Search in Publications
Found 6525 publications
Servitization of public service processes with a simulation modelling approach
Publication Name: Engineering Management in Production and Services
Publication Date: 2020-09-01
Volume: 12
Issue: 3
Page Range: 116-131
Description:
This article aims to examine how the theory of co-production can be connected with servitization and digitalisation and used together for the public service development with the help of discrete-event simulation modelling to highlight time-related deficiencies of a complex public service process, which is most commonly used by patchwork families. Data was taken from the Guardianship Office in Gyor (Hungary), based on which in-depth interviews were conducted. Based on the legal background and the interviews, the authors of the article created the process model of the contacting procedure. Based on the model, discrete-event simulation was used to identify the process elements for potential improvement through servitization. Discrete-event simulation showed the insufficiency of national regulation regarding the whole process and weaknesses of the contacting procedures in terms of quality and success. Basic reasons were found for the dissatisfaction expressed by participants of the procedures (administrators and customers). The increasing customer demand for high quality and efficient public services and failures in the New Public Management (NPM) in Eastern European countries require other approaches to advance. The paper connects the theory of co-production and servitization in a public service context and demonstrates how a complex public service can be examined with this approach to find possible improvements. The government must change the process regulation considering the number of the cases, the workload of administrators and family types (divorced or patchwork). The emphasis should be placed on the training and experience of administrators.
Open Access: Yes
Estimating high mobility group box protein 1 (HMGB1) single nucleotide polymorphisms among hepatitis B virus infected patients of Pakistan origin
Publication Name: Brazilian Journal of Biology
Publication Date: 2025-01-01
Volume: 85
Issue: Unknown
Page Range: Unknown
Description:
HMGB1 is nuclear non-histone protein and unique member of cytokines. In viral hepatitis infection HMGB1 serum level increases and translocates towards cytoplasm and extracellular spaces where it activates single stimulating hepatic stellate cell proliferation which induces fibrogenic protein expression and causes hepatocellular carcinoma. In this study, total 150 subjects were recruited to assess the association between HMGB1 SNPs and HBV. Three types of genotypes were found visible in rs3742305 of HMGB1; wild type homozygous GG with 65%, homozygous minor type CC with 6% and heterozygous minor type GC with 26% frequency distribution. High prevalence of GG genotype in the selected population presenting that GG genotype may have higher risk for susceptibility to HBV infection. Our results showed significant correlation of HMGB1 polymorphism with HBV infection in the selected Pakistani population.
Open Access: Yes
Numerical Investigation of Glue Laminated Timber Beams considering Reliability-based Design
Publication Name: Acta Polytechnica Hungarica
Publication Date: 2023-01-01
Volume: 20
Issue: 1
Page Range: 109-122
Description:
Structural models and their related parameters, are most often considered as deterministic, in numerical analysis. However, according to test results, one can see the existence of uncertainties, in most cases, due to various reasons, such as, natural variabilities and ignorance. Thus, dealing with uncertainty has gained massive attention, due to its importance in structural analysis and anticipating the performance of models. In fact, in some cases of special structure components, like glue laminated timber beams, it appears to be, that there is an absence of information concerning uncertainties. Therefore, the main objective of this study is to inspect uncertainties that facing designers and their role in glue laminated timber beams behavior, by considering different material parameters as random variables. In addition, four-point bending tests are conducted and finite element analysis is conducted, using ABAQUS software, to model the nonlinear behavior of GLT beams. For purposes of numerical model calibration, Hill yield criterion constitutive model is considered based on the obtained data from the experimental test. The results of this study provide a better outline for understanding the effect of uncertainties on glue laminated timber beams.
Open Access: Yes
Greenhouse Gas Emissions in Agricultural Crops and Management Practices: The Impact of the Integrated Crop Emission Mitigation Framework on Greenhouse Gas Reduction
Publication Name: Agronomy
Publication Date: 2026-01-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
Greenhouse gas emissions from agricultural crops remain a critical challenge for climate change mitigation. This review synthesizes evidence on cropland management interventions and global N2 O mitigation potential. Agricultural practices such as cover cropping, agroforestry, reduced tillage, and diversification show promise in reducing CO2 , CH4 , and N2 O emissions, yet uncertainties in measurement, verification, and socio-economic adoption persist. This review highlights that biochar application reduces N2 O emissions by 16.2% (95% CI: 9.8–22.6%) in temperate systems, demonstrating greater consistency compared to no-till agriculture, which shows higher variability (11% reduction, 95% CI: −19% to +1%). Legume-based crop rotations reduce N2 O emissions by up to 39% through improved nitrogen efficiency and increase soil organic carbon by up to 18%. However, reductions in synthetic fertilizer use (65% lower in legume vs. cereal systems) can be offset by the effects of biological nitrogen fixation. Optimized nitrogen fertilization, when combined with enhanced-efficiency fertilizers, can reduce N2 O emissions by 55–64%. Complementing this, global-scale analysis underscores the dominant role of optimized nitrogen fertilization in curbing N2 O emissions while sustaining yields. To bridge gaps between practice-level interventions and global emission dynamics, this paper introduces the ICEMF, a novel approach combining field-based management strategies with spatially explicit emission modeling. Realistic implementation currently achieves 25–35% of technical potential, but bundled interventions combining financial incentives, training, and institutional support can increase adoption to 40–60%, demonstrating ICEMF’s value through integrated, context-adapted approaches. Only peer-reviewed articles published in English between 1997 and 2025 were selected to ensure recent and reliable findings. This review highlights knowledge gaps, evaluates policy and technical trade-offs, and proposes ICEMF as a pathway toward scalable and adaptive mitigation strategies in agriculture.
Open Access: Yes
Intelligent decision support technologies in public and individual transport
Publication Name: Intelligent Decision Technologies
Publication Date: 2017-01-01
Volume: 11
Issue: 4
Page Range: 441-449
Description:
Intelligent decision technologies can support travelling as well as planning transport systems. Trip makers have to choose between transport modes and then plan the optimal route which depends on many factors e.g. journey time, walking distances, transfers, waiting times, price of the journey as well as the individual preferences of the trip maker. This paper gives an overview of decisions in both individual and public transport. Then it shows some examples how intelligent cognitive info-communications can support these decisions and how they can be built into passenger information services.
Open Access: Yes
DOI: 10.3233/IDT-170307
Taxonomic analysis of the diversity in the level of wind energy development in european union countries
Publication Name: Energies
Publication Date: 2020-09-01
Volume: 13
Issue: 17
Page Range: Unknown
Description:
In this paper, the development of the wind energy sector in 28 European Union countries in 2017 is described. By means of taxonomic methods-i.e., Ward's method and the Wroclaw taxonomic methods-clusters of countries similar in terms of their potential and level of development of the wind energy sector in the EU are distinguished. The main purpose of the paper is to separate and cluster EU countries due to the current development potential of the wind energy sector and determinants stimulating the development of this sector. By means of the ranking methods of linear ordering (Technique for Order of Preference by Similarity to Ideal Solution-TOPSIS method), a ranking of EU countries that defines their position in the development of this very important wind energy sector was determined. The results show that the research hypothesis of a great diversity of EU countries considering the development potential of the wind energy sector is justified. The countries of the former European Union, which have focused for a long time on the development of wind energy in their energy policy and have had favorable climate and natural conditions, as well as a large social acceptance of programs supporting the acquisition of energy from renewable sources, have primacy in the development ranking of the energy sector. Additionally, new members of the union, in spite of some delays associated with the development of "green"energy, are trying to increase their energy potential in this area. The research may be extended to include further analyses regarding other renewable energy sources and take into account other European and world countries.
Open Access: Yes
DOI: 10.3390/en13174371
Direct sampling of food in atomic spectroscopy for trace element analysis
Publication Name: Trac Trends in Analytical Chemistry
Publication Date: 2026-09-01
Volume: 202
Issue: Unknown
Page Range: Unknown
Description:
Direct analysis in atomic spectroscopy offers an efficient and environmentally friendly alternative to conventional digestion-based methods for trace element detection and quantification in food matrices. This review explores applications of direct sample analysis across liquid, semi-liquid and solid food types, including fruit juice, milk and dairy products, alcoholic beverages, honey, fats and oils, seeds and nuts, milk powders, seafood, vegetables, powdered plant-based beverages, and cereals. Elements such as Al, As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, and Pb have been successfully quantified using direct sampling approaches. Analytical techniques such as AAS, ICP-MS, ICP-OES, GD-OES, XRF are critically evaluated, besides hydride generation, MIP-OES, HPLC coupling, laser ionization, and thermospray-assisted approaches. The review emphasizes key aspects influencing analytical performance parameters, matrix effects, reagent usage and measurement conditions. It identifies methodological gaps and suggests future directions to enhance applicability and reliability of direct food analysis using diverse atomic spectrometry techniques.
Open Access: Yes
INVESTIGATING THE ROLE OF ACTIVATION FUNCTIONS IN PREDICTING THE PRICE OF CRYPTOCURRENCIES DURING CRITICAL ECONOMIC PERIODS
Publication Name: Virtual Economics
Publication Date: 2024-12-31
Volume: 7
Issue: 4
Page Range: 64-91
Description:
Accurate cryptocurrency price forecasting is crucial due to the significant financial implications of prediction errors. The volatile and non-linear nature of cryptocurrencies challenges traditional statistical methods, revealing a gap in effective predictive modelling. This study addresses this gap by examining the impact of activation functions on neural network models during critical economic periods, specifically aiming to determine how optimising activation functions enhances accuracy in neural network models, including RNN, GRU, LSTM, and hybrid architectures. Using data from January 2016 to June 2022—encompassing stable periods, the COVID-19 pandemic, and the onset of the 2022 Ukraine conflict—we analysed price trends under various market conditions. Our methodology involved testing three activation functions (ReLU, sigmoid, and Tanh) across these models. Both univariate and multivariate analyses were conducted, with the latter incorporating additional metrics such as opening, highest, and lowest prices. The results indicate that optimising activation functions enhances prediction accuracy. Among the models, GRU demonstrated the highest accuracy, whereas RNN was the least efficient. Multivariate models outperformed univariate ones, highlighting the benefits of incorporating comprehensive data. Notably, the Tanh activation function led to the greatest improvements, particularly in underperforming models such as RNN. These findings underscore the critical role of activation function selection in enhancing the predictive power of neural networks for cryptocurrency markets. Optimising activation functions can lead to more reliable forecasts, facilitating better trading decisions and risk management. This study highlights activation functions as key parameters in neural network modelling, encouraging further exploration. Future research could investigate different economic periods and cryptocurrency behaviours to assess model robustness. Additionally, examining a broader range of cryptocurrencies may reveal whether the benefits of activation function optimisation are consistent across various assets. Incorporating external factors such as macroeconomic indicators or social media sentiment could further enhance models and improve forecasting accuracy.
Open Access: Yes
Concepts and Examples of Carbon-Free, Self-Sufficient Local Energy Systems
Publication Name: Chemical Engineering Transactions
Publication Date: 2024-01-01
Volume: 114
Issue: Unknown
Page Range: 931-936
Description:
The necessity of the “green revolution” in the field of energetics is not a question anymore; however, switching the current fossil fuel-based energy ecosystem to a fully renewable-based one poses enormous challenges. The historical structure of the present, centralised energy production infrastructure, as well as the fundamentally different characteristics of the three main fields of usage (electricity generation, heating and transportation), are among the most substantial hindering factors. The future energy system has to be much more flexible in several respects, with a fundamental contribution of smaller, independent energy communities. The current study focuses on the realisation aspects of such a small-scale energy community (or micro/nano-grid), considering the suitable technological solutions as well as the cost concerns. A high number of pilot projects and case studies around the world prove that the technical feasibility of a local grid/energy community is no longer a question. The real challenge is to find the appropriate incentives and strategy to catalyse the required transition at the legislation, system operator and end-user level as well. The outcomes of the present work contribute to this goal by pointing out the application potentials of a modular, scalable microgrid system based on a currently running microgrid-realization project at the ZalaZONE proving ground.
Open Access: Yes
DOI: 10.3303/CET24114156
