Search Results (5,051)

The number of CNN application areas is growing, which leads to the need for training data. The research conducted in this work aimed to obtain effective detection models trained only using simplified synthetic objects (SSOs). The research was conducted on inland shallow water areas, while images of bottom objects were obtained using a UAV platform. The work consisted in preparing SSOs, thanks to which composite images were created. On such training data, 120 models based on the YOLO (You Only Look Once) network were obtained. The study confirmed the effectiveness of models created using YOLOv3, YOLOv5, YOLOv8, YOLOv9, and YOLOv10. A comparison was made between versions of YOLO. The influence of the amount of training data, SSO type, and augmentation parameters used in the training process was analyzed. The main parameter of model performance was the F1-score. The calculated statistics of individual models indicate that the most effective networks use partial augmentation, trained on sets consisting of 2000 SSOs. On the other hand, the increased transparency of SSOs resulted in increasing the diversity of training data and improving the performance of models. This research is developmental, and further research should improve the processes of obtaining detection models using deep networks. Full article

Digestate valorization is essential for sustainable waste management and circular economy strategies, yet large-scale adoption faces technical, economic, and environmental challenges. Beyond waste-to-energy conversion, digestate is a valuable soil amendment, enhancing soil structure and reducing reliance on synthetic fertilizers. However, its agronomic benefits depend on feedstock characteristics, treatment processes, and application methods. This study reviews digestate composition, treatment technologies, regulatory frameworks, and environmental impact assessment through Life Cycle Assessment. It analyzes the influence of functional unit selection and system boundary definitions on Life Cycle Assessment outcomes and the effects of feedstock selection, pretreatment, and post-processing on its environmental footprint and fertilization efficiency. A review of 28 JCR-indexed articles (2018–present) analyzed LCA studies on digestate, focusing on methodologies, system boundaries, and impact categories. The findings indicate that Life Cycle Assessment methodologies vary widely, complicating direct comparisons. Transportation distances, nutrient stability, and post-processing strategies significantly impact greenhouse gas emissions and nutrient retention efficiency. Techniques like solid–liquid separation and composting enhance digestate stability and agronomic performance. Digestate remains a promising alternative to synthetic fertilizers despite market uncertainty and regulatory inconsistencies. Standardized Life Cycle Assessment methodologies and policy incentives are needed to promote its adoption as a sustainable soil amendment within circular economy frameworks. Full article

This study presents an integrated geospatial framework for assessing the risk to high-speed railway (HSR) infrastructure, combining a persistent scatterer interferometric synthetic aperture radar (PS-InSAR) analysis with multi-criteria decision-making in a geographic information system (GIS) environment. Focusing on the Honam HSR corridor in South Korea, the model incorporates both maximum ground deformation and subsidence velocity to construct a dynamic hazard index. Social vulnerability is quantified using five demographic and infrastructural indicators, and a two-stage analytic hierarchy process (AHP) is applied with dependency correction to mitigate inter-variable redundancy. The resulting high-resolution risk maps highlight spatial mismatches between geotechnical hazards and social exposure, revealing vulnerable segments in Gongju and Iksan that require prioritized maintenance and mitigation. The framework also addresses data limitations by interpolating groundwater levels and estimating train speed using spatial techniques. Designed to be scalable and transferable, this methodology offers a practical decision-support tool for infrastructure managers and policymakers aiming to enhance the resilience of linear transport systems. Full article

Stoichiometric single crystals of Mn₄Al₁₁ were synthesized from the elements using Sn as a flux. The crystal structure of Mn₄Al₁₁ was investigated using single crystal X-ray diffraction and showed a complex triclinic structure with a relatively small unit cell and interpenetrating networks of Mn and Al atoms. While our results generally agree with the previously reported data in the basic structure features such as triclinic symmetry and structure type, the atomic parameters differ significantly, likely due to different synthetic techniques producing off-stoichiometry or doped crystals used in the previous works. Our structural analysis showed that the view of the Mn substructure as isolated zigzag chains is incomplete. Instead, the Mn chains are coupled in corrugated layers by long Mn-Mn bonds. The high quality of the crystals with the stoichiometric composition also enabled us to study magnetic behavior in great detail and reveal previously unobserved magnetic ordering. Our magnetization measurements showed that Mn₄Al₁₁ is an antiferromagnet with T_N of 65 K. The presence of the maximum above T_N also suggests strong local interactions indicative of low-dimensional magnetic behavior, which likely stems from lowered dimensionality of the Mn substructure. Full article

The cosmetics industry has been seeking to develop products with renewable natural ingredients to reduce the use of or even replace synthetic substances. Biosurfactants can help meet this demand. These natural compounds are renewable, biodegradable, and non-toxic or have low toxicity, offering minimal risk to humans and the environment, which has attracted the interest of an emerging consumer market and, consequently, the cosmetics industry. The aim of the present study was to produce a biosurfactant from the yeast Starmerella bombicola ATCC 22214 cultivated in a mineral medium containing 10% soybean oil and 5% glucose. The biosurfactant reduced the surface tension of water from 72.0 ± 0.1 mN/m to 33.0 ± 0.3 mN/m after eight days of fermentation. The yield was 53.35 ± 0.39 g/L and the critical micelle concentration was 1000 mg/L. The biosurfactant proved to be a good emulsifier of oils used in cosmetic formulations, with emulsification indices ranging from 45.90 ± 1.69% to 68.50 ± 1.10%. The hydrophilic–lipophilic balance index demonstrated the wetting capacity of the biosurfactant and its tendency to form oil-in-water (O/W) emulsions, with 50.0 ± 0.20% foaming capacity. The biosurfactant did not exhibit cytotoxicity in the MTT assay or irritant potential. Additionally, an antioxidant activity of 58.25 ± 0.32% was observed at a concentration of 40 mg/mL. The compound also exhibited antimicrobial activity against various pathogenic microorganisms. The characterisation of the biosurfactant using magnetic nuclear resonance and Fourier transform infrared spectroscopy revealed that the biomolecule is a glycolipid with an anionic nature. The results demonstrate that biosurfactant produced in this work has potential as an active biotechnological ingredient for innovative, eco-friendly cosmetic formulations. Full article

Monitoring the health of wind turbine foundations is essential for ensuring their operational safety. This paper presents a cost-effective approach to obtain rotational stiffness of wind turbine foundations by using only acceleration and wind speed data that are part of SCADA data, thus lowering the use of moment and tilt sensors that are currently being used for obtaining foundation stiffness. First, a convolutional neural network model is applied to map acceleration and wind speed data within a moving window to corresponding moment and tilt values. Rotational stiffness of the foundation is then estimated by fitting a line in the moment-tilt plane. The results obtained indicate that such a mapping model can provide stiffness values that are within 7% of ground truth stiffness values on average. Second, the developed mapping model is re-trained by using synthetic acceleration and wind speed data that are generated by an autoencoder generative AI network. The results obtained indicate that although the exact amount of stiffness drop cannot be determined, the drops themselves can be detected. This mapping model can be used not only to lower the cost associated with obtaining foundation rotational stiffness but also to sound an alarm when a foundation starts deteriorating. Full article

Introduction: Biodegradable Temporizing Matrix (BTM) is a new synthetic dermal substitute suitable for wound closure and tissue regeneration. The data in paediatric population remain limited. The study purpose is to review the indications for BTM application in paediatric patients, evaluate the short-term and long-term results, including complications and functional outcomes, as well as to share some unique observations regarding the use of BTM in paediatric population. Patients and Methods: Patients undergoing reconstructive surgery and BTM application during the last three years were included. Data collected included patient demographics, primary diagnosis, previous surgical management, post-operative complications and final outcomes. BTM was used in 32 patients. The indications varied including epidermolysis bullosa (n = 6), burns (n = 4), trauma (n = 7), infection (n = 4), ischemia or necrosis (n = 11). Results: The results were satisfying with acceptable aesthetic and functional outcomes. Complications included haematoma underneath the BTM leading to BTM removal and re-application (n = 1), BTM infection (n = 1) and split-thickness skin graft failure on top of BTM requiring re-grafting (n = 2). Conclusions: BTM can be a good alternative to large skin grafts, locoregional flaps or even free flaps. The big advantages over other dermal substitutes or skin grafts are that BTM is less prone to infection and offers excellent scarring by preserving the normal skin architecture. Specifically in children, BTM might not require grafting, resulting in spontaneous healing with good scarring. In critically ill patients, BTM reduces the operation time and there is no donor site morbidity. BTM should be considered in the reconstructive ladder when discussing defect coverage options in children and young people. Full article

To explore an industrial fermentation approach for traditional mung bean sour pulp, this study isolated core microorganisms including lactic acid bacteria and yeasts from naturally fermented samples and constructed a synthetic microbial community. The optimized community consisted of Lactiplantibacillus pentosus, Lactococcus garvieae, and Cyberlindnera jadinii at a ratio of 7:3:0.1 and was used to ferment cooked mung bean pulp with a material-to-water ratio of 1:8 and 1% sucrose addition. Under these conditions, the final product exhibited significantly higher levels of protein (4.55 mg/mL), flavonoids (0.10 mg/mL), polyphenols (0.11 mg/mL), and vitamin C (7.75 μg/mL) than traditionally fermented mung bean sour pulp, along with enhanced antioxidant activity. The analysis of organic acids, free amino acids, and volatile compounds showed that lactic acid was the main acid component, the bitter amino acid content was reduced, the volatile flavor compounds were more abundant, and the level of harmful compound dimethyl sulfide was significantly decreased. These results indicate that fermentation using a synthetic microbial community effectively improved the nutritional quality, flavor, and safety of mung bean sour pulp. Full article

Against the backdrop of China’s fast-growing digital economy and its financial inclusion agenda, there is still little city-level evidence on whether the e-CNY pilot accelerates financial deepening at the grassroots. Using a balanced panel of 271 prefecture-and-above cities for 2016–2022, this study employs a staggered difference-in-differences (SDID) design augmented by the synthetic control method (SCM) to rigorously identify the policy effect of the e-CNY pilot. The results show that the pilot program significantly improves urban financial inclusion, contributing to more equitable access to financial services and supporting inclusive socio-economic development. Mechanism analysis suggests that the effect operates mainly through two channels, a merchant-coverage channel and a transaction-scale channel, with the former contributing the majority of the overall effect. Incorporating a migration-based mobility index shows that most studies’ focus on the merchant-coverage effect is amplified in cities under tight mobility restrictions but wanes where commercial networks are already saturated, whereas the transaction-scale channel is largely insensitive to mobility shocks. Heterogeneity tests further indicate stronger gains in non-provincial capital cities and in the eastern and central regions. Overall, the study uncovers a “penetration-inclusion” network logic and provides policy insights for advancing sustainable financial inclusion through optimized terminal deployment, merchant incentives, and diversified scenario design. Full article

A new series of 6-arylaminoflavones was synthesized via the Buchwald–Hartwig cross-coupling reaction, aiming to functionalize the flavone core efficiently. Reaction optimization revealed that Pd₂(dba)₃/XantPhos with Cs₂CO₃ in toluene provided the best yields, with isolated yields ranging from 8% to 95%, depending on the arylamine structure. Steric hindrance and electron-withdrawing groups at the arylamine ring impacted the reaction outcomes. Cytotoxicity assays in different human cancer cell lines indicated that substitution patterns at both the arylamine and B-rings strongly impacted biological activity. In particular, compounds bearing a 3,4-dimethoxy substitution at the B-ring and a trifluoromethyl (13c) or chlorine (13g) group at the aniline moiety exhibited enhanced cytotoxicity. These findings provide insights into the structure–activity relationship of 6-arylaminoflavones while contributing to the development of synthetic methodologies for functionalized flavones. Full article

Volcanic rock is a natural mineral material which has garnered interest for its potential application in water treatment due to its unique physicochemical properties. In this study, we prepared a polysilicate aluminum chloride (PSAC) coagulant using volcanic rock which exhibited good coagulation–flocculation performance. Further investigation into the influence of synthetic parameters, such as calcination temperature, reaction time, and alkali types, on the structure and performance of a volcanic rock-derived coagulant was conducted. Techniques including Scanning Electron Microscopy, Energy-Dispersive Spectroscopy, Fourier-Transform Infrared Spectroscopy, and X-Ray Diffraction were utilized to characterize it. Also, a ferron-complexation timed spectrophotometric method was used to study the distribution of aluminum species in the coagulant. Results indicated that the volcanic rock that was treated with acidic and alkaline solutions had the potential to form PSAC with Al-OH, Al-O-Si, Fe-OH, and Fe-O-Si bonds, which influenced the coagulation–flocculation efficiency. An acid leaching temperature of 90 °C, 8 mL of 2 mol/L NaOH, a reaction time of 0.5 h, and a reaction temperature of 60 °C were conducive to the preparation. A higher temperature could result in a higher proportion of Alb species, and, at 100 °C, the Ala, Alc, and Alb were 29%, 24%, and 47%, respectively, achieving a residual turbidity lower than 1 NTU at an appropriate dosage, as well as a reduction of over 0.1 to 0.018 in the level of UV₂₅₄. The findings of this study provide a feasible method to prepare a flocculant using volcanic rock. Further application is expected to yield good results in wastewater/water treatment. Full article

Winery wastewater (WWW), if released untreated, poses a serious environmental threat due to its high organic load. In this study, Chlorella vulgaris was cultivated in diluted WWW to assess its suitability as a culture medium. Two outdoor cultivation systems—a 270 L raceway and a 40 L bubble column—were operated over 33 days using synthetic medium (control) and WWW. A flow cytometry (FC) protocol was implemented to monitor key physiological parameters in near-real time, including cell concentration, membrane integrity, chlorophyll content, cell size, and internal complexity. At the end of cultivation, the bubble column yielded the highest cell concentrations: 2.85 × 10⁶ cells/mL (control) and 2.30 × 10⁶ cells/mL (WWW), though with lower proportions of intact cells (25% and 31%, respectively). Raceway cultures showed lower cell concentrations: 1.64 × 10⁶ (control) and 1.54 × 10⁶ cells/mL (WWW), but higher membrane integrity (76% and 36% for control and WWW cultures, respectively). On average, cells grown in the bubble column had a 22% larger radius than those in the raceway, favouring sedimentation. Heterotrophic cells were more abundant in WWW cultures, due to the presence of organic carbon, indicating its potential for use as animal feed. This study demonstrates that FC is a powerful, real-time tool for monitoring microalgae physiology and optimising cultivation in complex effluents like WWW. Full article

This study presents a DIKWP-driven artificial consciousness framework for IoT-enabled smart healthcare, integrating a Data–Information–Knowledge–Wisdom–Purpose (DIKWP) cognitive architecture with a software-defined IoT infrastructure. The proposed system deploys DIKWP agents at edge and cloud nodes to transform raw sensor data into high-level knowledge and purpose-driven actions. This is achieved through a structured DIKWP pipeline—from data acquisition and information processing to knowledge extraction, wisdom inference, and purpose-driven decision-making—that enables semantic reasoning, adaptive goal-driven responses, and privacy-preserving decision-making in healthcare environments. The architecture integrates wearable sensors, edge computing nodes, and cloud services to enable dynamic task orchestration and secure data fusion. For evaluation, a smart healthcare scenario for early anomaly detection (e.g., arrhythmia and fever) was implemented using wearable devices with coordinated edge–cloud analytics. Simulated experiments on synthetic vital sign datasets achieved approximately 98% anomaly detection accuracy and up to 90% reduction in communication overhead compared to cloud-centric solutions. Results also demonstrate enhanced explainability via traceable decisions across DIKWP layers and robust performance under intermittent connectivity. These findings indicate that the DIKWP-driven approach can significantly advance IoT-based healthcare by providing secure, explainable, and adaptive services aligned with clinical objectives and patient-centric care. Full article

Internal crack defects in high-strength low-alloy (HSLA) steels during continuous casting pose significant challenges to downstream processing and product reliability. However, due to the inherent class imbalance in industrial defect datasets, conventional machine learning models often suffer from poor sensitivity to minority class instances. This study proposes a predictive framework that integrates conditional tabular generative adversarial network (CTGAN) for synthetic minority sample generation and CatBoost for classification. A dataset of 733 process records was collected from a continuous caster, and 25 informative features were selected using mutual information. CTGAN was employed to augment the minority class (crack) samples, achieving a balanced training set. Feature distribution analysis and principal component visualization indicated that the synthetic data effectively preserved the statistical structure of the original minority class. Compared with the other machine learning methods, including KNN, SVM, and MLP, CatBoost achieved the highest metrics, with an accuracy of 0.9239, precision of 0.9041, recall of 0.9018, and F1-score of 0.9022. Results show that CTGAN-based augmentation improves classification performance across all models. These findings highlight the effectiveness of GAN-based augmentation for imbalanced industrial data and validate the CTGAN–CatBoost model as a robust solution for online defect prediction in steel manufacturing. Full article

This study presents the design, fabrication, and clinical validation of a lightweight, body-powered prosthetic index finger actuated via metacarpophalangeal (MCP) joint motion. The proposed system incorporates an underactuated, cable-driven mechanism combining rigid and compliant elements to achieve passive adaptability and embodied intelligence, supporting intuitive user interaction. Results indicate that the prosthesis successfully mimics natural finger flexion and adapts effectively to a variety of grasping tasks with minimal effort. This study was conducted in accordance with ethical standards and approved by the Institutional Review Board (IRB), Project No. 670161, titled “Biologically-Inspired Synthetic Finger: Design, Fabrication, and Application.” The findings suggest that the device offers a viable and practical solution for individuals with partial hand loss, particularly in settings where electrically powered systems are unsuitable or inaccessible. Full article