Search Results (5,102)

Road-surface distress poses a serious threat to traffic safety and imposes a growing burden on urban maintenance budgets. While modern detectors based on convolutional networks and Vision Transformers achieve strong frame-level performance, they often overlook an essential property of road environments—structural symmetry within road networks and damage patterns. We present Graph-MambaRoadDet (GMRD), a symmetry-aware and lightweight framework that integrates dynamic graph reasoning with state–space modeling for accurate, topology-informed, and real-time road damage detection. Specifically, GMRD employs an EfficientViM-T1 backbone and two DefMamba blocks, whose deformable scanning paths capture sub-pixel crack patterns while preserving geometric symmetry. A superpixel-based graph is constructed by projecting image regions onto OpenStreetMap road segments, encoding both spatial structure and symmetric topological layout. We introduce a Graph-Generating State–Space Model (GG-SSM) that synthesizes sparse sample-specific adjacency in $\mathcal{O}\left(M\right)$ time, further refined by a fusion module that combines detector self-attention with prior symmetry constraints. A consistency loss promotes smooth predictions across symmetric or adjacent segments. The full INT8 model contains only 1.8 M parameters and 1.5 GFLOPs, sustaining 45 FPS at 7 W on a Jetson Orin Nano—eight times lighter and 1.7× faster than YOLOv8-s. On RDD2022, TD-RD, and RoadBench-100K, GMRD surpasses strong baselines by up to +6.1 mAP_50:95 and, on the new RoadGraph-RDD benchmark, achieves +5.3 G-mAP and +0.05 consistency gain. Qualitative results demonstrate robustness under shadows, reflections, back-lighting, and occlusion. By explicitly modeling spatial and topological symmetry, GMRD offers a principled solution for city-scale road infrastructure monitoring under real-time and edge-computing constraints. Full article

This study reconstructs seven decades (1949–2019) of morphodynamic changes and sediment dynamics in the Diable River (Québec, Canada) using nine series of aerial photographs, a high-resolution LiDAR Digital Elevation Model (2021), and grain-size analysis. The objectives were to document long-term river evolution, quantify erosion and deposition, and evaluate sediment connectivity between eroding sandy bluffs and depositional zones. Planform analysis and sediment budgets derived from DEMs of Difference (DoD) reveal an oscillatory trajectory characterized by alternating phases of sediment export and temporary stabilization, rather than a simple trend of degradation or aggradation. The most dynamic interval (1980–2001) was marked by widespread meander migration and the largest net export (−142.5 m³/km/year), whereas the 2001–2007 interval showed net storage (+70.8 m³/km/year) and short-term geomorphic recovery. More recent floods (2017, 2019; 20–50-year return periods) induced localized but persistent sediment loss, underlining the structuring role of extreme events. Grain-size results indicate partial connectivity: coarse fractions tend to remain in local depositional features, while finer sediments are preferentially exported downstream. These findings emphasize the geomorphic value of temporary sediment sinks (bars, beaches) and highlight the need for adaptive river management strategies that integrate sediment budgets and local knowledge into floodplain governance. Full article

Dynamic pressure measurement is an important component in the turbo engine testing process. This paper presents a comparative analysis between two types of multichannel electronic pressure measurement systems, commonly known as pressure scanners, used for this purpose: ZOC17/8Px, with analog amplification per channel, and MPS4264, a modern digital system with integrated A/D conversion. The study was conducted in two stages: a metrological verification and validation in static mode, using a high-precision pressure standard, and an experimental stage in dynamic mode, where data was acquired from a turbojet engine test stand, in constant engine speed mode. The signal stability of the pressure scanners was statistically analyzed by determining the coefficient of variation in the signal and the frequency spectrum (FFT) for each channel of the pressure scanners. Furthermore, comprehensive uncertainty budgets were calculated for both systems. The results highlight the superior stability and reduced uncertainty of the MPS4264 pressure scanner, attributing its enhanced performance to digital integration and a higher resilience to external noise. The findings support the adoption of modern digital systems for dynamic applications and provide a robust metrological basis for the optimal selection of measurement systems. Full article

Short-form video platforms have shifted advertising from standalone, time-bounded spots to feed-embedded, swipeable stimuli, creating a high-velocity processing context that can penalize casting complexity. We ask whether a “one face, many roles” casting strategy (a single actor playing multiple characters) outperforms multi-actor executions, and why. A two-phase pretest (N = 3500) calibrated a realistic ceiling for “multi-actor” casts, then four experiments (total N = 4513) tested mechanisms, boundary conditions, and alternatives. Study 1 (online and offline replications) shows that single-actor ads lower cognitive load and boost account evaluations and purchase intention. Study 2, a field experiment, demonstrates that Need for Closure amplifies these gains via reduced cognitive load. Study 3 documents brand-type congruence: one actor performs better for entertaining/exciting brands, whereas multi-actor suits professional/competence-oriented brands. Study 4 rules out cost-frugality and sympathy using a budget cue and a sequential alternative path (perceived cost constraint → sympathy). Across studies, a chain mediation holds: single-actor casting reduces cognitive load, which elevates brand authenticity and increases purchase intention; a simple mediation links cognitive load to account evaluations. Effects are robust across settings and participant gender. We theorize short-form advertising as a context-embedded persuasion episode that connects information-processing efficiency to authenticity inferences, and we derive practical guidance for talent selection and script design in short-form campaigns. Full article

Long Range Wide Area Network (LoRaWAN) has become an attractive option for maritime communication because it is low-cost, long-range, and energy-efficient. Yet its performance at sea is often limited by fading, interference, and the strict energy budgets of maritime Internet of Things (IoT) devices. This review, prepared in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, examines 23 peer-reviewed studies published between 2019 and 2025 that explore adaptive antenna solutions for LoRaWAN in marine environments. The work covered four main categories: switched-beam, phased array, reconfigurable, and Artificial Intelligence or Machine Learning (AI/ML)-enabled antennas. Results across studies show that adaptive approaches improve gain, beam agility, and signal reliability even under unstable conditions. Switched-beam antennas dominate the literature (45%), followed by phased arrays (30%), reconfigurable designs (20%), and AI/ML-enabled systems (5%). Unlike previous reviews, this study emphasizes maritime propagation, environmental resilience, and energy use. Despite encouraging results in signal-to-noise ratio (SNR), packet delivery, and coverage range, clear gaps remain in protocol-level integration, lightweight AI for constrained nodes, and large-scale trials at sea. Research on reconfigurable intelligent surfaces (RIS) in maritime environments remains limited. However, these technologies could play an important role in enhancing spectral efficiency, coverage, and the scalability of maritime IoT networks. Full article

Cybersecurity is increasingly recognized as a key enabler of Sustainable Development Goals (SDGs) and especially SDG 3 (Good Health and Well-being) as healthcare systems become more digitized. This study prioritizes cybersecurity control families from the NIST 800-53r5 framework using a structured framework combining the Analytic Hierarchy Process (AHP) and the Impact–Feasibility Matrix. From the impact–feasibility perspective, expert judgment reveals that while impact is the primary driver in selecting controls, feasibility—particularly budget and cost constraints—plays a decisive role in real-world implementation. A group of fifteen experts, including cybersecurity officers, health IT professionals, and public health advisors, has participated in structured surveys as per the methodological framework of this paper. Financial and budgetary limitations emerged as the top feasibility barrier, often determining whether high-impact controls are deployed or delayed. This underscores the need for strategic investments and phased implementation approaches, particularly in resource-constrained health systems. The results provide a practical roadmap for policymakers and healthcare administrators to allocate cybersecurity resources effectively, balancing technical necessity with economic feasibility to support resilient digital health infrastructures. Full article

Between 2020 and 2024, museums underwent accelerated digital transformation driven by the global health crisis and technological advances, exposing deep inequalities in access to technology and communication capabilities. Museums with limited resources had to rethink their digital strategies to sustain audience engagement and cultural relevance. This article presents a comparative study of museums in Argentina and Spain with restricted budgets, analyzing how they responded to challenges of uncertainty and scarcity. Using a mixed methodology—surveys of 22 professionals, interviews with directors of four representative museums, and qualitative case studies—this study examines the implemented solutions and their impacts. The findings highlight innovative practices grounded in creativity, strategic alliances, and intensive use of social media. Argentine museums excelled in tactical adaptation amid economic instability, while Spanish institutions showed stronger strategic planning. Private museums proved more flexible than their public counterparts, which faced greater bureaucratic constraints. This work contributes to debates on institutional resilience and offers a framework for sustainable digital communication in resource-limited contexts. Full article

Vaccination has resulted in substantial public health benefits for human populations worldwide since it was first introduced more than a century ago. This article presents an overview of the history of vaccine development, its implementation, and price setting, the latter mainly from a developed world perspective. It considers potential issues and challenges. Over time, vaccine development and production has evolved to a market-driven approach, conducted largely by private commercial entities. The complex processes of identifying potential vaccine targets and developing and producing vaccines at scale have now become more efficient. However, vaccine pricing is an emerging concern. The elements that maximize the overall health benefit of vaccination include high volume, high coverage, and rapid initial implementation to achieve the high coverage with the vaccine as quickly as possible. It therefore requires substantial initial investment. Consequently, the price set for the vaccine should be reasonable to avoid limiting the coverage given the available budget. Suboptimal coverage leads to suboptimal benefit if herd protection is not fully achieved. This may disappoint health authorities and may result in program discontinuation. Conventional cost-effectiveness analysis is therefore not ideally suited to vaccine price setting, as it is based on the concept of ‘more for more’, i.e., higher health gain achieved at a higher reimbursement cost that does not account for limited budgets. Constrained optimization (CO) combines value assessment with constrained budget allocation into one analysis method and may therefore be the better option for vaccine pricing. Full article

Within the modernizing energy infrastructure of today, the integration of renewable energy sources and direct current (DC)-powered technologies calls for the re-examination of traditional alternative current (AC) networks. Low-voltage DC (LVDC) grids offer an attractive way forward in reducing conversion losses and simplifying local power management. However, ensuring reliable operation depends on a thorough understanding of DC distortions—phenomena generated by power converters, source instability, and varying loads. Two complementary traceable measurement chains are presented in this article with the purpose of measuring the steady-state DC component and the amplitude and frequency of the distortions around the DC bus with low uncertainties. One chain is optimized for laboratory environments, with high effectiveness in a controlled setup, and the other one is designed as a flexible and easily transportable solution, ensuring efficient and accurate assessments of DC distortions for field applications. In addition to our hardware solutions fully characterized by the uncertainty budget, we present the measurement method used for assessing DC distortions after evaluating the limitations of conventional AC techniques. Both arrangements are set to measure voltages of up to 1000 V, currents of up to 30 A, and frequency components of up to 150–500 kHz, with an uncertainty varying from 0.01% to less than 1%. This level of accuracy in the measurements will allow us to draw reliable conclusions regarding the dynamic behavior of future LVDC grids. Full article

This article aims to create insights concerning the remuneration of executives (also known as vice chancellors (VCs)) in higher education in South Africa. Their remuneration is a trending and contentious topic in the media and literature within the South African context. The motivation for conducting this study is that there are no clear indicators, norms, or standards to measure salaries. Therefore, this study is grounded in agency and institutional theories. Moreover, prior to this study, there were no longitudinal studies in the South African context that have analysed VCs’ salaries, using predictors like student enrolment, return on assets, debt ratio, and revenue. The research design was longitudinal, while the research approach was quantitative. The universities that did not meet the requirements for 2016 to 2023 were excluded from the analysis, which was conducted using Python, version 3.11.7, Python Software Foundation: Wilmington, DE, USA, 2025. Since the data points were small (n = 8), bootstrapping was used to resample 1000 samples. The correlation results showed a significant relationship with the fixed salary, whereas the regression results were not significant. It was found that the VCs’ salary is a larger portion of the fixed salary, and the historical data (2013 to 2016) showed an upward trend; the forecast from 2024 to 2026 showed a flat trend. The forecasts are salient and create insights that will assist remuneration practitioners to budget for VCs’ salaries in order to attract, motivate, and retain them. Full article

Educational institutions face complex challenges when allocating limited teaching resources to specialized seminars, where budget, capacity, and balanced disciplinary representation must all be satisfied simultaneously. We address this for the first time in the educational domain by formulating the teacher seminar selection problem as a multi-dimensional knapsack variant with category-specific benefit multipliers. To solve it, we design a constraint-aware genetic algorithm that incorporates smart initialization, category-sensitive operators, adaptive penalties, and targeted repair mechanisms. In experiments on a realistic dataset representing multiple academic categories, our method achieved an 11.5% improvement in solution quality compared to the best constraint-aware greedy baseline while maintaining perfect constraint satisfaction (100% feasibility) vs. 0–30% for baseline methods. Statistical tests confirmed significant and practically meaningful advantages. For comprehensive benchmarking, we also implemented binary particle swarm optimization (PSO) and Tabu Search (TS) solvers with standard parameterizations. While PSO consistently produced feasible solutions with high budget utilization, its optimization quality was substantially lower than that of the GA. Notably, Tabu Search achieved the highest performance, with a mean fitness of 1557.3 compared to GA’s 1533.2, demonstrating that memory-based local search can be highly competitive for this problem structure. These findings show that metaheuristic approaches, particularly those integrating constraint-awareness into evolutionary or memory-based search, provide effective, scalable decision-support frameworks for complex, multi-constraint educational resource allocation. Full article

Breast cancer (BC) is the most frequently diagnosed malignancy in women. Currently, BC is treated with a holistic and multidisciplinary approach from diagnostic, surgical, radio-oncological, and medical perspectives, and advances including in early detection and treatment methods have led to improved outcomes for patients in recent years. Yet, BC remains the second most common cause of cancer-related deaths among women and there is an array of gaps to achieve optimal care. To close gaps in cancer care, here we describe a collaborative Request For Proposals (RFP) framework supporting independent initiatives for metastatic breast cancer (MBC) patients and aiming at improving their quality of care. We set up a collaborative framework between Pfizer and Sharing Progress in Cancer Care (SPCC). Our model is based on an RFP system in which Pfizer and SPCC worked together ensuring the independence of the funded projects. We developed a three-step life cycle RFP. The collaborating framework of the project was based on an RFP with a USD 1.5 million available budget for funding independent grants made available from Pfizer and managed in terms of awareness, selection, and monitoring by SPCC. Our three-step model could be applicable and scalable to quality improvement (QI) initiatives that are devoted to tackling obstacles to reaching optimal care. Through this model, seven projects from five different European countries were supported. These projects covered a range of issues related to the experience of patients with MBC: investigator communication, information, and shared decision-making (SDM) practices across Europe; development, delivery, and evaluation of a scalable online educational program for nurses; assessment of disparities among different minority patient groups; development of solutions to improve compliance or adherence to therapy; an information technology (IT) solution to improve quality of life (QoL) of patients with MBC and an initiative to increase awareness and visibility of MBC patients. Overall, an average of 171 healthcare professionals (HCPs) per project and approximately 228,675 patients per project were impacted. We set up and describe a partnership model among different stakeholders within the healthcare ecosystem―academia, non-profit organizations, oncologists, and pharmaceutical companies―aiming at supporting independent projects to close gaps in the care of patients with MBC. By removing barriers at different layers, these projects contributed to the achievement of optimal care for patients with MBC. Full article

Vorticity budgets in traditional height or pressure coordinates are commonly examined to help explain how tropical cyclones evolve over time. One disadvantage of using these coordinates is that the vorticity flux due to diabatic heating cannot be easily assessed. Isentropic coordinates naturally lend themselves to determine the effect of diabatic heating—the vorticity budget simplifies, and a clear-cut distinction can be made between adiabatic (advective) and diabatic vorticity fluxes. Above the boundary layer, advective vorticity fluxes alone would lead to a quick spin-down of the mature tropical cyclone. Do diabatic processes prevent this from happening? If so, how? This paper investigates the vorticity budget of Hurricane Irma (2017) in its mature quasi-steady phase. We analyse a simulation of Irma with an operational high-resolution weather forecasting model. During Irma’s remarkably long period (37 h) of steady peak intensity, the radially outward advective isentropic vorticity flux in the eyewall above the boundary layer is balanced by a radially inward diabatic isentropic vorticity flux. Frictional effects and asymmetrical flow properties are of little importance to the maintenance of cyclone intensity in its mature phase, provided enough latent heat is released in the eyewall to maintain an inward vorticity flux that balances the advective flux. Full article

Vegetable cultivation plays an essential role in the agricultural economy. However, amid increasingly pressing economic and climatic factors that significantly influence the sustainability of this sector, vegetable production in Romania has a downward trend. Similarly to other field crops, open-field tomato production is exposed to climate risks, such as extreme temperatures and drought, factors that have significantly impacted Romanian agriculture during the 2024–2025 period. This study aims to analyze the risk exposure of tomato cultivation under unfavorable climatic conditions and to emphasize the importance of financial support in protecting farmers’ incomes. By using a detailed income and expenditure budget, the study evaluates the financial vulnerability of the production process and analyzes the effects of crop losses on farm profitability. The results indicate substantial income losses for farmers in the event of crop damage, with estimated losses of 5280 EUR/ha for a 30% damage level and 10,912 EUR/ha for 50% damage. These findings highlight the importance of financial support provided through national public policies (SP PAC 2023–2027), along with the proposal of crop insurance as an effective tool for risk management and financial protection of farmers. This measure could contribute to mitigating the economic impact on farmers affected by climatic factors. Full article

Optimizing pavement maintenance and rehabilitation (M&R) strategies is essential, especially in developing countries with limited budgets. This study presents an integrated framework combining a deterioration prediction model and a genetic algorithm (GA)-based optimization model to plan cost-effective M&R strategies for flexible pavements, including asphalt concrete (AC) and double bituminous surface treatment (DBST). The GA schedules multi-year interventions by accounting for varied deterioration rates and budget constraints to maximize pavement performance. The optimization process involves generating a population of candidate solutions representing a set of selected road sections for maintenance, followed by fitness evaluation and solution evolution. A mixed Markov hazard (MMH) model is used to model uncertainty in pavement deterioration, simulating condition transitions influenced by pavement bearing capacity, traffic load, and environmental factors. The MMH model employs an exponential hazard function and Bayesian inference via Markov Chain Monte Carlo (MCMC) to estimate deterioration rates and life expectancies. A case study on Cambodia’s road network evaluates six budget scenarios (USD 12–27 million) over a 10-year period, identifying the USD 18 million budget as the most effective. The framework enables road agencies to access maintenance strategies under various financial and performance conditions, supporting data-driven, sustainable infrastructure management and optimal fund allocation. Full article