Search Results (101)

Strategic logistics planning is used by management to define action plans that will enable organizations to always make decisions that are in the organization’s best interests. They are based on a knowledge repository of business experiences, which is usually represented by a centralized, organized, and searchable digital system where organizations store and manage critical institutional knowledge. Thus, an institutional knowledge base provides sustainability, making the experiences readily available while keeping them well organized. In this research, the experiences of logistics experts from selected scholarly designs for six-sigma business improvement projects have been collected, classified, and organized to form a logistics knowledge management system. Although originally meant to facilitate current and future decisions in strategic logistics planning of the cooperating companies, it is also used in logistics education to introduce knowledge-based engineering principles to enterprise strategic planning, based on continuous improvement of quality-related product or process performance indicators. The main goal of this article is to highlight the benefits of knowledge-based engineering over the established ontological logistics knowledge base in smart production, based on the predisposition that ontological institutional knowledge base management is more efficient, adaptable, and sustainable. Full article

This study examines how the Norwegian Child Welfare Tribunal justifies regulating telephone and digital communication between children in public care and their parents. The regulation of such contact represents a distinct form of state interference in family life and must adhere to principles of necessity, proportionality, and respect for children’s rights. Using a thematic analysis of 34 Tribunal decisions involving 44 children, the study identifies four central themes: ensuring stability and emotional security, addressing parental behavior, balancing proportionality and necessity, and considering the child’s view. The Tribunal’s reasoning often reflects a cautious, preventive approach, prioritizing emotional stability. However, the lack of transparent assessments of necessity and inconsistent inclusion of children’s perspectives raises concerns about proportionality and children’s autonomy. Additionally, the limited involvement of children in these decisions risks making restrictions difficult to implement in practice, as children may not understand or agree with them and instead seek unregulated contact. The findings underline the need for clearer justifications and more consistent consideration of a child’s view to ensure that decisions align with their best interests and remain feasible in practice. Full article

The results of numerous studies show that the control of power grid modes is carried out mainly using a technical criterion. The economic criterion is taken into account through the use of complex and inaccurate models that do not accurately predict the result. The emergence of market relations in the energy sector makes power systems economic entities in terms of production and satisfaction of demand for electricity by various economic entities (industry, households, businesses, etc.). Under these conditions, electricity is a commodity with a corresponding price and quality indicators. This requires the application of the risk assessment methodology as an economic category in the activities of power systems as a business entity. The methodology of risk assessment in market conditions requires business entities to search for methods to minimize risk as a possibility of adverse events. Under these conditions, it becomes possible to make the best management decisions regarding the most important criterion that reflects the interests of business entities at a given time. However, the imperfection of the relevant methodology for risk assessment in the energy sector delays their application in the industry. At the same time, when making management decisions, three possible levels can be distinguished: decision-making in conditions of certainty, when the result is presented in a deterministic form and can be determined in advance; decision-making under conditions of risk, when the outcome cannot be determined in advance, but there is information on the probability of distribution of possible consequences; decision-making in conditions where the outcome is random and there is no information about the consequences of the decision. An analysis of scientific publications shows that some authors’ works are devoted to solving the issues of applying the theory and principles of risks in the energy sector, in which the problem is solved only at the first two levels. At the same time, the operation of energy facilities is characterized by a high level of uncertainty and incomplete information about the consequences of such decisions. Therefore, the development of a methodology for making management decisions in the energy sector based on the theory and practice of risks, taking into account the high level of uncertainty and incomplete information, is an urgent scientific task. Implementation of algorithms and programs for controlling the modes of power grids based on them can meet the requirements for reliable and high-quality energy supply to the most demanding consumers and create favorable conditions for their business. This work is devoted to the development of scientific and methodological foundations for determining the voltage risk in power system networks, taking into account the uncertain nature of the loads and its impact on consumers. Based on the results of the study, a mathematical model of the risk of voltage collapses in networks, an algorithm and a methodology for its calculation were proposed. Full article

Reducing atmospheric emissions through the introduction of circular economy principles is one of the current tasks of sustainable regional development. The purpose of this research is to study the impact of the actions taken by Karachaganak Petroleum Operating B.V. (KPO) to reduce air pollution, and, based on this, to evaluate the potential of forming a circular economy in one of the biggest regions of Kazakhstan in which KPO is operating. The air pollution in the region is related to the oil and gas production activities of the company. This study was conducted using econometric modeling and statistical and comparative analyses. This study’s value lies in its interdisciplinary approach, which made it possible to combine environmental and economic criteria for sustainable regional development with the features of emissions and waste management technologies within the industry. Studying the production activities and analyzing the impact of KPO on the development of the region in the period from 2012 to 2022 made it possible to construct a matrix of the restorative potential of a circular economy in the region. A model for the formation of a circular economy was proposed, which is based on the introduction of innovations, investments in environmental protection, and the use of the best available technologies for reinjecting gas into the reservoir, increasing energy efficiency, and recycling waste, which resulted in a significant (2.2 times) reduction in the amount of air pollution in the region. According to the forecast model (2024–2028), it was determined that, in the case of maintaining certain independent indicators’ dynamics of development, the level of atmospheric emissions by KPO could be reduced by two times. The results of this work prove that further studies on the problems associated with reducing atmospheric pollution within the framework of the formation of a circular economy are quite promising. Additionally, the results of this study are interesting and may be useful for the implementation of measures to manage air quality in the region by managers, heads of organizations, state and local authorities, and researchers interested in promoting the Environmental Social Governance (ESG) concept of sustainable development. Full article

Background: We examined four potential challenges for the implementation of the European Union (EU) Regulation 2021/2282 on Health Technology Assessment (EU HTAR): interaction with the European Medicines Agency (EMA), expert input, the interface of European health technology assessment (EU HTA) joint procedures with those within Member States, and the management of conflict of interest. This research aims to explore how to address these challenges in a balanced manner and prioritise key actions for effective collaboration in the context of the EU HTA. Methods: The methodology included a pre-convention survey among relevant stakeholders as well as working groups and the plenary ranking of discussion outcomes at the European Access Academy (EAA) Spring Convention 2024. Results: In the survey, 65.5% of respondents indicated that experts are currently not sufficiently included in the upcoming joint scientific consultations and clinical assessments; only 37.9% suggested that the EU HTA joint procedures would accelerate national appraisal decision-making, and 58.6% believed that the principles of ‘transparency’ and ‘competency’ are balanced in the EU HTA position on conflict of interest. The top priority action points identified in the working groups were the involvement of the best available expertise, the early and inclusive involvement of experts, strengthened early scientific dialogue, and the fostering of the political willingness/financial support of EU Member States to increase capacities. Conclusions: The key topics identified were an approach to conflict of interest that balances transparency obligations and the need for expertise, strengthens the involvement of clinical and patient experts, intensifies early interaction between the EMA and EU HTA, and increases the involvement of the EU Member States. Full article

As a graphene-like material, h-BN has stimulated great research interest recently due to its potential application for next-generation electronic devices. Herein, a systematic theoretical investigation of electronic structures and optical properties of C-doped and Cu-Al co-doped h-BN is carried out by the first-principles calculations. Firstly, two different C-doped h-BN structures for the para-position and ortho-position are constructed. The results show that the C ortho-doped h-BN (BCN) structure with a band gap of 3.05 eV is relatively stable, which is selected as a substate to achieve the Cu-Al co-doped h-BN. Based on this, the effect of the concentration of C atom doping on the electronic and optical properties of Cu-Al co-doped BC_xN (x = 0, 11.1% and 22.2%) is investigated. The results demonstrate that the band gap of Cu-Al co-doped BC_xN decreases and the optical properties improve with the increase in C atom concentration. The band gap and static dielectric constant of Cu-Al co-doped BC₀N, BC₁N and BC₂N are 0.98 eV, 0.87 eV and 0.23 eV and 2.34, 3.03 and 3.77, respectively. As for all Cu-Al co-doped BC_xN systems, the adsorption peak is red-shifted, and the peak intensity obviously decreases compared to the undoped h-BN. Additionally, the Cu-Al co-doped BC₂N exhibits the best response to visible light. This work will provide valuable guidance for designing and developing h-BN-based doping systems with good performance in the field of optical and photocatalysis. Full article

This paper explores contemporary approaches to preserving and promoting cultural heritage by integrating game elements and advanced technologies, such as Virtual Reality (VR) and Augmented Reality (AR). In an era increasingly shaped by digital innovation, preserving cultural heritage demands new strategies to sustain engagement with historical narratives and artifacts. Emerging technologies like VR and AR offer immersive, interactive experiences that appeal to modern audiences, especially younger generations accustomed to digital environments (Bekele and Champion). Gamification—the use of game design principles in non-game contexts—has gained significant traction in education and cultural heritage, providing new methods for increasing user engagement and retention (Werbach and Hunter). By incorporating gamified features, heritage can be made more accessible, fostering emotional connections and deeper understanding (Huotari and Hamari; Zichermann and Cunningham). This aligns with the shift toward interactive digital storytelling as a tool to transform static heritage presentations into dynamic, participatory experiences (Champion and Rahaman). Central to this research is the conceptualization and development of a mobile application leveraging VR and AR to enhance user engagement and education around cultural heritage. Drawing on the principles of self-determination theory (Deci and Ryan) and empirical findings on gamified learning (Landers and Landers), the application combines educational content with interactive elements, creating an immersive learning environment. By addressing both content accessibility and interactive immersion, this application bridges the gap between traditional heritage preservation and the expectations of a digitally native audience. The recent literature underscores the potential of VR and AR in cultural preservation, emphasizing their ability to transcend physical boundaries, simulate historical environments, and promote active participation (Milgram and Kishino, Addison; Azuma). As virtual environments evolve, platforms like the metaverse expand possibilities for experiencing cultural heritage in spaces free of geographical limitations (Cipresso et al.; Radianti et al.). Such advancements have already demonstrated significant educational and experiential benefits (Wu et al.; Akçayır and Akçayır). This study employs both quantitative and qualitative methods to examine the target group’s attitudes toward gamified technologies for cultural heritage preservation. The initial results indicate substantial interest and willingness among users to engage with applications employing VR and AR. This aligns with findings in the literature that suggest immersive experiences can enhance learning outcomes and foster long-term engagement (Merchant et al.; Speicher et al.). The project has garnered significant recognition, receiving the Rector’s Award for the best scientific paper in the technical field at the University of Zagreb and earning bronze medals at the ARCA Innovation Fair and the INOVA Fair. These accolades underscore the project’s innovative approach and its potential for real-world application. By presenting a robust framework for integrating gamification and immersive technologies into cultural heritage preservation, this paper contributes to the growing discourse on utilizing advanced digital tools to ensure the sustainability and relevance of cultural heritage for future generations. Full article

Molecularly imprinted polymers (MIPs) are defined as artificial receptors due to their selectivity and specificity. Their advantageous properties compared to biological alternatives have sparked interest among scientists, as detailed in numerous review papers. Currently, there is significant attention on adhering to the principles of green chemistry and environmental protection. In this context, MIP research groups have focused on developing eco-friendly procedures. The application of “greener” monomers and reagents, along with the utilization of computational methodologies for design and property analysis, are two activities that align with the green chemistry principles for molecularly imprinted technology. This review discusses the application of computational methodologies in the preparation of MIPs based on eco-friendly non-acrylic/vinylic monomers and precursors, such as alkoxysilanes, ionic liquids, deep eutectic solvents, bio-based molecules—specifically saccharides, and biomolecules like proteins. It provides a brief introduction to MIP materials, the green aspects of MIP production, and the application of computational simulations. Following this, brief descriptions of the studied monomers, molecular simulation studies of green monomer-based MIPs, and computational strategies are presented. Finally, conclusions and an outlook on the future directions of computational analysis in the production of green imprinted materials are pointed out. To the best of my knowledge, this work is the first to combine these two aspects of MIP green chemistry principles. Full article

On-chip spectrometers are increasingly becoming tools that might help in everyday life needs. The possibility offered by several available integration technologies and materials to be used to miniaturize spectrometers has led to a plethora of very different devices, that in principle can be compared according to their metrics. Having access to a reference database can help in selecting the best-performing on-chip spectrometers and being up to date in terms of standards and developments. In this paper, an overview of the most relevant publications available in the literature on miniaturized spectrometers is reported and a database is provided as an open-source project to which researchers can have access and participate in order to improve the share of knowledge in the interested scientific community. Full article

This work continues the review and illustrative application to energy systems of the “Fourth-Order Best-Estimate Results with Reduced Uncertainties Predictive Modeling” (4th-BERRU-PM) methodology. The 4th-BERRU-PM methodology uses the Maximum Entropy (MaxEnt) principle to incorporate fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses with respect to model parameters. The 4th-BERRU-PM methodology yields the fourth-order MaxEnt posterior distribution of experimentally measured and computed model responses and parameters in the combined phase space of model responses and parameters. The 4th-BERRU-PM methodology encompasses fourth-order sensitivity analysis (SA) and uncertainty quantification (UQ), which were reviewed in the accompanying work (Part 1), as well as fourth-order data assimilation (DA) and model calibration (MC) capabilities, which will be reviewed and illustrated in this work (Part 2). The applicability of the 4th-BERRU-PM methodology to energy systems is illustrated by using the Polyethylene-Reflected Plutonium (acronym: PERP) OECD/NEA reactor physics benchmark, which is modeled using the linear neutron transport Boltzmann equation, involving 21,976 imprecisely known parameters. This benchmark is representative of “large-scale computations” such as those involved in the modeling of energy systems. The result (“response”) of interest for the PERP benchmark is the leakage of neutrons through the outer surface of this spherical benchmark, which can be computed numerically and measured experimentally. The impact of the high-order sensitivities of the response with respect to the PERP model parameters is quantified for “high-precision” parameters (2% standard deviations) and “typical-precision” parameters (5% standard deviations). Analyzing the best-estimate results with reduced uncertainties for the 1st—through 4th-order moments (mean values, covariance, skewness, and kurtosis) produced by the 4th-BERRU-PM methodology for the PERP benchmark indicates that, even for systems modeled by linear equations (e.g., the PERP benchmark), retaining only first-order sensitivities is insufficient for reliable predictive modeling (including SA, UQ, DA, and MC). At least second-order sensitivities should be retained in order to obtain reliable predictions. Full article

This work (in two parts) will review the recently developed predictive modeling methodology called “4th-BERRU-PM” and its applicability to nuclear energy systems as exemplified by an illustrative application to the Polyethylene-Reflected Plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. The acronym 4th-BERRU-PM designates the “Fourth-Order Best-Estimate Results with Reduced Uncertainties Predictive Modeling” methodology, which uses the Maximum Entropy (MaxEnt) principle to incorporate fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters, while yielding best-estimate results with reduced uncertainties for the first fourth-order moments (mean values, covariance, skewness, and kurtosis) of the optimally predicted posterior distribution of model results and calibrated model parameters. The 4th-BERRU-PM methodology encompasses the scopes of high-order sensitivity analysis (SA), uncertainty quantification (UQ), data assimilation (DA) and model calibration (MC), as will be illustrated in this work by means of the above-mentioned OECD/NEA reactor physics benchmark. This benchmark is modeled using the neutron transport Boltzmann equation involving 21,976 imprecisely known parameters, the solution of which is representative of “large-scale computations”. The model result (“response”) of interest is the leakage of neutrons through the outer surface of this spherical benchmark, which can be computed numerically and measured experimentally. Part 1 of this work illustrates the impact of high-order sensitivities, in conjunction with parameter standard deviations of various magnitudes, on the determination of the expected value and variance of the computed response in terms of the first four moments of the distribution of the uncertain model parameters. Part 2 of this work will illustrate the capabilities of the 4th-BERRU-PM methodology for combining computational and experimental information, up to and including forth-order sensitivities and distributional moments, for producing best-estimate values for the predicted responses and model parameters while reducing their accompanying uncertainties. Full article

In the area of optimization, metaheuristic algorithms have attracted a lot of interest. For many centuries, human beings have utilized metaheuristic algorithms as a problem-solving approach. The application of these methods to combinatorial optimization problems has rapidly become a growing area of research, incorporating principles of natural selection, evolution, and problem-solving strategies. While conventional software engineering methods may not always be effective in resolving software issues, mathematical optimization using metaheuristics can offer a solution. As a result, metaheuristics have become an increasingly important part of modern optimization, with a large number of algorithms emerging over the last two decades. The purpose of this study is to present a quick overview of these algorithms so that researchers may choose and use the best metaheuristic method for their optimization issues. The key components and concepts of each type of algorithm have been discussed, highlighting their benefits and limitations. This paper aims to provide a comprehensive review of these algorithms, including evolution-based methods, swarm intelligence-based, physics-based, human-related, and hybrid metaheuristics by highlighting their key components and concepts and comparing and contrasting their similarities and differences. This work also addressed some of the difficulties associated with metaheuristic algorithms. Some practical uses of these metaheuristic algorithms were addressed. Full article

A circular economy (CE) is an economic model that involves more sustainable management of raw materials and waste. Implementation of CE assumptions is highly recommended in the form of dedicated CE technologies as well as CE business models, so-called circular business models (CBMs), which are an integral part of environmental management in organizations. Depending on the application and the type of sector or enterprise, CBMs are defined differently, focusing on various areas of raw materials and waste management. In general, they should create added value for the given enterprise that meets the CE assumptions or integrate CE principles with the organization’s business practices. This paper aims to analyze different approaches to CBMs with the use of comparative analysis and desk research methods. The scope of this paper includes a comparative analysis of CBM definitions and their typologies, as well as the basics for creating CBMs in enterprises. Moreover, good practices of implemented CMBs in various enterprises are presented. The general definition of CBM is developed as “a business model that assumes creating, delivering and capturing added value for the consumer while considering the CE principles”. Furthermore, the basics of building CBM using a modified Business Model Canvas are proposed. In general, CBM should consider the key CE assumption, i.e., increased raw material efficiency. In the coming years, a further increase in interest in CBMs dedicated to specific sectors and their areas of activity is expected. Various stakeholders could use them as a benchmark to compare and define the best practices for the successful adoption of CBMs in the future. Full article

Yttrium nitride (YN) is a hard and refractory material with a high melting point. It is a semiconductor that has been investigated for its potential applications in the field of semiconductor technology, including as a material for electronic devices. It is also of interest for its optical properties and its potential for use in optoelectronics. However, investigating its mechanical properties for a possible application in optical coatings has not been completed. This study involved the exploration of the mechanical properties of YN alloyed with niobium (Nb) and zirconium (Zr) for possible application in optical coatings using a first-principles approach. The result showed that the addition of Nb and Zr into the YN matrix had a profound effect on the mechanical properties of the modeled structures, with the Y-N-Nb (CYN_5) sample having the best mechanical properties. The bulk modulus was the most affected, with an increase of 26.48%, while the Vickers hardness had the smallest increase of 6.128% compared with those of pure YN. The modeled structures were thus found to be ideal alternative materials for optical coatings due to their improved mechanical properties. Full article

Molecular switches based on functionalized graphene nanoribbons (GNRs) are of great interest in the development of nanoelectronics. In experiment, it was found that a significant difference in the conductance of an anthraquinone derivative can be achieved by altering the pH value of the environment. Building on this, in this work we investigate the underlying mechanism behind this effect and propose a general design principle for a pH based GNR-based switch. The electronic structure of the investigated systems is calculated using density functional theory and the transport properties at the quasi-stationary limit are described using nonequilibrium Green’s function and the Landauer formalism. This approach enables the examination of the local and the global transport through the system. The electrons are shown to flow along the edges of the GNRs. The central carbonyl groups allow for tunable transport through control of the oxidation state via the pH environment. Finally, we also test different types of GNRs (zigzag vs. armchair) to determine which platform provides the best transport switchability. Full article