Search Results (174)

In the digital era, rapid urban growth and the demand for sustainable mobility are placing increasing pressure on transport systems, where congestion, energy consumption, and schedule variability complicate intermodal journey planning. This work proposes an AI-enhanced transfer-graph framework that models each transport mode as an independent subnetwork connected through explicit transfer arcs. This modular structure captures modal interactions while reducing graph complexity, enabling algorithms to operate more efficiently in time-dependent contexts. A Deep Q-Network (DQN) agent is further introduced as an exploratory alternative to exact and meta-heuristic methods for learning adaptive routing strategies. Exact (Dijkstra) and meta-heuristic (ACO, DFS, GA) algorithms were evaluated on synthetic networks reflecting Casablanca’s intermodal structure, achieving coherent routing with favorable computation and memory performance. The results demonstrate the potential of combining transfer-graph decomposition with learning-based components to support scalable intermodal routing. Full article

In the context of the ongoing digitalization of organizations, the question of how organizations facing complex AI can implement adoption decisions in order to maximize the effectiveness of their organizational AI adoption has become a topic of common concern in both academic and industrial circles. Given the significant impact of AI on enterprise productivity and the active embrace of AI by many enterprises, this paper, based on digital enterprises that have initially adopted AI, proposes the organizational AI adoption maturity model for further assessment of the process variable of organizational AI continuous adoption level. This model effectively classifies, conceptualizes and standardizes AI adoption levels, and develops a set of theory and application guidelines, which can integrate existing research into the AI adoption process. The objective of this study is to develop an application guide that will unify the existing research findings, identify the stage of a particular organization, diagnose and assess the level of AI continuous adoption in the organization, and plan for future development. Furthermore, the guide will continue to broaden the application of the conceptual framework to explain the dynamics and relativity of the model, thus laying the foundation for the future development of the organizational AI adoption maturity theory. This journey from “Stupid” to “Smart” reflects the evolving sustainability of AI integration within organizations. By mapping this progression, the study provides a clear pathway for enterprises to enhance their AI adoption strategies systematically. Ultimately, the sustainability map not only guides organizations in diagnosing their current AI maturity but also empowers them to plan strategically for intelligent and sustainable growth. Full article

Urban Air Mobility (UAM) promises to reduce ground traffic and journey times by using electric vertical take-off and landing (eVTOL) aircraft for short, low-altitude flights, especially in urban environments. However, low-flying aircraft are at particularly high risk of collisions with wildlife, such as birds. This study builds on previous research into UAM collision avoidance systems (UAM-CAS) by implementing one such system in the BlueSky open-source air traffic simulator and evaluating its efficacy in reducing bird strikes. Several modifications were made to the original UAM-CAS framework to improve performance. Realistic UAM flight plans were developed and combined with real-world bird movement datasets representing typical birds in sustained flight from all seasons, recorded by an avian radar at Leeuwarden Air Base. Fast-time simulations were conducted in the BlueSky Open Air Traffic Simulator using the UAM flight plan, the bird datasets, and the UAM-CAS algorithm. Results demonstrated that, under modelling assumptions, the UAM-CAS reduced bird strikes by 62%, with an average delay per flight of 15 s, whereas 27% of the remaining strikes occurred with birds outside the system’s design scope. A small number of flights faced substantially longer delays, indicating some operational impacts. Based on the findings, specific avenues for future research to improve UAM-CAS performance are suggested. Full article

Artificial intelligence (AI) is rapidly transforming cardiovascular medicine, with profound implications for congenital heart disease (CHD). Tetralogy of Fallot (ToF), the most common cyanotic disease, requires lifelong surveillance and complex management because of late complications such as pulmonary regurgitation, arrhythmias, and right ventricular dysfunction. This review synthesizes current evidence on AI applications across the continuum of ToF care—from prenatal diagnosis to adulthood follow-up. We examine advances in imaging, perioperative planning, intraoperative monitoring, intensive care, and long-term surveillance, including wearable and implantable technologies. Machine learning (ML), deep learning (DL), and natural language processing (NLP) are revolutionizing diagnostic accuracy, risk stratification, surgical decision-making, and personalized long-term care. The future lies in the integration of multimodal data, including imaging, electronic health records (EHRs), genomic information, and continuous monitoring, to support precision medicine. Challenges remain regarding dataset limitations, interpretability, regulatory standards, and ethical concerns. Nevertheless, ongoing innovation and collaboration between clinicians, engineers, and regulators promise a new era in congenital cardiology. By embedding AI throughout the patient journey, healthcare systems may improve outcomes and quality of life for individuals with ToF. Full article

Short-form video platforms such as TikTok, Instagram Reels, and YouTube Shorts have become influential social commerce and interactive marketing tools, shaping consumer attitudes and behaviors beyond the digital environment. This study examines how short-form video content affects consumers’ intention to visit destination retail stores by integrating the Theory of Planned Behavior (TPB) with the constructs of perceived usefulness, curiosity, and envy. Data from 423 Gen Z and Millennial consumers were collected through an online survey and analyzed using structural equation modeling. The findings indicate that perceived usefulness, curiosity, and envy significantly influence attitudes toward short-form video content, which subsequently drive intentions to visit destination retailers. Social influence also emerged as a stronger predictor of behavioral intention than practical barriers such as cost or accessibility, underscoring the importance of peer validation in motivating digital-to-physical consumer behavior. This study advances electronic commerce research by extending TPB to short-form video marketing and identifying key emotional and cognitive triggers that facilitate consumer engagement. Practically, the results highlight strategies for retailers to develop video campaigns that spark curiosity, evoke aspirational emotions, and leverage social endorsement. More broadly, the study demonstrates how short-form video platforms operate as interactive ecosystems that merge emotional engagement, social validation, and technological affordances to shape hybrid consumer journeys from digital exposure to in-store action. Full article

Cities in developing nations such as India have undergone unregulated growth and uneven urbanization, fostering economic expansion while exacerbating spatial, social, and economic inequalities. This urbanization has significantly degraded water bodies and green spaces, affecting human health and well-being. Blue–green infrastructure (BGI) has emerged as a promising solution for addressing environmental challenges, stormwater management, social well-being, and urban heat mitigation. However, developing countries such as India lack adequate knowledge of their design, planning, and implementation under specific local conditions. This study employs a semi-systematic literature review to identify essential components for BGI implementation in developing nations, with contextual references to India. Among the 797 studies reviewed in total, with 42 studies selected for the final review, only 26% focused on developing countries such as China, with none specifically addressing India. Furthermore, this review discusses global city and country cases across the Global South and Global North to obtain pertinent information from empirical applications worldwide. In total, 32 country cases are analyzed globally, comprising an even larger number of city cases. This review has derived eight thematic areas critical for BGI implementation: spatial configuration, plans and policies, best practices, BGI features and components, stakeholder perceptions, barriers to adoption, local government capacity, and scientific research. Each thematic area is analyzed in relation to stormwater management functions. This study emphasizes that these areas can guide urban planners and researchers in designing effective BGI strategies tailored to specific contexts. By bridging the knowledge gap in India’s development journey, this research underscores the importance of integrating BGI into urban planning to achieve the Sustainable Development Goals and address the adverse effects of rapid urbanization. Full article

Navigating and planning optimal paths for resource delivery algorithms poses significant physical and technical challenges in urban areas, primarily due to the limitations of existing infrastructure. As smart cities continue to develop, the importance of these algorithms becomes increasingly evident. The saturation of current urban landscapes exacerbates the complexity of navigating essential resources. Navigating densely connected networks can be intricate and often requires substantial computational resources or additional algorithms, as it can easily transform into an NP problem. Unfortunately, there is a lack of explicit algorithms designed for navigating these networks, resulting in a dependence on heuristic approaches and previous network systems. This reliance can create computational challenges, as navigation in this context typically involves a combinatorial search space. Current advances in Morphological Mathematics (MM) help to model everyday tasks as processes in discrete spaces, which take advantage of the properties offered by the morphological operators. Morphological Shortest-Path-Planning (MSPP) is a recent solution that effectively calculates the optimal trajectory within complex graphs. By utilizing morphological operators, this approach takes into account discrete properties and maps the process as a complete implementation algorithm using integer logic. In larger cities, determining the optimal delivery route and time from a resource center is a common task. This process is influenced by factors such as average speed, travel time, and distance, which generate a complex graph representation of the town, complicating its analysis. This paper presents a strategy for computing and analyzing delivery times by determining the accessibility of reliable paths from a delivery center to potential destinations in dense urban areas. The strategy presented and the use of the MSPP approach are suitable for calculating the time spent delivering and the distance traveled in working journeys. The MSPP approach is found to be nearly $60\%$ more efficient than the reference approach for computing the optimal path in the case study presented. Full article

Combining public transportation (PT) with Bike-Sharing Systems (BSSs) offers a pathway toward the sustainable development of urban mobility. These systems can reduce fuel consumption, air pollution, and street congestion, especially during peak hours. Moreover, PT and BSS are frequently used by individuals without access to private vehicles, including low-income groups and students. Whereas increasing PT network infrastructure is constrained by issues such as high capital costs and limited street space (which inhibits mass transit options like BRT or trams), BSS can be used as an adaptable and affordable solution to fill these gaps. In particular, BSS can facilitate the “first-mile–last-mile” legs of PT journeys. However, many transit agencies still rely on traditional joint service planning and overlook BSS as a critical mode in integrated travel chains. This paper proposes that PT and BSS be considered as a unified network and introduces a framework to assess whether access to this integrated system is equitably distributed across urban areas. The framework estimates demand for travel using public mobility options and supply at the level of Traffic Analysis Zones (TAZs), treating PT and BSS as complementary modes. Spatial accessibility analysis is employed to examine connectivity using factors that affect access to both PT and BSS. The proposed approach is tested by taking Tehran as the focus of the case analysis. The results identify the most accessible areas and highlight those that require improved PT-BSS integration. These findings provide policy-relevant suggestions to promote equity and efficiency in urban transport planning. The outcomes reveal that central TAZs in Tehran receive the highest level of PT-BSS integration, while the western and southern TAZs are in urgent need of adjustment to ensure better distribution of integrated public transportation and bike-sharing services. Full article

The typical ranges available for electric vehicles (EVs) may be considered by users to be inadequate when compared to long, real-life trips, and charging operations may need to be planned along journeys. To evaluate the compatibility between vehicle features and charging options for realistic journeys performed by car, a simulation approach is proposed here, using travel data collected from real vehicles to obtain trip chains for multiple consecutive days. Car travel activities, including stops with the option of charging, were simulated by applying an agent-based approach. Charging operations can be integrated into trip chains for user activities, assuming that they remain unchanged in the event that vehicles switch to electric. The energy consumption of the analyzed trips, disaggregated by vehicle type, was estimated using the average travel speed, which is useful for capturing the main route features (ranging from urban to motorways). Data were recorded for approximately 25,000 vehicles in the Turin Metropolitan Area for six consecutive days. Market segmentation of the vehicles was introduced to take into consideration different energy consumption rates and charging times, given that the electric power, battery size, and consumption rate can be related to the vehicle category. Charging activities carried out using public infrastructure during idle time between consecutive trips, as well as those carried out at home or work, were identified in order to model different needs. Full article

Background: Gastrointestinal (GI) cancer patients face a four-fold higher suicide risk than the general US population. This study explores psychosocial aspects of GI cancer patient experiences, assessing suicidal ideation and behavior, mental distress during treatment phases, and psychosocial factors on mental health. Methods: A two-phase mixed-methods approach involved a web-based survey and follow-up interviews. Quantitative data analysis validated mental health and suicidal ideation constructs, and correlation analyses were performed. The patient journey was charted from diagnosis to treatment. Results: Two hundred and two individuals participated, with 76 from the rural Appalachian region and 78 undergoing treatments. Quantitative analysis showed a higher prevalence of passive suicidal ideation than active planning. The post-treatment recovery period was the most emotionally challenging. Qualitative data emphasized emotional support and vulnerability to isolation. Care quality concerns included individualized treatment plans and better communication. Patients also needed clear, comprehensive information about treatment and side effects. The in-depth interview with four GI cancer patients revealed a healthcare system prioritizing expedient treatment over comprehensive care, lacking formal psychological support. AI emerged as a promising avenue for enhancing patient understanding and treatment options. Conclusions: Our research advocates for a patient-centric model of care, enhanced by technology and empathetic communication. Full article

Introduction: The escalating scarcity of skilled healthcare professionals is particularly pronounced within surgical specialties, where the prospect of attracting prospective medical practitioners poses formidable challenges. Throughout their academic journey, students exhibit diminishing enthusiasm and motivation to pursue careers in surgery, including trauma surgery. It is postulated that the caliber of teaching plays a pivotal role in influencing students’ subsequent specialization choices. Methods: This prospective observational study was conducted among a cohort of third-year medical students at the German University Medicine Greifswald. The methodology encompassed the utilization of a self-administered questionnaire to procure data. Results: The study encompassed 177 participants, of whom 34.7% expressed an inclination toward a career in surgery (22.7% in trauma surgery). Participants who reported a favorable impact from the examination course displayed a significantly heightened interest in clinical clerkships within trauma surgery (p < 0.001), and even expressed a contemplation of specializing in orthopedics and trauma surgery (p = 0.001). Logistic regression analysis highlighted that the convergence of practical training and positive role modeling emerged as the most influential factors augmenting the allure of trauma surgery. Conclusions: Evidently, students who gleaned substantial benefits from high-quality practical instruction in trauma surgery exhibited a significantly heightened likelihood of pursuing this domain in their future endeavors. Surgical academic institutions stand to leverage this insight in their strategic planning for attracting and retaining potential residents. Cultivating a positive affinity for trauma surgery should be instilled early in the curriculum, subsequently sustained through ongoing immersive engagement that encompasses professional as well as interpersonal dimensions. Full article

Current tourism route recommendation systems often overemphasize popular destinations, thereby overlooking geographical accessibility between attractions and the experiential coherence of the journey. Leveraging multidimensional attribute perceptions derived from tourist reviews, this study proposes a Spatial–Semantic Integrated Model for Tourist Attraction Representation (SSIM-TAR), which holistically encodes the composite attributes and multifaceted evaluations of attractions. Integrating these multidimensional features with inter-attraction relationships, three relational metrics are defined and fused: spatial proximity, resonance correlation, and thematic-sentiment similarity, forming a Tourist Attraction Multidimensional Association Network (MAN-SRT). This network enables precise characterization of complex inter-attraction dependencies. Building upon MAN-SRT, the Tourism Sentiment Chain (TSC) model is proposed that incorporates geographical accessibility, associative resonance, and thematic-sentiment synergy to optimize the selection and sequential arrangement of attractions in personalized route planning. Results demonstrate that SSIM-TAR effectively captures the integrated attributes and experiential quality of tourist attractions, while MAN-SRT reveals distinct multidimensional association patterns. Compared with popular platforms such as “Qunar” and “Mafengwo”, the TSC approach yields routes with enhanced spatial efficiency and thematic-sentiment coherence. This study advances tourism route modeling by jointly analyzing multidimensional experiential quality through spatial–semantic feature fusion and by achieving an integrated optimization of geographical accessibility and experiential coherence in route design. Full article

This study aims to present an integrated approach to customer experience, which was developed considering the identification and application of essential factors from the product life cycle. The study was conducted in the automotive industry and may be transferable to other products with high complexity and medium–long in-service use. The main goal is to identify the determining factors and perform a regression analysis of the effect of attribute-level performance on overall customer satisfaction through the customer’s entire journey during the product development phase. This study is based on a generic example that is meant to capture trends influencing customer satisfaction in the launch of a new product vehicle, focusing on factors that influence each stage of the process, from planning–exploration, design and development, and manufacturing and validation to performance measurement and after-sales assistance. Based on multiple surveys that were used as the main instruments for measuring the level of customer satisfaction at defined touchpoints, the product life cycle was followed through several stages: prospecting survey, upstream survey, launch preparation survey, post-launch investigation, life cycle survey, and after-sales support. Three meta-factors were identified—design, price, and durability—for which the ordinal regression demonstrated that they are significant predictors of customer experience in general. The approach may be transferable to other sectors by identifying relevant attributes and adapting tools for measuring customer satisfaction, customer experience, and consumer concerns, which act as key vectors influencing the product life cycle and, by extension, business sustainability. Full article

Background: Globally, pneumonia claims the lives of about 700,000 children under the age of 5 every year. Pneumococcal conjugate vaccine (PCV) was introduced in India phase-wise, beginning in high-burden states, and the rollout was completed nationwide by 2021—representing a major initiative by the Ministry of Health and Family Welfare (MoHFW). Despite the challenges posed by the COVID-19 pandemic, the campaign succeeded in maintaining progress and achieving nationwide coverage. This narrative review highlights the significant decisions, processes, and coordinated efforts of the various stakeholders involved that led to this successful PCV rollout. Methodology: A comprehensive desk review of both published and unpublished literature relevant to pneumonia burden and the efficacy and effectiveness of PCVs, along with documentation of PCV introduction and the scale-up was carried out. Results: The documentation of the PCV journey has been broken down into four sections: pre-introduction, PCV Phase-I introduction, pan-India rapid expansion, and the period post-introduction. Since the nationwide rollout in 2021, PCV coverage in India has steadily increased, reflecting successful immunization efforts. WUENIC, which is an annual WHO, and UNICEF estimates of national immunization coverage also show a positive trend in vaccination coverage (PCV booster coverage = 25% (2021), rising to 83% (2023), aligning with the goals of the WHO and UNICEF’s Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea (GAPPD). Conclusions: The phased rollout was an ambitious effort by the MoHFW, which was particularly challenging given the overlap with the COVID-19 pandemic. Despite these hurdles, the MoHFW, along with strong collaboration from development partners and stakeholders, successfully navigated the complex rollout. Future studies on the role of PCVs in reducing antibiotic resistance and the economic benefits of PCV introduction could help policymakers sustain funding and prioritize vaccine procurement decisions. Full article

In the years since the emergence of the railway, the main objective has been focused on trains arriving and stopping at stations, with stations being considered a secondary or even residual objective for bringing people or goods on or off. The arrival of high-speed trains at stations has allowed for the creation of integrated, environmentally friendly stations which have become mobility hubs, connecting different modes of transportation and cities, as well as being clusters of economic activities that stimulate the inclusive growth of the areas where they are located. These transport infrastructures condition the social and communication relationships of many spaces. The consequences that have been demonstrated in the stations analyzed have been strengthened intermodally with other means of transport, giving value to commercial developments and old stations, as well as the environments where they are located, a development aimed beyond the railway users themselves. From an operational point of view, the main consequence of this transformation is the necessity to absorb the increase in passenger demand. The integration of the railway within an urban space is shaped through the construction of new stations within the already existing urban framework or, in some cases, by relocating them to the periphery of the city. New stations have undergone changes compared to those built a century ago. Their conception has evolved, adapting to the architecture of their time, but the most radical change they have experienced is related to the new uses that have been developed within them and how these spaces are utilized. The introduction of high-speed trains has initiated a series of reflections on new station concepts. The new operation is characterized by journey times, frequency, and comfort. This comfort is not only perceived on board a train but also in stations during a passenger’s stay, which has a direct impact on the design of stations. Provisional railway stations are valuable tools in situations where flexibility, speed, and reduced costs are required. Although they are not designed to be permanent, their ability to adapt to specific needs makes them a strategic option for temporary projects, though not in the case studied of the Valencia station. The planning of projects makes it necessary to implement proxemic standards in the design of spaces that contribute to the diversification of economic activity around and in a station itself, such as commercial, residential, or cultural areas. Full article