Search Results (7,402)

This study investigates the seismic performance of the V3.0 220 kV standard-designed substation of the Southern Power Grid, located in a high-intensity seismic zone, with a focus on the application of seismic isolation technology. Seismic isolation and structural analysis were conducted and shaking table tests were performed on both isolated and non-isolated structural models. A total of 40 tests were carried out using three levels of ground motion intensity (i.e., 140 gal, 400 gal, and 800 gal) and in three directions (unidirectional, bidirectional, and triaxial). The dynamic characteristics, seismic response, and isolation effectiveness were evaluated. Results indicate that the test models exhibit strong agreement with theoretical and numerical predictions, with an average frequency deviation of 10.98%. The fundamental period of the isolated structure was extended by a factor of 2.33 compared to the non-isolated configuration. As the peak ground acceleration increased, structural frequency decreased, and the period increased. The isolated structure showed a lower first-period growth rate (4.82%) than the non-isolated structure (15.38%). Even under 800 gal excitations, the isolated structure remained within the elastic range. Seismic isolation significantly reduced structural response, with a control effectiveness exceeding 50%, enabling a one-degree reduction in seismic design intensity. A vulnerability analysis based on 200 simulated earthquake cases revealed that the isolated structure exhibited lower failure probabilities across four performance states. At 600 gal PGA, the failure probability in the LS3 state was reduced by 27.8%. These findings confirm the effectiveness and reliability of seismic isolation design for substations in high seismic intensity regions. Full article

Objective: The present study aimed to evaluate the feasibility and safety of performing extubation in the operating room following aortic valve replacement (AVR) via right anterior mini-thoracotomy (RAMT), as the safety profile of this approach has not been fully established. Methods: We conducted a retrospective analysis of patients who underwent isolated AVR through a RAMT between February 2012 and December 2023. Emergency cases and reoperations were excluded. Patients were categorized according to the location of extubation—either in the operating room (on-table) or in the intensive care unit (ICU). Multivariable logistic regression analysis was used to identify predictors associated with successful on-table extubation. Results: Among 423 patients who underwent non-emergent isolated AVR, 73.3% were extubated in the operating room. This group was characterized by younger age, lower EuroSCORE II, and higher preoperative serum albumin levels. While the surgical techniques did not differ between groups, those extubated on-table had significantly shorter cardiopulmonary bypass times (84.0 [68.0–104.0] vs. 104.0 [85.0–131.5], p < 0.001). Although early postoperative outcomes were comparable, the on-table extubation group had significantly shorter ICU stays (24.0 [22.0–26.0] vs. 25.0 [23.0–30.0], p < 0.001) and hospital stays (5.0 [4.0–6.0] vs. 6.0 [5.0–8.0], p < 0.001). A predictive model incorporating age, albumin levels, and cardiopulmonary bypass time demonstrated a predictive accuracy of approximately 78.4% for on-table extubation success. Conclusions: Extubation in the operating room was found to be both safe and effective for the majority of patients undergoing isolated AVR via RAMT. It was associated with low reintubation rates and significantly reduced lengths of ICU and hospital stays. These findings support the adoption of routine on-table extubation in suitable patients undergoing this procedure. Full article

Amberboa moschata (L.) DC. (Asteraceae) is an endangered species, listed in the Red Book of Plants of the Republic of Armenia. The restricted extent of occurrence and habitat degradation necessitate conservation measures of this species, not only in the wild but also through ex situ cultivation. This study examines the comprehensive morpho-phenological, karyological, palynological, eco-physiological, and ornamental characteristics of A. moschata in the context of ex situ conservation. A. moschata plants cultivated ex situ demonstrated high adaptive traits, undergoing a full development cycle and experiencing less water stress compared to wild populations. The diploid cytotype has been found for the species to be 2n = 32, the karyotype is asymmetric, with chromosomes, 0.77–1.91 µm in size. The average pollen fertility of A. moschata is high, 96.7–96.9% in both natural and cultivated samples. A scale of decorativeness was developed, which includes 15 characteristics of the plant, providing an objective means to assess its visual appeal. The scale can be useful for integrating A. moschata into various landscaping schemes. Under cultivation, the total ornamental period lasts approximately 98 days, with the peak ornamental effect observed during the flowering phase, which spans 68–70 days. The study recommends A. moschata for inclusion in living collections in botanical gardens and for use in ornamental gardening and landscaping as part of its ex situ conservation strategy. A map, original photographs, and tables illustrate the article. Full article

Time-of-flight (ToF) 3D cameras can obtain a real-time point cloud of human respiratory motion in medical robot scenes. Through this point cloud, real-time displacement information can be provided for the medical robot to avoid the robot injuring the human body during the operation due to the positioning deviation. However, multi-camera deployments face a conflict between spatial coverage and measurement accuracy due to the limitations of different types of ToF modulation. To address this, we design a multi-camera acquisition system incorporating different modulation schemes and propose a multi-view voxelized point cloud fusion algorithm utilizing a two-dimensional voxel block index table. Our algorithm first constructs a voxelized scene from multi-view depth maps. Then, the two-dimensional voxel block index table estimates and reconstructs overlapping regions across views. Experimental results demonstrate that fusing multi-view point clouds from low-precision 3D cameras achieves accuracy comparable to high-precision systems while maintaining the extensive spatial coverage of multi-view configurations. Full article

This article describes an effective computing method for singularly perturbed parabolic problems with small negative shifts in convection and reaction terms. To handle the small negative shifts, the Taylor series expansion is used. The asymptotically equivalent singularly perturbed parabolic convection–diffusion–reaction problem is then discretized with the Crank–Nicolson method on a uniform mesh for the time derivative and a hybrid method on Shishkin-type meshes for the space derivative. The method’s stability and parameter-uniform convergence are established. To substantiate the theoretical findings, the numerical results are presented in tables and graphs are plotted. The present results improve the existing methods in the literature. Due to the effect of the small negative shifts in Examples 1 and 2, the numerical results using Shishkin and Bakhvalov–Shishkin meshes are almost the same. Since there are no small shifts in Examples 3 and 4, the numerical results using the Bakhvalov–Shishkin mesh are more efficient than using the Shishkin mesh. We conclude that the present method using the Bakhvalov–Shishkin mesh performs well for singularly perturbed problems without small negative shifts. Full article

The adoption of artificial intelligence (AI) in sports training has the potential to revolutionize skill development, yet cost-effective solutions remain scarce, particularly in table tennis. To bridge this gap, we present an intelligent training system leveraging computer vision and machine learning for real-time performance analysis. The system integrates YOLOv5 for high-precision ball detection (98% accuracy) and MediaPipe for athlete posture evaluation. A dynamic time-wrapping algorithm further assesses stroke effectiveness, demonstrating statistically significant discrimination between beginner and intermediate players (p = 0.004 and Cohen’s d = 0.86) in a cohort of 50 participants. By automating feedback and reducing reliance on expert observation, this system offers a scalable tool for coaching, self-training, and sports analysis. Its modular design also allows adaptation to other racket sports, highlighting broader utility in athletic training and entertainment applications. Full article

This study addresses the need for effective, real-time monitoring of indoor air quality, a critical factor for health and environmental well-being. The aim is to develop an affordable, Arduino-based IoT sensor system capable of continuous measurement of key air pollutants, including CO₂, PM_2.5, NO₂, and VOCs. The system integrates multiple sensors and transmits data to an online server, where it is stored in a MySQL database for analysis and visualization. Validation studies conducted at Concordia University and Qatar University confirm the system’s accuracy and reliability, with discrepancies reduced to under 15% through calibration and adjustment techniques. Comparative analysis with commercial monitoring instruments reveals strong correlations and negligible deviations, supporting the system’s validity for real-time air quality monitoring. The system also includes a user-friendly interface that displays real-time data through intuitive charts and tables, along with an indoor air quality index to help users assess and address air pollution levels. The system demonstrates a 90% cost reduction versus commercial tools while maintaining a mean deviation of <15% across climatic extremes. Its combination of comprehensive sensors, data visualization tools, and an air quality index makes it an effective tool for environmental monitoring and decision-making. Full article

Text-to-SQL leverages large language models (LLMs) for natural language database queries, yet existing benchmarks like BIRD (12,751 question–SQL pairs, 95 databases) suffer from inconsistencies—e.g., 30% of queries misalign with SQL outputs—and ambiguities that impair LLM evaluation. This study refines such datasets by distilling logically sound question–SQL pairs and enhancing table schemas, yielding a benchmark of 146 high-complexity tasks across 11 domains. We assess GPT-4o, GPT-4o-Mini, Qwen-2.5-Instruct, llama 370b, DPSK-v3 and O1-Preview in zero-shot scenarios, achieving average accuracies of 51.23%, 41.65%, 44.25%, 47.80%, and 49.10% and a peak of 78.08% (O1-Preview), respectively. Prompt-based strategies improve performance by up to 4.78%, addressing issues like poor domain adaptability and inconsistent training data interpretation. Error-annotated datasets further reveal LLM limitations. This refined benchmark ensures robust evaluation of logical reasoning, supporting reliable NLP-driven database systems. Full article

Low-Earth-Orbit (LEO) satellite networks offer a promising avenue for achieving global connectivity, despite certain technical and economic challenges such as high implementation costs and the complexity of network management. Nonetheless, real-time routing remains challenging because of rapid topology changes and strict energy constraints. This paper proposes a GPU-accelerated Eclipse-Aware Routing (EAR) method that simultaneously minimizes hop count and balances energy consumption for real-time routing on an onboard computer (OBC). The approach first employs a Breadth-First Search (BFS)–based K-Shortest Paths (KSP) algorithm to generate candidate routes and then evaluates battery usage to select the most efficient path. In large-scale networks, the computational load of the KSP search increases substantially. Therefore, CUDA-based parallel processing was integrated to enhance performance, resulting in a speedup of approximately 3.081 times over the conventional CPU-based method. The practical applicability of the proposed method is further validated by successfully updating routing tables in a SpaceWire network. Full article

We present the first fully curated, publicly accessible archive of infrasonic records from ten large bolide events documented by the U.S. Air Force Technical Applications Center’s global microbarometer network between 1960 and 1972. Captured on analog strip-chart paper, these waveforms predate modern digital arrays and space-based sensors, making them a unique window on meteoroid activity in the mid-twentieth century. Prior studies drew important scientific conclusions from the records but released only limited artifacts, chiefly period–amplitude tables and unprocessed scans, leaving the underlying data inaccessible for independent study. The present release transforms those limited excerpts into a research-ready resource. By capturing ten large events in the mid-20th century, the dataset constitutes a critical reference point for assessing bolide activity before the advent of modern space-based and digital ground-based monitoring. The multi-year coverage and worldwide distribution of events provide a valuable reference for comparing past and more recent detections, facilitating assessments of long-term flux and the dynamics of acoustic wave propagation in Earth’s atmosphere. The dataset’s availability in a consolidated format ensures straightforward access to waveforms and derived measurements, supporting a wide range of scientific inquiries into bolide physics and infrasound monitoring. By preserving these historical acoustic observations, the collection maintains a significant record of mid-20th-century meteoroid entries. It thereby establishes a basis for further refinement of impact hazard evaluations, contributes to historical continuity in atmospheric observation, and enriches the study of meteoroid-generated infrasound signals on a global scale. Full article

In the current paper, an analysis of magnetohydrodynamic Williamson nanofluid boundary layer flow is presented, with multiple slips in a porous medium, using a newly designed human-brain-inspired Ricker wavelet neural network solver. The solver employs a hybrid approach that combines genetic algorithms, serving as a global search method, with sequential quadratic programming, which functions as a local optimization technique. The heat and mass transportation effects are examined through a stretchable surface with radiation, thermal, and velocity slip effects. The primary flow equations, originally expressed as partial differential equations (PDEs), are changed into a dimensionless nonlinear system of ordinary differential equations (ODEs) via similarity transformations. These ODEs are then numerically solved with the proposed computational approach. The current study has significant applications in a variety of practical engineering and industrial scenarios, including thermal energy systems, biomedical cooling devices, and enhanced oil recovery techniques, where the control and optimization of heat and mass transport in complex fluid environments are essential. The numerical outcomes gathered through the designed scheme are compared with reference results acquired through Adam’s numerical method in terms of graphs and tables of absolute errors. The rapid convergence, effectiveness, and stability of the suggested solver are analyzed using various statistical and performance operators. Full article

This paper introduces LocRecNet, a deformation-aware network for table localization and correction, aimed at improving the recognition accuracy of complex table data. Conventional algorithms typically depend on table cell or line features for model training but exhibit limitations when processing real-world deformed table data. LocRecNet addresses these challenges by correcting deformations prior to table structure recognition, significantly enhancing model performance. The proposed network employs a novel keypoint detection method to precisely locate table edge points, enabling the efficient correction of deformed tables. Experimental results reveal that integrating LocRecNet substantially improves table recognition algorithms in terms of various key performance metrics, with recall rates increasing by up to 10% and F1 scores nearing 90%. Tests conducted on real-world datasets further validate its effectiveness, demonstrating a reasonable trade-off between computational cost and performance gains. Additionally, LocRecNet enhances performance even on standard table data, highlighting its strong generalizability and potential for broader application. Full article

Effective molecular imaging and targeted cancer therapy rely on receptor-specific targeted delivery systems that are both metabolically stable and kinetically inert for optimal in vivo performance. Until now, no single metal complexing agent has demonstrated the versatility to coordinate metals across the periodic table while maintaining the kinetic inertness required for clinical theranostic applications. Therefore, enhancing the in vivo kinetic stability of radiolabeled, cell-targeting, biologically active compounds remains a critical goal to minimize unintended accumulation of radioactivity in collateral tissues. This review describes the usage of NOTA [NOTA = 1,4,7-triazacyclononane-1,4,7-triacetic acid] and derivatives of NOTA, a metal complexing agent that has been found to have the ability to effectively coordinate with a wide range of radiometals, including metal-radiohalogens, to form stable complexes. This enables the development of new cell-targeting small molecule and peptide conjugates with the potential to resist demetallation in vivo, thereby reducing radionuclide uptake in non-target tissues. Herein, we discuss the design and development of NOTA-based, cell-targeting, small molecules having very high affinity and selectivity for the GRPR (Gastrin-Releasing Peptide Receptor), the SSTR2 (Somatostatin Receptor Subtype 2), and the MC1R (Melanocortin-1) receptors that are present on the surfaces of numerous solid primary human tumors and their metastatic counterparts. Full article

Background: Most studies on polyphenols and antioxidant activity focus on raw ingredients, often overlooking the impact of technological processes—a gap that is particularly notable given that many population studies rely on theoretical calculations from nutritional databases. Therefore, it is essential to verify whether these theoretical values align with experimental findings on model dishes and to determine the extent to which processing affects polyphenol content and antioxidant activity in processed foods. Methods: As model dishes, this study analyzed soups prepared through thermal processing, along with commercially available ready-to-eat and instant soups. Total polyphenol content was measured using the Singleton–Rossi method, while antioxidant activity was assessed using the FRAP (ferric-reducing antioxidant potential) method and an electrochemical method. Theoretical calculations were performed based on original recipes from Polish nutritional value tables, as well as data from available polyphenol and antioxidant activity databases for raw ingredients. Results: The total polyphenol content varied significantly between experimental measurements and theoretical calculations, with deviations ranging from −42% to +1370%. FRAP antioxidant activity also differed, ranging from −62% to +524%, depending on the type of soup. The polyphenol content in homemade soups ranged from 3.692 to 16.534 mg GAE/100 mL, in ready-to-eat soups from 4.387 to 18.431 mg GAE/100 mL, and in instant soups from 1.624 to 7.254 mg GAE/100 mL, with tomato soups consistently having the highest polyphenol content across all categories. FRAP values ranged from 0.021 to 0.189 mmol/100 g in homemade soups, 0.029 to 0.269 mmol/100 g in ready-to-eat soups, and 0.033 to 0.134 mmol/100 g in instant soups, with tomato soups again showing the highest FRAP values. Antioxidant activity measured electrochemically ranged from 44.410 to 52.467 mC/g in homemade soups, 22.750 to 58.900 mC/g in ready-to-eat soups, and 22.515 to 47.680 mC/g in instant soups, with broccoli soups showing the highest values. Conclusions: This study demonstrates that theoretical models alone are insufficient for accurately determining polyphenol content and antioxidant activity in food, reinforcing the importance of experimental validation in processed food. Full article

During emergency evacuations, pedestrians may use three-dimensional (3D) motions, such as low crawling and climbing up/down, to navigate above or below indoor objects (e.g., tables, chairs, and stair flights). Understanding how these motions influence evacuation processes can facilitate the development of behavioural instructions. This study examines the influence of 3D motions through a simulation-based method. This method combines a voxel-based 3D indoor model with an agent-based model. Three use case studies are elaborated upon, considering varying building types, agent numbers, urgency levels, and demographic differences. These case studies serve as exploratory demonstrations rather than validated simulations grounded in real-world evacuation experiments. Our findings are as follows: (1) Three-dimensional motions may create alternative and local 3D paths, enabling agents to bypass congestion, particularly in narrow corridors and confined spaces. (2) While 3D motions may help alleviate local congestion, they may intensify bottlenecks near exits, especially in highly crowded and high-urgency scenarios. (3) As urgency and agent numbers increase, differences in evacuation efficiency between scenarios with and without 3D motions are likely to diminish. We suggest further investigation into evacuation behavioural instructions, including the following: (1) conditional use of 3D motions in different buildings and (2) instructions tailored to different demographic groups. These use cases illustrate new directions for evacuation managers to consider the incorporation of 3D motions. Full article