Search Results (457)

Green technological innovation integrates the two major strategies of innovation-driven development and green development and serves as a crucial pathway to achieving the goal of high-quality and sustainable development in the Yangtze River Economic Belt (YREB). Against the backdrop of regional integration, it is of great significance to study the coordinated development trend of green technological innovation, with urban agglomerations as the unit of study. This study takes 108 cities in the YREB as research objects, constructs a Green Technological Innovation Efficiency (GTIE) measurement framework based on a two-stage DEA model, and decomposes GTIE into Technological Innovation Efficiency (TIE) and Green Production Capacity (GCP). On this basis, using the System GMM model, this study examines the mechanism by which the economic connection structure affects GTIE, TIE, and GCP from the perspective of urban agglomeration spatial networks. The empirical results show that from 2006 to 2020, the overall GTIE of the YREB showed a steady upward trend, and its spatial pattern evolved from “high in the east and low in the west” to “coordinated development of the three major urban agglomerations.” The three urban agglomerations played a core leading role in the diffusion of regional green innovation. Specifically, the economic integration development of urban agglomeration spatial networks significantly promoted the improvement of GTIE; the spatial network structure of TIE within the urban agglomerations exerted a significant positive spillover effect on GCP, while the GCP network structure also showed a significant feedback effect on TIE. Overall, through strengthening the inter-city flow of innovative factors and collaboration, regional integration has effectively promoted the coordinated growth and diffusion of green technological innovation, providing important support for the high-quality improvement of regional productivity and contributing to the sustainable development of the region. Full article

Background: Temporomandibular disorders (TMDs) exhibit a complex relationship with depression, anxiety disorders, and oral behaviors. This cross-sectional study aimed to assess the differences in oral behaviors among subgroups of TMD-related pain and patients with varying levels of anxiety and depression. Methods: A total of 120 patients diagnosed with TMD according to the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD), completed the Oral Behavior Checklist (OBC), Visual Analog Scale (VAS), Patient Health Questionnaire-9 (PHQ-9), General Anxiety Disorder (GAD-7), Graded Chronic Pain Scale (GCPS), Patient Health Questionnaire-15 (PHQ-15), and Jaw Functional Limitation Scale-8 (JFLS-8). Associations were examined using Chi-square, Fisher’s exact, and Spearman’s correlation; logistic regression and multivariable linear regression were performed (p < 0.05). Results: In univariate analyses, several item-level OBs were more prevalent with higher anxiety, including nocturnal bruxism, sleep positions exerting jaw pressure, daytime grinding, and gum chewing (p = 0.007, 0.041, 0.011, and 0.014, respectively). A modest difference among pain subgroups was observed for sleep position (p = 0.044). In multivariable models, anxiety was independently associated only with nocturnal bruxism (OR = 2.95; 95% CI: 1.30–6.67; p = 0.010), whereas depression showed no independent associations. Pain intensity remained the sole predictor of total OBC scores (Coef = 1.829; 95% CI: 0.51–3.15; p = 0.007). No independent effects were detected for TMD subgroups. Conclusions: Psychosocial factors appeared related to OBs in univariate analyses, but these associations were explained by confounding influences. After adjustment, pain intensity and anxiety emerged as key determinants. These findings highlight the need for comprehensive TMD management integrating pain control with behavioral strategies. Full article

Unmanned Aerial Vehicle (UAV) photogrammetry technique offers significant potential for generating highly detailed digital surface models (DSM) of gullies. However, different flight schemes can considerably influence measurement accuracy. The objectives were (i) to evaluate the influences of flight altitude, photo overlap, Ground Control Points (GCPs), and other environmental factors on the accuracy of the UAV-derived DSMs and (ii) to analyze the main factors affecting the accuracy of UAV gully monitoring and explore flight schemes that balance accuracy and efficiency. The results indicated that DSM accuracy improved markedly as the number of GCPs increased from 0 to 3, with consideration given to both horizontal and vertical distribution. However, further increases in the number of GCPs did not lead to significant improvements. The accuracy of DSMs increased with a decrease in the flight altitude, but was not substantially affected by photo overlap when it exceeded 50%/40% The accuracy of DSM was significantly reduced by shadows, and flight altitude rather than slope gradient was identified as the key factor leading to high-error checkpoints (error > 0.1 m). The proportion of point clouds penetrating tree canopies decreased when the flight altitude was 150 m or higher, which could help reduce the influence of vegetation on the accuracy of DSMs. In general, with a reasonable spatial distribution of GCPs, flight altitude is the primary factor affecting monitoring accuracy. However, when balancing accuracy and efficiency, the optimal flight scheme was determined to be a flight altitude of 70 m, photo overlap of 80%/70%, and nine GCPs. Full article

Real-time kinematic (RTK) unmanned aerial vehicles (UAVs) have become more popular in recent years, mostly because they can reduce the number of ground control points (GCPs) that have to be measured in the field and are required for aerial triangulation. Additionally, thanks to RTK technology, every image has its exterior orientation parameters measured with centimeter accuracy; thus, the block is more stable and there is a lower risk of some geometric distortions appearing within the block, especially in its central part. In this article, the influence of RTK observations on image orientation is analyzed based on a planned UAV test field in Józefosław, near Warsaw, Poland. As part of the experiment, UAV flights with DJI Phantom 4 RTK and DJI Phantom 4 Pro V2.0 were conducted, and 38 GCPs were located in the area. The results show that RTK observations from UAVs can significantly improve the accuracy of aerial triangulation, as inclusion of oblique images also does. For Phantom 4 RTK images, a single GCP was generally sufficient to achieve satisfactory accuracy, whereas six GCPs were required for the Phantom 4 Pro V2.0. Full article

High-resolution pushbroom satellites routinely acquire multi-tenskilometer-scale strips whose vendors’ rational polynomial coefficients (RPCs) exhibit systematic, direction-dependent biases that accumulate downstream when ground control is sparse. This study presents a physically interpretable stripwise extrapolation framework that predicts along- and across-track RPC correlation coefficients for inaccessible segments from an upstream calibration subset. Terrain-independent RPCs were regenerated and residual image-space errors were modeled with weighted least squares using elapsed time, off-nadir evolution, and morphometric descriptors of the target terrain. Gaussian kernel weights favor calibration scenes with a Jarque–Bera-indexed relief similar to the target. When applied to three KOMPSAT-3A panchromatic strips, the approach preserves native scene geometry while transporting calibrated coefficients downstream, reducing positional errors in two strips to <2.8 pixels (~2.0 m at 0.710 m Ground Sample Distance, GSD). The first strip with a stronger attitude drift retains 4.589 pixel along-track errors, indicating the need for wider predictor coverage under aggressive maneuvers. The results clarify the directional error structure with a near-constant across-track bias and low-frequency along-track drift and show that a compact predictor set can stabilize extrapolation without full-block adjustment or dense tie networks. This provides a GCP-efficient alternative to full-block adjustment and enables accurate georeferencing in controlled environments. Full article

Practicing medical research based on the best evidence is gaining increased value and popularity among most medical societies in the current era. Good clinical practice (GCP) is internationally recognized as the scientific and ethical standard for the design, conduct, performance, auditing, recording, analysis, and reporting of clinical trials involving human subjects. GCP ensures the accuracy and credibility of trial while safeguarding the rights, integrity, and confidentiality of participants. Adherence to GCP facilitates the generation of high-quality studies that can be incorporated in Evidence-Based Medicine (EBM). The clinical practice of EBM seeks to integrate robust medical literature into daily medical practice. This process involves systematically searching for high-quality evidence, critically appraising the retrieved literature, applying sound clinical principles and finally evaluating the efficacy of the chosen approach. Although EBM has been evaluated in many resource settings, it has not been addressed sufficiently in the field of Pediatrics and more specifically in indigenous populations. In this review, we briefly explain the EBM approach and its applications in Pediatrics, in order to help physicians care for young subjects more efficiently by integrating the best available information into their routine clinical practice. Also, the basic good practice principles for conducting clinical trials in children and adolescents are highlighted, emphasizing the importance of applying high ethical principles in this vulnerable population. Full article

Bundle adjustment without Ground Control Points (GCPs) using stereo remote sensing images represents a reliable and efficient approach for realizing the demand for regional and global mapping. This paper proposes a bundled-images based geo-positioning method that leverages a Kalman filter to effectively integrate new image observations with their corresponding historical bundled images. Under the assumption that the noise follows a Gaussian distribution, a linear mean square estimator is employed to orient the new images. The historical bundled images can be updated with posterior covariance information to maintain consistent accuracy with the newly oriented images. This method employs recursive computation to dynamically orient the new images, ensuring consistent accuracy across all the historical and new images. To validate the proposed method, extensive experiments were carried out using two satellite datasets comprising both homologous (IKONOS) and heterogeneous (TH-1 and ZY-3) sources. The experiment results reveal that without using GCPs, the proposed method can meet 1:50,000 mapping standards with heterogeneous TH-1 and ZY-3 datasets and 1:10,000 mapping accuracy requirements with homologous IKONOS datasets. These experiments indicate that as the bundled images expand further, the image quantity growth no longer results in substantial improvements in precision, suggesting the presence of an accuracy ceiling. The final positioning accuracy is predominantly influenced by the initial bundled image quality. Experimental evidence suggests that when using the proposed method, the bundled image sets should exhibit superior precision compared to subsequently new images. In future research, we will expand the coverage to regional or global scales. Full article

This study evaluates the positional accuracy of Global Navigation Satellite Systems (GNSS) and Unmanned Aerial vehicle (UAV)-based LiDAR systems in terrain modeling, using a total station as a reference. The research was conducted over 17 Ground Control Points (GCPs), with measurements obtained using a CHCNAV i50 GNSS receiver and a DJI Zenmuse L1 Light Detection and Ranging (LiDAR) sensor mounted on a UAV. Accuracy was assessed for horizontal (X, Y) and vertical (Z) components by comparing the results against total station data. Errors were quantified using statistical metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and RMS at 1σ. GNSS exhibited superior horizontal accuracy with an RMS 1σ of 1.1 cm, while LiDAR achieved 1.7 cm. In contrast, GNSS outperformed LiDAR in vertical precision, achieving a 1σ RMS of 6.4 cm compared to 6.6 cm for LiDAR. These findings align with manufacturer specifications and international standards such as those of the American Society for Photogrammetry and Remote Sensing (ASPRS). The results highlight that GNSS is preferable for applications requiring high horizontal precision, while LiDAR is better suited for vertical modeling and terrain analysis. The combination of both systems may offer enhanced results for comprehensive geospatial surveys. Overall, both technologies demonstrated sub-decimetric accuracy suitable for precision agriculture, civil engineering, and environmental monitoring. Full article

This study evaluates the performance of the Precise Point Positioning with Ambiguity Resolution (PPP-AR) method under varying durations and software platforms in determining the optimal placement of Ground Control Points (GCPs) for use in photogrammetric products generated by Unmanned Aerial Vehicles (UAVs) over valley-type rugged terrain. In the field experiment, six GCPs and twenty checkpoints were established, and GNSS measurements with 5-s intervals were collected for 2 h at the GCPs. The collected GNSS data were segmented into 3-min and 10-min intervals, and PPP-AR-based solutions were generated for the complete datasets as well as for the 3- and 10-min subsets. The software tools used for PPP-AR processing included CSRS-PPP, Pride PPP-AR, PPP Arisen, and raPPPid. Eleven photogrammetric models were constructed using the coordinates obtained, and their accuracies were assessed using the checkpoints. The results indicate that, in terms of horizontal accuracy, the best performance was achieved using CSRS-PPP and Pride PPP-AR with 10-min observation durations. The static GNSS method yielded the most precise results for vertical accuracy, while among PPP-AR solutions the 10-min CSRS-PPP application demonstrated superior performance. Additionally, models were generated using only three GCPs placed according to different strategies, revealing that satisfactory levels of accuracy can be achieved when GCPs are strategically positioned. This study demonstrates that the PPP-AR method can be reliably utilized for high-accuracy GCP acquisition within short durations, even in challenging terrain conditions. Full article

Our previous studies identified the Gcp/TsaD protein as essential for Staphylococcus aureus survival and implicated it in tRNA modification. Here, we demonstrate its broader role in bacterial physiology. Through a morphological analysis, RNA sequencing, network-based bioinformatics, and antibiotic susceptibility testing, we show that Gcp/TsaD influences cell morphology, cell wall integrity, transcriptional regulation, virulence, and antibiotic response. Gcp/TsaD depletion caused reduced cell size and increased cell wall thickness, suggesting its roles in cell division and peptidoglycan biosynthesis. The kinetic transcriptomic analysis revealed widespread changes in gene expression, particularly in the translation and amino acid biosynthesis pathways, supporting its function in maintaining translational fidelity via tRNA modification. Its depletion also upregulated the genes involved in cell envelope biosynthesis, including capsule formation, enhancing resistance to antimicrobial peptides, while downregulating the key virulence genes, indicating a role in pathogenicity. Functionally, the Gcp/TsaD-deficient cells were more susceptible to fosfomycin, reinforcing its importance in cell wall integrity. Together, these findings highlight the multifaceted contribution of Gcp/TsaD to S. aureus physiology and underscore its potential as a therapeutic target, particularly against antibiotic-resistant strains. Full article

Rehabilitation plans are based on pavement condition assessments, which are crucial to modern pavement management systems. However, some of the disadvantages of conventional approaches for road maintenance and repair include the time consumption, high costs, visual errors, seasonal limitations, and low accuracy. Continuous and efficient pavement monitoring is essential, necessitating reliable equipment that can function in a variety of weather and traffic conditions. UAVs offer a practical and eco-friendly alternative for tasks including road inspections, dam monitoring, and the production of 3D ground models and orthophotos. They are more affordable, accessible, and safe than traditional field surveys, and they reduce the environmental effects of pavement management by using less fuel and producing less greenhouse gas emissions. This study uses UAV technology in conjunction with ground control points (GCPs) to assess the kind and amount of damage in flexible pavements. Vertical photogrammetric mapping was utilized to produce 3D road models, which were then processed and analyzed using Agisoft Photoscan (Metashape Professional (64 bit)) software. The sorts of fractures, patch areas, and rut depths on pavement surfaces may be accurately identified and measured thanks to this technique. When compared to field exams, the findings demonstrated an outstanding accuracy with errors of around 3.54 mm in the rut depth, 4.44 cm² for patch and pothole areas, and a 96% accuracy rate in identifying cracked locations and crack varieties. This study demonstrates how adding GCPs may enhance the UAV image accuracy, particularly in challenging weather and traffic conditions, and promote sustainable pavement management strategies by lowering carbon emissions and resource consumption. Full article

Data Spaces appear to offer a solution to data sovereignty concerns in public cloud environments, which are managed by third parties and must therefore be considered potentially untrusted. The IDS Connector, a key component of Data Space architecture, acts as a secure gateway, enforcing data sovereignty by controlling data usage and ensuring that data processing occurs within a trusted and verifiable environment. This study compares the performance of cloud-native data sharing services offered by major cloud providers—Amazon, Microsoft, and Google—with Data Spaces services delivered via two connector implementations: the Dataspace Connector and the Prometheus-X Dataspace Connector. An extensive set of experiments reveals significant differences in the performance of cloud-native managed services, as well as between connector implementations and hosting methods. The results indicate that the differences in the performance of data sharing services are unexpectedly substantial between providers, reaching up to 187%, and that the performance of different connector implementations also varies considerably, with an average difference of 56%. This indicates that the choice of cloud provider and data space Connector implementation has a major impact on the performance of the designed solution. Full article

Adipose-derived mesenchymal stem cells (ASCs) have great potential in regenerative medicine due to their abundance and innate multi-lineage differentiation potential. However, the therapeutic efficacy of ASCs is often compromised by poor microenvironmental conditions in the damaged tissues after transplantation. In this study, we generated and assessed genetically modified ASCs that expressed granulocyte chemotactic protein-2 (GCP-2) and platelet-derived growth factor-β (PDGF-β). The results revealed that three-dimensional (3D)-cultured ASCs overexpressing GCP-2 and PDGF-β (3D-A/GP) yielded a significant increase in proangiogenic gene expression, cell migration, and endothelial tube formation in vitro. Moreover, the Matrigel plug assay revealed that 3D-A/GP formed functional blood vessels, and 3D-A/GP injection in a hind limb ischemia (HLI) model revealed higher blood flow recovery, limb salvage, and capillary density and lower apoptosis in mice, compared to the controls. Notably, 3D-A/GP exhibited differentiation into endothelial-like cells and upregulated expression of angiogenic factors in ischemic limb tissue. Our results highlight the value of using a combination of genetic engineering and 3D culture systems to improve the therapeutic effect of ASCs in terms of angiogenesis-dependent tissue repair. The dual modulation of GCP-2 and PDGF-β, in combination with 3D culture, presents a new and synergistic opportunity to maximize the use of ASC-based therapies for ischemic diseases and other regenerative medicine applications. Full article

Temporomandibular disorders (TMDs) encompass a heterogeneous group of musculoskeletal and neuromuscular conditions affecting the temporomandibular joint (TMJ) and masticatory system. Due to academic stress and parafunctional habits, dental students may be particularly vulnerable to TMD. Objective: To determine the prevalence of TMD symptoms and their psychosocial and functional correlates among students at the Faculty of Dental Medicine, UMPh Iasi, Romania, using the diagnostic criteria for TMD (DC/TMD) self-report axis and axis II instruments. Methods: In this cross-sectional survey, 356 volunteer students (66.0% female; mean age, 22.9 ± 3.6 years) out of a total population of 1874 completed an online DC/TMD–based questionnaire. Axis I assessed orofacial pain, joint noises, and mandibular locking. Axis II instruments included the Graded Chronic Pain Scale (GCPS), Jaw Functional Limitation Scale (JFLS-20), Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Oral Behaviors Checklist (OBC). Descriptive statistics summarized frequencies, means, and standard deviations; χ² tests and t-tests compared subgroups by sex; Pearson correlations explored relationships among continuous measures (α = 0.05). Results: A total of 5% of respondents reported orofacial pain in the past 30 days; 41.6% observed TMJ noises; 19.7% experienced locking episodes. Mean JFLS score was 28.3 ± 30.5, with 4.8% scoring > 80 (severe limitation). Mean PHQ-9 was 5.96 ± 5.37 (mild depression); 15.5% scored ≥ 10. Mean GAD-7 was 5.20 ± 4.95 (mild anxiety); 16.0% scored ≥ 10. Mean OBC score was 12.3 ± 8.5; 30.1% scored ≥ 16, indicating frequent parafunctional habits. Symptom prevalence was similar by sex, except temporal headache (43.4% females vs. 24.3% males; p = 0.0008). Females reported higher mean scores for pain intensity (2.09 vs. 1.55; p = 0.0013), JFLS (32.5 vs. 18.0; p < 0.001), PHQ-9 (6.43 vs. 5.16; p = 0.048), and OBC (13.9 vs. 9.7; p = 0.0014). Strong correlation was observed between PHQ-9 and GAD-7 (r = 0.74; p < 0.001); moderate correlations were observed between pain intensity and PHQ-9 (r = 0.31) or GAD-7 (r = 0.30), between JFLS and pain intensity (r = 0.33), and between OBC and PHQ-9 (r = 0.39) (all p < 0.001). Conclusions: Nearly half of dental students reported TMD symptoms, with appreciable functional limitation and psychosocial impact. Parafunctional behaviors and psychological distress were significantly associated with pain and dysfunction. These findings underscore the need for early screening, stress-management interventions, and interdisciplinary care strategies in the dental student population. Full article

Intrinsic parameter estimation by self-calibration is commonly used in Unmanned aerial vehicle (UAV)-based photogrammetry with Structure from Motion (SfM). However, obtaining stable estimates of these parameters from image-based SfM—which relies solely on images, without auxiliary data such as ground control points (GCPs)—remains challenging. Aerial imagery acquired with the constant-pitch (CP) flight pattern often exhibits non-linear deformations, highly unstable intrinsic parameters, and even alignment failures. We hypothesize that CP flights form a “critical configuration” that renders certain intrinsic parameters indeterminate. Through numerical experiments, we confirm that a CP flight configuration does not provide sufficient constraints to estimate focal length (f) and the principal point coordinate (cy) in image-based SfM. Real-world CP datasets further demonstrate the pronounced instability of these parameters. As a remedy, we show that by introducing intermediate strips into the CP flight plan—what we call a CP-Plus flight—can effectively mitigate the indeterminacy of f and cy in simulations and markedly improve their stability in all tested cases. This approach enables more effective image-only SfM workflows without auxiliary data, simplifies data acquisition, and improves three-dimensional reconstruction accuracy. Full article