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Publications - 6374

Rapid, Matrix-Dependent Changes in Polyphenols and Antioxidant Capacity of Methanol Plant Extracts During Short-Term Storage: Implications for Analytical Timing

Tarek Alshaal Attila Kiss

Publication Name: International Journal of Molecular Sciences

Publication Date: 2026-05-01

Volume: 27

Issue: 9

Page Range: Unknown

Description:

Throughout this study, the short-term stability of methanol extracts was evaluated in cases of 15 distinctive, antioxidant-rich plant materials over 3, 7, and 14 days under refrigeration (4 °C), dark room-temperature, and light-exposed room-temperature conditions. A great variability in the matrix-dependent stability of the antioxidants, as well as the pronounced impact of the implied storage conditions on their plausible degradation, was revealed and featured. Initial total polyphenol content (TPC) ranged from 50.50 ± 0.44 mg gallic acid (GAE)/g DW (rosemary) to only 0.02 ± 0.006 mg GAE/g DW (amaranth). After 14 days, pigment-rich vegetable extracts (basil, beetroot powder, spinach powder, dried onion, tomato powder, and yarrow tail) lost 86.2–89.2% of TPC and 80–99% of DPPH (2,2-diphenyl-1-picrylhydrazyl) activity across all conditions, even under refrigeration. In contrast, for Lamiaceae species, markedly higher levels of the referred parameters were to be observed after 14-day-long storage. Decrease in TPC values was found to be 43.7% (rosemary), 50.6% (thyme), and 42.9% (oregano), respectively, while DPPH values were reduced by only 17–29%. Turmeric and walnut flour showed intermediate stability. Refrigeration consistently minimized the degradation of antioxidants (e.g., rosemary’s decrease in DPPH was only 20.3% at 4 °C vs. >70% under ambient conditions), while light exposure significantly accelerated losses of antioxidants in nearly all samples. Methanol extracts of many dietary plants, particularly pigment-rich ones, exhibit rapid and pronounced changes during short-term storage. Comparison with values obtained immediately after extraction shows that even brief storage can lead to substantial deviations. Although the current sampling intervals do not capture changes within the first hours, the results clearly indicate the need to minimize delays and standardize analytical timing to avoid underestimating phenolic content and antioxidant capacity. Moreover, these findings demonstrate that measured antioxidant properties are not solely inherent to the plant material but are strongly influenced by the extract matrix and methodological conditions. Consequently, antioxidant data should be regarded as matrix- and protocol-dependent, with important implications for their interpretation, comparability, and reproducibility across studies.

Open Access: Yes

DOI: 10.3390/ijms27093723

Disease-Group-Specific Antimicrobial Use Patterns and Farm-Level Stewardship Features in Large-Scale Hungarian Swine Herds: A Multi-Farm Survey

László Ózsvári Ádám Kerek Marietta Máté László Gombos

Publication Name: Animals

Publication Date: 2026-05-01

Volume: 16

Issue: 10

Page Range: Unknown

Description:

Background: Farm-level antimicrobial stewardship in swine production requires indication-specific knowledge of treatment patterns and the herd-level features associated with them. Methods: We analyzed questionnaire-based data collected in 2015 from 13 Hungarian swine farms covering 15,725 sows and their progeny. The survey captured production indicators, pathogen occurrence, vaccination, resistance-testing practices, drug costs, and disease-group-specific antimicrobial use. As a separate, non-mergeable descriptive temporal comparator, we also considered independent digital farm-monitoring data from three large-scale swine herds from 2022 to 2024. Results: The most frequently reported pathogens were Mycoplasma hyopneumoniae (13/13 farms), Lawsonia intracellularis (12/13), Escherichia coli (12/13), swine influenza virus (11/13), and Streptococcus suis (10/13). S. suis ranked as the leading damaging pathogen on 69% of farms. Among farms with antibiotic cost data (9/13), antibiotics accounted for a mean of 31.8% of veterinary drug expenditures. Among farms with treatment-by-indication data (8/13), the highest relative frequency of reported treatment events was linked to porcine respiratory disease complex, where doxycycline represented 38% of reported PRDC treatment events. Colistin dominated E. coli-associated diarrhea control, whereas beta-lactams were central for S. suis-related disease. In the 2022–2024 comparator dataset, enteric and respiratory disorders and arthritis remained the main recorded health problems, but corrected antimicrobial use was markedly lower in the later dataset. Conclusions: Antimicrobial use showed clear disease-group-specific patterns, supporting syndrome-focused stewardship rather than generic reduction targets.

Open Access: Yes

DOI: 10.3390/ani16101570

Ant Colony Optimization-Driven Ensemble Learning for Carbon Emission Modelling in Fly Ash–Slag Geopolymer Concrete

Brajkishor Prasad Mizan Ahmed Sanjay Kumar Ardalan B. Hussein Pramod Kumar Indra Kumar Pandey

Publication Name: Materials

Publication Date: 2026-05-01

Volume: 19

Issue: 10

Page Range: Unknown

Description:

This study investigates the prediction of carbon emissions from fly ash and ground granulated blast furnace slag-based geopolymer concrete (GPC) using advanced ensemble machine learning (ML) techniques. Although ML has been extensively utilized to model GPC’s mechanical performance, its application in estimating environmental impacts, specifically carbon emissions, is limited. The research employs six ensemble ML models, such as random forest, gradient boosting, extreme gradient boosting (XGB), CatBoost, and light gradient boosting machine (LGBM), including versions optimized using ant colony optimization (ACO). Among them, the ACO-enhanced XGB model demonstrated the highest predictive accuracy with a coefficient of determination (R2) of 0.97, with low prediction errors (MAE = 3.92, RMSE = 6.17). However, cross-validation and uncertainty analyses indicate that the performance differences among top models are relatively small. Conversely, LGBM exhibited the least predictive reliability. Feature importance analysis revealed that curing parameters, specifically initial curing time, curing temperature, and the dosage of dry sodium hydroxide, had the most influence on carbon emissions. To evaluate model robustness and interpretability, Monte Carlo simulation and Gaussian white noise analyses were conducted. Results confirmed that CatBoost and ACO–gradient boosting (ACO-GB) demonstrated greater stability under varying and noisy conditions, whereas XGB-based models, although highly accurate, were comparatively more sensitive to input variability. Overall, the research establishes a data-driven, efficient framework for quantifying carbon emissions in GPC, highlighting the importance of evaluating both predictive accuracy and model robustness, advancing sustainable material design through intelligent modelling.

Open Access: Yes

DOI: 10.3390/ma19102168

Self-Diagnostic Opportunities for Battery Systems in Electric and Hybrid Vehicles

I. Lakatos Szabolcs Kocsis Szurke Péter Ori Gergő Sütheö

Publication Name: Machines

Publication Date: 2024-05-01

Volume: 12

Issue: 5

Page Range: Unknown

Description:

The number of battery systems is also growing significantly along with the rise in electric and hybrid car sales. Different vehicles use different types and numbers of batteries. Furthermore, the layout and operation of the control and protection electronics units may also differ. The research aims to develop an approach that can autonomously detect and localize the weakest cells. The method was validated by testing the battery systems of three different VW e-Golf electric vehicles. A wide-range discharge test was performed to examine the condition assessment and select the appropriate state of charge (SoC) for all three vehicles. On the one hand, the analysis investigated the cell voltage deviations from the average; the tests cover deviations of 0 mV, 12 mV, 60 mV, 120 mV, and 240 mV. On the other hand, the mean value calculation was used to filter out possible erroneous values. Another important aspect was examining the relationship between the state of charges (SoC) and the deviations. Therefore, the 10% step changes were tested to see which SoC level exhibited more significant voltage deviations. Based on the results, it was observed that there are differences between the cases, and the critical range is not necessarily at the lowest SoC level. Furthermore, the load rate (current) and time of its occurrence play an important role in the search for a faulty cell. An additional advantage of this approach is that the process currently being tested on the VW e-Golf can be relatively simply transferred to other types of vehicles. It can also be a very useful addition for autonomous vehicles, as it can self-test the cells in the system at low power consumption.

Open Access: Yes

DOI: 10.3390/machines12050324

Varying Levels of Trust across Multi-Level Governance: a Sustainability Perspective

Lívia Ablonczy-Mihályka Zsuzsanna Pálffy

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 1045-1050

Description:

Social sustainability, the third pillar of sustainability alongside ecological and economic dimensions, focuses on maintaining the well-being and viability of communities, as a healthy functioning society is a prerequisite for sustainable operation. Trust, a common measure of social sustainability, is a fundamental pillar of a sustainable, resilient, inclusive, transparent and accountable society. This research aims to analyse how trust as a measure of social sustainability interacts with different levels of governance and institutional performance in the Visegrád Four countries. The study found that although there is a significant correlation between various factors of institutional trust at the national level, there is no meaningful relationship between general and institutional trust across the examined countries (Czech Republic, Hungary, Slovakia, and Poland). The analysis found that institutional trust is influenced more by endogenous factors, such as perceived governance effectiveness and citizen satisfaction, than by general trust. However, no strong correlation could be shown between Word Governance Indicator and institutional trust. The findings show that trust does not progressively decline towards higher levels of institutions; instead, proximity and citizen engagement boost trust at the local level, while different mechanisms likely drive trust at higher government levels. Additionally, the research highlights that in post-communist societies, strong traditions of particular trust limit general trust in institutions, emphasizing the complexity of trust dynamics within different governance levels.

Open Access: Yes

DOI: 10.3303/CET24114175

RFId application in production process of an automotive industry supplier

No authors available

Publication Name: INES 2006: 10th International Conference on Intelligent Engineering Systems 2006

Publication Date: 2006-12-01

Volume:

Issue:

Page Range: 45-48

Description:

The Department of Logistics and Forwarding at Széchenyi István University in Györ, Hungary started a project in an automotive industry supplier company. The purpose of the project is to grow the efficiency of the production process. In order to achieve the target we should reorganized the IT system. During the research we had to take the special production circumstances and the already exist ad hock information system into consideration. The article adumbrates the course of the project shortly, the faults of the system, the own-developed new information system and represents how the human failures could be eliminated though RFId application. © 2006 IEEE.

Open Access: No

DOI: DOI not available

Effects of foreign direct investment on the labour market in the Komárom-Komárno area

Ingrid Szabó András Kovács

Publication Name: Foldrajzi Ertesito

Publication Date: 2008-01-01

Volume: 57

Issue: 1-2

Page Range: 229-241

Description:

The industrial park located in the town of Komárom (Hungary) belongs to the most successful examples of the Hungarian economic transition process and structural change. Nowadays the Nokia cell phone factory and its suppliers secure workplace for about 15,000 workers (half of them commuting from the neighbouring Slovakia) laying down the long-term, stable prosperity of the region. This paper analyses the situation and changes in labour market of Komárom-Komárno borderland region, and introduces the micro- and macroeconomic factors, which are influencing its further development. The draining of reserves in free labour force of the region, and the diminishing number of Slovakian workers will fundamentally influence the structure of employment of the border region and will ultimately result in a steady over-demand in labour force. In the analysis it is argued that only a proactive, regional, integrated labour force development strategy and a conscious plan for attraction of new workers into the town(s) can result a sustainable economic development for Komárom and its region.

Open Access: Yes

DOI: DOI not available

On measures of dependence between possibility distributions

Istvan A. Harmati Peter Varlaki Robert Fuller

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2018-01-01

Volume: 15

Issue: 1

Page Range: 231-246

Description:

A measure of possibilistic correlation between marginal possibility distributions of a joint possibility distribution can be defined as (see Fullér, Mezei and Várlaki, An improved index of interactivity for fuzzy numbers, Fuzzy Sets and Systems, 165(2011), pp. 56-66) the weighted average of probabilistic correlations between marginal probability distributions whose joint probability distribution is defined to be uniform on the level sets of their joint possibility distribution. Using the averaging technique we shall discuss three quantities (correlation coefficient, correlation ratio and informational coefficient of correlation) which are used to measure the strength of dependence between two possibility distributions. We discuss the inverse problem, as we introduce a method to construct a joint possibility distribution for a given value of possibilistic correlation coefficient. We also discuss a special case when the joint possibility distribution is defined by the so-called weak t-norm and based on these results, we make a conjecture as an open problem for the range of the possibilistic correlation coefficient of any t-norm based joint distribution.

Open Access: Yes

DOI: 10.12700/APH.15.1.2018.1.14

The spatial structure of flows, Reynolds stress and turbulence in the CASTOR tokamak

No authors available

Publication Name: 33rd EPS Conference on Plasma Physics 2006, EPS 2006

Publication Date: 2006-12-01

Volume: 2

Issue:

Page Range: 1452-1455

Description:

Open Access: No

DOI: DOI not available