. Quantitative linguistic features of the sample essays, including accuracy, lexical and syntactic complexity, and discourse features, were also gleaned to investigate the differences (or similarities) in construct representation valued by both systems and human raters. Results show that (1) Pigai and iWrite largely agreed with each other but differed a lot from human raters in essay scoring; (2) high-human-score essays were prone to be assigned low machine scores; (3) machines relied heavily on the quantifiable features, which, however, had limited impacts on human raters.

Abstract The existing literature consists of various studies that have addressed the interrelationship between banking expansion and carbon emissions but failed to consider supply‐side ecological issues. Keeping this in view, the research aims to assess the impact of green energy transition, banking sector expansion, and import price of crude oil on the “load capacity factor (LCF)” in the United States from 1990 to 2021. The “LCF” has emerged as a novel ecological proxy to date that includes both “biocapacity and ecological footprint.” Using the “bootstrap autoregressive distributed lag” model, the research found that the consumption of renewable energy can enhance the ecological quality of the United States. The results verified the acceptance of the “load capacity curve” hypothesis. Moreover, it demonstrates that banking development promotes environmental quality. Specifically, a 1% improvement in the banking industry leads to a 0.93% increase in the LCF in the short term, as well as a 1.28% increase in the long run. Furthermore, the increase in crude oil import prices has a positive impact on the LCF and eventually promotes environmental sustainability. To be precise, a 1% rise in the price of imported crude oil results in a 0.35% increase in the long‐term LCF level. These results were backed by the findings of several robustness tests. The study, lastly, recommends that the banking sector and government policymakers should use banking growth in promoting green energy to attain their target of zero carbon emissions by 2050.

Flat roofs and platform sinking are two common installation configurations for high-speed pantographs. The cavity formed by the platform sinking is a potential source of aerodynamic drag and noise. In this paper, the shape of the rectangular cavity is optimized, and the aerodynamic performance of the high-speed pantograph with or without platform sinking is compared and discussed based on the optimized cavity results. The flow field and sound propagation are predicted by the improved delayed detached eddy simulation (IDDES) method and the FW-H equation. The results show that the rectangular cavity produces the largest aerodynamic drag and radiation noise. The upstream, downstream, and bottom surfaces of the cavity can be optimized by rounded and sloped edges to reduce aerodynamic drag and noise. The unstable shear flow and recirculation zone formed by flow separation and reattachment can be reduced by modifying the upstream and downstream surfaces of the cavity. In addition, the vortex in front of the downstream surface of the cavity can be reduced or even eliminated by modifying the bottom surface. When the upstream and downstream surfaces of the cavity are rounded and the bottom surface is sloped (R/H = 0.8), the aerodynamic performance of the cavity is better. Compared with the pantograph installed on the flat roof, the aerodynamic drag and noise of the pantograph with platform sinking are significantly reduced due to the shielding of the lower structure by the cavity, and the total drag and noise are reduced by 5.22% and 1.45 dBA, respectively.

Urban rail transit station has a large number of people gathering and relatively closed space, which has become a high incidence of emergencies. In the process of emergency evacuation, due to the unbalanced utilization rate of exits, the evacuation time is prolonged, which seriously threatens the safety of people in the station. In order to find out the reasons for the imbalance of the utilization rate of the exit, and put forward the solution, balance the utilization rate of each exit, improve the evacuation efficiency. In this paper, a subway station platform in Southwest China is taken as an example to establish a three-dimensional simulation model by using anylogic software. Through in-depth analysis, it is found that the reason for the unbalanced utilization of the platform floor exit is that the number of evacuation people at each exit does not match the evacuation capacity. According to the analysis results, the optimization model is put forward. Through comparative analysis, it is found that the optimization model can effectively balance the export utilization rate. Under the current conditions of off peak passenger flow, peak passenger flow and long-term peak passenger flow, the evacuation time can be saved by more than 20%.

Abstract With the continuous development, computer technology promotes the rapid development of science, and the Internet of things (hereinafter referred to as IOT) technology is the product of the rapid development of science and technology. With the increasing popularity of IOT technology, modern technology has been gradually applied to various fields. Building intelligent system has also begun to apply IOT technology, which has become an important area of building intelligent system. A complete intelligent building system is composed of many different networks, which requires IOT technology to play an important role. Building intelligent system construction needs to rely on a variety of technologies, such as network system, information system, lighting system and security defense system, which will achieve various functional systems. Therefore, IOT technology can not only achieve the goal of unattended, but also reduce the cost of building management. Through IOT technology, we promote the communication between things and people. Firstly, this paper analyzes IOT technology. Finally, this paper lists the application of IOT technology in intelligent building system

For urban rail transit station simulation evacuation, domestic and foreign scholars for panic, conformity, reason, gender ratio research has been more mature. However, in the actual evacuation process, the line of sight will be blocked due to the block of buildings, no scholars have studied the influence of the obstruction of sight on the evacuation. In this paper, using Anylogic software, an experimental model is established to compare and analyze the influence of line of sight obstruction on evacuation time, taking a subway station in Southwest China as an example, this paper introduces the factor of line of sight obstruction, when setting up evacuation route, it integrates the evacuation distance and exit congestion degree, establishes the dynamic selection model of pedestrian evacuation path, obtains the evacuation bottleneck of the station, and puts forward the evacuation bottleneck of the station Optimize the scheme and shorten the evacuation time of the station.