Search Results (6,554)

The mounting global concern regarding the accumulation of plastic waste underscores the necessity for the development of innovative solutions, with particular emphasis on the incorporation of plant-based biofillers into polymer composites as a sustainable alternative to conventional materials. This review provides a comprehensive and structured overview of the recent progress (2020–2025) in the integration of plant-based biofillers into both thermoplastic and thermosetting polymer matrices, with a focus on surface modification techniques, physicochemical characterization, and emerging industrial applications. Unlike the prior literature, this work highlights the dual environmental and material benefits of using plant-derived fillers, particularly in the context of waste valorization and circular material design. By clearly identifying a current research gap—the limited scalability and processing efficiency of biofillers—this review proposes a strategy in which plant-derived materials function as key enablers for sustainable composite development. Special attention is given to extraction methods of lignocellulosic fillers from renewable agricultural waste streams and their subsequent functionalization to improve matrix compatibility. Additionally, it delineates the principal approaches for biofiller modification, demonstrating how their properties can be tailored to meet specific needs in biocomposite production. This critical synthesis of the state-of-the-art literature not only reinforces the role of biofillers in reducing dependence on non-renewable fillers but also outlines future directions in scaling up their use, improving durability, and expanding performance capabilities of sustainable composites. Overall, the presented analysis contributes novel insights into the material design, processing strategies, and potential of plant biofillers as central elements in next-generation green composites. Full article

The construction of prefabricated concrete houses in Ecuador poses significant challenges in terms of environmental and social sustainability, amid growing housing demand and the urgent need to mitigate adverse impacts associated with the construction processes and materials. In particular, the lack of a comprehensive assessment of these impacts limits the development of effective strategies to improve the sustainability of the sector. In addition, in rural areas, the design of flexible and adapted solutions is required, as evidenced by recent studies in the Andean area. This study conducts a comprehensive assessment of the impacts and sustainability indicators for prefabricated concrete houses, employing international certification systems such as LEED, BREEAM, and VERDE, to validate various relevant environmental and social indicators. The methodology used is the Hierarchical Analytical Process (AHP), which facilitates the prioritization of impacts through paired comparisons, establishing priorities for decision-making. Hydrological, soil, faunal, floral, and socioeconomic aspects are evaluated in a regional context. The results reveal that the most critical environmental impacts in Ecuador are climate change (28.77%), water depletion (13.73%) and loss of human health (19.17%), generation of non-hazardous waste 8.40%, changes in biodiversity 5%, extraction of mineral resources 12.07%, financial risks 5.33%, loss of aquatic life 4.67%, and loss of fertility 3%, as derived from hierarchical and standardization matrices. Despite being grounded in a literature review and being constrained due to the scarcity of previous projects in the country, this research provides a useful framework for the environmental evaluation and planning of prefabricated housing. To conclude, this study enhances existing methodologies of environmental assessment techniques and practices in the construction of precast concrete and promotes the development of sustainable and socially responsible housing in Ecuador. Full article

Power electronics convert and control electrical power in applications ranging from electric motors to telecommunications and computing. Ongoing efforts to miniaturize these systems and boost power density demand advanced thermal management solutions to maintain optimal cooling and temperature control. Spray cooling offers an effective means of removing high heat fluxes and keeping power electronics within safe operating temperatures. This study presents an experimental investigation of flash spray cooling in a closed-loop system using R410A refrigerant. In particular, two nozzles with different spraying angles are used to study the effects of the distance between the spray nozzle and a heated flat surface, as well as the mass flow rate of the coolant. Results indicate that three key flow-pattern factors—surface coverage, impingement intensity, and liquid film dynamics—govern the heat transfer mechanisms and determine cooling efficiency. Flash spray cooling using refrigerants like R410A demonstrates strong potential as a high-performance thermal management strategy for next-generation power electronics. Full article

Here, we study boundary value problems for the Laplace–Beltrami operator on a three-dimensional sphere with a circular cut, obtained by removing a smooth closed geodesic from $S^3$ embedded in ${\mathbb{R}}^4$. The presence of the cut introduces singular perturbations of the domain, and we develop an analytical framework to characterize well-posed problems in this setting. Our approach combines Green’s functions, spectral analysis, and Sobolev space methods to establish solvability criteria and uniqueness results. In particular, we identify explicit conditions for the existence of solutions with data supported near the cut, and extend the formulation to include delta-type perturbations supported on the removed circle. These results generalize earlier work on punctured two-dimensional spheres and provide a foundation for the study of PDEs on manifolds with localized singularities. Full article

This work presents an efficient analytical technique for obtaining approximate solutions to time-fractional system partial differential equations. The proposed method combines the Natural generalized Laplace transform with the decomposition method to construct a systematic solution framework. A general formulation of the method is developed for a broad class of time-fractional system equations. In particular, we check the validity and effectiveness of the approach by providing three illustrative examples, confirming its accuracy and applicability in solving both linear and nonlinear fractional problems. Full article

This study evaluates the viability of a specific hybrid renewable energy system (HRES) installation designed for a remote community as a case study in Cuba. The system integrates solar, wind, and biomass resources to address localised challenges of energy insecurity and environmental degradation. Rather than offering a generalised evaluation of HRES technologies, this work focuses on the performance, impacts, and viability of this particular configuration within its unique geographical, social, and technical context. Using life cycle assessment (LCA) and input–output modelling, the research assesses environmental and socioeconomic impacts. The proposed HRES reduces greenhouse gas emissions by 60% (from 1.14 to 0.47 kg CO₂eq/kWh) and fossil energy consumption by 50% compared to diesel-based systems. Socioeconomic analysis reveals that the system generates 40.3 full-time equivalent (FTE) jobs, with significant employment opportunities in operation and maintenance. However, initial investments primarily benefit foreign suppliers due to Cuba’s reliance on imported components. The study highlights the potential for local economic gains through workforce training and domestic manufacturing of renewable energy technologies. These findings underscore the importance of integrating multiple renewable sources to enhance energy resilience and sustainability in Cuba. Policymakers should prioritise strategies to incentivise local production and capacity building to maximise long-term benefits. Future research should explore scalability across diverse regions and investigate policy frameworks to support widespread adoption of HRES. This study provides valuable insights for advancing sustainable energy solutions in Cuba and similar contexts globally. Full article

Ore blending plays a critical role in ensuring feed consistency and optimizing downstream processes in the mining industry. Despite its importance, effective blending remains challenging due to ore variability and operational constraints. This review focuses exclusively on modern, data-driven blending methodologies, with particular emphasis on the application of data science and machine learning (ML) in predicting key process variables and supporting real-time decision-making. It discusses core challenges such as data quality, feature engineering, and model generalization, alongside enabling technologies including sensor integration, automation platforms, and real-time data acquisition systems. By consolidating the recent literature and highlighting emerging trends, this work outlines future directions for advancing intelligent blending systems and underscores the importance of standardized, high-quality data in the development of robust digital solutions for mineral processing. Full article

As IoT (internet of things) devices grow in prominence, safeguarding them from cyberattacks is becoming a pressing challenge. To bootstrap IoT security, device identification or authentication is crucial for establishing trusted connections among devices without prior trust. In this regard, radio frequency fingerprinting (RFF) is gaining attention because it is more efficient and requires fewer computational resources compared to resource-intensive cryptographic methods, such as digital signatures. RFF works by identifying unique manufacturing defects in the radio circuitry of IoT devices by analyzing over-the-air signals that embed these imperfections, allowing for the identification of the transmitting hardware. Recent studies on RFF often leverage advanced classification models, including classical machine learning techniques such as K-Nearest Neighbor (KNN) and Support Vector Machine (SVM), as well as modern deep learning architectures like Convolutional Neural Network (CNN). In particular, CNNs are well-suited as they use multidimensional mapping to detect and extract reliable fingerprints during the learning process. However, a significant limitation of these approaches is that they require large datasets and necessitate retraining when new devices not included in the initial training set are added. This retraining can cause service interruptions and is costly, especially in large-scale IoT networks. In this paper, we propose a novel solution to this problem: RFF using Siamese networks, which eliminates the need for retraining and allows for seamless authentication in IoT deployments. The proposed Siamese network is trained using in-phase and quadrature (I/Q) samples from 10 different Software-Defined Radios (SDRs). Additionally, we present a new algorithm, the Similarity-Based Embedding Classification (SBEC) for RFF. We present experimental results that demonstrate that the Siamese network effectively distinguishes between malicious and trusted devices with a remarkable 98% identification accuracy. Full article

In the IT sector, the relevance of looking at security from many different angles and the inclusion of different areas is already known and understood. This approach is much less pronounced in the area of cyber physical systems and not present at all in the area of building automation. Increasing interconnectivity, undefined responsibilities, connections between secured and unsecured areas, and a lack of understanding of security among decision-makers pose a particular threat. This systematic review demonstrates a paucity of literature addressing real-world scenarios, asymmetric/hybrid threats, or composite vulnerabilities. In particular, the attack surface is significantly increased by the deployment of smart sensors and actuators in unprotected areas. Furthermore, a range of additional hybrid threats are cited, with practical examples being provided that have hitherto gone unnoticed in the extant literature. It will be shown whether solutions are available in neighboring areas and whether these can be transferred to building automation to increase the security of the entire system. Consequently, subsequent studies can be developed to create more accurate behavioral models, enabling more rapid and effective analysis of potential attacks to building automation. Full article

Background: Mandibular defects caused by trauma or tumor resection pose significant challenges in both functional and aesthetic reconstruction. Additive manufacturing (AM) technologies offer promising solutions for surgical planning and personalized treatment. Objectives: This review aims to evaluate current trends in the application of AM technologies for mandibular resection and reconstruction, with a particular focus on material selection, clinical integration, and technology-specific advantages. Methods: A structured literature review was performed using PubMed, Scopus, Web of Science, and Google Scholar. Studies published between January 2020 and May 2025 were screened using the following inclusion criteria: original peer-reviewed English-language research involving AM in mandibular surgery. The exclusion criteria included review articles, non-English sources, and non-mandibular studies. A total of 77 studies met the inclusion criteria and were analyzed in this review. Results: Based on the literature review conducted from 2020 to 2025, the most common restorative methods for the mandible using additively manufactured models include reconstruction with a titanium surgical plate bent to the curvature of the edges and angle of the mandible or a personalized titanium or PEEK surgical plate made directly based on the patient’s diagnosis. Implants made of Ti-6AL-4V ELI and bioceramic scaffolds are also used in the reconstruction process. They are developed based on patient diagnostic data and effectively replace the loss of mandibular bone structure. In addition, based on models and surgical guides created using additive manufacturing techniques, the performance of autogenous grafts from the fibula or iliac crest has improved significantly when used with a titanium implant plate. Conclusions: Additive manufacturing supports highly personalized and accurate mandibular reconstruction. The advantages of these methods include a reduced overall duration of procedures, a lower health risk for patients due to less reliance on general anesthesia, a near perfect match between the implant and the remaining hard tissues, and satisfactory aesthetic outcomes. However, success depends on the appropriate selection AM technology and material, particularly in load-bearing applications. Full article

The complexity of the processes occurring in both natural and artificial joints necessitates carrying out the analysis on a 3D model based on already existing mathematical models. All the presented numerical calculations define qualitative conclusions about the influence of certain parameters of endoprostheses on the values of stresses and strains arising in polyethylene parts of hip and knee endoprostheses. The obtained results make it possible to reveal “weak points” in the studied models and thus counteract the later effects resulting from premature wear of the endoprosthesis components. The study included a numerical analysis of the stress and strain distribution of polyethylene components of hip and knee endoprostheses working with the most commonly used material associations in this type of solution. The most common are metal alloys and ceramics. The analyses were carried out using ADINA and Autodesk Simulation Mechanical software. Geometric models were designed based on current solutions used by leading endoprosthesis manufacturers. The load models adopted are based on models commonly used in musculoskeletal biomechanics. Particular attention was paid to modeling the resistance due to friction at the hip endoprosthesis node. To build the hip endoprosthesis model, eight-node 3D solid elements were used. Due to the axisymmetric geometry of the model, the resulting discrete model consisted of 10,000 cubic elements described by 10,292 nodes. In the case of the knee endoprosthesis, a finite element mesh was adopted for the calculations, which was built with 3600 3D solid cubic elements and 4312 nodes. The accuracy of the adopted numerical model did not differ from the generally used solutions in this field. Full article

The rapid advancements in wireless technology and digital electronics have led to the widespread adoption of compact, intelligent devices in various aspects of daily life. These advanced systems possess the capability to sense environmental changes, process data, and communicate seamlessly within interconnected networks. Typically, such devices integrate low-power radio transmitters and multiple smart sensors, hence enabling efficient functionality across wide ranges of applications. Alongside these technological developments, the concept of the IoT has emerged as a transformative paradigm, facilitating the interconnection of uniquely identifiable devices through internet-based networks. This paper aims to provide a comprehensive exploration of sensor technologies, detailing their integral role within IoT frameworks and examining their impact on optimizing efficiency and service delivery in modern wireless communications systems. Also, it presents a thorough review of sensor technologies, current research trends, and the associated challenges in this evolving field, providing a detailed explanation of recent advancements and IoT-integrated sensor systems, with a particular emphasis on the fundamental architecture of sensors and their pivotal role in modern technological applications. It explores the core benefits of sensor technologies and delivers an in-depth classification of their fundamental types. Beyond reviewing existing developments, this study identifies key open research challenges and outlines prospective directions for future exploration, offering valuable insights for both academic researchers and industry professionals. Ultimately, this paper serves as an essential reference for understanding sensor technologies and their potential contributions to IoT-driven solutions. This study offers meaningful contributions to academic and industrial sectors, facilitating advancements in sensor innovation. Full article

This study explores the antioxidant potential and delivery performance of five structurally distinct cannabinoids, with a particular focus on cannabinol (CBN). Comprehensive structural characterization using mass spectrometry (MS) and nuclear magnetic resonance (NMR) revealed key molecular features relevant to antioxidant function. Among the tested compounds, CBN exhibited the most potent and balanced radical scavenging activity against 2,2-diphenyl-1-picrylhydrazyl (DPPH), hydroxyl, and superoxide radicals. Based on these findings, CBN was selected for formulation into soy lecithin liposomes. The resulting CBN-loaded liposomes displayed favorable colloidal properties, with an average size of approximately 122.9 ± 0.4 nm. Results indicating increased membrane order upon CBN incorporation suggest enhanced stability of the liposomal bilayer. Antioxidant activity assays showed that CBN-loaded liposomes retain significant radical scavenging capacity, though with a moderate reduction compared to free CBN. EPR imaging further demonstrated superior diffusion of liposomal CBN through a gelatin-based semi-solid model compared to the control solution. While the current model does not replicate skin architecture, it provides a cost-effective and reproducible platform for early-stage screening of formulation mobility. These results position CBN-loaded liposomes as a promising candidate for dermal antioxidant applications, combining favorable physicochemical properties with enhanced diffusion behavior. Full article

This study investigates the influence of hybrid filler systems comprising carbon black (CB), mica, and surface-modified mica (SM) on the properties of ethylene–propylene–diene monomer (EPDM)/butadiene rubber (PB) composites. To reduce the environmental issues associated with CB, mica was incorporated as a partial substitute, and its compatibility with the rubber matrix was enhanced through surface modification using ureidopropyltrimethoxysilane (URE). The composites with hybrid filler systems and surface modification were evaluated in terms of curing behavior, crosslink density, mechanical and elastic properties, and dynamic viscoelasticity. Rheological analysis revealed that high mica loadings delayed vulcanization due to reduced thermal conductivity and accelerator adsorption, whereas SM composites maintained comparable curing performance. Swelling tests showed a reduction in crosslink density with increased unmodified mica content, while SM-filled samples improved the network density, confirming enhanced interfacial interaction. Mechanical testing demonstrated that the rubber compounds containing SM exhibited average improvements of 17% in tensile strength and 20% in toughness. In particular, the CB20/SM10 formulation achieved a well-balanced enhancement in tensile strength, elongation at break, and toughness, surpassing the performance of the CB-only system. Furthermore, rebound resilience and Tan δ analyses showed that low SM content reduced energy dissipation and improved elasticity, whereas excessive filler loadings led to increased hysteresis. The compression set results supported the thermal stability and recovery capacity of the SM-containing systems. Overall, the results demonstrated that the hybrid filler system incorporating URE-modified mica significantly enhanced filler dispersion and rubber–filler interaction, offering a sustainable and high-performance solution for elastomer composite applications. Full article

This article presents experimental studies on the characterization of geopolymer composites intended for applications in aquatic environments, with particular emphasis on underwater infrastructure. The motivation for conducting the research was the growing need to develop durable and ecological building materials that will be resistant to long-term exposure to moisture and aggressive chemical agents, typical for the underwater environment, where traditional cement concretes undergo gradual degradation due to long-term water impact, including hydrotechnical and underwater infrastructure. Geopolymer binders were produced based on metakaolin activated by alkaline solutions containing sodium hydroxide. Several series of mixtures with additives such as blast furnace slag, amphibolite and carbon fibers were developed to evaluate the effect of these components on mechanical strength, water absorption and chemical durability. The conducted studies showed that slag additions improved mechanical properties, for the best composition it across 50 MPa. In contrast, the addition of amphibolite had an unfavorable effect, which probably results from introducing inhomogeneity into the material structure. The presence of carbon fibers promoted matrix cohesion, but their uneven distribution could lead to local strength differences. Water absorption tests have shown that geopolymers reach full water saturation within 24 to 48 h, which indicates rapid establishment of capillary equilibrium and limited further water penetration. The conclusions from the work indicate that geopolymer composites with a moderate amount of blast furnace slag and subjected to appropriate curing conditions. High strength, water and chemical resistance make them suitable for, among others, the construction of marine foundations, protection and structural shields of submerged applications. Full article