Analysis of Traffic Conflicts at Roundabout Entrances and Exits – A Machine Learning Approach for Enhanced Safety

As a component of the urban road network, roundabouts play a crucial role in ensuring operational efficiency. The safety performance of roundabouts significantly impacts overall traffic safety, making it necessary to conduct safety analysis and evaluation. This study utilises UAV to capture video of vehicle trajectory at roundabouts, employing the time to collision (TTC) index and vehicle evasive actions to identify and analyse traffic conflicts. A real-time traffic safety evaluation method has been developed using machine learning algorithms, including random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost) and decision tree (DT) model. This method aims to analyse the relationship between traffic states and conflicts, providing insights into potential safety risks in various traffic conditions. The four machine learning algorithms trained a total of 12 models, with RF demonstrating superior training effectiveness. It achieved high accuracy in predicting traffic conflict areas at the entrances and exits of a roundabout, with a prediction accuracy of 0.86 and an AUC (area under the receiver operating characteristic curve) of 0.88. In addition, this paper further explores the relationship between traffic conflict and state. The results show that traffic flow, speed, density, speed standard deviation and vehicle type ratio have a significant relationship to traffic conflict. This research provides valuable insights for transportation authorities to understand the nature of traffic conflicts at roundabouts, enabling them to implement appropriate early warning systems and management strategies

Impact of land use on bicycle usage: A big data-based spatial approach to inform transport planning

Bicycling is an alternative of urban transport mode, which is significantly influenced by land use. This paper makes an effort to quantify the magnitude and direction of the impact. We first develop a theoretical framework to establish links between land use and bicycle usage. Then, trip data is crawled from Mobike, one of the largest newly emerging, free-floating bike sharing operators in Shenzhen (China), for a total of more than 7.8 million records over 191 consecutive days. And bicycling frequency, travel duration, and riding distance are obtained to be proxies of bicycle usage. Land-use characteristics regarding bicycling are comprehensively indicated by a set of standardized variables including three dimensions, land-use type, land-use mix, land-use connections, and 12 concrete indices. Panel spatial model is applied to quantify the associations at the district level with socioeconomics controlled. Results show that the percentage of green land has a remarkable impact on bicycle usage outcomes and land-use mix is positively associated with bicycling frequency. Density of intersections contributes to longer trip duration. Bicycle lane is a positive facilitator on workdays, while the number of stations is positively related to bicycle usage, especially frequency and distance. These findings provide insight into land use-transport interaction and could be of value to policymakers, planers and practitioners for transport planning while incorporating bicycling-friendly principles

A Comprehensive Double Index Left-Turn Conflict Model at Contraflow Left-Turn Lane Intersections

The study comprehensively evaluates the safety of contraflow left-turn lane intersection, characterised by unique traffic operational features distinct from conventional intersections. The evaluation specifically focuses on the process of left-turning vehicles entering the receiving lane within the intersection. The vehicle arrival rate of left-turning vehicles is analysed to identify vertical conflict features in contraflow left-turn lane design. By subdividing lanes within the intersection, the study delves into the lateral displacement of left-turning vehicles to establish lateral conflict features. To quantify the overall conflict potential, a multiple unit conflicts index is derived by integrating both vertical and lateral conflict features. Furthermore, the double index left-turn conflict model is constructed by introducing the potential collisions severity index during the conflict process. The results indicate that conflict hotspots along the vehicle travel path are primarily concentrated in two regions: (1) at pedestrian crosswalks and within a 2-meter extension; (2) within a range of 6 to 18 meters from the pedestrian crosswalk. The proposed model demonstrates good evaluation effectiveness, providing valuable insights into enhancing the safety of contraflow left-turn lane intersections

A case of left atrial intimal sarcoma with rhabdomyosarcoma differentiation: a case report and literature review

Primary cardiac malignancies are rare, with cardiac sarcomas being the main type. Among these, intimal sarcomas are the most common. However, they tend to occur in the great vessels and are rare in the heart, with only a few isolated cases reported. We report a challenging case of a patient with left atrial intimal sarcoma with rhabdomyosarcoma differentiation. The patient was admitted after a physical examination detected left heart occupancy, and initial imaging suspected a left atrial thrombus. The patient then underwent extracorporeal circulation-assisted open cardiac surgery with resection of an atrial mass. The postoperative pathological findings were suggestive of an arterial intimal sarcoma, which included areas of rhabdomyosarcoma differentiation within the tumor tissue. Unfortunately, the patient’s tumor recurred 4 months later, and she died due to treatment failure. This case highlights the rarity and risk of misdiagnosis of cardiac intimal sarcoma. Additionally, we aim to improve the understanding of intimal sarcoma through a review of immunohistochemistry and gene amplification techniques

Clinical diagnostic biomarker “circulating tumor cells” in breast cancer - a meta-analysis

ObjectiveUsing meta-analysis, we evaluate circulating tumor cells(CTCs) as a potential diagnostic tool for breast cancer.MethodsA document search was conducted using publicly available databases up to May 2021. Specific inclusion and exclusion criteria were formulated and summarize relevant data through literature types, research types, case populations, samples, etc. Subgroup analysis of documents based on regions, enrichment methods, and detection methods. The included research projects were evaluated using DeeKs’ bias, and evaluation indicators such as specificity (SPE), sensitivity (SEN), diagnosis odds ratio (DOR) were used as evaluation indicators.Results16 studies on the use of circulating tumor cells to diagnose breast cancer were included in our meta-analysis. Overall sensitivity value was 0.50 (95%CI:0.48-0.52), specificity value was 0.93 (95%CI:0.92- 0.95), DOR value was 33.41 (95%CI:12.47-89.51), and AUC value was 0.8129.ConclusionIn meta-regressions and subgroup analysis, potential heterogeneity factors were analyzed, but the source of heterogeneity is still unclear. CTCs, as a novel tumor marker, have a good diagnostic value, but its enrichment and detection methods still need to continue to be developed to improve detection accuracy. Therefore, CTCs can be used as an auxiliary means of early detection, which is helpful to the diagnosis and screening of breast cancer

Measurement of cultivated land green use efficiency based on carbon emission and its influencing factors: A case study of 39 cities in the Yangtze River Basin

Abstract In order to promote the high-quality development of cultivated land and ensure food security, based on the carbon emissions in the process of cultivated land use, this study incorporated the total carbon emissions of each carbon source and the food security factor of the study area into the calculation system of cultivated land use efficiency（CLGUE）. Using the Super-SBM model, kernel density estimation and geographic detector method, the CLGUE values in 39 cities in the upstream, midstream and downstream of the Yangtze River Basin from 2011 to 2020 were specifically measured, their temporal and spatial heterogeneity was described, and the influencing factors were detected at both single and interactive levels. The results showed that: （1）The green land use efficiency values of cultivated land in the Yangtze River Basin show an overall upward trend during the decade of 2011-2020；（2）There is a clear spatial heterogeneity the CLGUE values in the Yangtze River Basin cities, as shown by: downstream region &gt; midstream region &gt; upstream region; (3) Cultivated land resource endowment, socioeconomic development, and agricultural production technology are important factors affecting the variability of CLGUE values. However, there are some differences in the degree and direction of influence of different influencing factors on different sample subgroups.</jats:p

Study on Green Utilization Efficiency of Urban Land in Yangtze River Delta

Based on the panel data of 41 cities in the Yangtze River Delta region from 2006–2018, this paper constructed an index system of measuring green urban land use efficiency (green land use efficiency), including input-expected output-unexpected output (input-expected output-unexpected output) and used the unexpected output-SBM model to calculate the green land use efficiency of the region. The spatial and temporal evolution characteristics of urban land green use efficiency in this area were studied by the Dagum Gini coefficient, decomposition, and exploratory spatial data analysis. The results show that (1) the temporal evolution characteristics of green land use efficiency in the whole region of the Yangtze River Delta, provinces (municipalities directly under the central government), and cities all show an upward trend of fluctuation. Among them, the green land use efficiency of the whole region is between 0.258 and 0.377, the gap in the green land use efficiency of the provinces (municipalities directly under the central government) is accelerating, and the green land use efficiency of the cities is gradually advancing to the middle and high efficiency areas. (2) Spatial evolution: On the one hand, the spatial difference in the green use efficiency of urban land in this region is gradually expanding. On the other hand, the green use efficiency of urban land in this region has a significant positive spatial correlation, the agglomeration pattern is dominated by high agglomeration and low agglomeration, and the low high agglomeration is supplemented.</jats:p

Study on Green Utilization Efficiency of Urban Land in Yangtze River Delta

Based on the panel data of 41 cities in the Yangtze River Delta region from 2006–2018, this paper constructed an index system of measuring green urban land use efficiency (green land use efficiency), including input-expected output-unexpected output (input-expected output-unexpected output) and used the unexpected output-SBM model to calculate the green land use efficiency of the region. The spatial and temporal evolution characteristics of urban land green use efficiency in this area were studied by the Dagum Gini coefficient, decomposition, and exploratory spatial data analysis. The results show that (1) the temporal evolution characteristics of green land use efficiency in the whole region of the Yangtze River Delta, provinces (municipalities directly under the central government), and cities all show an upward trend of fluctuation. Among them, the green land use efficiency of the whole region is between 0.258 and 0.377, the gap in the green land use efficiency of the provinces (municipalities directly under the central government) is accelerating, and the green land use efficiency of the cities is gradually advancing to the middle and high efficiency areas. (2) Spatial evolution: On the one hand, the spatial difference in the green use efficiency of urban land in this region is gradually expanding. On the other hand, the green use efficiency of urban land in this region has a significant positive spatial correlation, the agglomeration pattern is dominated by high agglomeration and low agglomeration, and the low high agglomeration is supplemented

Optimizing Wide Band Gap Cu(In,Ga)Se2 Solar Cell Performance: Investigating the Impact of &ldquo;Cliff&rdquo; and &ldquo;Spike&rdquo; Heterostructures

In recent years, the efficiency of high-efficiency Cu(In,Ga)Se2 (CIGS) solar cells has been significantly improved, particularly for narrow-gap types. One of the key reasons for the enhancement of narrow-gap device performance is the formation of the &ldquo;Spike&rdquo; structure at the CdS/CIGS heterojunction interface. Wide-gap CIGS solar cells excel in modular production but lag behind in efficiency compared to narrow-gap cells. Some studies suggest that the &ldquo;Cliff&rdquo; structure at the heterojunction of wide-gap CIGS solar cells may be one of the factors contributing to this decreased efficiency. This paper utilizes the SCAPS software, grounded in the theories of semiconductor physics and photovoltaic effects, to conduct an in-depth analysis of the impact of &ldquo;Cliff&rdquo; and &ldquo;Spike&rdquo; heterojunction structures on the performance of wide band gap CIGS solar cells through numerical simulation methods. The aim is to verify whether the &ldquo;Spike&rdquo; structure is also advantageous for enhancing wide-gap CIGS device performance. The simulation results show that the &ldquo;Spike&rdquo; structure is beneficial for reducing interfacial recombination, thereby enhancing the VOC of wide-gap cells. However, an electronic transport barrier may form at the heterojunction interface, resulting in a decrease in JSC and FF, which subsequently reduces device efficiency. The optimal heterojunction structure should exhibit a reduced &ldquo;Cliff&rdquo; degree, which can facilitate the reduction of interfacial recombination while simultaneously preventing the formation of an electronic barrier, ultimately enhancing both VOC and device performance