Transit Route Research Articles

International Migration, Refugees, and Spread of Tuberculosis in Brazil: Analysis of Clusters, Trends, and Associated Factors (2010-2021).

International migration is a global phenomenon with significant implications on the health-disease process due to exposures along transit routes and local/destination epidemiological indicators. We aimed to analyze the transmission and spread of tuberculosis among international migrants and refugees from a spatiotemporal perspective and the associated factors. This was an ecological study of cases of tuberculosis in international migrants in Brazil, between 2010 and 2021. Annual incidence rates were calculated and spatiotemporal scan techniques were used to identify municipalities at risk. Multiple logistic regression was used to identify factors associated with tuberculosis in international migrants. A total of 4037 cases of tuberculosis were reported in Brazil in international migrants. Municipalities at risk for this event were identified using the spatiotemporal scan technique, and a cluster was identified with ITT: +52.01% and ETT: +25.60%. A higher probability of TB infection was identified in municipalities with a TB incidence rate >14.40 cases/100 inhabitants, population >11,042 inhabitants, Gini index >0.49, and illiteracy rate >13.12%. A lower probability was found in municipalities with average per capita household income >BRL 456.43. It is recommended that health authorities implement monitoring and rigorous follow-up in affected areas to ensure proper diagnosis and treatment completion for international migrants, preventing disease spread to other communities.

Examining the potential of pharmacies to expand pre-exposure prophylaxis access along Georgia’s fixed-route public transit: A geospatial analysis

BackgroundDespite accounting for more than half of new Human Immunodeficiency Virus diagnoses in the United States, the South has fewer than 30% of all pre-exposure prophylaxis users. Pre-exposure prophylaxis access geospatial analyses have focused on drive time but analyses along public transit routes have not been evaluated. Given the proximity to pharmacists and pharmacies, involvement in pre-exposure prophylaxis services may increase access and uptake of this preventative health need. ObjectiveThe objectives were to compare the rate of pre-exposure prophylaxis uptake between Georgia counties with and without public transit, to assess the geospatial accessibility of services along public transit, and to evaluate the potential impact of expanding pre-exposure prophylaxis services to community pharmacies. MethodsPre-exposure prophylaxis uptake rates between counties with and without public transit were compared using the Mann–Whitney U test. Geospatial analysis was performed using ArcGIS Pro and Geoda. The Pearson correlation coefficient was used to determine the relationship between pre-exposure prophylaxis uptake rates and population and county characteristics. Spatial analysis was completed to uncover predictors for pre-exposure prophylaxis uptake rates. Increased access to pre-exposure prophylaxis along public transit was calculated by reporting the number of counties that would experience at least a 50% increase in pre-exposure prophylaxis access through community pharmacies. ResultsPre-exposure prophylaxis uptake is significantly higher in Georgia counties with versus without public transit (P < 0.001). Pre-exposure prophylaxis rate is positively correlated with the accessibility of community pharmacies and pre-exposure prophylaxis clinics along fixed-route public transit (R2 = 0.524). Among pre-exposure prophylaxis clinics, 44% are inaccessible by public transit alone. Community pharmacies are significantly more widely distributed and accessible along public transit routes than pre-exposure prophylaxis clinics. ConclusionTransportation remains a barrier to accessing pre-exposure prophylaxis. Georgia community pharmacies along public transit may serve as a solution to pre-exposure prophylaxis care access barriers.

4-(Azolyl)-Benzamidines as a Novel Chemotype for ASIC1a Inhibitors.

Acid-sensing ion channels (ASICs) play a key role in the perception and response to extracellular acidification changes. These proton-gated cation channels are critical for neuronal functions, like learning and memory, fear, mechanosensation and internal adjustments like synaptic plasticity. Moreover, they play a key role in neuronal degeneration, ischemic neuronal injury, seizure termination, pain-sensing, etc. Functional ASICs are homo or heterotrimers formed with (ASIC1-ASIC3) homologous subunits. ASIC1a, a major ASIC isoform in the central nervous system (CNS), possesses an acidic pocket in the extracellular region, which is a key regulator of channel gating. Growing data suggest that ASIC1a channels are a potential therapeutic target for treating a variety of neurological disorders, including stroke, epilepsy and pain. Many studies were aimed at identifying allosteric modulators of ASIC channels. However, the regulation of ASICs remains poorly understood. Using all available crystal structures, which correspond to different functional states of ASIC1, and a molecular dynamics simulation (MD) protocol, we analyzed the process of channel inactivation. Then we applied a molecular docking procedure to predict the protein conformation suitable for the amiloride binding. To confirm the effect of its sole active blocker against the ASIC1 state transition route we studied the complex with another MD simulation run. Further experiments evaluated various compounds in the Enamine library that emerge with a detectable ASIC inhibitory activity. We performed a detailed analysis of the structural basis of ASIC1a inhibition by amiloride, using a combination of in silico approaches to visualize its interaction with the ion pore in the open state. An artificial activation (otherwise, expansion of the central pore) causes a complex modification of the channel structure, namely its transmembrane domain. The output protein conformations were used as a set of docking models, suitable for a high-throughput virtual screening of the Enamine chemical library. The outcome of the virtual screening was confirmed by electrophysiological assays with the best results shown for three hit compounds.

Passenger‐based adaptive transit signal priority for BRT systems with multiple loading areas

AbstractAn adaptive transit signal priority strategy is presented in this paper with the objective of passenger delay minimization at isolated intersections serving conflicting bus rapid transit (BRT) routes. The proposed passenger‐based adaptive signal priority for BRT systems (PASPB) is designed to optimize both green times and phase sequences at the start of each cycle and for a prespecified decision horizon. Since a public transportation (PT) vehicle travel time model capable of estimating the dwell time at stops with multiple loading areas has not yet been developed, PT vehicle dwell time is modeled in this study by analyzing the cases of passenger service by single or double PT vehicles. The problem is formulated as a mixed‐integer nonlinear program (MINLP) and at each execution, the optimization is conducted by genetic algorithm. The model is deployed to a real‐field intersection with conflicting BRT routes under the SUMO microsimulation environment. The results show that PASPB outperforms the SYNCHRO optimal solution and phase insertion strategy regarding PT passenger delay. Besides, the sensitivity analysis proves that at high demand levels of the PT system or general traffic, PASPB presents the best performance in terms of general traffic, PT, and total passenger delay compared to other models.

Energy-saving speed profile planning for a connected and automated electric bus considering motor characteristic

Speed profiles play an important impact on the operational energy consumption of electric buses (EBs). In this study, an eco-driving method is proposed for a connected and automated EB serving on the bus rapid transit (BRT) route. Considering the effect of speed and road load conditions on motor efficiency in estimating energy consumption, a nonlinear programming model is proposed to optimize the energy-saving speed profile. Then the sparrow search algorithm is used for the solution to ensure that the computing time is less than the predetermined time gap. Finally, a real BRT route is taken as an example to carry out comparative and sensitivity analyses. Results indicate that: (i) the average motor efficiency can be improved by 2.11% after taking into account the effect of speed and road load conditions on motor efficiency in estimating energy consumption; (ii) the number of driving stages with uniform speed on each segment is recommended as 2 for balancing the computation time and solution quality; (iii) planning the energy-saving speed profile while regulating the signal timing at intersections improves the operational efficiency and exploit the energy-saving potential of the CAEB; (iv) as bus operation punctuality constraints become tighter, there is an increase in the operational efficiency, but a decline in the energy-saving potential of the CAEB.

Efficient Traffic Control Using Graph Theory: A Comprehensive Overview and Application

The use of graph theory in the area of traffic control is presented in-depth in this article. Urban transport networks have recurring difficulties with congestion, safety, and traffic efficiency. Graph theory offers a methodical and practical solution to these issues. We examine the fundamental ideas of graph theory in further detail, including its applicability to transportation networks and the many kinds of graphs that are employed in traffic control, including their static and dynamic performance. The article shows how graphical algorithms may be used to improve traffic management, including the shortest path method, flow optimisation, and traffic light synchronisation. Furthermore, we show the usefulness of graph theory in smart city traffic light synchronisation, public transit routing, incident management, and ITS integration through case studies and real-world applications. Data collecting, scalability, and the influence of autonomous cars are just a few of the difficulties and future trends in this sector that are highlighted. In conclusion, this study emphasises the crucial part that graph theory plays in raising transportation efficiency and safety. Its incorporation into traffic control systems holds the possibility of creating more flexible and responsive transport networks, enhancing urban sustainability.

An artificial fish swarm optimization algorithm for the urban transit routing problem

The Urban Transit Routing Problem (UTRP) is an NP-hard discrete problem that deals with the design of routes for public transport systems. It is a highly complex, multiply constrained problem, while the evaluation of candidate route sets can prove both challenging and time-consuming, with many potential solutions rejected on the grounds of infeasibility. Due to its difficulty, metaheuristic methods, such us swarm intelligence algorithms, are considered highly suitable for the UTRP. The suitability of these methods heavily relies on the correct adaptation of the chosen method for a discrete-space problem, the initialization procedure, and the solution evaluation method. In this context, this study proposes an artificial fish swarm optimization algorithm for the efficient solution of the UTRP, presenting a novel discrete-space adaptation of the former. The results are subsequently compared to 14 other algorithms, including evolutionary, swarm intelligence and hyper-heuristic implementations, using Mandl’s widely used and accepted benchmark. Comparison of the produced solutions with published results on Mandl’s benchmark network, shows that the developed algorithm yields superior results to the existing techniques, yielding very high shares of direct trip coverage, which is vital for transit systems to attract riders and contribute to urban sustainability. A new indicator for operator cost calculation is also developed and integrated into our analysis, offering insights on the trade-offs between user and operator costs. Differences in generated solutions, influenced by the weighting factor value, can result in variations of up to 13% in direct trip coverage and 1.5 minutes in average travel time.

Influence of magnetic field on dynamic behavior of double-diffusive convection

Double-diffusive convection under an external magnetic field has several industrial applications, and how the magnetic field affects flow and heat and mass transfer is a research focus. This paper studies the dynamical behavior of two-dimensional double-diffusive convection in a uniform magnetic field is investigated using a high-accuracy numerical method. The effects of the magnetic field strength on the flow and on the heat and mass transfer are analyzed, and the process of flow transition in the presence of a magnetic field is studied. The results show that, as the strength of the magnetic field increases, the flow is gradually inhibited, and most of the heat transfer occurs through conduction. For a fixed magnetic field strength, the temperature-dominated flow changes from periodic to chaotic, and finally back to periodic, as the orientation of the magnetic field increases. Two types of periodic flow occur in the transition route, namely, a simple periodic flow with an integer multiple of the fundamental frequency and a complex periodic flow with multiple lower-frequency subharmonic waves. In the presence of a strong magnetic field, the effect of the magnetic field orientation on the flow is significant. At high Rayleigh numbers and a fixed magnetic field strength, the heat transfer efficiency of a vertical magnetic field surpasses that of a horizontal magnetic field by approximately 50% when temperature is dominant, achieving a mass transfer efficiency of about 100%. In cases when concentration is dominant, the heat transfer efficiency of a vertical magnetic field is 20% higher than that of a horizontal magnetic field, and the mass transfer efficiency is approximately 60% higher for the vertical magnetic field compared to the horizontal magnetic field. The flow transitions from chaotic or periodic to steady as the Prandtl number increases. The solution branch bifurcates at certain Prandtl numbers, and hysteresis appears when Prandtl number is equal to 0.023. For low Rayleigh numbers, the heat and mass transfer efficiencies increase monotonically with increasing Prandtl number under a weak magnetic field but remain constant for various Prandtl numbers under a strong magnetic field.

Investigation of ambient BTEX concentrations along a bus rapid transit route in Tabriz: Spatio-temporal variations and health risk assessment

Urgent actions are imperative to assess ambient BTEX concentration in urban areas and increase awareness of the significant health risks linked to exposure to these volatile compounds. This study examines the spatiotemporal variations of BTEX concentration in BRT stations and provides a health risk assessment in Tabriz, located in the northwest of Iran. We collected samples repeatedly from four BRT stations and three areas between stations (N = 86). The mixture BTEX compounds had average concentrations ranging from 6.7 to 52.9 μg/m3, with the highest concentration belonging to o-xylene. Additionally, the average ratios of toluene/benzene, m-xylene/benzene, and o-xylene/benzene were 2.4, 2.3, and 3.0, respectively. Total BTEX concentrations were significantly higher in BRT stations than areas between stations. Furthermore, the concentration of total BTEX doubled in the evening compared to the morning. Although the maximum concentrations of BTEX were recorded in winter, there were no significant seasonal differences. The lifetime cancer risk (LCR) of benzene exposure was 1.07 × 10−7 and 1.52 × 10−5 for passengers and residents located in the vicinity of the BRT lane, respectively. In conclusion, this study suggests that emissions from BRT buses are one of the main contributors to BTEX in Tabriz.

Topographic Monitoring of the Operational Behaviour of the Longest Cantilever Viaduct in Romania

Over time, bridges have been built to fulfil different roles. With the development of industry came the need to build new transit routes linking industrial areas to cities or freight routes. The peak period of industrial development in Romania was in the 1960s, when a large number of bridges were built and put into operation. One of these bridges is the Sidex viaduct, located in Galaţi. The construction has a total length of 1,070 m, with 15 spans of different lengths (47.40 m + 13 * 75.00 m + 47.40 m). The resistance structure is made of 7 prestressed concrete frames linked together by joints located at the level of the cantilevers, the structure being the largest cantilever viaduct in operation in our country. The present article focuses on the presentation of the implementation of a special monitoring program of the viaduct’s in-service performance. For this purpose, special technologies have been used, such as topographic monitoring of the evolution of structural displacements at the most representative points of the structure, an implementation that we develop in detail.

Redesigning large-scale multimodal transit networks with shared autonomous mobility services

This study addresses a large-scale multimodal transit network design problem, with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an origin-to-destination mode. The framework captures spatial demand and modal characteristics, considers intermodal transfers and express services, determines transit infrastructure investment and path flows, and generates transit routes. A system-optimal multimodal transit network is designed with minimum total door-to-door generalized costs of users and operators, satisfying transit origin–destination demand within a pre-set infrastructure budget. Firstly, the geography, demand, and modes in each zone are characterized with continuous approximation. The decisions of network link investment and multimodal path flows in zonal connection optimization are formulated as a minimum-cost multi-commodity network flow (MCNF) problem and solved efficiently with a mixed-integer linear programming (MILP) solver. Subsequently, the route generation problem is solved by expanding the MCNF formulation to minimize intramodal transfers. The model is illustrated through a set of experiments with the Chicago network comprised of 50 zones and seven modes, under three scenarios. The computational results present savings in traveler journey time and operator cost demonstrating the potential benefits of collaboration between multimodal transit systems and SAMS.

Метод оперативной корректуры спутниковой гидрометеорологической информации в районе плавания судна с помощью подспутниковых измерений

The problem of assessing the state of the sea surface by combining satellite and ship measurements is considered. Information about the strength and direction of the wind at the sea surface is important to ensure safe navigation and planning of vessel transit routes. It is of key importance for weather forecasting and excitement. Wind data is traditionally obtained from passing ships and buoys. Ship data covers only limited areas of the World Ocean and is received unevenly, buoy data is highly sparse, which makes it impossible to obtain an adequate picture of the distribution of atmospheric currents. The use of remote sensing satellites has made it possible to increase the density of measurements of wind speed and direction by orders of magnitude, and the relevance of the data obtained. However, satellite measurements can be distorted. In particular, the influence of atmospheric precipitation (rain) can give a two-fold error in measuring wind speed. Strong and weak winds also create problems: in strong winds, the measured data underestimate the true wind speed, in weak winds they overestimate. A method for correcting satellite data on wind speed and direction is proposed. The essence of the method is to use subsatellite ship measurements in conjunction with satellite information. Knowing the weather data measured locally (from the ship), it is possible to calculate regression parameters for correcting satellite data. By applying regressions with calculated parameters to satellite images in the water area, it is possible to obtain more accurate weather data in the area of the vessel's route. The results of calculations based on real satellite and on-board data in the waters of the Sea of Okhotsk are presented. A polynomial of the second degree is taken as a regression function. It is shown that the correction using subsatellite ship measurements more accurately characterizes the wave than the data directly received from the satellite.

Digitalizing Tourism and Interactive Navigation: A Case Study of Pakistan

The emergence of technology-driven tourism is transforming Pakistan's economic landscape, prompting a detailed examination to improve tourist experiences and streamline tour planning. This study introduces a customized application framework and User Interface (UI) design to assist tourists in effortlessly locating accommodations, dining options, attractions, and leisure spots while exploring Pakistan's diverse demographic appeal. Through a structured questionnaire merging Information Technology (IT) and Pakistan's tourism industry, primary data is meticulously analyzed, revealing the pivotal role of digitization and innovation in enhancing ongoing tourism events. Descriptive and correlational analyses highlight the widespread preference among tourists for using mobile applications and social media platforms for vacation planning, with a notable 62.4% of male respondents among 398 participants. Using insights utilizing from the survey, interactive maps provide comprehensive information on tourist locales, historical contexts, imagery, and transit routes, thereby enriching navigation experiences. This research's significance lies in its potential to revolutionize Pakistan's tourism sector through digitization and interactive navigation, enabling the country to leverage its rich cultural heritage and diverse attractions to attract a broader range of visitors. Through the development of user-friendly applications and initiatives, Pakistan can enhance its economic outlook and promote sustainable tourism practices, ensuring long-term viability and inclusivity within the industry.

An experiential learning-based transit route choice model using large-scale smart-card data

An experiential learning-based transit route choice model using large-scale smart-card data

Enhancing Public Transit System Through AI and IoT

The paper investigates the synergy between AI and IoT in revolutionizing public transit systems, emphasizing their role in addressing existing challenges and improving overall efficiency. It explores the application of IoT devices in creating a smart infrastructure that enables real-time data collection, monitoring, and management of transit operations. The research delves into the realm of predictive maintenance, showcasing how AI algorithms, powered by IoT data, can anticipate potential issues in transit vehicles. By analyzing sensor data, transit authorities can proactively address maintenance needs, minimizing downtime, reducing repair costs, and ensuring a more reliable and sustainable public transit service. Route optimization emerges as another crucial aspect of the study, highlighting how AI algorithms leverage historical and real-time data to recommend the most efficient transit routes. Factors such as traffic patterns, weather conditions, and passenger demand are considered to enhance overall system efficiency and reduce travel time for passengers. The paper introduces the concept of dynamic scheduling, illustrating how AI-driven algorithms adapt transit schedules in real-time based on changing passenger needs and external factors. This dynamic approach aims to provide more responsive services, ultimately reducing wait times and improving overall user satisfaction. Passenger information systems are explored as a pivotal component, illustrating how AI and IoT technologies enhance the passenger experience. Real-time communication through mobile apps, digital displays, and other channels ensures that passengers have accurate and timely information about arrival times, delays, and alternative routes, empowering them to make informed decisions. The researchers also delve into fare optimization, examining how AI algorithms analyze data on passenger demographics, travel patterns, and economic factors to create fair and affordable fare structures. This approach aims to encourage ridership, increase revenue, and improve the financial sustainability of public transit systems. The abstract presents a comprehensive overview of how the integration of AI and IoT technologies in public transit systems transforms urban mobility. The findings suggest that leveraging real-time data, predictive analytics, and dynamic solutions can significantly enhance the reliability, accessibility, and sustainability of public transit. As cities continue to explore innovative solutions, the abstract serves as a roadmap for developing smarter, user-friendly, and efficient urban transportation networks, ultimately contributing to improved quality of life for residents.

Separation-induced transition on a T106A blade under low and elevated free stream turbulence

The separation-induced transition on the suction surface of a T106A low pressure turbine blade is a complex phenomenon with implications for aerodynamic performance. In this numerical investigation, we explore an adverse pressure gradient-dominated flow subjected to varying levels of free stream excitation, as the underlying separation-induced transition is a critical factor in assessing blade profile loss. By comprehensively analyzing the effects of free stream turbulence (FST) on the transition process, we delve into the various mechanisms which govern the instabilities underlying bypass transition by studying the instantaneous enstrophy field. This involves solving the two-dimensional (2D) compressible Navier–Stokes equation through a series of numerical simulations, comparing a baseline flow to cases where FST with varying turbulent intensity (Tu=4% and 7%) is imposed at the inflow. Consistent with previous studies, the introduction of FST is observed to delay flow separation and trigger early transition. We explore the different stages of bypass transition, from the initial growth of disturbances (described by linear stability theory) to the emergence of unsteady separation bubbles that merge into turbulent spots (due to nonlinear interactions), by examining the vorticity dynamics. Utilizing the compressible enstrophy transport equation for the flow in a T106A blade passage, we highlight the various routes of bypass transition resulting from different levels of FST, emphasizing the relative contributions from baroclinicity, compressibility, and viscous terms.

ENERGY SECURITY IN THE GLOBAL CONTEXT: A COMPREHENSIVE REVIEW OF GEOPOLITICAL DYNAMICS AND POLICIES

Energy security is a critical dimension in the contemporary global landscape, where the availability, affordability, and reliability of energy resources play a pivotal role in shaping geopolitical dynamics and national policies. This paper presents a comprehensive review of the intricate interplay between energy security, geopolitics, and policies on the global stage. The quest for energy security is inherently linked to the geopolitical landscape, as nations strategically position themselves to secure access to vital energy resources. The competition for control over key energy reserves, transit routes, and distribution networks often shapes international relations, leading to geopolitical tensions and conflicts. The study delves into the geopolitical dynamics surrounding major energy-producing regions, such as the Middle East, Central Asia, and the Arctic, analyzing the impact of these dynamics on global energy security. Policies and strategies employed by nations to enhance their energy security are critical aspects of this review. The analysis encompasses a range of policy dimensions, including diversification of energy sources, investments in renewable energy technologies, and the development of resilient energy infrastructure. Moreover, the study explores the role of international collaborations, agreements, and institutions in fostering energy security and addressing common challenges. The transition towards a sustainable and secure energy future is a key focus, considering the increasing importance of climate change mitigation and the imperative to reduce dependence on finite fossil fuel resources. The paper emphasizes the significance of policy frameworks that balance economic, environmental, and security considerations to achieve a holistic approach to energy security. This comprehensive review provides a nuanced understanding of energy security within the global context, offering insights into the complex interconnections between geopolitics and policies. It underscores the need for a collaborative and multifaceted approach to address the challenges and opportunities inherent in securing the world's energy future.&#x0D; Keywords: Energy Security, Policies, Geopolitical Dynamics, Energy, Review.

Enhancing bilateral ties: the escalation of Azerbaijan's economic investments in Turkey

This research explores the strengthening economic partnership between Azerbaijan and Turkey, particularly focusing on Azerbaijan's increasing investments in the Turkish economy since the signing of the "Trade and Economic Cooperation" agreement in 1992. It analyzes significant projects like the Baku-Tbilisi-Ceyhan and Baku-Tbilisi-Erzurum pipelines, which transcend mere infrastructural achievements to become strategic assets in the geopolitical landscape. These pipelines facilitate the safe transportation of hydrocarbons from the Caspian basin, bypassing traditional transit routes, and thereby reducing political and economic vulnerabilities. Additionally, Azerbaijan’s substantial investments in Turkey's PETKIM petrochemical complex and the STAR Oil Refinery are examined as strategic steps enhancing the economic depth of both countries. These investments represent more than capital inflows; they symbolize a deep-rooted strategic alliance that promotes energy independence and industrial diversification. The STAR Oil Refinery plays a pivotal role in Turkey's energy supply chain, significantly contributing to its self-sufficiency in processed oil products. This bilateral economic engagement exemplifies how states with complementary resources and strategic visions can create sustainable economic corridors, highlighting the role of economic diplomacy in shaping international relations in an increasingly interconnected global economy. The evolving partnership not only exemplifies successful bilateral cooperation but also indicates strategic foresight in using economic synergies for regional stability and prosperity.

2022 Russian-Ukrainian War and the Future of EU Energy and Transport Security: Analyzing the Implications of Diversifification the Transport and Energy Transit Routes – the Case of the Black Sea/Caspian Region

Given recent events, such as the full invasion of Ukraine’s sovereign territories by the Russian armyin 2022, this article critically analyzes how the use of the Caucasus-Caspian region could serve Brusselsas an alternative means of diversifying energy sources to ensure its energy security. The study iscomprehensive and covers various forms of energy projects. Particular attention is paid to exploringthe various phases regarding Shah Deniz and potential expansion plans. In addition, it carefully examinesall other important factors associated with the production, transportation, and explorationof energy resources in the Caspian reserves.In addition, a key task is to classify and compare the EU’s geopolitical priorities before and after the2022 war, present an analysis of the complex paths of transformation of the EU’s energy supply,and clarify its new policies regarding the relations between the main regional players: the RussianFederation, the EU, Turkey, Azerbaijan, and Georgia.It has been established that the Black Sea-Caspian steppe contains valuable energy reserves. Dueto the critical geopolitical, geostrategic, and geoeconomic importance of the region, the EU has aninterest in the region. The study provides a comparative overview of different aspects of EU energydiversification policies. It examines how these policies have influenced the approach of foreignstates to the Caucasus-Caspian region, taking into account recent events. Moreover, it considersnational goals and takes into account the important interests of leading powers.Keywords: energy security, diversification of fossil fuels, Caucasus-Caspian region, Black Sea-Caspian steppe, EU policy on energy diversification, energy projects.

Urban Mobility Analysis Using Geospatial Analysis

This project proposes a method to analyze the traffic and urban mobility of a locality with advanced visualization and understanding mechanisms. urban areas worldwide face escalating challenges in managing transportation systems efficiently. This research delves into the realm of urban mobility analysis, leveraging geospatial data to extract insightful patterns and trends. The project aims to contribute a comprehensive understanding of the dynamics governing urban transportation, enabling informed decision- making for city planning and infrastructure development. The methodology encompasses the collection of extensive geospatial datasets, including traffic flow, public transportation routes, and demographic information. Utilizing advanced geospatial analysis techniques, such as Geographic Information Systems(GIS) and spatial analytics, the study explores spatial-temporal patterns of traffic congestion, public transit usage, and pedestrian movement. Machine learning algorithms are employed to predict future mobility trends and assess the impact of potential interventions. The findings of this research offers valuable insights for urban planners, policymakers, and transportation authorities. By identifying key bottlenecks, optimizing transit routes, and understanding the interplay between land use and growing populations and foster sustainable urban development. This project not only contributes to academic understanding of urban mobility but also provides actionable recommendations for creating smarter and resilient cities. The integration of geospatial analysis techniques in urban planning emerges as a powerful tool to address the complexities of modern urban transportation systems. Keywords: informed decision-making, geospatial data, Geographic Information System(GIS), spatial analysis, sustainable urbandevelopment.