Connecting Lines Research Articles

P-991. Repercussions of the COVID-19 Pandemic on Maternal and Congenital Syphilis in South Brazil: A Time Series Analysis 2010-2022

Abstract Background The global rise in maternal syphilis prevalence and congenital syphilis incidence over the past decade has been concerning. In South Brazil, a promising stabilization in these rates has been undermined since the COVID-19 pandemic began. This study examines the pandemic's impact on the epidemiological trends of maternal and congenital syphilis. Holt-Winters Forecast of maternal syphilis monthly prevalence rates 2010-2022 Observed monthly rates used in forecast represented by black dots and connecting black line with gray upper and lower 95% confidence intervals on pre-pandemic panel. Holt-Winters seasonal monthly forecast shown as lime green dots and connecting lime green line with dark green upper and lower 95% confidence intervals. Observed monthly rates not used in forecast represented by blue circles and blue connecting line with gray upper and lower 95% confidence intervals on pandemic panel. Methods We conducted a retrospective review of hospital records from a South Brazilian tertiary care center, covering the period from January 1, 2010, to December 31, 2022. Assessment of gestational syphilis status was performed using prenatal syphilis records. Maternal syphilis status at delivery and congenital transmission rates were extracted from all recorded deliveries. A Holt-Winters seasonal forecasting model was used to predict maternal syphilis prevalence from pandemic onset, against which we compared actual pandemic period rates. Using data from 2017-2022, a more detailed analysis of total births and corresponding rates of maternal syphilis, congenital transmission, and infant outcomes was performed. Total deliveries and total maternal syphilis prevalence per year 2017-2022 Bar height in green represents total number of births per year in left panel. Bar height in right panel represents total maternal syphilis prevalence for that year with 95% confidence intervals. Blue section of bar represents percentage of patients diagnosed with syphilis during prenatal care. Yellow section of bar represents percentage of patients diagnosed with syphilis at delivery. * Indicate statistically significant differences (Wilson/Brown p<0.05) between total maternal syphilis rates between years Results Projections using 2010-2019 data indicated a potential stabilization in maternal syphilis during the subsequent COVID-19 pandemic years. Contrary to this, the actual rates recorded during 2020-2022 were much higher than those predicted. In 2021 and 2022, forecasting predicted an average yearly rate of 8.7% and 8.8%, while the observed average yearly rate was 12.5% and 10.3%, respectively. Total births throughout 2017-2022 remained stable with a small decline in the pandemic period. With most cases detected at delivery, 2020 saw an artificial decline in total syphilis prevalence at 9.1% that proceeded to increase significantly to 14.5% in both 2021 and 2022. Congenital syphilis transmission initially showed a decrease from 58% to 26% pre-pandemic and rose to 31% in 2022. The incidence of pregnancy terminations and fetal demises in syphilis positive patients declined throughout the period and stabilized at approximately 15 cases per year. Total black bar height represents total maternal syphilis cases for that year. Blue section of bar height represents total number of congenital syphilis transmission events for that year. Percentage next to blue bar height displays congenital syphilis transmission incidence. Conclusion The COVID-19 pandemic has been a significant setback in the recent progress made against maternal and congenital syphilis in South Brazil. It is imperative that post-pandemic health strategies prioritize the reinstatement of interventions targeting these infections. Gestational syphilis infant birth outcomes 2017-2022 Total bar height represents total maternal syphilis cases for that year. Blue section of bar height represents total number of infants born alive to syphilis positive patients. Black section of bar height represents total number of abortions/fetal demises in syphilis positive patients. Yellow section represents missing data, or patients who delivered elsewhere. Disclosures All Authors: No reported disclosures

Correspondence between Euler charges and nodal-line topology in Euler semimetals.

Real multi-bandgap systems have non-abelian topological charges, with Euler semimetals being a prominent example characterized by real triple degeneracies (RTDs) in momentum space. These RTDs serve as "Weyl points" for real topological phases. Despite theoretical interest, experimental observations of RTDs have been lacking, and studies mainly focus on individual RTDs. Here, we experimentally demonstrate physical systems with multiple RTDs in crystals, analyzing the distribution of Euler charges and their global connectivity. Through Euler curvature fields, we reveal that type I RTDs have quantized point Euler charges, while type II RTDs show continuously distributed Euler charges along nodal lines. We discover a correspondence between the Euler number of RTDs and the abelian/non-abelian topological charges of nodal lines, extending the Poincaré-Hopf index theorem to Bloch fiber bundles and ensuring nodal line connectivity. In addition, we propose a "no-go" theorem for RTD systems, mandating the balance of positive and negative Euler charges within the Brillouin zone.

Free Vibration Analysis of Hydraulic Quick Couplings Considering Fluid–Structure Interaction Characteristics

As an important component of the automatic hydraulic quick coupling device (AHQCD) on rescue vehicles, the hydraulic quick couplings (HQCs) are used to rapidly dock hydraulic lines and transport fluid while changing and operating hydraulic working tools. However, during tool operation at rescue sites, pressure pulsations at multiple frequencies in the hydraulic lines can coincide with the natural frequencies of the HQCs, potentially causing resonance that severely affects the stability of fluid conveying and damages the connection of hydraulic lines accidentally. To investigate the natural frequencies of the HQCs with upstream and downstream lines, the characteristics of fluid–structure interaction were considered between the poppets and the fluid in this study, and an equivalent stiffness model of the fluid domain was derived based on the fluid compressibility. A dynamic model, along with 6-DOF equations for the system, was established, and the natural frequencies and mode vectors were determined by free vibration analysis. In addition, the effects of working pressure, air content, and stiffness of the springs on the natural frequency of the HQC system were analyzed. The results show the natural frequency increases with a higher working pressure and lower air content, while the effect of spring stiffness on natural frequencies varies with different modes. Furthermore, the proposed model is validated by experimental pressure signals, showing good agreement, with an average error of 2.7% for the first-order natural frequency. This paper presents a theoretical method for improving the stability of fluid transport when operating various hydraulic tools under complex rescue conditions.

자연에서 관찰되는 육각구조의 이해를 위한 모델링 교육 프로그램이 예비교사들의 인식에 미치는 효과 - 포디프레임을 중심으로

Purpose: This study utilized a modeling education program using the 4Dframe to investigate changes in the perception of hexagonal structures observed in natural phenomena among pre-service teachers, and then examined the this educational practice. Methods: This study was conducted with thirty pre-service teachers using the educational program developed in this research. To examine changes in their understanding of natural phenomena and attitudes towards cooperative learning, pre- and post-tests were administered. Additionally, a Likert scale post-test was utilized to gauge teachers' perceptions of the educational program experience, including the evaluation of the program using the 4D frame. Data analysis was performed using statistical methods such as t-tests, and the specific content was supplemented through qualitative data analysis. Results: Pre-service teachers decreased their tendency to explain the phenomenon of hexagonal structures through simple observation, and instead increased the tendency to explain them through concepts such as force, spatial division, and stability. The understanding of the relationship between a structure that connects the four vertices of a regular tetrahedron with connecting lines and hexagonal structures was also greatly improved. In the attitude test toward cooperative learning, perceptions of problem solving and creative production changed positively. In the Likert scale post-test to determine the perception of the educational program experience, the educational effectiveness was confirmed by showing higher average values in items such as immersion, satisfaction, program, and aesthetics than in previous studies. In addition, pre-service teachers evaluated the educational program by relating that they were able to develop creative thinking and problem-solving skills and increase interest and immersion in learning by producing and modifying various structures through the flexible and elastic 4D frame. Conclusion: By using the 4D frame, students can reproduce educational materials expressed in two dimensions in three dimensions, and it is possible to implement models that explain natural phenomena that are difficult to confirm experimentally.

Effect of infusion line connection and infusion line characteristics on start-up fluid delivery from syringe infusion pumps used for microinfusion.

Connecting an infusion line to a closed stopcock results in pressurization of fluid within the syringe infusion pump assembly leading to flow irregularities when opening the stopcock and activating the pump. It was the purpose of this study to assess the extent of pressurization under different conditions and its impact on start-up fluid delivery. Intraluminal pressures and start-up fluid delivery at 1 mL/h flow rate were assessed with connection of the infusion line 1 min (delayed connection) or immediately after purging (immediate connection) using two different infusion lines made from polyvinylchloride (PVC) or polyethylene (PE). Delayed connection resulted in an increase of intraluminal pressures from zero to 5.1 [4.5 to 5.7] mmHg with the PVC line and from zero to 47.1 [44.8 to 49.3] mmHg with the PE line (mean difference 42.0 [95% CI 39.3-44.7] mmHg; p < .0001). Immediate connection resulted in an increase of intraluminal pressures from zero to 44.3 [41.8-46.8] mmHg with the PVC line and from zero to 61.3 [57.2-65.4] mmHg with the PE line (mean difference 17.0 [95% CI 11.8-22.2] mmHg; p < .0001). The increase in intraluminal pressures was significantly higher with PE lines for both delayed and immediate connection when compared to the PVC lines (mean difference 29.5 [95% CI 19.3-39.7] mmHg; p < .0001). Related fluid volumes delivered at 10 s and 360 s after starting the pump ranged from -252% to 1321% (10 s) of expected infusion volumes and from 59% to 129% (360 s), respectively. Both, timing of infusion line connection after purging and infusion line characteristics considerably affect intraluminal pressures and start-up fluid delivery when connecting a new syringe infusion pump assembly to a closed stopcock. Consecutive alterations in drug administration can have considerable hemodynamic consequences when dealing with catecholamine infusions in critically ill patients.

Research on adaptive circuit structure optimization in electronic design based on Asynchronous Advantage Actor Critic (A3C) algorithm

The circuit structure optimizationed with the traditional method is often difficult to meet the complex and changeable design requirements. In this paper the A3C algorithm has been applied to integrate strategy learning and value learning for the circuit structure optimization. This integration can facilitate continuous interaction with the environment, enabling automatic adjustment of circuit structures to meet the complex design requirements. Gain, bandwidth, latency, and power consumption have been set as the optimization objectives, and the actions of the intelligent agent, which include adding, deleting, modifying connection lines, and adjusting component parameters have been introduced in detail. Once the Actor and Critic networks have been established, multiple agents can operate concurrently, translating optimization objectives into reward signals and providing direction and motivation for agent learning. Then with the proposed method, the circuit structure of one switch audio power amplifier has been designed in a simulation environment. The structure optimization results demonstrated that the gain can reach 78.4 dB at convergence of the A3C algorithm, while the bandwidth can reach 156.2 MHz at convergence, and both the circuit delay and power consumption have been reduced significantly. Obviously, the application of the A3C algorithm can effectively optimize the circuit structures through offering more flexible and efficient solutions.

A multi-task learning based line parameter identification method for medium-voltage distribution network

Accurate line parameters are critical for and dispatch in distribution systems. External operating condition variations affect line parameters, reducing the accuracy of state estimation and power flow calculations. While many methods have been proposed and obtained results rather acceptable, there is room for improvement as they don’t fully consider line connections in known topologies. Furthermore, inaccuracies in measurement devices and data acquisition systems can introduce noise and outliers, impacting the reliability of parameter identification. To address these challenges, we propose a line parameter identification method based on Graph Attention Networks and Multi-gate Mixture-of-Experts. The topological structure of the power grid and the capabilities of modern data acquisition equipment are utilized to capture. We also introduce a multi-task learning framework to enable joint training of parameter identification across different branches, thereby enhancing computational efficiency and accuracy. Experiments show that the GAT-MMoE model outperforms traditional methods, with notable improvements in both accuracy and robustness.

Exploring Trends in Chemical Education: A Bibliometric Analysis (2019-2024)

A Bibliometric analysis is essential to comprehensively evaluate the progress and impact of chemical education research. The purpose is to analyze the visualization of bibliometric mapping on the network between keys, the most frequently discussed topics, and recommendations for research opportunities on the topic of Chemical Education. This research is quantitative descriptive research with a bibliometric approach. The stages carried out include the data collection process, checking and refilling bibliographic attributes, then bibliometric analysis using VOS viewer software. Data collection is done by searching for Scopus indexed journal articles through Publish or Perish (PoP). Data from Publish or Perish (PoP) is filled in and completed in the author keywords section manually using desktop Mendeley software then integrated into the VOS viewer software for mapping. The results of the analysis of keyword mapping in Scopus indexed scientific articles from 2019-2024, it is known that in the last 5 years, in Scopus indexed journals there are 462 different keywords and form 2072 connecting lines and 35 clusters. The keywords with the strongest links based on VOS viewer include: chemistry education (27), first-year undergraduate/general (25), curriculum (22), general public (20), green chemistry (18), systems thinking (18), high school/introductory chemistry (16), upper-division undergraduate (14).

Resilience of Interurban Public Transport and Impact of COVID-19 on Rural Connectivity in Sparsely Populated Regions

The aim of this research consisted of assessing the effects of the COVID-19 pandemic on the interurban public transport system in a rural region with a sparse population density, considering the number of tickets sold and passengers in each locality, as well as the different connecting lines. From a methodological point of view and with the intention of identifying patterns to explain the behaviour of both the routes and passengers, a series of variables were selected, becoming determining factors that sought to offer a solution to the search for a common trend. Additionally, data processing by the means of statistical analysis and the application of Geographic Information Systems (GIS) tools complemented the procedure. The results obtained in the investigation were provided both by municipality and by interurban routes. An interesting finding of this research was the uneven recovery of the municipalities. The localities closest to the attractor nucleus have recovered more quickly to pre-pandemic mobility levels due to their geographical proximity, larger populations, higher incomes per household, and need to access certain public services. In terms of routes, all the lines showed significant decreases in ticket sales, although with variations. Although passenger numbers have shown a gradual recovery, the initial loss was considerable, and pre-pandemic normality has not been completely achieved. This research provides a comprehensive overview of the changes in interurban mobility over a four-year period. The incorporation of critical variables and the segmentation by municipality and route provide a way to identify discernible patterns of mobility. However, the lack of previous research focusing on the impact of the pandemic in rural areas of low population density restricts the possibility of establishing a comparison and to generalise the findings. The authors consider that future research should include other alternative means of transport in these interurban areas and incorporate variables to characterise passengers, such as age, gender, etc.

A geographic-semantic context-aware urban commuting flow prediction model using graph neural network

Urban commuting flow prediction is crucial for urban planning, transportation optimization, and supply chain management. Traditional models and machine learning solutions often fall short in capturing the complex dynamics of urban mobility, overlooking factors like spatial correlation and human mobility patterns. Recent deep learning advancements have shown promise by integrating spatial correlation through incorporating geographical adjacency. However, this approach may not fully capture spatial correlation, particularly the semantic adjacency effect of zones connected via public transportation lines, such as metro networks—a novel dimension overlooked in prior research. The metro station serves as a major transit hub, attracting passengers from various origins and destinations and correlating the flow between the connected zones and other zones within the metro network. Devising an optimized model to encapsulate these spatial correlations is another crucial area of research where scientists are actively seeking the most effective solutions. We propose a novel sequential hybrid approach leveraging graph-based learning, focusing on the underexplored impact of metro networks on commuting flow prediction. Our model integrates two types of adjacency—geographic and semantic—using Graph Convolutional Networks (GCNs) to embed geographic correlations among proximate zones and Graph Attention Networks (GATs) to incorporate semantic adjacency defined by metro line connectivity. Furthermore, our approach innovatively incorporates features directly from online maps, eliminating reliance on third-party resources and enhancing scalability and efficiency. We validate our model using real-world datasets from Montreal, Canada, comprising travel surveys and GPS trajectory types, totaling nearly 900,000 trip records. Through evaluation using established performance metrics such as MAE, RMSE, MAPE, and CPC, we demonstrate significant improvement in predictive accuracy compared to existing state-of-the-art models. Our research has practical implications for urban planning and infrastructure development, aiding policymakers and urban planners in analyzing the impact of new urban infrastructure on commuting flow dynamics and facilitating informed decisions regarding transportation and infrastructure planning.

A graph model for genomic prediction in the context of a linear mixed model framework.

Genomic selection is revolutionizing both plant and animal breeding, with its practical application depending critically on high prediction accuracy. In this study, we aimed to enhance prediction accuracy by exploring the use of graph models within a linear mixed model framework. Our investigation revealed that incorporating the graph constructed with line connections alone resulted in decreased prediction accuracy compared to conventional methods that consider only genotype effects. However, integrating both genotype effects and the graph structure led to slightly improved results over considering genotype effects alone. These findings were validated across 14 datasets commonly used in plant breeding research.

From Catalysis of Evolution to Evolution of Catalysis.

ConspectusThe mystery of the origins of life is one of the most difficult yet intriguing challenges to which humanity has grappled. How did biopolymers emerge in the absence of enzymes (evolved biocatalysts), and how did long-lasting chemical evolution find a path to the highly selective complex biology that we observe today? In this paper, we discuss a chemical framework that explores the very roots of catalysis, demonstrating how standard catalytic activity based on chemical and physical principles can evolve into complex machineries. We provide several examples of how prebiotic catalysis by small molecules can be exploited to facilitate polymerization, which in biology has transformed the nature of catalysis. Thus, catalysis evolved, and evolution was catalyzed, during the transformation of prebiotic chemistry to biochemistry. Traditionally, a catalyst is defined as a substance that (i) speeds up a chemical reaction by lowering activation energy through different chemical mechanisms and (ii) is not consumed during the course of the reaction. However, considering prebiotic chemistry, which involved a highly diverse chemical space (i.e., high number of potential reactants and products) and constantly changing environment that lacked highly sophisticated catalytic machinery, we stress here that a more primitive, broader definition should be considered. Here, we consider a catalyst as any chemical species that lowers activation energy. We further discuss various demonstrations of how simple prebiotic molecules such as hydroxy acids and mercaptoacids promote the formation of peptide bonds via energetically favored exchange reactions. Even though the small molecules are partially regenerated and partially retained within the resulting oligomers, these prebiotic catalysts fulfill their primary role. Catalysis by metal ions and in complex chemical mixtures is also highlighted. We underline how chemical evolution is primarily dictated by kinetics rather than thermodynamics and demonstrate a novel concept to support this notion. Moreover, we propose a new perspective on the role of water in prebiotic catalysis. The role of water as simply a "medium" obscures its importance as an active participant in the chemistry of life, specifically as a very efficient catalyst and as a participant in many chemical transformations. Here we highlight the unusual contribution of water to increasing complexification over the course of chemical evolution. We discuss possible pathways by which prebiotic catalysis promoted chemical selection and complexification. Taken together, this Account draws a connection line between prebiotic catalysis and contemporary biocatalysis and demonstrates that the fundamental elements of chemical catalysis are embedded within today's biocatalysts. This Account illustrates how the evolution of catalysis was intertwined with chemical evolution from the very beginning.

Twins of conic hexagons

Six points on a conic section define 60 different hexagons and therefore 60 Pascal lines. Each Pascal line passes through three of the 45 intersections of connecting lines of the six given points. Instead of searching for collinear triples (Pascal lines) among these 45 points, we identify and classify all six-tuples among the 45 points that lie on a conic section. These six-tuples will be called Pascal twins of the given six points. It turns out that there are also six-tuples that lie on a conic section that have two points in common with the given six points. These six-tuples are called Siamese Pascal twins for evident reasons.

Application of UAV airborne LiDAR technology in highway engineering construction

Abstract The airborne LiDAR technology of UAVs is an efficient and high-precision spatial information acquisition technology. This paper introduces the airborne LiDAR technology of UAV in detail and studies the application of airborne LiDAR technology of UAV in highway construction based on the sixth section of the Leibokahalo-Yongshan connection line of G4216 Yibin Xinshi to Panzhihua Section. Engineering application practice shows that this technology can solve the difficult problem of obtaining basic geographic information data, and verify the rationality of the scheme and the matching degree with the field environment. In addition, compared with traditional survey technology, the technology has obvious advantages in the construction of highways in complex terrain, which helps to improve the quality of survey and design.

ERIRMS Evaluation of the Reliability of IoT-Aided Remote Monitoring Systems of Low-Voltage Overhead Transmission Lines.

Researchers have studied instances of power line technical failures, the significant rise in the energy loss index in the line connecting the distribution transformer and consumer meters, and the inability to control unauthorized line connections. New, innovative, and scientific approaches are required to address these issues while enhancing the reliability and efficiency of electricity supply. This study evaluates the reliability of Internet of Things (IoT)-aided remote monitoring systems specifically designed for a low-voltage overhead transmission line. Many methods of analysis and comparison have been employed to examine the reliability of wireless sensor devices used in real-time remote monitoring. A reliability model was developed to evaluate the reliability of the monitoring system in various situations. Based on the developed models, it was found that the reliability indicators of the proposed monitoring system were 98% in 1 month. In addition, it has been proven that the reliability of the system remains high even when an optional sensor in the network fails. This study investigates various IoT technologies, their integration into monitoring systems, and their effectiveness in enhancing the reliability and efficiency of electrical transmission infrastructure. The analysis includes data from field deployments, case studies, and simulations to assess performance metrics, such as accuracy, latency, and fault detection capabilities.

A new method for the prediction of vibration responses of thin plates coupled with discontinuous connections

Due to the limitation caused by the assumption of ideal continuous line junctions between plates or the high computation cost, the existing methods cannot provide reliable prediction solutions of vibration responses of coupled plates with real connections, such as bolts and corner irons. To this end, a discontinuous energy finite element analysis (dEFEA) method with high accuracy is proposed to predict the vibration responses of discontinuously connected plates, which can revert the real connection. This method developes the coupling loss factors (CLFs) on the steady-state energy flow technique to characterize vibration transmission between plates with different connections. In addition, a discontinuous energy finite element equation of coupled plates is established to obtain the vibration responses of those. The efficacy of the dEFEA method is demonstrated by experiments and the method can improve the prediction accuracy of vibration, which is verified by the comparison between discontinuous and ideal continuous connections. To sum up, vibration transmission of connected structures varies greatly depending on the way of connection and cannot be simplified to a line connection.

Research on Modeling Method for Optimal Allocation of Wellhead Targets in Large Well Clusters

The paper proposes a genetic ant colony algorithm that integrates genetic and ant colony algorithms, enhancing the heuristic function of the latter, to address target point distribution issues in large well clusters. This algorithm utilizes genetic algorithms for initial pheromone distribution and employs the ant colony algorithm to achieve rapid convergence. Introducing genetic operators in each iteration addresses the ant colony system’s drawbacks, including scarcity of initial pheromones, susceptibility to local optima, and slow convergence speed. The model aims to minimize the sum of horizontal displacement and intersections in line connections from wellheads to target points as its dual-objective function. It validates the effectiveness of the genetic ACO algorithm in optimizing target point allocation at wellheads through a case study, highlighting its advantages over traditional methods in reducing displacement, ensuring result stability, and preventing collisions.

Определение диссипативных потерь в гидравлическом приводе газораспределительного механизма двигателя внутреннего сгорания

Controlling the opening and closing times of intake and exhaust valves can improve the efficient parameters of an internal combustion engine and reduce the toxicity of combustion products. The valves are moved by an electronically controlled hydraulic drive. The energy consumption for the operation of a hydraulic valve drive is greater than when using a traditional mechanical drive. The dissipative energy losses in the accumulator one-way hydraulic valve drive are investigated. The working fluid of the hydraulic drive is SAE 5W-30 motor oil. The oil pressure behind the pump is 8 MPa, the diameter of the hydraulic cylinder is 16 mm. The main items of energy consumption are identified, and a methodology for their determination is proposed. The assessment of the efficiency of the hydraulic drive was based on the law of conservation of energy. To determine energy costs, a hydraulic drive model was compiled in the Simulink environment. A law of valve movement similar in shape to trapezoidal was obtained. The maximum speed of valve movement during the opening process is 4 m/s, during the closing process 3.8 m/s. During the period when the valve is held near the maximum lift of 14 mm, free oscillations with an amplitude of about 1 mm are observed. The energy consumption for a single actuation of the valve, which has a progressively moving mass of 0.5 kg, amounted to 25.9 J. Of this, a little more than 70% is spent on filling the hydraulic cylinder with liquid, the rest is spent when emptying it. As a result of throttling the fluid flow in the hydraulic cylinder rod stroke limiter and hydraulic brake, 56% of the energy is lost. Large energy losses are observed between the hydraulic accumulators and the hydraulic cylinder. When the cylinder is filled, 21.1% is lost here, and when it is emptied, 10.4%. Increasing the capacity of the supply and drain lines between hydraulic accumulators and hydraulic cylinders allows you to increase the speed of opening and closing valves. The main ways to increase the energy efficiency of the drive are to shift the hydraulic accumulators to the hydraulic cylinder, increase the diameter of the connecting lines, and increase the throughput of the solenoid valves.

Influence of ground motion parameters on seismic response of a large-longitudinal-slope and small-radius curved girder bridge.

The mechanical performance of curved bridges under the action of an earthquake is complex. To obtain the influence of seismic parameters on the seismic response of curved girder bridges, this paper relies on a large slope small-radius curved steel box girder bridge (LSCGB) and selects seismic wave incidence angle, vertical component of ground motion, and site category as seismic parameters to carry out nonlinear time history analysis. Based on the analysis results of the case bridge, it is shown that the torsional vibration of the first 10 modes of LSCGB is significant, the modes are dispersed, and the contribution of high-order modes of vibration cannot be ignored. The most unfavorable seismic wave incidence angle is in the direction of 45°∼60° counterclockwise Angle from the central connection line of Pier No. 1 and Pier No. 4 of the bridge. The seismic response of the curved bridge components increases with the vertical seismic intensity, and the influence on displacement responses is more significant. The basic vibration period of curved girder bridges built on soft soil sites is extended by approximately 18.23%, and the seismic response of key components increases with the softening of the site soil. Therefore, when analyzing the seismic response of LSCGBs, the influence of vertical component of ground motion and site category should not be ignored.

Directive transportation in smart cities with line connectivity at distinctive points using mode control algorithm

This article examines the operational functionality of intelligent transport systems to enhance smart cities by reducing traffic congestion. Given the increasing populations of smart cities, there is a growing demand for public transit systems to address the issue of traffic congestion. Therefore, the suggested system is developed using a few parametric design models, which combine point-to-point protocol and mode control optimization. The multi-objective parametric design for a smart transportation system is conducted using min–max functions to minimize the waiting time period for end users. Furthermore, customers are given the option to utilize a line following mechanism that offers suitable connectivity, along with independent identification and revitalize functions. The predicted model effectively eliminates the delay produced by transportation devices when positioning units are involved, ensuring that individual messages are delivered without any interruptions. In order to evaluate the results of the proposed system model, four different scenarios were examined. A comparison analysis revealed that the suggested method achieves a suitable directional flow for 96% of smart transport units. Additionally, it reduces delays and waiting periods by 2% and 6% respectively, while increasing energy consumption by 29%.