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Comparative evaluation of nonparametric density estimators for Gaussian mixture models with clustering support /
No full textThe article investigates the accuracy of nonparametric univariate density estimation methods applied to various Gaussian mixture models. A comprehensive comparative analysis is performed for four popular estimation approaches: adaptive kernel density estimation, projection pursuit, log-spline estimation, and wavelet-based estimation. The study is extended with modified versions of these methods, where the sample is first clustered using the EM algorithm based on Gaussian mixture components prior to density estimation. Estimation accuracy is quantitatively evaluated using MAE and MAPE criteria, with simulation experiments conducted over 100,000 replications for various sample sizes. The results show that estimation accuracy strongly depends on the density structure, sample size, and degree of component overlap. Clustering before density estimation significantly improves accuracy for multimodal and asymmetric densities. Although no formal statistical tests are conducted, the performance improvement is validated through non-overlapping confidence intervals obtained from 100,000 simulation replications. In addition, several decision-making systems are compared for automatically selecting the most appropriate estimation method based on the sample’s statistical features. Among the tested systems, kernel discriminant analysis yielded the lowest error rates, while neural networks and hybrid methods showed competitive but more variable performance depending on the evaluation criterion. The findings highlight the importance of using structurally adaptive estimators and automation of method selection in nonparametric statistics. The article concludes with recommendations for method selection based on sample characteristics and outlines future research directions, including extensions to multivariate settings and real-time decision-making systems
Numerical method for internal structure and surface evaluation in coatings /
No full textThis study introduces a MATrix LABoratory (MATLAB, version R2024b, update 1 (24.2.0.2740171))-based automated system for the detection and measurement of indication areas in coated surfaces, enhancing the accuracy and efficiency of quality control processes in metal, polymeric and thermoplastic coatings. The developed code identifies various indication characteristics in the image and provides numerical results, assesses the size and quantity of indications and evaluates conformity to ISO standards. A comprehensive testing method, involving non-destructive penetrant testing (PT) and radiographic testing (RT), allowed for an in-depth analysis of surface and internal porosity across different coating methods, including aluminum-, copper-, polytetrafluoroethylene (PTFE)- and polyether ether ketone (PEEK)-based materials. Initial findings had a major impact on indicating a non-homogeneous surface of obtained coatings, manufactured using different technologies and materials. Whereas researchers using non-destructive testing (NDT) methods typically rely on visual inspection and manual counting, the system under study automates this process. Each sample image is loaded into MATLAB and analyzed using the Image Processing Tool, Computer Vision Toolbox, Statistics and Machine Learning Toolbox. The custom code performs essential tasks such as image conversion, filtering, boundary detection, layering operations and calculations. These processes are integral to rendering images with developed indications according to NDT method requirements, providing a detailed visual and numerical representation of the analysis. RT also validated the observations made through surface indication detection, revealing either the absence of hidden defects or, conversely, internal porosity correlating with surface conditions. Matrix and graphical representations were used to facilitate the comparison of test results, highlighting more advanced methods and materials as the superior choice for achieving optimal mechanical and structural integrity. This research contributes to addressing challenges in surface quality assurance, advancing digital transformation in inspection processes and exploring more advanced alternatives to traditional coating technologies and materials
Sustainable composites from banana plant waste /
No full textIn view of the growing concern about global pollution, sustainable composites made from food waste products are emerging as a key direction for the development of new materials. Banana plants are cultivated primarily for fruit production, and after the fruits are harvested, the plants become waste. However, banana plants contain a significant amount of fiber, which can be used for industrial applications. While banana fibers are not of sufficient quality for clothing manufacturing, they can be useful for technical applications, such as composites. In this work, several types of banana fibers were used for composite reinforcement, sourced from different parts of the banana plant: outer bark, middle bark, inner bark, and midrib. It was found that fibers from different parts of the banana plant exhibit distinct properties, and the mechanical properties of composites made from these fibers also varied. Two types of polymer matrices-bio-based epoxy resin and unsaturated polyester resin-were used for composite manufacturing. Various surface treatments were applied at different stages of material development to enhance the properties of the nonwovens and composites. These included alkali treatment to improve the mechanical properties of the fibers, water-repellent treatment to enhance the hydrophobicity of the nonwoven surfaces, and gamma radiation to further improve the mechanical properties of the composite. The results showed that composites made from outer bark banana fibers exhibited superior mechanical properties and water absorbency compared to others. Additionally, the epoxy-based composites demonstrated significantly higher mechanical properties and hydrophobicity compared to polyester-based composites. The developed composites have potential applications in various technical fields, such as packaging materials, construction panels, and more
Gluten functionality modification: the efect of enzymes and ultrasound on the structure of the gliadin-glutenin complex and gelling properties /
No full textThe broader application of gluten in both the food and non-food industries is limited by its lack of functional properties, such as solubility, foaming ability, and rheological characteristics. This study aimed to evaluate the physicochemical properties of proteins in various gluten products and to investigate the effects of enzymatic hydrolysis and ultrasound (US) treatment on wheat flour gluten yield, gliadin–glutenin complex structure, and gelation properties. The gelation properties of wheat gluten (GL)/pea protein (PP) treated with US and transglutaminase (TG) were studied. The results demonstrated that the ratio of low- to high-molecular-weight components in gliadins and glutenins significantly influenced the quality of commercial gluten products. A 90 min treatment of wheat flour with 24 TGU/100 g increased the yield of high-quality gluten by 32% while reducing the gliadin content by up to 6-fold. Additionally, a 30 min US treatment of 18–20% pure gluten suspensions yielded a sufficiently strong gel. The addition of PP isolate (80% protein) improved the texture of gluten gels, with the best results observed at a GL:PP ratio of 1:2. The application of TG increased the hardness, consistency, and viscosity of GL-PP gels by an average of 5.7 times while reducing stickiness. The combined TG and US treatments, along with the addition of PP, notably increased the levels of lysine, isoleucine, and tryptophan, thereby enhancing both the nutritional quality and amino acid balance of the final product
Formation of production cost by the methods of “target costing” and “kaizen costing” and their impact on the enterprise efficiency /
No full textThe object of this research is the process of formation of costs of enterprises for the production and sale of industrial products. The need for such a study is determined by the use of outdated methods of forming the cost of production at Ukrainian industrial enterprises, which are based on the actual costs of the enterprise. It is proved that the existing provisions of direct costing do not reproduce the provisions of the market pricing mechanism, since the market price is focused not on actual costs, but on the needs and preferences of consumers of products. A detailed study of the existing methods of forming the cost of production was carried out, among which special attention was paid to modern methods of target costing and kaizen costing, developed and widely tested by economists of Japanese enterprises. The main advantages of target costing and kaizen costing systems when they are used in the conditions of the Ukrainian economy are studied and substantiated. The systems proposed for use provide for putting in the first place not the actual costs, but the market price of the product, and the costs are formed taking into account the desired level of profit for the enterprise. This approach involves the integral (complex) use of target costing and kaizen costing. It has been proven that the combination of these two systems allows to create a continuous cycle of production cost management at all stages of the product life cycle. Target costing provides strategic cost control during the product design phase, while kaizen costing supports and increases efficiency during the production and operation phase. The combination of targeted costing and kaizen costing provides a significant increase in the efficiency of industrial enterprises, is an effective way to achieve strategic and operational goals, increase the competitiveness and sustainable development of industrial enterprises. This is achieved due to the complementarity of these systems at different stages of the product life cycle
Rethinking the future of intellectual capital: emerging perspectives in IC theory and practice /
No full textIntellectual capital (IC) theory, emphasizing that the primary source of organizational value is derived from intangible, knowledge-based resources, has long been recognized as a critical driver of sustainable competitive advantage. However, as the business landscape continues to evolve in the face of technological, institutional and socio-political disruptions, and natural disturbances, it seems viable that the theories for understanding IC and practices for managing it should also be updated. This paper seeks to challenge and advance existing IC theory by presenting a forward-looking exploration of the evolving landscape of IC. We propose some critical theoretical and practical updates that can bridge the gap between conceptual advancements and real-world applications. By adopting an ecosystem-oriented approach, we highlight how IC operates across different levels of analysis- from individual to societal - and how multilevel, dynamic, and complex interactions within the IC ecosystem contribute to innovation, value creation, and sustainable development. The paper challenges traditional IC frameworks by emphasizing the fluid, interconnected nature of IC, arguing that a more holistic, dynamic model is essential for understanding and leveraging IC in today’s rapidly changing environment. Furthermore, we argue that future IC agendas must address broader concerns, including sustainability, IC ethics, IC diplomacy, fair and socially equitable distribution of value, and societal justice. Recognizing this progress in IC research and practice as essential for sustainable growth and social well-being in the coming era, we aim to contribute to a deeper understanding of emerging paradigms and to align IC theory and practice with future economic, technological and social transformations
Eco-sustainable printing of cellulosic polymeric material using bio-colorants and bio-crosslinkers /
No full textA sustainable solution to lessen environmental damage, improve health and fulfill the increasing need for environmentally conscious goods might be for the textile industry to use eco-friendly printing techniques and natural colors. Without the use of toxic metal-based mordants, this research work set out to examine how natural thickeners, biomordants, and dyes interacted when printed on cotton knit fabric. Two natural dyes from natural resources leaves Jujube leaves (JL) and Eucalyptus bark (EB) were extracted in an aqueous medium. A printing paste was produced using different proportions of two bio-mordants. For an eco-friendly printing process, tamarind seeds, and Indian gooseberries were used that have been extracted using a Soxhlet apparatus at 80°C for 8 h. All but a handful of samples using natural binders showed outstanding fastness in the printed sample which was graded 4 or 5. The development of the dye-fiber bond was indicated by the presence of an intense covalent bond between the dye and fiber molecules as indicated by FTIR. The CMC lab data and K/S value of the printed samples were also obtained satisfactorily with maximum RFL value 77.319 and K/s value 1.659. This method not only lessens the environmental impact of the sector but also supports a better and more ecologically sensitive manufacturing technique. Moreover, sustainable apparel, household textiles, technical fabrics, and environmentally friendly packaging can all benefit from eco-friendly printing using bio-colorants and bio-crosslinkers. Highlights: Eco-friendly printing on cotton using jujube and eucalyptus dyes reduces environmental harm. Bio-mordants from tamarind seeds and gooseberry effectively replace harmful metal-based mordants. Printed samples show excellent fastness ratings of 4–5, proving the quality of eco-friendly printing. FTIR analysis confirms strong covalent bonds between dye and fiber molecules. This method supports sustainability by using renewable, biodegradable resources in textile production
User-driven climate resilience across Southern European regions /
No full textThis study presents the ClimEmpower framework, a user-driven approach to enhancing climate resilience across five climate-vulnerable regions in Southern Europe: Costa del Sol (Spain), Central Greece, the Troodos Mountains (Cyprus), Osijek-Baranja County (Croatia), and Sicily (Italy). The project employs a region-specific methodology that integrates climate risk assessments, stakeholder engagement through Communities of Practice (CoPs), and the development of innovative climate services tailored to local needs. These regions, characterized by unique environmental and socio-economic vulnerabilities, face shared hazards such as droughts, heatwaves, and floods, alongside region-specific challenges like salinization and biodiversity loss. ClimEmpower identifies critical gaps in high-resolution data, cross-sectoral collaboration, and capacity-building efforts, underscoring barriers to effective adaptation. This work aims to provide a foundational resource, offering a comprehensive overview of the current situation, including needs, gaps, priorities, and expectations across the target regions. By establishing this baseline, it facilitates future research and comparative analyses, contributing to the development of robust, region-specific resilience strategies. The ClimEmpower framework offers scalable and replicable solutions aligned with the European Green Deal’s climate resilience goals, advancing adaptation planning and providing actionable insights for broader European initiatives
Efektyvių elektroliuminescencinių prietaisų kūrimas panaudojant organinių spinduolių eksitonų virsmus iš tripletinės į singletinę būseną.
No full textThe study of organic semiconductors has got significant attention due to their unique potential and associated challenges. These materials, predominantly composed of carbon-based small molecules or polymers, exhibit distinct advantages over conventional inorganic semiconductors, including intrinsic flexibility, cost-efficient production processes, and solution-processability. Such characteristics position organic semiconductors as ideal candidates for applications in flexible displays, wearable electronics, and biodegradable sensors. A critical focus in this field lies in the efficient manipulation of excitons — electron-hole pairs within semiconductors, which is central to optimizing their performance in optoelectronic applications. Despite these advances, the effective utilization of excitons for light emission remains a fundamental challenge. Among the most promising approaches to address this issue is triplet harvesting, a technique that facilitates the conversion of non-emissive triplet excitons into emissive singlet excitons, thereby enhancing theoretical internal quantum efficiency (IQE) from 25% to nearly 100%. This dissertation systematically investigates three distinct triplet harvesting mechanisms: thermally activated delayed fluorescence (TADF), triplet-triplet annihilation (TTA), and hybridized local and charge-transfer excited states (HLCT). These mechanisms have been crucial in enabling organic light-emitting diodes (OLEDs) to achieve external quantum efficiencies exceeding 25%, marking a significant advancement in the field of organic optoelectronic devices
Flexural and pseudo-ductile performance of unidirectional and bidirectional carbon fabric-reinforced mortar /
No full textThis research aims to study the effect of introducing unidirectional (CFu) and bidirectional (CFb) carbon fabric into cement mortar (CM) on its flexural and pseudo-ductile performances. The experiments were performed on fabric/CM samples with a varying fabric distribution (single, double, and triple layers). The cohesion of fabrics in CM matrices and morphology of the damaged surfaces were examined using an optical microscope, while the flexural response was measured using a universal testing machine. The pseudo-ductile property, in the form of the ductility index (DI), was numerically modelled for CM matrices based on the measured flexural curves using different energy criteria models. Microstructure analysis showed a strong fabric cohesion in the matrices along with the production of more hydration products, which led to a transformation in the linear load–deformation relationship of mortar into the ideal shape of ductile material in the case of CFb/CM. In the case of the CFu/CM samples, two main drop points appeared with a long distance between them. In addition, the flexural load was significantly increased by introducing three layers of each type of fabric to CM, with an improvement of 75% (CFu/CM) and 68% (CFb/CM) compared to neat mortar. Similarly, the deformation till break was improved by 452% (CFu/CM) and 367% (CFb/CM). The DI analysis confirmed these results: the DI performance was improved by up to 140% by embedding. Based on these results, carbon fabric has high potential to enhance the strength and ductility of cementitious matrix