Search Results (10,850)

The present reported work deals with the preparation of an energy-efficient smart window based on liquid crystal (LC) using a polymer-dispersed liquid crystal (PDLC) technique. The smart window was prepared using an LC–polymer composite by mixing photopolymer NOA-71 into nematic liquid crystal (NLC) 4-cyano-4’-pentylbiphenyl (5CB). The liquid crystal cell was prepared, the LC–polymer composite was filled inside the cell, and voltage was applied after the exposure of ultraviolet (UV) light. Textural analysis was carried out, and microscope images were taken out with the variation in voltage. Optical measurements were also performed for the smart window based on the PDLC system. Threshold voltage and saturation voltages were measured to carry out the operating voltage analysis. Transmittance was measured as a function of wavelength at different voltages. An absorbance study was also performed, varying the voltage and wavelength. The change in the power of the laser beam passing through the prepared smart window as a function of voltage was also investigated. The working of a prepared smart window using liquid crystal and a photopolymer composite is also demonstrated in opaque and transparent states in the absence and presence of voltage. The output of the present investigation into a PDLC-based smart window can be useful in the applications of adaptive or light shutter devices and in aerospace technology, as it shows the dual nature of opaque and transparent states in the absence and presence of electric field. Full article

In the present paper, the interaction between metal oxide nanoparticles and carbon materials was studied, and the results showed a synergetic effect, leading to an improvement in the properties of the obtained hybrid composites. The In₂O₃ NPs were prepared by the precipitation method and thermal treatment at 550 °C. The composites were obtained using an ex situ method, by mixing the In₂O₃ NPs with reduced oxide graphene (rGO) in a ratio of 10:1. The structural, morphological, and chemical composition studies of the In₂O₃ NPs and In₂O₃-rGO composites were investigates by FTIR and EDX spectroscopy, SEM microscopy, and XRD analysis. These techniques have highlighted the obtaining of In₂O₃ of high purity, and crystallinity, with the mean particle size in the range of 8–25 nm, but also, the dispersion of In₂O₃ NPs onto rGO sheets. We examined the influence of the In₂O₃ nanostructure morphology and In₂O₃-rGO composites on the electrochemical properties using cyclic voltammetry. The surface properties of the In₂O₃ and composite films were studied by contact angles, which indicate the maintenance of the hydrophilic nature. The obtained results establish the synergy between the main components to form In₂O₃-rGO, which can be used for the development of biosensors to enhance the device performance. Full article

Poly(3-hydroxybutyrate) is a biobased and biodegradable polymer, produced via bacterial fermentation and characterized by an isotactic structure and mechanical properties similar to those of polyethylene and polypropylene. However, its brittleness—due to high crystallinity (~70%) and thermal degradation, starting at a temperature range of 180–190 °C near its melting point (175 °C)—makes its processing difficult and limits its applications. Most recent studies on modifying P3HB involved solution casting, typically using chloroform, which raises sustainability concerns. In this study blends of isotactic poly(3-hydroxybutyrate) (i-P3HB) with atactic poly(3-hydroxybutyrate) (a-P3HB) and poly(3-hydroxybutyrate-co-4-hydroxybutyrate) (P34HB) were prepared through solvent-free extrusion, and the thermal and mechanical properties of these blends were characterized. The obtained blends showed an extended processing window with reduced processing temperatures (150–160 °C), which were significantly lower than the onset of the decomposition temperature of i-P3HB, thereby avoiding thermal degradation. Furthermore, the crystallinity of these blends could be varied between 17 and 70%, depending on the polymer ratio, which allows for tailormade materials with tunable mechanical properties and an elongation at break up to 600%. Based on the results, the obtained blends in this study are promising candidates for various applications and processing techniques, such as injection molding, extrusion, and fiber spinning, offering a sustainable alternative to conventional plastics. Full article

The emergence of the Internet of Things (IoT) has brought about a significant technological shift, coupled with the rise of intelligent computing. IoT integrates various digital and analogue devices with the Internet, enabling advanced communication between devices and humans.The pervasive adoption of IoT has transformed urban infrastructures into interconnected smart cities. Here, we propose a framework that mathematically models and automates power consumption management for IoT devices in smart city environments ranging from residential buildings to healthcare settings. The proposed framework utilises set theoretic association-rule mining and combines unsupervised preprocessing with frequent-item set mining and iterative numerical optimisation to reduce non-critical energy consumption. Readings are first converted into binary transaction matrices; then a modified Apriori algorithm is applied to extract high-confidence usage patterns and association rules. Dimensionality reduction techniques compress these transaction profiles, while the Gauss–Seidel method computes control set points that balance energy efficiency. The resulting rule set is deployed through a web portal that provides real-time device status, remote actuation, and automated billing. These associative rules generate predictive control functions, optimise the response of the framework, and prepare the framework for future events. A web portal is introduced that enables remote control of IoT devices and facilitates power usage monitoring, as well as automated billing. Full article

The rapid advancement of general large models has significantly impacted and introduced new concepts to the traditional “one task, one model” research paradigm in construction automation. In this paper, we evaluate the performance of existing large models and those developed on large model platforms, using building material counting as an example. We compare three categories of large AI models for building material counting, including multimodal large models, purely visual large models, and secondary models developed on platforms. Through this research, we aim to explore the accuracy and practicality of these models in real-world construction scenarios. The results indicate that directly applying general large models faces challenges in processing photos with complex shapes or backgrounds, failing to provide accurate counting results. Additionally, while purely visual large models excel in instance segmentation tasks, their application to the specific counting of building materials requires additional programming work. To address these issues, this study explores solutions based on large model secondary development platforms and trains a model using EasyDL as an example. Leveraging deep learning techniques, this model achieves effective counting of building materials through five steps: data preparation, model type selection, model training, model validation, and model deployment. Although models developed based on large model platforms are presently less accurate than specialized models, they still represent a highly promising approach. Full article

African swine fever (ASF) is a highly pathogenic and hemorrhagic swine infectious disease caused by the African swine fever virus (ASFV). It encodes over 150 proteins, among which the CD2v protein plays multiple roles throughout the infection process. Single B-cell antibody technology is a cutting-edge method for preparing monoclonal antibodies (mAbs), which has the advantages of rapid, efficient, and high yield in antibody production, while possessing natural conformations. In this study, by cloning and expressing antibody genes in vitro, 14 murine-derived mAbs were prepared using recombinant CD2v proteins as immunogenic sources, which brings sufficient enrichment and selectivity for the development of antibodies based on the single B-cell antibody technique. All 14 mAbs demonstrated reactivity with CD2v protein by indirect ELISA, whereas 8 mAbs successfully detected CD2v in ASFV-infected PAM cells by IFA, indicating the tested mAbs can effectively recognize and bind to ASFV CD2v. Finally, a blocking ELISA method for detecting CD2v antibodies using CD2v mAb C89 was established, which holds significant potential for broad application in the serological diagnosis of ASFV with determination of the CD2v-blocking ELISA specificity, sensitivity, reproducibility, and compliance rate. It could be used for the rapid clinical detection of ASFV CD2v protein to provide a powerful tool for the monitoring of epidemics. Full article

Bulk chalcogenides from the system (GeTe₄)_1−xIn_x, where x = 0; 5 and 10 mol%, were synthesized by a two-step melt quenching technique. New layered composite materials based on them and the azo polymer [1-4-(3-carboxy-4-hydrophenylazo) benzensulfonamido]-1,2-ethanediyl, sodium salt] has been prepared through spin coating, electrospray deposition and via vacuum-thermal evaporation of the chalcogenide and spin coating of the azo polymer onto it. Using the latter technology, a material consisting of one chalcogenide and one azo polymer film and three chalcogenide and three azo polymer films has been fabricated. The carried-out SEM analysis shows that in the materials, initially prepared as a bilayer and multilayer structure, diffusion at the chalcogenide/polymer interface occurs leading to the formation of a homogenous composite environment. Birefringence was induced at 444 nm in all the fabricated thin film materials. The highest value of the maximal induced birefringence has been measured for the material fabricated as a stack, Δn_max = 0.118. For the material prepared as a bilayer structure and the composite material obtained through electrospray deposition, the maximal induced birefringence takes values of Δn_max = 0.101 and Δn_max = 0.095, respectively. The sample prepared via spin coating of the chalcogenide/PAZO dispersion has the lowest value of the maximal induced birefringence (Δn_max = 0.066) in comparison to the pure PAZO polymer film (Δn_max = 0.083). Full article

This study compares the Eddy current technique and optical microscopy for measuring the anodized layer thickness in a 6063 aluminum alloy with the aim of establishing an efficient and accurate methodology capable of delivering optimal results in a time-efficient manner. Optical microscopy was used as the reference method, with five measurements taken in different fields for each specimen. The Eddy current method was applied using two calibration strategies: one calibration before each measurement and another after every ten specimens. The Bland–Altman analysis was employed to compare both measurement techniques. The results indicated that the calibration before each measurement strategy using Eddy current showed higher agreement with the reference method, suggesting that both techniques can be considered equivalent and interchangeable. Furthermore, the Eddy current method demonstrated significant advantages in detecting thickness variations along the specimen, revealing non-uniform distribution of the anodized layer. This method also proved to be faster and eliminated the need for metallographic preparation required by optical microscopy, thus significantly reducing analysis time and cost. In conclusion, the Eddy current method with calibration before each measurement strategy is proposed as an effective alternative for measuring anodized layer thickness in applications where speed and precision are critical. Full article

This mini-review article is focused on polymeric materials that comprise thermoresponsive and fluorescent organic units. The combination of fluorescent clusters/dots embedded in or grafted with polymers is not considered in this article. Here we review the preparation, characterization, and application of thermoresponsive polymers functionalized covalently with organic fluorescent compounds either compartmentalized or randomly distributed: block-copolymers, self-assembled micelles or vesicles, core–shell nanogels, and their temperature driven self-assembly/shrinkage/expansion and resulting effect in fluorescence: quenching, enhancing, shifting. The applications suggested for these smart-materials are reviewed in the last ten years and range from nanothermometers, drug delivery systems, agents for bioimaging, sensors, and advanced materials for theranostics focused on cancer treatment. This article is organized reviewing the preparation methods, the main characterization techniques, and the application, depending on polymer architecture and the emission wavelength of the fluorophores. Finally, comments, suggestions, and problems to be solved for the advancement of these materials in the future prior to real-life applications are given. Full article

Laser-Directed Energy Deposition (L-DED) is an additive manufacturing technique used for producing and repairing components, mainly for coating applications, depositing metal matrix composites such as cemented carbides, composed of hard metal carbides and a metallic binder. In this sense, this study evaluated the preparation of a ready-to-press WC-25Co powder as a reliable feedstock for L-DED process. This powder required pre-heat treatment studies to prevent fragmentation during powder feeding, due to the absence of metallurgical bonding between WC and Co particles. In the current study, the Taguchi methodology was used, varying laser power, powder feed rate, and scanning speed to reach an optimised deposition window. The best bead morphology resulted from 2400 W laser power, 11 mm/s scanning speed, and 9 g/min feed rate. Moreover, defects such as porosity and cracking were mitigated by applying a remelting strategy of 2400 W and 9 mm/s. Therefore, a perfect deposition is obtained using the optimised processing parameters. Microstructural analysis of the optimised deposited line revealed a fine structure, comprising columnar and equiaxed dendrites of complex carbides. The average hardness of the deposited WC-25Co powder on a AISI 1045 steel was 854 ± 37 HV0.2. These results demonstrate the potential of L-DED for processing high-performance cemented carbide coatings. Full article

Full-thickness skin grafts are a cornerstone in reconstructive surgery for extensive skin defects, particularly in pediatric patients, where rapid vascularization is essential for successful engraftment. Traditional defatting methods using scalpels and scissors are labor-intensive and increase the risk of graft or operator injury. To improve efficiency and safety, a mechanical defatting device called LOMA (named after the inventors Loff and Maja) was developed at Klinikum Stuttgart. This study evaluates the first 28 transplants performed with it, assessing graft outcomes using the POSAS and comparing physical properties of the grafts with those of healthy contralateral skin, ankle skin, and palmar skin using DermaLab Combo’s ultrasound and elasticity probes. Results showed that grafts prepared with LOMA exhibited similar physical characteristics to contralateral healthy skin. Differences in elasticity were observed when compared to ankle skin, and significant disparities were found when compared to palmar skin. POSAS scores averaged 3.3 from patients and 2.2 from physicians, indicating satisfaction with functional and aesthetic outcomes. The findings support the effectiveness of full-thickness skin grafts, particularly when prepared using the LOMA system. Further multicenter studies are recommended to compare LOMA-prepared grafts with those using conventional techniques to quantify the added value of this mechanical defatting approach. Full article

With the increasing demand for sustainable and cost-effective alternatives in the construction industry, polymer composites have emerged as a promising solution. This study focuses on the development of innovative composite tiles using Linear Low-Density Polyethylene (LLDPE) powder blended with epoxy resin and a hardener as a green substitute for conventional ceramic and cement tiles. LLDPE is recognized for its flexibility, durability, and chemical resistance, making it an effective filler within the epoxy matrix. To optimize its material properties, composite samples were fabricated using three different LLDPE-to-epoxy ratios: 30:70, 40:60, and 50:50. Flexural strength testing revealed that while the 50:50 blend achieved the highest maximum value (29.887 MPa), it also exhibited significant variability, reducing its reliability for practical applications. In contrast, the 40:60 ratio demonstrated more consistent and repeatable flexural strength, ranging from 16 to 20 MPa, which is ideal for flooring applications where mechanical performance under repeated loading is critical. Scanning Electron Microscopy (SEM) images confirmed uniform filler dispersion in the 40:60 mix, further supporting its mechanical consistency. The 30:70 composition showed irregular and erratic behaviour, with values ranging from 11.596 to 25.765 MPa, indicating poor dispersion and increased brittleness. To complement the development of the materials, deep learning techniques were employed for real-time defect detection in the manufactured tiles. Utilizing the YOLOv8 (You Only Look Once version 8) algorithm, this study implemented an automated, vision-based surface monitoring system capable of identifying surface deterioration and defects. A dataset comprising over 100 annotated images was prepared, featuring various surface defects such as cracks, craters, glaze detachment, and tile lacunae, alongside defect-free samples. The integration of machine learning not only enhances quality control in the production process but also offers a scalable solution for defect detection in large-scale manufacturing environments. This research demonstrates a dual approach to material innovation and intelligent defect detection to improve the performance and quality assurance of composite tiles, contributing to sustainable construction practices. Full article

Background/Objectives: Despite the continuous development of medicine, the treatment of dermatological fungal infections is difficult due to their chronic nature, recurrence, and resistance of some pathogens to standard therapies. In order to improve the effectiveness of treatment, not only are new active substances with antifungal activity synthesized, but new, unconventional carriers are also developed for substances already used. Methods: Therefore, the focus of this research was to evaluate the possibility of using a combination of two cross-linking techniques for sodium alginate ionic cross-linking with Zn²⁺ ions and electrostatic interaction with ε-poly-L-lysine. The pharmaceutical properties, antifungal activity against Candida strains, and compatibility with human fibroblasts of the designed hydrogels were assessed. Results: It was shown that the double cross-linking process increased the viscosity of the developed hydrogels, improved bioadhesive properties to hairless mice skin, and provided an extended release profile of the active substance. In addition, obtained formulations were characterized by improved antifungal effect against C. albicans, C. krusei, and C. parapsilosis. Prepared hydrogels expressed biocompatibility with human fibroblasts. Conclusions: Dual-cross-linked alginate hydrogels are a promising dermatological formulation that might improve the efficacy of posaconazole in the treatment of antifungal infections. Full article

Background: Saudi coffee, made from Khawlani beans, is known for its sweeter, less acidic flavor and rich content of bioactive compounds. However, traditional preparation methods are time consuming and inefficient in extracting these compounds, limiting their global appeal. This study introduces an ultrasonic-assisted nanoparticle preparation technique to enhance the extraction efficiency, chemical profile, and sensory quality of Saudi coffee. The method aims to overcome limitations of traditional grinding by reducing the particle size while preserving key bioactive compounds. Methods: Finely ground coffee was subjected to ultrasonic processing at optimized parameters 450 W (60% of 750 W output), with 10 min of pulsed sonication to produce nanoparticles. These were characterized using SEM, FT-IR, XRPD, and particle size analysis. Comparative chemical analysis (caffeine, total phenols) and sensory evaluation were conducted against regular Saudi coffee. Results: Ultrasonication reduced the particle size to ~101 nm, significantly enhancing caffeine (from 0.54 to 3.21 mg/g) and phenolic content (from 426.7 to 1825.3 µg GAE/g). Solubility also increased from 40.7% to 75.9%. Sensory tests showed an improved aroma, mouthfeel, and flavor. These improvements are attributed to an enhanced extraction and surface area at the nanoscale. Conclusion: Ultrasonic-assisted nanoparticle technology significantly improves the physicochemical and sensory properties of Saudi coffee. This approach offers a fast, scalable, and eco-friendly method for quality enhancement, positioning Saudi coffee for greater global competitiveness. Full article

This study investigated the impact of preparing lesson plans and conducting microteaching activities—aligned with the learning outcomes of the mathematics curriculum—on the development of sustainability beliefs among teacher candidates. The rationale behind this research stems from the growing global emphasis on sustainability and the urgent need to embed sustainability literacy into teacher education programs, particularly in disciplines such as mathematics, which are often perceived as abstract and value-neutral. There is a recognized gap in equipping pre-service teachers with the pedagogical skills and conceptual awareness needed to integrate sustainability meaningfully into mathematics instruction. Employing a mixed-methods design, the Sustainability Belief Scale was administered to 45 teacher candidates (22 in the experimental group and 23 in the control group) as both a pre-test and post-test. During the intervention, participants in the experimental group collaboratively designed lesson plans and delivered them through microteaching sessions. Throughout the process, they maintained individual reflective journals. The lesson plans and microteaching performances were evaluated using instructor-developed rubrics. Data were analyzed using both quantitative statistical techniques and qualitative content analysis. The findings indicate that integrating sustainability themes into mathematics education significantly enhances teacher candidates’ sustainability beliefs and informs their pedagogical orientations. This study underscores the importance of structured, practice-based learning experiences—such as sustainability-focused microteaching—as a means to develop the competencies needed for education for sustainable development in mathematics classrooms. Full article