Search Results (2,181)

In recent years, there has been an ever increasing interest in UxVs and the technology surrounding them. A more recent area of interest within the UxV ecosystem is the development of UxV swarms. In these systems, multiple UxVs synchronize, continuously exchange information, and operate as a cohesive unit. This evolution requires a higher level of autonomy, enhanced coordination, and more efficient communication channels. In this survey, we present relevant research on swarms of UxVs, always considering artificial intelligence (AI) as the key technological enabler for the swarm operations. We view the swarm from three distinct perspectives; these are intelligence-wise, communication-wise, and security-wise. Our main goal is to explore in which ways and to what extent AI has been integrated in these aspects. We aim to identify which of these aspects are the most researched and which need deeper investigation, the types of AI that are mainly used, and which types of vehicles are preferred. We then discuss the results of our work and present current limitations as well as areas of future research in the realm of UxVs, AI, swarm intelligence, communications, and security. Full article

Accelerated oxidation experiments on Chinese 0# diesel fuel were performed with a self-designed aging reactor system. Five experimental conditions covering pressures ranging from atmospheric pressure to 0.8 MPa, temperatures ranging from room temperature (25 °C) to 80 °C, and their synergistic effects were adopted to simulate the long-term oxidation of diesel fuel. The extent of deterioration was evaluated based on the measurement of three key indicators, i.e., oxidation stability, wear scar diameter, and viscosity. Thermogravimetric analysis (TGA) tests were performed, and the measured thermogravimetric (TG) curves and derivative thermogravimetric (DTG) curves were used to evaluate the effects of reactor material, heating rate, bath gas, and reactive gas on the deterioration and vaporization processes of diesel fuel. Based on a comparison of the deterioration indicators of diesel fuel collected from the accelerated oxidation experiments and oil depots serving actual operating emergency diesel generators (EDGs), a rapid assessment method of real-time diesel deterioration was explored. Based on the experimental observations, the affecting mechanisms of the increases in temperature and oxygen partial pressure were discussed. Two test methods of accelerated oxidation, with the respective conditions of 0.8 MPa/80 °C and atmospheric pressure/80 °C, were proposed, which could effectively compress the time needed for long-term storage simulations (e.g., 200 h lab aging equals three years of actual operation). The optional temperature and pressure windows for acceleration oxidation were confirmed (40–80 °C/0.3–0.8 MPa). These results are valuable for the further understanding of the processes of deterioration and vaporization of diesel fuel. Full article

A critical aspect in the design of power electronics packages is the prediction of their mechanical response under severe thermomechanical loads and the consequent structural damage. For this purpose, finite element (FE) simulations are used to estimate the mechanical performance and reliability under operational conditions, typically alternate high voltages/currents resulting in thermal gradients. When simulations are performed, it is common practice to consider the as-received package to be in a stress-free state. Namely, residual stresses and plastic deformation induced by the manufacturing processes are neglected. In this study, an advanced FE modeling approach is proposed to assess the structural consequences of the encapsulating resin curing, typical in the production of silicon carbide (SiC)-based power electronics modules for electric vehicles. This work offers a general modeling framework that can be further employed to simulate the effects of thermal gradients induced by the production process on the effective shape and residual stresses of the as-received package for other manufacturing stages, such as metal brazing, soldering processes joining copper and SiC, and, to lower extents, the application of polyimide on top of passivation layers. The obtained results have been indirectly validated with experimental data from literature. Full article

The deployment of autonomous vehicles (AVs) depends on the readiness of both physical and digital infrastructure. However, existing national and city-level indices often overlook deficiencies along specific routes, particularly in developing contexts such as Thailand, where infrastructure conditions vary widely. This study develops and applies a corridor-level framework to assess AV readiness on five controlled-access roads in western Bangkok. The framework evaluates key infrastructure dimensions beyond conventional vehicle requirements. In this study, infrastructure readiness means the extent to which essential physical (EV charging capacity, traffic sign visibility, and lane marking retroreflectivity) and digital (5G speed and coverage) subsystems meet minimum operational thresholds required for AV deployment. Data were collected through field measurements and secondary sources, utilizing tools such as a retroreflectometer, a handheld spectrum analyzer, and the Ookla Speedtest application. The results reveal significant contrasts for physical infrastructure, showing that traffic signage is generally satisfactory, but EV charging capacity and road marking retroreflectivity are insufficient on most routes. On the digital side, 5G coverage was generally adequate, but network speeds remained less than half of the global benchmark. Kanchanaphisek Road demonstrated comparatively higher digital readiness, whereas Ratchaphruek Road exhibited the weakest road marking conditions. These findings point out the need for stepwise enhancements to EV charging infrastructure, lane marking maintenance, and digital connectivity to support safe and reliable AV operations. The proposed framework not only provides policymakers in Thailand with a practical tool for prioritizing corridor-level investments but also offers transferability to other rapidly developing urban regions experiencing similar infrastructure challenges for AV deployment. Full article

Existing point cloud registration methods can effectively handle large-scale and partially overlapping point cloud pairs. However, registering unbalanced point cloud pairs with significant disparities in spatial extent and point density remains a challenging problem that has received limited research attention. This challenge primarily arises from the difficulty in achieving accurate local registration when the point clouds exhibit substantial scale variations and uneven density distributions. This paper presents a novel registration method for unbalanced point cloud pairs that utilizes the local point cluster structure feature for effective outlier rejection. The fundamental principle underlying our method is that the internal structure of a local cluster comprising a point and its K-nearest neighbors maintains rigidity-preserved invariance across different point clouds. The proposed pipeline operates through four sequential stages. First, keypoints are detected in both the source and target point clouds. Second, local feature descriptors are employed to establish initial one-to-many correspondences, which is a strategy that increases correspondences redundancy to enhance the pool of potential inliers. Third, the proposed Local Point Cluster Structure Feature is applied to filter outliers from the initial correspondences. Finally, the transformation hypothesis is generated and evaluated through the RANSAC method. To validate the efficacy of the proposed method, we construct a carefully designed benchmark named KITTI-UPP (KITTI-Unbalanced Point cloud Pairs) based on the KITTI odometry dataset. We further evaluate our method on the real-world TIESY Dataset which is a LiDAR-scanned dataset collected by the Third Railway Survey and Design Institute Group Co. Extensive experiments demonstrate that our method significantly outperforms the state-of-the-art methods in terms of both registration success rate and computational efficiency on the KITTI-UPP benchmark. Moreover, it achieves competitive results on the real-world TIESY dataset, confirming its applicability and generalizability across diverse real-world scenarios. Full article

Background: The digitalization of medical services is promoted as a solution for improving access, quality, and efficiency within healthcare systems. In this context, the study investigates the extent to which digitalization in Romania meets the current needs of patients through a convergent analysis of user perceptions and managerial perspectives. Based on the specialized literature, the research tests two hypotheses: (H1) the implementation of digital technologies significantly contributes to improving the quality of medical services and operational efficiency; (H2) digitalization has a positive impact on patient satisfaction by facilitating access to care and improving communication with medical personnel. Methods: The study adopted methodology is cross-sectional and mixed, including an online mixed-methods questionnaire for patients, distributed between 6 and 14 May 2025, and a qualitative questionnaire with open-ended questions distributed via e-mail to managers from public hospitals through The Administration of Hospitals and Medical Services of Bucharest, between 3 and 24 March 2025. Results: In total, 125 patients and 15 hospital managers participated in the study. Statistical analysis (χ², ordinal regression) and data triangulation highlight a predominantly positive, yet heterogeneous, patient perception of digitalization, with Hypothesis H1 only partially supported (weak, inconsistent, and in some cases negative associations between technology use and perceived service quality). By contrast, H2 was robustly validated, with patient satisfaction strongly linked to tangible benefits, particularly easier access and online appointment scheduling. However, use remains limited to administrative functions, while advanced technologies such as telemedicine or electronic health records are poorly adopted. From an institutional perspective, hospitals predominantly use IT systems for internal purposes, without real patient access to their own data, no interoperability between medical units, and marginal implementation of telemedicine. This reveals a significant gap between user perception and organizational realities, emphasizing the lack of a patient-oriented digital infrastructure. Conclusions: The results highlight the potential of digitalization to enhance patient experience and service efficiency, while also pointing out structural limitations that hinder the full realization of this potential. Patient satisfaction is strongly associated with tangible benefits, particularly easier access and online scheduling, whereas the effect on perceived quality is weaker and sometimes inconsistent. There are significant disparities in digitalization levels between healthcare providers, perceived by patients as public–private differences, and gaps among public hospitals are also confirmed by managerial data. These findings suggest that a successful digital transformation of the medical system in Romania must address both technological infrastructure gaps and organizational barriers, within a coordinated national strategy that ensures interoperability, patient-centered design, and sustainable implementation. Full article

Perovskite materials have garnered significant attention in both fundamental research and practical applications owing to their exceptional light absorption coefficients, low fabrication costs, and inherent advantages for thin-film and flexible device fabrication. Nevertheless, interface defects within perovskite films induce detrimental non-radiative carrier recombination and pronounced hysteresis effects, which collectively impose substantial limitations on the photovoltaic performance and long-term operational stability of perovskite solar cells (PSCs). Conventional passivation strategies, despite their demonstrated efficacy in mitigating interface defects, often inadvertently introduce secondary defects in originally defect-free regions, thereby restricting the extent of device performance improvement. To overcome this critical limitation, we have developed a precision defect passivation methodology that employs a targeted two-step immersion–cleaning process, achieving selective defect passivation while concomitantly eliminating residual passivating agents. This approach effectively prevents the formation of new defects in unaffected regions of the perovskite films, and the resultant PSC possesses a power conversion efficiency (PCE) of 21.08%, accompanied by a substantial mitigation of hysteresis behavior. Furthermore, unencapsulated devices demonstrate remarkable stability, retaining over 81% of their initial efficiency after 20 days of atmospheric storage under 50% relative humidity, which underscores the effectiveness of our passivation strategy in simultaneously enhancing both device performance and operational stability. Full article

Coal mining disturbances in semi-arid grasslands affect land surface phenology (LSP), impacting ecosystem functions, restoration target setting, and carbon sequestration; however, the magnitude and spatial extent of these disturbances and their detectability across vegetation indices (VIs), remain insufficiently constrained. We developed and applied a streamlined quantitative framework to delineate the extent and intensity of mining-induced phenological disturbance and to compare the sensitivity and stability of commonly used VIs. Using Harmonized Landsat Sentinel (HLS) surface reflectance data over the Yimin mine, we reconstructed multitemporal VI trajectories and derived phenological metrics; directional phenology gradients were used to delineate disturbance, and VI responsiveness was evaluated via mean difference (MD) and standard deviation (SD) between affected and control areas. Research findings indicate that the impact of mining extends to an area approximately four times the size of the mining site, with the start of season (SOS) in affected areas occurring about 10 days later than in unaffected areas. Responses varied markedly among VIs, with the Modified Soil-Adjusted Vegetation Index (MSAVI) exhibiting the highest spectral stability under disturbance. This framework yields an information-rich quantification of phenological impacts attributable to mining and provides operational guidance for index selection and the prioritization of restoration and environmental management in semi-arid mining landscapes. Full article

This study investigates the firm- and country-level determinants that influence the extent of financial disclosure under International Financial Reporting Standards (IFRS) in selected Latin American Organisation for Economic Co-operation and Development (OECD) members or countries in the accession process in the period under analysis. Using a sample of 168 publicly listed companies from Argentina, Chile, Colombia, Mexico, and Peru, we construct a self-developed disclosure index based on compliance with International Accounting Standards IAS 16 (Property, Plant and Equipment) and IAS 2 (Inventories). These standards were selected due to their relevance across a broad range of sectors in emerging markets. Drawing on agency theory, stakeholder theory, institutional theory, signaling theory, and legitimacy theory, we examine how internal firm characteristics, macroeconomic performance, and institutional quality impact disclosure practices. Our empirical findings show that firm size, leverage, Gross Domestic Product (GDP) growth, and shareholder protection have a positive and statistically significant influence on the level of IFRS disclosure. However, not all institutional variables are equally effective, highlighting the complex interplay between regulatory environments and corporate reporting behavior in developing countries. The study contributes to the ongoing debate on the applicability and effectiveness of IFRS in emerging economies by offering evidence from underexplored Latin American markets and emphasizing the need for context-specific policy and regulatory interventions. Full article

Background: Acute exacerbation (AE) of idiopathic inflammatory myopathy-associated interstitial lung disease (IIM-ILD) is fatal. Infection is one of the most important triggers of the AE of IIM-ILD. We evaluated the clinical features and prognosis of idiopathic (I-AE) and infection-triggered (iT-AE) acute exacerbation in IIM-ILD patients. Methods: We retrospectively reviewed 278 consecutive patients with IIM admitted to our hospital between January 2014 and December 2020. Among them, 69 patients experienced AE of IIM-ILD, including 34 with I-AE and 35 with iT-AE. Clinical features and short- and long-term outcomes were analyzed in this preliminary study. Results: Compared with I-AE, patients with iT-AE presented with lower hemoglobin and PaO₂/FiO₂ ratios but higher pulse, body temperature, white blood cell count, neutrophil percentage (NEU), C-reactive protein, erythrocyte sedimentation rates, lactate dehydrogenase, and hydroxybutyrate dehydrogenase levels. They also had more extensive ground-glass opacities (GGOs) on high-resolution computed tomography (all p < 0.05). Mortality was significantly higher in iT-AE than that in I-AE at 30 days (28.6% vs. 5.9%), 90 days (34.3% vs. 14.9%), and 1 year (54.3% vs. 17.6%; log-rank test, p = 0.002). Multivariate logistic regression showed that the combination of NEU and GGO extent could help discriminate iT-AE from I-AE (area under the receiver operating characteristic curve: 0.812; 95% confidence interval: 0.711–0.913; sensitivity: 71.4%, specificity: 73.5%, accuracy: 72.5%). Conclusion: This study found that iT-AE patients exhibited more severe hyperinflammation and markedly worse survival than I-AE patients. Combining NEU and GGO extent may assist in differentiating AE subtypes. Larger prospective studies are required to validate these findings. Full article

The use of additive manufacturing (AM) has seen increased utilization over the last decade, thanks to well-documented advantages such as lower startup costs, reduced wastage, and the ability to rapidly prototype. The poor surface finish of unprocessed AM components is one of the major drawbacks of this technology, with the research literature suggesting a measurable impact on flow characteristics and burner operability. For instance, surface roughness has been shown to potentially increase resistance to boundary layer flashback—an area of high concern, particularly when utilizing fuels with high hydrogen content. A more detailed understanding of the underlying thermophysical mechanisms is, therefore, required. Computational fluid dynamics can help elucidate the impact of these roughness effects by enabling detailed data interrogation in locations not easily accessible experimentally. In this study, roughness effects on a generic gas turbine swirler were numerically modeled using a low-y+ detached eddy simulation (DES) approach. Three DES models were investigated utilizing a smooth reference case and two rough cases, the latter employing a literature-based and novel equivalent sand-grain roughness (k_s) correlation developed for this work. Existing experimental isothermal and CH₄ data were used to validate the numerical simulations. Detailed investigations into the effects of roughness on flow characteristics, such as swirl number and recirculation zone position, were subsequently performed. The results show that literature-based k_s correlations are unsuitable for the current application. The novel correlation yields more promising outcomes, though its effectiveness depends on the chosen turbulence model. Moreover, it was demonstrated that, for identical k_s values, while trends remained consistent, the extent to which they manifested differed under reacting and isothermal conditions. Full article

The goal of this study is to estimate the amount of lost data in electron microscopy and to analyze the extent to which experimentally acquired images are utilized in peer-reviewed scientific publications. Analysis of the number of images taken on electron microscopes at a core user facility and the number of images subsequently included in peer-reviewed scientific journals revealed low efficiency of data utilization. Up to around 90% of electron microscopy data generated during routine instrument operation can remain unused. Of the more than 150,000 electron microscopy images evaluated in this study, only approximately 3500 (just over 2%) were made available in publications. For the analyzed dataset, the amount of lost data in electron microscopy can be estimated as >90% (in terms of data being recorded but not being published in peer-reviewed literature). On the one hand, these results highlight a shortcoming in the optimal use of microscopy images; on the other hand, they indicate the existence of a large pool of electron microscopy data that can facilitate research in data science and the development of AI-based projects. The considerations important to unlock the potential of lost data are discussed in the present article. Full article

Cognitive deficiencies are significant factors affecting aviation piloting capabilities. However, due to the limited stability resulting from the insufficient appeal of traditional attention or memory cognitive training, multi-task gamified cognitive training (MTGCT) may be more beneficial in generating far transfer effects in task performance. This study explores the enhancement effects of simulated flight operation capabilities based on visuo-spatial attention and working memory MTGCT. Additionally, we explore the neurophysiological impacts through changes in EEG power spectral density (PSD) characteristics and brain asymmetry, and whether these impacts exhibit a certain retention effect. This study designed a 28-day simulated flight operation capability enhancement experiment. In addition, the behavioral performance and EEG signal changes in 28 college students (divided into control and training groups) were analyzed. The results indicated that MTGCT significantly enhanced simulated flight operational capabilities, and the neural framework formed by physiological changes remains effective for at least two weeks. The physiological changes included a decrease in the $\theta$ band PSD and an increase in the $\alpha$ band PSD in the frontal and parietal lobes due to optimized cognitive resource allocation, as well as the frontal $\theta$ band leftward asymmetry and the frontoparietal $\alpha$ band rightward asymmetry due to the formation of neural activity patterns. These findings support, to some extent, the feasibility and effectiveness of using MTGCT as a periodic training method to enhance the operational and cognitive abilities of aviation personnel. Full article

Imaging in controlled agriculture helps maximize plant growth by saving labor and optimizing resources. By monitoring specific plant traits, growers can prevent crop losses by correcting environmental conditions that lead to physiological disorders like leaf tipburn. This study aimed to identify morphometric and spectral markers for the early detection of tipburn in two Romaine lettuce (Lactuca sativa) cultivars (‘Chicarita’ and ‘Dragoon’) using an image-based system with color and multispectral cameras. By monitoring tipburn in treatments using melatonin, lettuce cultivars, and with and without supplemental lighting, we enhanced our system’s accuracy for high-resolution tipburn symptom identification. Canopy geometrical features varied between cultivars, with the more susceptible cultivar exhibiting higher compactness and extent values across time, regardless of lighting conditions. These traits were further used to compare simple linear, logistic, least absolute shrinkage and selection operator (LASSO) regression, and random forest models for predicting leaf fresh and dry weight. Random forest regression outperformed simpler models, reducing the percentage error for leaf fresh weight from ~34% (LASSO) to ~13% (RMSE: 34.14 g to 17.32 g). For leaf dry weight, the percentage error decreased from ~20% to ~12%, with an explained variance increase to 94%. Vegetation indices exhibited cultivar-specific responses to supplemental lighting. ‘Dragoon’ consistently had higher red-edge chlorophyll index (CIrededge), enhanced vegetation index, and normalized difference vegetation index values than ‘Chicarita’. Additionally, ‘Dragoon’ showed a distinct temporal trend in the photochemical reflectance index, which increased under supplemental lighting. This study highlights the potential of morphometric and spectral traits for early detection of tipburn susceptibility, optimizing cultivar-specific environmental management, and improving the accuracy of predictive modeling strategies. Full article

Recent evidence demonstrates that mitral valve prolapse (MVP) increases mechanical stress on the subvalvular apparatus and is linked to regional myocardial fibrosis and life-threatening ventricular arrhythmias. However, current surgical guidelines do not account for the extent of myocardial fibrosis or the severity of leaflet involvement, both key features of arrhythmogenic MVP. To address this gap, we conducted histopathological analysis of endomyocardial biopsies from patients with MVP and regionalized myocardial fibrosis (n = 6) who underwent mitral valve repair. Using digital pathology-based quantitative image analysis (QIA), we found that fibrosis in peri-papillary biopsies exhibited a significantly higher Morphometric Composite Score compared with remote biopsies (5.68 ± 0.69 vs. 3.71 ± 0.49, p = 0.042), reflecting larger, more branched, and more assembled collagen fibers, indicative of a mature and persistent fibrotic phenotype. These findings suggest that myocardial scarring in MVP is well-established by the time of surgery and underscore the potential value of earlier surgical intervention to reduce the risk of arrhythmia and preserve post-operative left ventricular function. Full article