Search in Publications

Found 6342 publications

Assessing the texture profile and optimizing the temperature and soaking time for the rehydration of hot air-dried Auricularia auricula-judae mushrooms

Balázs Ásványi E. Lakatos Székelyhidi Rita Beatrix Sik Zsolt Schott

Publication Name: Discover Food

Publication Date: 2025-12-01

Volume: 5

Issue: 1

Page Range: Unknown

Description:

Rehydrating dried jelly ear mushrooms allows them to take on the original shape, and texture, but no thorough study has been done to date to determine the ideal rehydration parameters. The study aimed to optimize the rehydration conditions of the hot-air-dried jelly ear mushroom, to achieve the most similar stock to the fresh mushroom. To achieve this, the mushrooms dried to a constant weight at 40 °C were soaked in water that had been heated to 20–100 °C for 10–70 min. The mushrooms were weighed and examined the texture profile to determine the rehydration %, hardness, gumminess, chewiness, springiness, and cohesiveness at each tested temperature and soaking time. The fresh mushroom used as a control had a moisture content of 95.39 m/m%, hardness of 847.40, springiness of 0.70, gumminess of 562.04, chewiness of 423.98 N/m2, and cohesiveness of 0.66 J/m3. These results were compared to the rehydrated mushroom samples texture profile test results, and it was found that the dried mushrooms recovered nearly the same texture as the fresh mushrooms with a 20-minute soak at 40 °C. As consumers prefer rehydrated products to be similar to fresh products in terms of texture and enjoyment value, it is crucial to determine the ideal rehydration parameters. However, each drying method and temperature has a different effect on the texture and water absorption capacity of the mushrooms, so the mentioned results are only achieved with the described parameters.

Open Access: Yes

DOI: 10.1007/s44187-025-00610-4

Regenerative soil treatments with alginite, mulch, and cover crops under minimum tillage: Impacts on soil organic matter content and quality in a 3-year study

Tünde Takács Zsolt Kotroczó Sándor Attila Pabar Borbála Biró

Publication Name: Agronomy Journal

Publication Date: 2025-09-01

Volume: 117

Issue: 5

Page Range: Unknown

Description:

The degradation of arable land globally, largely due to declining soil organic matter (SOM), is a pressing issue. SOM is essential for various soil functions and significantly influences soil quality and health. Our study aimed to compare soil regenerative management methods for soil quality and basic essential functions and their effectiveness. We focused on selecting methods suitable for effectively monitoring changes during soil management. Over 3 years, we employed core methods, including minimum-till practices and natural mineral applications, to enhance soil physical characteristics, using cover crops and mulch to enrich SOM content. We assessed chemical soil properties such as total organic carbon (TOC), labile-C (permanganate oxidizable carbon [POXC], dissolved organic carbon [DOC], NaOH-soluble fulvic acids), glomalin content, and plant productivity. Our findings revealed that minimum-till had a significant time-dependent effect, increasing surface soil TOC by 17.58%, NaOH-soluble humic acids by 40.85%, and POXC by 77.75% over 3 years. Mulch and cover crop treatments enhanced specific carbon parameters and crop production. Different methods of assessing carbon levels proved useful for tracking time-dependent changes in soil quality. Labile-C forms such as DOC and POXC were most effective for shorter experiments, while TOC, glomalin, and NaF-soluble humic acids were better indicators for more extended experiments. These findings provide valuable insights for sustainable soil management practices.

Open Access: Yes

DOI: 10.1002/agj2.70140

Localization robustness improvement for an autonomous race car using multiple extended Kalman filters

Krisztian Enisz Erno Horvath Istvan Szalay

Publication Name: Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering

Publication Date: 2025-08-01

Volume: 239

Issue: 9

Page Range: 3771-3783

Description:

In this paper, we introduce a vehicle localization method designed for the SZEnergy race car, which competes in the Shell Eco-marathon. The proposed method comprises four different extended Kalman filter-based localization algorithms and a selection algorithm that determines the most suitable one based on vehicle speed, GNSS availability, and signal quality. The low-speed Kalman filters are based on a kinematic vehicle model while the high-speed variants are based on a dynamic vehicle model. Several measurements were performed during test maneuvers to evaluate the performance of the filters. The proposed method succesfully handles sensor miscalibration and GNSS outages.

Open Access: Yes

DOI: 10.1177/09544070241266281

Correlation Analysis of Factors Affecting Firm Performance and Employees Wellbeing: Application of Advanced Machine Learning Analysis

Miklós Illéssy Sina Ardabili Amir Mosavi József Pap Bernat Torok Zef Dedaj Csaba Makó

Publication Name: Algorithms

Publication Date: 2022-09-01

Volume: 15

Issue: 9

Page Range: Unknown

Description:

Given the importance of identifying key performance points in organizations, this research intends to determine the most critical intra- and extra-organizational elements in assessing the performance of firms using the European Company Survey (ECS) 2019 framework. The ECS 2019 survey data were used to train an artificial neural network optimized using an imperialist competitive algorithm (ANN-ICA) to forecast business performance and employee wellbeing. In order to assess the correctness of the model, root mean square error (RMSE), mean absolute percentage error (MAPE), mean square error (MSE), correlation coefficient (r), and determination coefficient (R2) have been employed. The mean values of the performance criteria for the impact of internal and external factors on firm performance were 1.06, 0.002, 0.041, 0.9, and 0.83, and the value of the performance metrics for the impact of internal and external factors on employee wellbeing were 0.84, 0.0019, 0.0319, 0.83, and 0.71 (respectively, for MAPE, MSE, RMSE, r, and R2). The great performance of the ANN-ICA model is indicated by low values of MAPE, MSE, and RMSE, as well as high values of r and R2. The outcomes showed that “skills requirements and skill matching” and “employee voice” are the two factors that matter most in enhancing firm performance and wellbeing.

Open Access: Yes

DOI: 10.3390/a15090300

How Does State Fragility Drive Environmental Degradation? A Multidimensional Analysis of Governance and Socio-Economic Vulnerabilities

Cristian Barra Pasquale Marcello Falcone Luca Esposito

Publication Name: Kyklos

Publication Date: 2026-05-01

Volume: 79

Issue: 2

Page Range: 399-428

Description:

The growing crises in the environmental sector worldwide have increased the call for better comprehension of the linkage among governance, socio-economic stability, and environmental degradation. In this respect, state fragility—a term covering governance gaps, political instability, and economic turmoil—has emerged as a vital and rather unexplored cause of environmental degradation. This study examines how state fragility drives environmental degradation by analyzing the Fragile States Index (FSI) and PM2.5 air pollution across 130 countries from 2006 to 2020. Using generalized least squares (GLS) and Lewbel (2012) heteroskedasticity-based IV estimators, we disaggregate FSI into cohesion, economic, political, social, and external-intervention dimensions to identify heterogeneous effects. Results show that higher overall fragility is associated with increased PM2.5 and CO2 emissions, with economic and political fragility exerting the strongest positive impacts. Social pressures and external interventions also worsen air quality, while cohesion's effect is context-dependent—positive in baseline GLS but negative after addressing endogeneity—suggesting measurement and endogeneity issues. Controls reveal trade openness tends to raise pollution, whereas FDI and stronger institutions reduce it. Findings are more pronounced in low-income countries, underscoring sample heterogeneity. Policy implications stress strengthening governance, mobilizing green finance, and aligning external assistance with environmental objectives to break the fragility–pollution nexus.

Open Access: Yes

DOI: 10.1111/kykl.70031

Predicting Modified Fournier Index by Using Artificial Neural Network in Central Europe

Tamás Ratonyi Endre Harsányi A. Széles Bashar Bashir Safwan Mohammed Muhammad Farhan Ul Moazzam Firas Alsilibe István Takács Abdullah Alsalman A. Nyéki

Publication Name: International Journal of Environmental Research and Public Health

Publication Date: 2022-09-01

Volume: 19

Issue: 17

Page Range: Unknown

Description:

The Modified Fournier Index (MFI) is one of the indices that can assess the erosivity of rainfall. However, the implementation of the artificial neural network (ANN) for the prediction of the MFI is still rare. In this research, climate data (monthly and yearly precipitation (pi, Ptotal) (mm), daily maximum precipitation (Pd-max) (mm), monthly mean temperature (Tavg) (°C), daily maximum mean temperature (Td-max) (°C), and daily minimum mean temperature (Td-min) (°C)) were collected from three stations in Hungary (Budapest, Debrecen, and Pécs) between 1901 and 2020. The MFI was calculated, and then, the performance of two ANNs (multilayer perceptron (MLP) and radial basis function (RBF)) in predicting the MFI was evaluated under four scenarios. The average MFI values were between 66.30 ± 15.40 (low erosivity) in Debrecen and 75.39 ± 15.39 (low erosivity) in Pecs. The prediction of the MFI by using MLP was good (NSEBudapest(SC3) = 0.71, NSEPécs(SC2) = 0.69). Additionally, the performance of RBF was accurate (NSEDebrecen(SC4) = 0.68, NSEPécs(SC3) = 0.73). However, the correlation coefficient between the observed MFI and the predicted one ranged between 0.83 (Budapest (SC2-MLP)) and 0.86 (Pécs (SC3-RBF)). Interestingly, the statistical analyses promoted SC2 (Pd-max + pi + Ptotal) and SC4 (Ptotal + Tavg + Td-max + Td-min) as the best scenarios for predicting MFI by using the ANN–MLP and ANN–RBF, respectively. However, the sensitivity analysis highlighted that Ptotal, pi, and Td-min had the highest relative importance in the prediction process. The output of this research promoted the ANN (MLP and RBF) as an effective tool for predicting rainfall erosivity in Central Europe.

Open Access: Yes

DOI: 10.3390/ijerph191710653

DNA of Ehrlichia muris, hyperendemicity of Babesia microti in Ixodes ricinus and age-related detection of nuclear mitochondrial DNA (NUMTs) in Dermacentor reticulatus from an urban, marshy biotope of South-central Europe

Jenő Kontschán Tim Warbroek Tijs J.M. van den Bosch Paulina Lesiczka Gergő Keve Orsolya Péteri Nóra Takács Sándor Hornok

Publication Name: Ticks and Tick Borne Diseases

Publication Date: 2026-05-01

Volume: 17

Issue: 3

Page Range: Unknown

Description:

The present study was initiated to analyze ticks collected periodically from the vegetation in an urban marshy biotope of central Europe. During the one-year-long study period, 1960 ticks were found, including Ixodes ricinus (n = 1037), Dermacentor reticulatus (n = 610) and Haemaphysalis concinna (n = 313). DNA was extracted from 199 Dermacentor reticulatus and 47 Ixodes ricinus, selected from the beginning of their questing period. Molecular analysis of the cytochrome c oxidase subunit I (cox1) barcoding gene with the classical Folmer primers revealed that among 37 D. reticulatus all except two ticks had serial mutations along a 129-bp-long part of the gene. The majority of these ticks were young, freshly molted adults. However, when the complete mitogenome was sequenced from two such "aberrant" ticks, these serial mutations were absent. In D. reticulatus, host DNA was detected from four synanthropic bird species, the dog, the red fox, the bank vole, the Eurasian shrew and the wild boar. Besides long-known endemic tick-borne pathogens, specimens of D. reticulatus and I. ricinus were shown to contain the DNA of Ehrlichia muris. Babesia microti had very high, 36% prevalence in I. ricinus. In conclusion, mutations in the cox1 fragment amplified with the Folmer primers were not present in the complete mitochondrial genome of D. reticulatus, indicating that probably nuclear mitochondrial DNA (NUMT) was amplified with the first method. To our knowledge, similarly high local prevalence of B. microti was only reported in ticks in North America, where this piroplasm is responsible for most cases of human babesiosis (unlike in Europe).

Open Access: Yes

DOI: 10.1016/j.ttbdis.2026.102648

Digital Transformation of Public Services: The Case of the Document Management Application

Roland Zsolt Szabó Borbála Szedmák László Varga

Publication Name: International Journal of Public Administration

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The article examines digital transformation in the public sector, focusing on its implementation and impact. A key milestone in Hungary’s municipal digitalization is analyzed through a case study on the document management system of the Application Service Provider. Based on longitudinal data from over 3,000 municipalities, findings show that digital transformation delivers significant value to citizens and shortens administrative lead times. It enhances transparency, comparability, and efficiency in public administration. The study also emphasizes that adopting new technologies, standardizing processes, and centralizing IT management are critical factors in achieving these efficiency gains and modernizing public sector operations.

Open Access: Yes

DOI: 10.1080/01900692.2025.2520522

An interval-valued spherical fuzzy framework for strategic renewable energy selection

Shervin Zakeri Sercan Edinsel Galip Cihan Yalçın Prasenjit Chatterjee

Publication Name: Decision Analytics Journal

Publication Date: 2025-09-01

Volume: 16

Issue: Unknown

Page Range: Unknown

Description:

Many countries are prioritizing renewable energy sources in response to fossil fuel depletion, environmental concerns, and the need for energy resilience. This study evaluates five renewable energy alternatives: Biomass, Wind, Solar, Geothermal, and Hydro, with the aim of reducing foreign energy dependency and enhancing flexibility under potential geopolitical disruptions. A three-stage hybrid decision-making framework is proposed, integrating Modified Preference Selection Index (MPSI) and Multi-Attributive Border Approximation Area Comparison (MABAC) methods within an Interval-Valued Spherical Fuzzy (IVSF) environment. In the first stage, expert input is collected. The second stage applies IVSF-MPSI to determine the criteria weights under uncertainty. The third stage employs IVSF-MABAC to rank the alternatives based on these weights. The results indicate that Solar Energy, with a distance value of 0.2783, is the most suitable renewable energy, followed by Wind, Hydro, Geothermal, and Biomass. The proposed IVSF-MPSI-MABAC model equips decision-makers with a mathematically rigorous, uncertainty-resilient evaluation framework that supports quantitative trade-off analysis, prioritization of capital-intensive projects, and alignment of renewable energy portfolios with long-term energy security and sustainability objectives, while the integrated sensitivity analysis ensures ranking stability and robustness against variations in decision parameters.

Open Access: Yes

DOI: 10.1016/j.dajour.2025.100625