Search Results (1,707)

To address the problems of traditional methods that rely on destructive sampling, the poor adaptability of fixed equipment, and the susceptibility of single-view angle measurements to occlusions, a non-destructive and portable device for three-dimensional phenotyping and biomass detection in lettuce was developed. Based on the Structure-from-Motion Multi-View Stereo (SFM-MVS) algorithms, a high-precision three-dimensional point cloud model was reconstructed from multi-view RGB image sequences, and 12 phenotypic parameters, such as plant height, crown width, were accurately extracted. Through regression analyses of plant height, crown width, and crown height, and the R² values were 0.98, 0.99, and 0.99, respectively, the RMSE values were 2.26 mm, 1.74 mm, and 1.69 mm, respectively. On this basis, four biomass prediction models were developed using Adaptive Boosting (AdaBoost), Support Vector Regression (SVR), Gradient Boosting Decision Tree (GBDT), and Random Forest Regression (RFR). The results indicated that the RFR model based on the projected convex hull area, point cloud convex hull surface area, and projected convex hull perimeter performed the best, with an R² of 0.90, an RMSE of 2.63 g, and an RMSEn of 9.53%, indicating that the RFR was able to accurately simulate lettuce biomass. This research achieves three-dimensional reconstruction and accurate biomass prediction of facility lettuce, and provides a portable and lightweight solution for facility crop growth detection. Full article

Background/Objectives: Curcumin is a promising therapy for glioblastoma but is limited by poor water solubility, rapid metabolism, and low blood–brain barrier penetration. This study aimed to evaluate curcumin and six curcumin derivatives with improved activity against a glioblastoma cell line and favorable absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Methods: Twenty-one curcumin derivatives were assessed and subjected to in vitro MTT cytotoxicity assays in SF268 glioblastoma and Vero cells. On the basis of the cytotoxicity results, six derivatives with the most favorable characteristics were selected for additional mechanistic studies, which included microtubule depolymerization, mitochondrial membrane potential (ΔΨm), and BAX activation assays. ADMET properties were determined in silico. Results: Compounds 2–4, 6, and 11 demonstrated better activity (IC₅₀: 0.59–3.97 µg/mL and SI: 3–20) than curcumin (IC₅₀: 6.3 µg/mL; SI: 2.5). Lead derivatives destabilized microtubules, induced ΔΨm collapse, and activated BAX. In silico ADMET prediction analysis revealed that compounds 4 and 6 were the most promising for oral administration from a biopharmaceutical and pharmacokinetic point of view. Conclusions: Strategic modifications were made to one or both hydroxyl groups of the aromatic rings of curcumin to increase its physicochemical stability and activity against glioblastoma cell line SF268. Compound 4, bearing fully protected aromatic domains, was identified as a prime candidate for in vivo validation and formulation development. Full article

The present study aimed to optimize amaranth microgreen production by evaluating key factors such as the seeding density (SD), substrate type (ST), electrical conductivity (EC), and the application intervals of the nutrient solution. A split-plot experimental design was employed, with three EC levels (tap water at 0.3 dS m⁻¹) and nutrient solutions at 1.0 (50% half-strength) and 2.0 dS m⁻¹ (100% full-strength) assigned to the main plots. The subplots combined two ST (coconut fiber and phenolic foam) with four SD (25, 50, 75, and 100 g m⁻²). Two experiments were conducted using this setup, varying the application intervals of water or nutrient solutions for either two or four hours. Asteca amaranth microgreens were cultivated for eight days (a total of 10 days from sowing). The traits analyzed were seedling height (SH), seedling fresh matter (SFM), SFM yield (SFMY), seedling dry matter (SDM), SDM yield (SDMY), water content in seedling, and water productivity of SFM. The results showed that using a half-strength nutrient solution was sufficient for amaranth production compared to using water alone. Coconut fiber outperformed phenolic foam across all evaluated parameters. Based on these findings, we recommend cultivating amaranth microgreens at a SD of 80 g m⁻² on coconut fiber substrate using a nutrient solution of 1.0 dS m⁻¹ EC applied at 2 h intervals. Full article

Low-altitude drones, which are unimpeded by traffic congestion or urban terrain, have become a critical asset in emergency rescue missions. To address the current lack of emergency rescue data, UAV aerial videos were collected to create an experimental dataset for action classification and localization annotation. A total of 5082 keyframes were labeled with 1–5 targets each, and 14,412 instances of data were prepared (including flight altitude and camera angles) for action classification and position annotation. To mitigate the challenges posed by high-resolution drone footage with excessive redundant information, we propose the SlowFast-Traffic (SF-T) framework, a spatio-temporal sequence-based algorithm for recognizing traffic accident rescue actions. For more efficient extraction of target–background correlation features, we introduce the Actor-Centric Relation Network (ACRN) module, which employs temporal max pooling to enhance the time-dimensional features of static backgrounds, significantly reducing redundancy-induced interference. Additionally, smaller ROI feature map outputs are adopted to boost computational speed. To tackle class imbalance in incident samples, we integrate a Class-Balanced Focal Loss (CB-Focal Loss) function, effectively resolving rare-action recognition in specific rescue scenarios. We replace the original Faster R-CNN with YOLOX-s to improve the target detection rate. On our proposed dataset, the SF-T model achieves a mean average precision (mAP) of 83.9%, which is 8.5% higher than that of the standard SlowFast architecture while maintaining a processing speed of 34.9 tasks/s. Both accuracy-related metrics and computational efficiency are substantially improved. The proposed method demonstrates strong robustness and real-time analysis capabilities for modern traffic rescue action recognition. Full article

This study presents an AI-enhanced pedestrian simulation model for subway stations, combining the Social Force Model (SFM) with LiDAR trajectory data from Samseong Station in Seoul. To reflect time-dependent behavioral differences, RMSProp-based optimization is performed separately for the morning peak, leisure hours, and evening peak, yielding time-specific parameter sets. Compared to baseline models with static parameters, the proposed method reduces prediction errors (MSE) by 50.1% to 84.7%. The model integrates adaptive learning rates, mini-batch training, and L2 regularization, enabling robust convergence and generalization across varied pedestrian densities. Its accuracy and modular design support real-world applications such as pre-construction design testing, post-opening monitoring, and capacity planning. The framework also contributes to Sustainable Urban Mobility Plans (SUMPs) by enabling predictive, data-driven evaluation of pedestrian flow dynamics in complex station environments. Full article

This study presents a critical evaluation of image-based 3D reconstruction techniques for small archaeological artifacts, focusing on a quantitative comparison between Neural Radiance Fields (NeRF), its recent Gaussian Splatting (GS) variant, and traditional Structure-from-Motion (SfM) photogrammetry. The research targets artifacts smaller than 5 cm, characterized by complex geometries and reflective surfaces that pose challenges for conventional recording methods. To address the limitations of traditional methods without resorting to the high costs associated with laser scanning, this study explores NeRF and GS as cost-effective and efficient alternatives. A comprehensive experimental framework was established, incorporating ground-truth data obtained using a metrological articulated arm and a rigorous quantitative evaluation based on root mean square (RMS) error, Chamfer distance, and point cloud density. The results indicate that while NeRF outperforms GS in terms of geometric fidelity, both techniques still exhibit lower accuracy compared to SfM, particularly in preserving fine geometric details. Nonetheless, NeRF demonstrates strong potential for rapid, high-quality 3D documentation suitable for visualization and dissemination purposes in cultural heritage. These findings highlight both the current capabilities and limitations of neural rendering techniques for archaeological documentation and suggest promising future research directions combining AI-based models with traditional photogrammetric pipelines. Full article

The confluence of financial constraints, climate change mitigation efforts, and evolving user expectations has significantly transformed the concept of facility management (FM). Traditional FM has now evolved to enhance sustainability in the built environment. Sustainable facility management (SFM) can add value to companies, organizations, and governments by balancing the financial, environmental, and social outcomes of the FM processes. The systematic literature review revealed a limited number of studies developing a performance measurement framework for SFM in office buildings and/or other building types in the literature. Given that the lack of this theoretical basis inhibits the effective deployment of SFM practices, this study aims to fill this gap by developing a performance measurement framework for SFM in office buildings. Accordingly, an in-depth literature review was initially conducted to synthesize sustainable performance measurement factors. Next, a series of focus group discussion (FGD) sessions were organized to refine and verify the factors and develop a novel performance measurement framework for SFM. Lastly, consistency analysis, the Bayesian best worst method (BBWM), and sensitivity analysis were implemented to determine the priorities of the factors. What the proposed framework introduces is the combined use of two performance measurement mechanisms, such as continuous performance measurement and comprehensive performance measurement. The continuous performance measurement is conducted using high-priority factors. On the other hand, the comprehensive performance measurement is conducted with all the factors proposed in this study. Also, the BBWM results showed that “Energy-efficient material usage”, “Percentage of energy generated from renewable energy resources to total energy consumption”, and “Promoting hybrid or remote work conditions” are the top three factors, with scores of 0.0741, 0.0598, and 0.0555, respectively. Moreover, experts should also pay the utmost attention to factors related to waste management, indoor air quality, thermal comfort, and H&S measures. In addition to its theoretical contributions, the paper makes practical contributions by enabling decision makers to measure the SFM performance of office buildings and test the outcomes of their managerial processes in terms of performance. Full article

This paper compares two methods, inferential statistics and Systems Dynamics, to study the evolution of individual happiness after a single dose of drug consumption. In an application case, the effect of alcohol and caffeine on happiness is analyzed through a single-case experimental design, with replication, involving two participants. Both inferential statistical analysis and Systems Dynamics methods have been used to analyze the results. Two scales were used to measure happiness—the Euphoria Scale (ES) and the Smiling Face Scale (SFS)—in trait and state format. A single-case experimental ABC design was used. Phase A had no treatment, and Phases B and C saw both subjects receiving 26.51 mL of alcohol and 330 mg of caffeine, respectively. The participants filled in a form with both scales in a state format every 10 min over a 3 h period, operating in each one of the three phases A, B and C. The main conclusion of the analysis performed is that both methods provide similar results about the evolution of individual happiness after single dose consumption. Therefore, the article shows that inferential statistics and the stimulus response model derived from the Systems Dynamics approach can be used in a complementary and enriching way to obtain prediction results. Full article

Mangrove forests are vital blue carbon (BC) ecosystems that significantly contribute to climate change mitigation through carbon sequestration. Accurate, scalable, and cost-effective methods for estimating carbon stocks in these environments are essential for conservation planning. In this study, we assessed the potential of drones, also known as unmanned aerial vehicles (UAVs), for estimating above-ground biomass (AGB) and BC in Avicennia marina stands by integrating drone-based canopy measurements with field-measured tree heights. Using structure-from-motion (SfM) photogrammetry and a consumer-grade drone, we generated a canopy height model and extracted structural parameters from individual trees in the Melgonze mangrove patch, southern Iran. Field-measured tree heights served to validate drone-derived estimates and calibrate an allometric model tailored for A. marina. While drone-based heights differed significantly from field measurements (p < 0.001), the resulting AGB and BC estimates showed no significant difference (p > 0.05), demonstrating that crown area (CA) and model formulation effectively compensate for height inaccuracies. This study confirms that drones can provide reliable estimates of BC through non-invasive means—eliminating the need to harvest, cut, or physically disturb individual trees—supporting their application in mangrove monitoring and ecosystem service assessments, even under challenging field conditions. Full article

Introduction: Knee osteoarthritis (OA) is defined by articular cartilage loss, increased discomfort, and functional restrictions. Changes in lifestyle, painkillers, intra-articular injections, and, as a last resort, surgery are all part of clinical therapy. In this setting, intra-articular injections of hyaluronic acid (HA) represent a relevant and diffused therapeutic option. Materials and Methods: A prospective observational study was performed from October 2024 to May 2025 in 70 patients with knee OA. HA was administered in three intra-articular injections and was followed up at 3 and 6 months from the last injection. Knee Injury and Osteoarthritis Outcome Score (KOOS) was evaluated as primary outcome measure; Visual Analogue Scale (VAS), time up and go test, six-minute walking test, general health assessment with 36-Item Short Form Health Survey (SF-36), Zung’s Self-Rating Anxiety Scale (Zung SAS), and Zung’s Self-Rating Depression Scale (Zung SDS) as secondary outcome measures. Results: We observed a statistically significant improvement in clinical scores at 3 months in both HA formulations compared to the control group. No relevant side effects were described during the study. Conclusion: Hyalubrix 30 mg/2 mL and DIART 1.8%/2 mL are two safe and effective therapeutic options to manage knee OA, offering benefits in pain control, functionality and emotional wellness. Full article

This study aimed to evaluate the effect of including silage from devilfish waste (SF-Hypostomus plecostomus) and probiotics (PB-Pediococcus acidilactici BX-B122 and Bacillus coagulans BX-B118) in ruminants on greenhouse gas production. The diets evaluated contained 0, 8, 14 and 20% of silage made from SF and the addition of PB at a dose of 0.2 mL/g of diet, using steers and sheep (rams) as rumen inoculum donors in a completely randomized statistical design with a 2 × 4 × 2 factorial arrangement. Asymptotic gas production (GP) was influenced (p < 0.01) by the interactions between rumen liquor (RL), SF, and PB. The inclusion of SF and PB resulted in a higher (p < 0.01) GP rate in sheep; however, the values were reduced with increasing levels of SF. Asymptotic CH₄ in the rumen fluid of steers decreased with an increasing SF percentage up to 14%. Probiotics had different effects on the rumen fluid of sheep and steers. In steers, probiotics substantially reduced (p < 0.01) CH₄ synthesis while supplementation increased it in sheep rumen fluid. Similarly, diets with probiotics had higher CO formation (p < 0.05) in sheep and steer liquor. Similarly, CO decreased (p < 0.05) with increasing levels of SF. In the rumen fluid of sheep and steers, the probiotics were found to reduce H₂S, while there was an SF-dose-dependent decrease in H₂S concentration. The ruminal pH and dry matter digestibility of sheep were higher than in steers. It can be concluded that increasing SF levels generally reduced the total gas and CH₄ production, with probiotics further enhancing this reduction, especially in CH₄ per unit of gas. Full article

Quantifying the slip rate along geometrically complex strike-slip faults is essential for understanding kinematics and strain partitioning in orogenic systems. The Karlik Tagh forms the easternmost terminus of Tian Shan and represents a critical restraining bend along the sinistral strike-slip Gobi-Tian Shan Fault System. The North Karlik Tagh Fault (NKTF) is an important fault demarcating the north boundary of the Karlik Tagh. While structurally significant, it is poorly understood in terms of its late Quaternary tectonic activity. In this study, we analyze the offset geomorphology based on interpretations of satellite imagery, field survey, and digital elevation models derived from structure-from-motion (SfM), and we provide the first quantitative constraints on the late-Quaternary slip rate using the abandonment age of deformed fan surfaces and river terraces constrained by the ¹⁰Be cosmogenic dating method. Our results reveal that the NKTF can be divided into the Yanchi and Xiamaya segments based on along-strike variations. The NW-striking Yanchi segment exhibits thrust faulting with a 0.07–0.09 mm/yr vertical slip, while the NE-NEE-striking Xiamaya segment displays left-lateral slip at 1.1–1.4 mm/yr since 180 ka. In easternmost Tian Shan, the interaction between thrust and sinistral strike-slip faults forms a transpressional regime. These left-lateral faults, together with those in the Gobi Altai, collectively facilitate eastward crustal escape in response to ongoing Indian indentation. Full article

Avian pathogenic Escherichia coli (APEC) is highly infective in poultry, causing significant economic losses to the poultry industry. As an extraintestinal pathogenic strain, adherence is a critical step in the infection. The functions of several adhesins, including type I, P, and Curli fimbriae, have been extensively studied. However, the roles of other adhesins, like Sfm, remain largely unexplored. Sfm is widely present in E. coli. Although the Sfm cluster is an ortholog of the fim gene cluster of Salmonella type I fimbriae, the biological function of Sfm in APEC has not yet been elucidated. To investigate whether Sfm in APEC CE129 plays a role in virulence, in this study, we constructed recombinant strains by expressing Sfm in the fimbriae-deficient strain SE5000. Additionally, a CE129 sfmA mutant strain was constructed. The resulting changes in adherence, biofilm formation, resistance to macrophage phagocytosis, and resistance to serum bactericidal ability were observed. The adherence ability of CE129ΔsfmA was reduced by 41%. HD-11 cells demonstrated a 30% increase in the phagocytosis of CE129ΔsfmA, and a 50% reduction in SE5000 (pBR322-sfm). The sfm deletion mutant showed a 23.9% reduction in the resistance to serum bactericidal ability, while SE5000 (pBR322-sfm) displayed a 32% increase. SE5000 (pBR322-sfm) exhibited a 34% increase in biofilm formation, and CE129ΔsfmA demonstrated a 21% decrease. Real-time PCR was employed to examine the impact of Sfm deletion on the transcription level of key virulence factors (fimA, fliC, papC, tsh, ompA, and iss). The results indicated that Sfm in CE129 is closely associated with bacterial adherence and survivability, contributing to biofilm formation and influencing the expression of key virulence factors. This study yields initial insight into the functional roles of Sfm in APEC and provides a foundation for the effective control of E. coli in the poultry industry. Full article

This research investigates the metric accuracy of 3D transparent object reconstruction, a task where conventional photogrammetry often fails. The topic is especially relevant in cultural heritage (CH), where accurate digital documentation of glass and transparent artifacts is important. The work proposes a practical methodology using existing tools to verify metric accuracy standards. The study compares three methods, conventional photogrammetry, 3D Gaussian splatting (3DGS), and 2D Gaussian splatting (2DGS), to assess their ability to produce complete and metrically reliable 3D models suitable for measurement and geometric analysis. A transparent glass artifact serves as the case study. Results show that 2DGS captures fine surface and internal details with better geometric consistency than 3DGS and photogrammetry. Although 3DGS offers high visual quality, it introduces surface artifacts that affect metric reliability. Photogrammetry fails to reconstruct the object entirely. The study highlights that visual quality does not ensure geometric accuracy, which is critical for measurement applications. In this work, ground truth comparisons confirm that 2DGS offers the best trade-off between accuracy and appearance, despite higher computational demands. These findings suggest extending the experimentation to other sets of images featuring transparent objects, and possibly also reflective ones. Full article

Three-dimensional (3D) reconstruction has become a fundamental technology in applications ranging from cultural heritage preservation and robotics to forensics and virtual reality. As these applications grow in complexity and realism, the quality of the reconstructed models becomes increasingly critical. Among the many factors that influence reconstruction accuracy, the lighting conditions at capture time remain one of the most influential, yet widely neglected, variables. This review provides a comprehensive survey of classical and modern 3D reconstruction techniques, including Structure from Motion (SfM), Multi-View Stereo (MVS), Photometric Stereo, and recent neural rendering approaches such as Neural Radiance Fields (NeRFs) and 3D Gaussian Splatting (3DGS), while critically evaluating their performance under varying illumination conditions. We describe how lighting-induced artifacts such as shadows, reflections, and exposure imbalances compromise the reconstruction quality and how different approaches attempt to mitigate these effects. Furthermore, we uncover fundamental gaps in current research, including the lack of standardized lighting-aware benchmarks and the limited robustness of state-of-the-art algorithms in uncontrolled environments. By synthesizing knowledge across fields, this review aims to gain a deeper understanding of the interplay between lighting and reconstruction and provides research directions for the future that emphasize the need for adaptive, lighting-robust solutions in 3D vision systems. Full article