Search Results (8,291)

Current marine research that leverages remote sensing data urgently requires gridded data of high spatial and temporal resolution. However, such high-quality data is often lacking due to the inherent physical and technical constraints of sensors. A necessary trade-off therefore exists between spatial, temporal, and spectral resolution in satellite remote sensing technology: increasing spatial resolution often reduces the coverage area, thereby diminishing temporal resolution. This manuscript introduces an innovative remote sensing image fusion algorithm that combines Sentinel-2 (high spatial resolution) and Sentinel-3 (relatively high spectral and temporal resolution) satellite data. The algorithm, based on a cross-attention mechanism and referred to as the Cross-Attention Spatio-Temporal Spectral Fusion (CASTSF) model, accounts for variations in spectral channels, spatial resolution, and temporal phase among different sensor images. The proposed method enables the fusion of atmospherically corrected ocean remote sensing reflectance products (Level 2 OSR), yielding high-resolution spatial data at 10 m resolution with a temporal frequency of 1–2 days. Subsequently, the algorithm generates chlorophyll-a concentration remote sensing products characterized by enhanced spatial and temporal fidelity. A comparative analysis against existing chlorophyll-a concentration products demonstrates the robustness and effectiveness of the proposed approach, highlighting its potential for advancing remote sensing applications. Full article

This article presents selected issues related to the reliability of the power supply for electronic security systems (ESSs) used in smart buildings (SBs). ESSs operate in diverse environmental conditions and are responsible for the safety of lives, property and the natural environment of SB users. The operational tasks of ESSs in SBs require a continuous power supply from various sources, including renewable energy sources. The authors conducted an analysis of the power supply for selected ESSs used in SBs, which enabled the development of a power supply model. For the proposed model, the authors designed a proprietary graph of the ESS operational process, taking into account power supply implementation. Considering the operational indicators for the analysed ESSs, such as repair and failure rates, a computer simulation was performed. The simulation allowed the determination of the reliability of the ESS power supply within the considered redundancy configuration of additional energy sources, which can be utilised during the design phase. The reliability analysis of the power supply and the determination of rational parameters conducted in the article are crucial for achieving all the functionalities of ESSs in SBs, as envisioned during the design process. The article is divided into six chapters, structured to address the topics sequentially: an introduction to the state of the issue, a critical literature review, an analysis of the power supply for selected ESSs, implementation of renewable energy sources, the development of a proprietary model and operational graph, a computer simulation and conclusions. Full article

The increasing environmental impacts caused by the high demand for concrete production have underscored the need for sustainable alternatives in the design of eco-concrete mixtures. Additionally, important industries, such as construction and mining, generate massive amounts of waste/by-products that could be repurposed towards sustainability. Consequently, this study investigates the valorization of copper slag (CS), a by-product of the mining industry as a supplementary cementitious material (SCM), and concrete as recycled coarse aggregate (RCA), derived from construction and demolition waste, as partial substitutes for Ordinary Portland Cement (OPC) and natural coarse aggregate (NCA), respectively. Eco-concrete mixtures were designed with varying replacement levels: 15% for CS, and 0%, 20%, 50%, and 100% for RCA. The mechanical properties (compressive, indirect tensile, and flexural strengths), permeability characteristics (porosity and capillary suction), and environmental impacts (carbon footprint) of these mixtures were evaluated. The results showed that the use of CS and of increasing proportions of RCA led to a monotonic loss in each of the concretes’ mechanical strength properties at 7, 28 and 90 days of curing. However, at extended ages (180 days of curing), the concrete mixtures with CS and only NCA presented an average compressive strength 1.2% higher than that of the reference concrete (mixture with only OPC and natural aggregate). Additionally, the concrete mixture with CS and 20% RCA achieved 3.2% and 5.8% higher average values than the reference concrete in terms of its indirect tensile strength and flexural strength, respectively. Finally, a cradle-to-gate life cycle assessment (LCA) analysis was implemented, whose results showed that the greatest effect on reducing the carbon emission impacts occurred due to the substitution of OPC with CS, which confirmed that the adequate technical performances of some of the concrete mixtures developed in this study are positively complemented with reduced environmental impacts. Moreover, this study presents a viable approach to minimizing resource consumption and waste generation, contributing to the advancement of eco-friendly construction materials, which aligns with the sustainable development goals. Full article

The transport of oversized loads, such as wind turbine components, represents a key logistical challenge due to specific technical and regulatory requirements. The development of the renewable energy sector, particularly wind energy in Poland, has significantly increased the demand for this type of transport. The implementation of wind farm construction projects requires not only advanced technological solutions but also special attention to transport safety and the organization of logistical processes. This study employed the FMEA (Failure Mode and Effects Analysis) risk analysis method, which allows for the identification of potential defects and their causes. Data were collected through surveys, interviews with representatives of transport companies, and field observations. The research sample included 11 companies specializing in oversized transport in Poland and European countries. Based on the gathered information, 15 typical risks associated with the transport of wind turbine components were identified. The most significant risks include the possibility of road accidents and discrepancies between the actual dimensions of the cargo and the transport documentation. The results highlight the need for improvements in route planning, precise verification of cargo parameters, and better management of administrative processes related to obtaining permits. The development of the wind energy sector and dynamic investments in wind farms make the optimization of oversized transport a crucial element in supporting the execution of eco-friendly projects and sustainable development. Full article

Enabling technologies (KETs) offer transformative potential for agriculture by addressing major challenges such as climate change, resource efficiency, and sustainable development across economic, social, and environmental dimensions. However, KET adoption is often limited by high R&D requirements, rapid innovation cycles, investment costs, and cultural or training barriers, especially among small agricultural businesses. Sicily’s agricultural sector, already strained by pandemic-related economic setbacks and inflationary pressures, faces additional barriers in adopting these technologies. To investigate these adoption challenges and develop viable solutions, the ARIA Living Lab (Agritech Research Innovation Environment) was established within the PNRR framework. A qualitative approach was used, involving documentary analysis and data from stakeholders across Sicilian agriculture. This approach enabled an in-depth exploration of sector-specific needs, infrastructure, and socio-economic factors influencing KET adoption. The analysis highlighted that adoption barriers differ significantly across sectors (citrus, olive, and wine), with public incentives and digital infrastructure playing key roles. However, a persistent lack of technical skills among farmers reduces the effectiveness of these innovations. The findings suggest that an integrated approach—combining targeted incentives, training, and enhanced infrastructure—is essential for a sustainable transition to KETs. Future research should examine collaborative efforts between farms and tech providers and evaluate the impact of public policies in promoting the widespread, informed adoption of enabling technologies. Full article

Agricultural services, understood as the rental of machinery and equipment with appropriate labor, are one of the three types of production services in agriculture distinguished by European Union legislation. The aim of this paper is to identify clusters of regions in the European Union that differ in the level of use of agricultural services on farms and in selected characteristics related to production potential, labor input, and type of agricultural production. For this purpose, Ward’s method, from the group of hierarchical agglomerative cluster analysis methods, was used. Based on data on farms using agricultural services in 124 regions of the European Union, six clusters were formed. The study showed that agricultural services substitute for labor inputs in intensive agricultural production conditions, but in a situation with good technical equipment, farms may more often choose to employ hired workers. Such substitution does not occur in regions that are moderately and less well-equipped with machinery and equipment, because hired labor cannot completely replace the scarcity of machinery. The level of use of agricultural services is also related to the profile of the production carried out and the area of agricultural land, followed by the resources of land, capital, and labor. The level of economic development and historical background are also important. Full article

This study examines the impact of issue-based teaching (IBT) on programming self-efficacy among non-Computer Science students. Grounded in social cognitive theory, the research investigates how IBT influences learning satisfaction and project success compared to traditional metrics. This study employed a mixed-methods approach, combining the quantitative analysis of student performance and self-efficacy measures with qualitative feedback from learning portfolios and project reports. The findings indicate that programming self-efficacy is a stronger predictor of learning satisfaction and project success than traditional performance metrics like grades. For novice programmers, IBT effectively enhances self-efficacy, positively influencing goal identification and performance. This cascade effect highlights the importance of fostering self-efficacy in programming education for non-technical students. Qualitative analysis reveals that IBT contributes to students’ sense of achievement, motivation, and learning satisfaction, encouraging them to view programming as a practical problem-solving tool. This study concludes that IBT offers an effective approach to enhancing interdisciplinary and STEAM education, recommending that educators focus on building self-efficacy through issue-based, learner-centered approaches. Full article

To maximize the business value of the cloud, the cost of cloud solutions is explored alongside technical quality and performance. To enable this form of exploration engineering, finance and business teams collaborate in the context of FinOps, the operational framework that provides the required decision-making. Prominent providers, such as Google and Microsoft, provide FinOps to their customers, integrating cost factors when designing a cloud solution. However, different providers apply different pricing policies for their products, and these policies also change through time. Therefore, there are numerous efforts to explore price evolution through time for different cloud products applying different decision-making methods using different datasets. In an effort to establish a systematic approach to support decision-making on alternative pricing policies for cloud services and compare them across services and providers, the CloudPricingOps framework is proposed in this paper. It constitutes a decision support system that provides alternative decision-making methods, such as hedonic models, time series, and clustering and machine learning techniques, to deal with problems related to cloud product pricing policy analysis, comparison and prediction. It also constitutes a systematic method of discrete steps to integrate additional decision-making methods to deal with these problems and input datasets to be used regardless of the method or the cloud pricing problem that needs to be solved. Two discrete examples based on real data are also presented in this paper to demonstrate the usefulness of the CloudPricingOps framework for cloud engineering and business teams. Full article

This paper concerns the application of the AHP (analytic hierarchy process) multi-criteria decision support method for the final selection of the structure of a hybrid power system with RESs (renewable energy sources) and EES (electrical energy storage) from a set of solutions obtained through multi-criteria optimization. These solutions, depending on their position within the Pareto front, may differ significantly in terms of the values of the criteria functions, or may be located very close to each other in the solution space. The role of the expert is to select the final solution, taking into account many additional criteria, often of a subjective nature. The article optimizes the structure of the proposed system using the multi-criteria NSGA-II (Non-dominated Sorting Genetic Algorithm) method, taking into account three technical criteria. The AHP method was used to select the final solution, which allows determination of the ranking of solution variants, taking into account selected additional criteria. In the analyzed case, these are primarily economic indicators, technical conditions, and preferences of the system recipients. In addition to determining the ranking of solutions, a sensitivity analysis was performed, which gives the expert extensive knowledge on the impact of individual criteria on the order of variants in the ranking. It was shown that in the case of selecting hybrid structures of generating systems with EES for a specific type of receiver, the use of the AHP method significantly facilitates making the final decision. Full article

The aim of the presented research was to evaluate the impacts of modifications to the technical properties of fly ash-based geopolymer composites, particularly focusing on enhancing the thermal insulation. Through the utilization of a generalized utility function, optimal dosages of additives such as perlite sand, waste perlite powder, and cenospheres were determined. The study aimed to increase the thermal insulation of the composites while maintaining satisfactory compressive and flexural strength. The results indicated that dosages of perlite dust and cenospheres significantly influenced the technical characteristics of the composites; an exception was the flexural strength, for which these modifications did not show a statistically significant effect. The average compressive strength values, except for the mixes with poor workability, were at least 3.5 MPa (RILEM class II). Notably, a balanced dosage of additives, around 75 kg per cubic meter of the mixture in the total mixture, yielded the most favorable outcomes in terms of thermal isolation (0.18–0.24 W/(m·K) and workability (cone immersion 40–70 mm). Additionally, perlite dust emerged as a potentially superior modifier due to its waste origin. However, further analysis considering life cycle parameters including the carbon footprint and water footprint would be necessary to validate this claim. Overall, the study highlights the potential of utilizing perlite-based modifiers to enhance the thermal insulation of geopolymers while addressing environmental concerns. Full article

In the repeated launching process, there is an Aluminum Deposited Layer (ADL) on the rail surface. The ADL will melt when heated, and its different melting states will have an important influence on the armature melting process. Therefore, it is necessary to analyze the melting characteristics of the armature under different melting states of the ADL. Firstly, the ADL’s thickness and its melting state are analyzed. Secondly, theoretical calculation models of armature melting are established under the partially melted state and the fully melted state of the ADL, respectively, and the influence of the melting state of the ADL on armature melting is investigated. Finally, considering the effect of non-uniform contact pressure on contact resistance, a three-dimensional finite element simulation model of armature surface melting morphology was established based on multi-physics field coupling for a more accurate analysis of armature surface melting and making a comparative analysis with the experimental results and theoretical analysis results. The results show that the ADL’s thickness increases linearly with the number of shots. When the ADL’s thickness is thin enough, it is in a fully melting state. With the increase in the ADL’s thickness, the ADL will transition to a partially melting state. When the ADL is in a fully melting state, the melting of the armature decreases with the increase in the ADL’s thickness. When the ADL’s thickness reaches a certain value, the corresponding armature melting is reduced to the minimum and no longer changes. The maximum melting depth of the armature surface calculated by finite element is 0.617 mm, which is close to the experimental measurement result of 0.6 mm, verifying the accuracy of the model. The research results can provide a basis for studying the melting mechanism of the armature and provide technical support for controlling ADL and optimizing the design of the armature structure. Full article

The paper explores the concept of energy poverty (EP) by examining its definition, dimensions, determinants, and impacts on households. The study underscores the necessity of comprehending the multifaceted subjective and objective nature of energy poverty, as evidenced by the proposal of a comprehensive tool for measuring energy poverty from a broad perspective. The concept of energy poverty comprises seven principal dimensions, namely, political, economic, health, infrastructure, social, energy transfer, and climate and environmental. Each of these dimensions operates as both a cause and a consequence of energy poverty, thereby creating a cyclical relationship between the various determinants. A significant aspect of the study is the utilization of objective and subjective indicators. These include measures of the relationship between expenditure and income, the technical condition of buildings, thermal comfort, debt, and initiatives taken to prevent this phenomenon at the household level. The concept posits a novel attribute of EP, namely, “transitional state”, which signifies that energy poverty can concurrently serve as a catalyst and a consequence of adverse socio-economic phenomena in certain instances affecting the overall quality of life. The recommendations encompass using a holistic method that considers not only the analysis of the energy poverty index but also detailed and subjective indicators. The proposed tool will enable a more effective formulation of public policy at the European Union level, providing a unified direction to research this phenomenon at multiple precision levels. Full article

Background/Objectives: Strokes remain a major global health concern, contributing significantly to disability and healthcare costs. Currently, there are no established indicators to accurately assess the degree of muscle tissue impairment in stroke-affected individuals. However, ultrasound imaging with an echotexture analysis shows potential as a quantitative tool to assess muscle tissue quality. This study aimed to identify specific echotexture features in the gastrocnemius medialis that effectively characterize muscle impairment in post-stroke individuals. Methods: An observational study was conducted with 22 post-stroke individuals. A total of 21 echotexture features were extracted and analyzed, including first-order metrics, a grey-level co-occurrence matrix, and a grey-level run length matrix. The modified Heckmatt scale was also applied to correlate with the most informative echotexture features. Results: Among the features analyzed, echovariation (EV), echointensity, and kurtosis emerged as the most informative indicators of muscle tissue quality. The EV was highlighted as the primary feature due to its strong and significant correlation with the modified Heckmatt scale (r = −0.81, p < 0.001) and its clinical and technical robustness. Lower EV values were associated with poorer muscle tissue quality, while higher values indicated better quality. Conclusions: The EV may be used as a quantitative indicator for characterizing the gastrocnemius medialis muscle tissue quality in post-stroke individuals, offering a more nuanced assessment than traditional qualitative scales. Future studies should investigate the correlation between the EV and other clinical outcomes and explore its potential to monitor the treatment efficacy, enhancing its applicability in clinical practice. Full article

Agrivoltaics (AV) are expanding worldwide, but knowledge about the perception and acceptance of this approach is far from complete. The aim of the present study was to investigate the visual perception and acceptance of AV systems, focussing on the central research question of whether the type of grassland use influences the visual perception and acceptance of vertical interspace AV. For this purpose, three photo-based pictures of a vertical interspace AV plant were used in a laboratory experiment with 29 participants: the original photo showing the AV plant with grassland only; an edited photo with cattle added and an edited photo with silage bales added. The eye-tracking results showed that additional picture elements (i.e., cattle and silage bales) at least partially attracted visual attention, but did not distract from the technical elements of the depicted AV systems. The analysis of the acceptance ratings indicated relatively stable attitudes towards AV, which could not be easily modulated by depicting different types of grassland use within AV systems. Short-term and limited changes in attitudes towards AV appeared to result from the provision of information and mental engagement with the topic. We recommend carrying out further research based on larger, representative samples and more realistic stimuli of AV systems that would provide a better understanding of visual perception and acceptance than photos alone, such as on-site visits or VR visualisations, to enhance the external validity of the results. We also suggest conducting longitudinal studies to explore possible long-term effects on the public acceptance of AV systems. Full article

(1) Background: Fetal chromosomal examination is a critical component of modern prenatal testing. Traditionally, maternal serum biomarkers such as free β-human chorionic gonadotropin (Free β-HCG) and pregnancy-associated plasma protein A (PAPPA) have been employed for screening, achieving a detection rate of approximately 90% for fetuses with Down syndrome, albeit with a false positive rate of 5%. While amniocentesis remains the gold standard for the prenatal diagnosis of chromosomal abnormalities, including Down syndrome and Edwards syndrome, its invasive nature carries a significant risk of complications, such as infection, preterm labor, or miscarriage, occurring at a rate of 7 per 1000 procedures. Beyond Down syndrome and Edwards syndrome, other chromosomal abnormalities, such as trisomy of chromosomes 9, 16, or Barr bodies, pose additional diagnostic challenges. Non-invasive prenatal testing (NIPT) has emerged as a powerful alternative for fetal genetic screening by leveraging maternal blood sampling. However, due to the extremely low abundance of fetal cells in maternal circulation, NIPT based on fetal cells faces substantial technical challenges. (2) Methods: Fetal nucleated red blood cells (FnRBCs) were first identified in maternal circulation in a landmark study published in The Lancet in 1959. Due to their fetal origin and presence in maternal peripheral blood, FnRBCs represent an ideal target for non-invasive prenatal testing (NIPT). In this study, we introduce a novel self-assembled cell array (SACA) chip system, a microfluidic-based platform designed to efficiently settle and align cells into a monolayer at the chip’s base within five minutes using lateral flow dynamics and gravity. This system is integrated with a fully automated, multi-channel fluorescence scanning module, enabling the real-time imaging and molecular profiling of fetal cells through fluorescence-tagged antibodies. By employing a combination of Hoechst+/CD71+/HbF+/CD45− markers, the platform achieves the precise enrichment and isolation of FnRBCs at the single-cell level from maternal peripheral blood. (3) Results: The SACA chip system effectively reduces the displacement of non-target cells by 31.2%, achieving a single-cell capture accuracy of 97.85%. This isolation and enrichment system for single cells is well suited for subsequent genetic analysis. Furthermore, the platform achieves a high purity of isolated cells, overcoming the concentration detection limit of short tandem repeat (STR) analysis, demonstrating its capability for reliable non-invasive prenatal testing. (4) Conclusions: This study demonstrates that the SACA chip, combined with an automated image positioning system, can efficiently isolate single fetal nucleated red blood cells (FnRBCs) from 50 million PBMCs in 2 mL of maternal blood, completing STR analysis within 120 min. With higher purification efficiency compared to existing NIPT methods, this platform shows great promise for prenatal diagnostics and potential applications in other clinical fields. Full article