Search Results (6,707)

This article investigates the intricate interplay between ressentiment—as social emotion—social love, and solidarity in democratic societies, focusing on the urban environment as the primary stage where these processes materialize. Far from being a marginal emotion, ressentiment is deeply intertwined with democratic life, arising from the gap between proclaimed values and lived conditions. It represents an affective reaction to the perceived betrayal of the promise of equality inscribed in democratic ideals. The discussion explores how perceptions of injustice can fracture trust and intensify divisions, but also how they, under certain conditions, can be redirected toward political engagement and common action. The city, characterized by density, diversity, and the continuous negotiation of difference, can serve as a privileged arena for this transformation. Urban space does not merely reflect inequalities; it actively shapes social processes and provides the infrastructure through which collective sentiments are articulated. In this context, “social love” is conceptualized not as a sentimental aspiration, but as a relational force capable of redirecting the moral indignation of ressentiment, far from strategies of grievance politics toward constructive forms of social and political belonging. Cities can function as laboratories of solidarity where grievances are reframed into collective projects that strengthen social cohesion. Mitigating the destructive potential of ressentiment requires addressing its structural roots through inclusive urban policies and dialogical spaces. An approach grounded in social love can counter fragmentation, mobilizing emotions in the service of substantive equality. In this perspective, the city can become a space and a laboratory for change, where resentment can be channeled as a generative force capable of sustaining widespread forms of social love and a sense of the common good. Full article

Progressive collapse has become a critical concern in resilient structural design due to accidental impacts, abnormal loading scenarios, and sudden localized damage events that may lead to the sudden loss of structural elements under extreme or unforeseen actions. In this context, UFC 4-023-03 provides design approaches for improving collapse resistance, including the Alternate Path Method, Enhanced Local Resistance Method, and Tie Forces Method. This study focuses on the Tie Forces Method, which is based on mechanical interconnection but remains relatively underexamined in the literature. A six-story reinforced concrete office building was evaluated to determine the required tie reinforcement area for progressive collapse resistance according to UFC 4-023-03. Ten national building codes were considered, with office live loads ranging from approximately 2.0 to 4.8 kN/m². In this study, the selected national codes are not compared in terms of their complete progressive collapse provisions. Instead, UFC 4-023-03 is adopted as the main Tie Forces Method calculation framework, while national-code-based live load values and reinforcement properties are used as input parameters. Peripheral, longitudinal, transverse, and vertical ties were comparatively assessed. The largest percentage reduction was observed for the peripheral transverse tie reinforcement at the first floor, where the Eurocode-based input set produced a required tie reinforcement area approximately 21.7% lower than that obtained from the Russian input set. In contrast, Canadian provisions govern the highest demand at the ground floor, while South Korean provisions produce the highest demand at upper floors. Overall, the findings highlight the influence of national live load provisions and reinforcement properties on tie force requirements. Full article

Spatial studies play a significant role in navigating the actions, experiences, and interactions happening in a specific place and context. The intersection of spatiality and theology will expand the scope of relating the biblical elements to contemporary relevant issues. Genesis 6–9, often termed the flood narrative, is considered a major biblical evidence in terms of environmental vulnerability and divine faith. By incorporating geocriticism alongside the other spatial theories of Tuan, Bachelard, and Tally, this study offers a critical, exegetical textual analysis of Genesis 6–9 to understand the dynamics of mobility, spatial agency, and re-habitation as shown in the narrative. The paper’s primary argument is that the ark functions as an affective space and an architectural structure of protection, belonging, and preservation during and after the flood. Secondly, it focuses on how the flood narrative negotiates between the real, imagined and textual spaces of spatial re-creation and how it resonates with contemporary environmental concerns by interpreting it as an instance of environmentally induced displacement while retaining its theological significance. Full article

Information disorders condition electoral processes, becoming a major institutional concern. In response, the European Union and various fact-checking organisations co-organised the Elections24Check project to curb disinformation in the 2024 European elections. This research analyses the activities, strategies, and editorial behaviour of the five Spanish fact-checking agencies that are integrated into the initiative. Through a content analysis applied to 3256 publications, the findings demonstrate the maturity of the Spanish ecosystem, which led the project by contributing 32.8% of the total content. Strategically, reactive action predominated, except for Newtral, which prioritised prebunking (62.6%). Political scrutiny was minor (6.6%), focusing on major coalitions and far-right leaders. Thematically, highlights included war conflicts, migration, and national/regional frameworks utilised for emotional polarisation, displacing the focus from the strictly European debate. In conclusion, Spain consolidates itself as a cornerstone of European fact-checking. However, the results reveal inefficiencies in the project’s extended timeframe, suggesting more constrained and effective frameworks for election campaigns. Furthermore, the persistence of narratives anchored to local agendas evidences a strategic fragmentation that hinders the construction of a fully pan-European public space. Full article

This paper examines how historic wooden-built environments and open-air museums can function as pedagogical settings for craft education. Drawing on teaching experiences from higher education in Norway, it analyses how students develop knowledge through guided engagement with tools, materials, and traditional practices in situated learning environments. Two teaching cases, spoon carving in a museum workshop and the investigation of a historic log-built structure, are presented as pedagogical designs. The analysis focuses on how learning is structured and develops through relational and responsive engagement with materials, tools, and professional guidance, rather than solely on learning outcomes. The cases demonstrate how teaching can be organised to support the development of embodied and practice-based knowledge. The paper develops a theoretical framework grounded in 4E cognition (embodied, embedded, extended, and enactive cognition) and Tim Ingold’s concepts of meshwork and wayfaring. These perspectives are applied as analytical tools to examine how learning emerges through action, feedback, and iterative engagement within specific learning environments. Historic workshops, tools, and buildings are approached as pedagogical resources that shape the conditions for learning. While such environments carry historical and material depth, the focus here is on how they structure students’ engagement and influence learning processes in practice. The paper argues that craft pedagogy involves the design of learning situations where material engagement, reflection, and professional guidance are integrated. It proposes an understanding of learning as a situated and relational practice, in which knowledge develops through participation in practice rather than through transmission alone. Full article

Money laundering remains a critical challenge for financial systems because of the complex, hidden, and interlinked nature of illicit financial transaction networks. Understanding how these networks respond to targeted disruption is essential for exposing structural vulnerabilities and refining existing anti-money laundering (AML) prevention and intervention strategies. This study involves a social network analysis (SNA)-based resilience framework to evaluate the robustness of financial transaction networks through targeted node removal. In this approach, a network is represented as a directed graph, where nodes correspond to accounts and edges represent transactions. Centrality measures (i.e., degree, closeness, betweenness and pagerank), which capture local influence, global reach, and control over information flow, are applied to identify the most influential nodes. Network resilience is assessed by analyzing the variation in the size of the Largest Connected Component (LCC) under progressive node removal. An adaptive LCC-based resilience strategy is used, starting with large batches of nodes and gradually moving to smaller ones until the LCC drops below 50% of its original size, allowing for a more detailed analysis near the fragmentation threshold. The findings reveal that Betweenness centrality is the most effective metric in disrupting network connectivity under targeted attack scenarios, both outflow- and inflow-based analyses. Specifically, targeting only the top 2% of nodes by Betweenness centrality collapses the network’s core, reducing the Largest Connected Component (LCC) to 60% of its original size. In contrast, random attack strategy exhibit limited impact on overall network resilience compared to targeted approaches. Our findings provide actionable AML insights, showing that resilience-driven targeting of structurally critical accounts can effectively fragment money laundering networks and support more focused interdiction strategies. Full article

The Tua River is a tributary of the Douro River in the North of Portugal used as a spawning ground for potamodromous fish, namely the Iberian barbel (Luciobarbus bocagei, Steindachner, 1864). Although access to this tributary became severely constrained after the construction of the Foz Tua Hydroelectric Facility (AHFT), fish continued to use the remaining accessible 1.1 km stretch of the Tua River below the dam, especially during their spawning season. Therefore, this study presents the monitoring of migratory fish influx downstream of the AHFT and associated mitigation measures. Fixed and mobile surveys, using an ARIS 1800 sonar, and focused on Iberian barbel were conducted between March and July, from 2023 to 2025. In 2023, fixed sonar monitoring recorded 100,289 individuals, showing a progressive increase over the sampling period, while mobile surveys confirmed high local concentrations (2083 individuals) and temporal fluctuations. In 2024, total counts rose substantially to 182,216 individuals (fixed surveys) and 2656 individuals (mobile surveys), with a peak in early May followed by a gradual reduction in these numbers. In 2025, the highest abundance was observed, with 196,935 individuals (fixed surveys) and 5441 individuals (mobile surveys), alongside higher variability between monitoring campaigns. Overall, these results suggest an intensifying pattern of fish accumulation downstream of the AHFT during the sampled periods, with recurring seasonal peaks. As a method to mitigate massive accumulation of fish downstream of this dam, in 2024 and 2025, a near real-time detection and mitigation protocol was implemented. This protocol identifies an initial “trigger” and a sequential methodology that recognizes possible massive accumulation scenarios, followed by the application of an adaptive operational management measure (e.g., ecological flow regulation) by the AHFT. The application of these measures effectively contributed to reducing fish accumulation during the critical periods. In conclusion, the results highlight a consistent increase in migratory fish accumulation, over the study period, downstream of the AHFT. The successful application of adaptive measures demonstrates that the implemented strategy seems to be effective so far and provides a strong basis for future management actions. Full article

Background/Objectives: Promoting postural health in children requires not only adequate knowledge but also the implementation of health-promoting behaviors in the school environment. Teachers play a key role in this process; however, the extent to which their knowledge is reflected in everyday practice remains unclear. The study aimed to analyze and compare the levels of knowledge among preschool, early school, and physical education teachers regarding postural health in children and adolescents, including postural abnormalities, ergonomics, the selection of corrective exercises, and behaviors that promote correct body posture. Methods: A cross-sectional study was conducted on a sample of 153 teachers in Poland: 24 preschool (P), 53 early school education (EE), and 76 physical education (PE) teachers. The self-report Teachers’ Body Posture Literacy Questionnaire (TBPLQ) was used to assess knowledge regarding postural abnormalities. Results: PE achieved the highest TBPLQ scores, with significant differences observed mainly in comparison with EE (r = 0.30–0.50, p < 0.001). Across all groups, teachers performed best in recognizing postural abnormalities and worst in selecting appropriate corrective exercises. Although knowledge levels were relatively high, only weak correlations were found between knowledge and postural hygiene-promoting behaviors. The largest behavioral differences concerned the use of appropriate sportswear during physical education classes (η² > 0.14). Conclusions: Teachers demonstrated relatively high levels of knowledge regarding posture health. However, a clear knowledge–behavior gap was identified. Knowledge was only partially translated into proactive health-promoting actions, particularly regarding corrective interventions and communication with parents. The results suggest the need for educational initiatives for teachers focusing on proactive health-promoting and postural hygiene behaviors. Full article

The rapid emergence of antimicrobial resistance has intensified the need for advanced therapeutic platforms capable of improving the efficacy, stability, and targeted delivery of antimicrobial agents. Electrospun nanofibers have emerged as highly promising materials for biomedical applications due to their large surface area, high porosity, tunable morphology, and ability to incorporate a broad range of bioactive compounds. This review provides a comprehensive overview of the design, fabrication, and biomedical applications of electrospun bioactive nanofibers functionalized with antimicrobial drugs. It presents the main nanofiber fabrication techniques, with particular emphasis on electrospinning and the influence of solution, process, and environmental parameters on fiber morphology and drug-loading efficiency. Natural, synthetic, and hybrid polymer systems commonly employed in electrospun antimicrobial nanofibers are analyzed in relation to their physicochemical properties, biocompatibility, and therapeutic performance. In addition, the review highlights different drug incorporation strategies, including encapsulation, immobilization, and surface coating, as well as the mechanisms of action of antimicrobial agents. Recent advances in nanotechnology-based antimicrobial systems and their role in overcoming analytical, biopharmaceutical, and drug-delivery limitations are also examined. Furthermore, the review addresses current challenges related to scalability, reproducibility, stability, and clinical translation of electrospun nanofibers. Finally, future perspectives focusing on multifunctional, stimuli-responsive, and personalized antimicrobial nanofiber systems are discussed as promising directions for combating bacterial infections and reducing the global burden of antimicrobial resistance. Full article

Air Traffic Control Officers (ATCOs) are responsible for controlling air traffic and ensuring the safety of the aircraft. Capacity, understood as the maximum number of aircraft that can be safely managed for one hour, is calculated based on the workload of ATCOs. This calculation normally is based on a manual and tedious data collection process that demands a high consumption of human resources. To improve and relieve human re-sources, automation tools that automatically generate a preliminary annotation of Air Traffic Control (ATC) activity have been developed. This paper focuses on the feasibility of employing data-driven approaches using neural networks to classify ATC events, as well as if it is possible to improve the performance of these ATC-activity tools. Particularly, this approach seeks to infer ATC intent for separation actions, which are the most critical in terms of ATC workload. A modular methodology has been developed to include information from different sources: flight plans, radar trajectories, trajectory prediction, conflict detection and rule-based knowledge. Different experiments are evaluated based on the different input’s combination, as well as three neural networks (Multilayer Perceptron, Convolutional Neural Network and TabNet). Results show that TabNet is the best neural network option, reaching a similar performance in task classification than current ATC tools and improving classification metrics around 4% by employing the outputs of ATC tool metrics as inputs. Full article

Accurate and scalable urban land cover mapping is critical for sustainable urban planning and environmental management. While deep learning models offer powerful tools for this task, their performance is often constrained by the need for vast, manually labeled datasets, which are costly and challenging to acquire for diverse urban environments. To address this limitation, we propose the Cross-Scale U-Net, an original, highly adaptable operational framework that systematically exploits the inherent scale effects of remote-sensing imagery to optimize transfer learning. By operationalizing prior theoretical findings on receptive fields, this workflow provides an actionable method for users to manipulate spatial resolution, identify an optimal scale to bridge the domain gap, and subsequently automate feature extraction with significantly reduced manual effort. Using the well-annotated ISPRS Potsdam dataset as the source domain, our framework transfers learned knowledge to classify National Agriculture Imagery Program (NAIP) data from Phoenix, AZ (2015), into four primary land cover classes. We systematically evaluated the framework’s performance across spatial resolutions ranging from 15 cm to 100 cm, achieving a peak overall accuracy (OA) of 82.45%. To assess generalizability, the model was applied in a label-free transfer scenario to NAIP imagery from Las Vegas, NV (2015), and Phoenix, AZ (2013 and 2019), consistently delivering OA values above 70%. In a comparative analysis, the Cross-Scale U-Net significantly outperformed traditional classification techniques. While our current empirical validation is focused on arid urban environments due to experimental constraints, the framework introduces a highly flexible, actionable scale-adjustment process. This approach offers a scalable workflow that can be tailored to various landscape scales—such as expanding to coarser resolutions for large-scale forests or protected areas—delivering high-fidelity maps while mitigating data scarcity. Full article

Background/Objectives: Lung cancer is a leading cause of cancer-related mortality worldwide. As patients increasingly utilize large language models (LLMs) for health information, evaluating the readability and patient-centeredness of these tools is critical. This study aims to compare the performance of ChatGPT-4o mini, Microsoft Copilot, and Google Gemini in providing lung cancer information, focusing on their utility for individuals with limited health literacy. Methods: In this cross-sectional study (March 2026), 30 responses to ten standardized lung cancer-related queries were analyzed. Outputs were assessed using JAMA benchmarks and mDISCERN for quality, the SMOG index for readability, and PEMAT-P for understandability and actionability. Inter-rater reliability was analyzed using intraclass correlation coefficients (ICCs). Results: ChatGPT-4o mini demonstrated superior readability, achieving a sixth-grade level (SMOG: 6.23 ± 0.72, p < 0.001). Gemini achieved higher JAMA scores, indicating stronger academic rigour. While PEMAT-P scores were highest for ChatGPT (63.7%), all models exhibited moderate mDISCERN quality. Inter-rater reliability was excellent for JAMA (ICC = 1.000) and PEMAT-P (ICC = 0.883), though moderate for mDISCERN (ICC = 0.365), reflecting inherent interpretative subjectivity in qualitative assessment. No hallucinations were observed. Conclusions: Current LLMs exhibit a trade-off between accessibility and academic rigour: ChatGPT favours patient-friendly readability, while Gemini emphasizes structured content. The observed inter-rater variability in mDISCERN underscores the complexity of standardizing qualitative AI evaluation. These findings suggest that LLMs function best as complementary aids rather than substitutes for physician-led communication. Full article

This paper investigates engineering decision optimization in uncertain environments. Subject to constraints on cost and expected returns, engineering decisions optimize material input, equipment selection and process arrangement to minimize costs and maximize economic benefits. As an efficient formal verification technique, model checking offers a new approach to addressing this problem. Traditional model checking focuses on qualitative verification, while quantitative approaches, including probabilistic and possibilistic model checking, have been gradually developed. Among them, possibilistic model checking is more applicable to systems with fuzzy uncertainty. However, existing possibilistic model-checking techniques have notable limitations: they are only designed for closed systems and ignore interactions between the system and external environments; their simplistic information aggregation leads to information asynchrony and loss; and they cannot model and verify systems with incomplete information. Model checking based on possibilistic decision processes enables the selection of uncertain actions and initially resolves the modeling and verification of open systems. In our previous work, we introduced quality constraints into possibilistic temporal logic to mitigate information asynchrony and loss. We also established the theories of intuitionistic fuzzy Kripke structure (IFKS) and Intuitionistic Fuzzy Computation Tree Logic (IFCTL), which support the modeling and verification of systems with incomplete information. To improve the practicality and accuracy of engineering decisions, this study adopts the ideas of uncertain decision-making behavior selection, quality constraints and incomplete information modeling. It extends IFKS to the Weighted Intuitionistic Fuzzy Kripke Structure (WIFKS) and evolves IFCTL into the intuitionistic fuzzy decision tree logic (IFDTL). We further propose an IFDTL model-checking algorithm and a multi-attribute engineering decision algorithm based on the proposed method, along with corresponding correctness proofs and complexity analysis. A case study on Qinling health-preserving tourism planning verifies the rationality and effectiveness of the presented approach. This research provides a novel formal solution for engineering decision-making under uncertainty. Full article

This article examines the utilization of WhatsApp as an alternative communication tool for disseminating visual content among social activists during protests. While WhatsApp is typically conceptualized as an interpersonal or group messaging platform, research on its role as an infrastructure for alternative media and citizen journalism remains limited. The study focuses on the “Tikva” group, established at the onset of the public struggle against the 2023 judicial reform in Israel, which evolved into a nine-month mass protest movement described as one of the largest in the country’s history. Through qualitative thematic content analysis of videos distributed within the group, the article explores how WhatsApp functions simultaneously as a channel for digital activism and as a site of bottom-up, democratic, non-institutional news production. The findings indicate two primary trends: functionally, WhatsApp operates as a mechanism for resource mobilization, calls to action in physical and digital spaces, and the cultivation of belonging and solidarity among activists facing institutional power; in terms of content and production, the videos articulate an anti-hegemonic discourse and challenge mainstream media conventions. The analysis shows how these videos dismantle delegitimizing frames and construct a counter-narrative depicting protesters as citizens defending democracy, thereby sustaining the protest movement’s momentum. Full article

Venous thromboembolism (VTE) remains a clinically relevant complication of radical prostatectomy despite advances in surgical techniques and perioperative care. Current thromboprophylaxis strategies are largely based on fixed-duration approaches and static risk models focused on the early postoperative period. However, accumulating evidence suggests that postoperative hypercoagulability is a dynamic and prolonged process that may extend beyond this timeframe. This review summarizes the pathophysiological mechanisms and temporal dynamics of postoperative hypercoagulability after radical prostatectomy, with particular emphasis on biomarker-based evidence, including thrombin generation and von Willebrand factor. Clinical and laboratory findings suggest that haemostatic activation may persist after hospital discharge, supporting the concept of a biologically relevant post-discharge period during which insufficiently captured thrombotic risk may remain despite apparent clinical recovery. Current risk assessment models do not account for the time-dependent nature of postoperative haemostatic changes and do not incorporate biomarker data. This discrepancy highlights a gap between guideline-based thromboprophylaxis strategies and the underlying biological processes. To address this, we propose a conceptual framework in which postoperative thromboprophylaxis is considered in relation to the temporal evolution of hypercoagulability. This framework is hypothesis-generating and may help inform future studies aimed at identifying patients who could benefit from extended prophylaxis while avoiding unnecessary anticoagulation in those with more rapid haemostatic recovery. Further prospective studies are required to validate biomarker-guided strategies and to define clinically actionable thresholds for individualized thromboprophylaxis in prostate cancer patients undergoing radical prostatectomy. Full article