Search Everything
Tip: Search using "First Name + Last Name", e.g.
János Kiss instead of
Kiss János.
Authors - 9551
Publications - 6278
Testing Sustainable 3D-Printed Battery Housings with DIC Technology †
Publication Name: Engineering Proceedings
Publication Date: 2024-01-01
Volume: 79
Issue: 1
Page Range: Unknown
Description:
Three-dimensional printing has rapidly gained traction in the automotive industry, offering significant benefits in terms of design flexibility, production speed, and cost efficiency. However, as the use of 3D printing grows, there is a rising focus on incorporating sustainable materials to minimize the environmental footprint of automotive components. This study centers on using eco-friendly, 3D-printable materials to produce electric vehicle battery covers. The primary goal is to assess these sustainable battery housings’ mechanical properties, durability, and overall feasibility. Additionally, the research explores the potential of foaming polylactic acid filaments in measurement applications using Digital Image Correlation technology, which is widely employed in the automotive sector. The study also evaluates these housings’ manufacturability and real-world applicability, offering insights into their role in the future of automotive production, where sustainability is becoming increasingly important. The research seeks to contribute to the broader movement toward greener manufacturing processes within the automotive industry by conducting these analyses.
Open Access: Yes
Implications of climate-change-induced stressors and water management for sterlet populations in the Middle and Upper River Danube
Publication Name: River Research and Applications
Publication Date: 2025-02-01
Volume: 41
Issue: 2
Page Range: 448-465
Description:
Sturgeons are a group of iconic rheophilic fish whose populations worldwide are currently undergoing significant declines. The study investigates the impact of climate change and anthropogenic activities, particularly the Gabčíkovo barrage system, on the survival and distribution of the sterlet, the last surviving sturgeon species in the Middle and Upper Danube River, specifically in the river part rkm 1708–1920 divided into three river sections: PT1 (Danube river part 1: rkm 1708–Gabčíkovo impoundment), PT2 (Danube river part 2: rkm 1854–1920), and PT3 (Old Danube part 3: rkm 1850–1810). Between years 1996 and 2020, water temperatures in the Danube River (PT1, PT2) rose by over 1°C on average, with the Old Danube (PT3) experiencing an alarming average increase of 3.5°C (df = 2, F = 145.03, p = <2.2e-16). Consequently, suitable sterlet habitat (depth ≥4 m) in the Old Danube (PT3) now covers only 11% of its total area compared with 67% in PT1 and 75% in PT2 (flow rate = 1924.27 m3 s−1) due to altered flow regimes, water levels, and siltation. Sterlets are increasingly caught in an artificial channel below to the Gabčíkovo Hydroelectric Power Plant (80%–90% of annual total catch), suggesting a shift in their distribution patterns. Conversely, there has been a notable decline in sterlet populations in other river sections, including a decrease in a section with moderate ecological status according to Water Frame Directive criteria. In light of these findings, the study proposes several mitigation measures to improve the status of the sterlet population in the area.
Open Access: Yes
DOI: 10.1002/rra.4361
Emerging macroscopic pretreatment
Publication Name: Food Waste Recovery Processing Technologies Industrial Techniques and Applications
Publication Date: 2020-01-01
Volume: Unknown
Issue: Unknown
Page Range: 173-193
Description:
Macroscopic pretreatment of food waste aims at the preparation of the food matrix for subsequent processing and recovery steps. The preparatory steps involve the adjustment of the phase content and properties (water, solid, and fats content), the moderation of enzyme activity as well as prevention and control of any microbial growth In recent times, several emerging technologies have been researched, developed, and/or adapted from other fields for drying, sterilization, enzyme inactivation, and enhancing mass transfer in food and biomaterials. This chapter focuses on these upcoming technologies with potential applications to food waste recovery and includes foam-mat drying, electro-osmotic drying, radio-frequency drying, cold plasma technology, and high-pressure processing. The content lays emphasis on discussing the successful applications and identification of future prospects, from both a technology and an economic point of view.
Open Access: Yes
Can multifarious types of green bonds be accused of greenwashing with a durative analysis? Insights from a permanent causality vs. temporary causality phenomenon
Publication Name: Environment Development and Sustainability
Publication Date: 2025-09-01
Volume: 27
Issue: 9
Page Range: 21425-21449
Description:
Green bonds are useful monetary tools that can finance sustainable endeavors to bolster an eco-friendly economy. This research inspects the frequency-domain causal relationship between diverse green bond types and the green economy from June 30, 2014 to August 3, 2023. The goal is to understand both permanent and temporary causal phenomena between them. The findings reveal that only pioneering green bonds display a robust bidirectional causal link with an eco-efficient economy. Meanwhile, other green bond types, like conventional, municipal, and currency-dominated green bonds, may be susceptible to greenwashing due to the absence of a thorough permanent causal tie with an ecologically sustainable economy. Additionally, enhancing pioneering green bonds by integrating ESG (Environmental, Social, and Governance) stocks can transform the cause-and-effect dynamic between specific green bonds and the green economy. It shifts from a bilateral cause to a unilateral one stemming from the environmentally friendly economy and extending to distinguished green bonds. This phenomenon persists whether the 5% annual fee for sustaining and managing the index combining green bonds and ESG equities is considered or not. Interestingly, an environmentally conscious economy, in both persistent and transient associations, consistently affects ecological bonds with diverse traits. This highlights the importance of the overall state of an environmentally responsible economy in enhancing green bonds. These discoveries provide novel perspectives for green market regulators and policymakers to design improved standards for green assets.
Open Access: Yes
Positive and Negative Expectations Associated with Coffee and Energy Drinks: Implications for Placebo–Nocebo Research in Sports
Publication Name: Nutrients
Publication Date: 2025-02-01
Volume: 17
Issue: 4
Page Range: Unknown
Description:
Background: Nutritional expectations have been shown to influence exercise performance via placebo and nocebo effects. The present study aimed to evaluate performance-enhancement expectations for coffee and energy drinks using the Stanford Expectations of Treatment Scale. Methods: A total of 402 participants (48.5% male) with an average exercise history of 4.53 years, engaging in average physical activity 3.91 times per week, were included in the study. Data collection was conducted through the Qualtrics platform. Results: Participants exhibited significantly higher positive expectations for coffee compared to energy drinks (p = 0.002), whereas negative expectations were more pronounced for energy drinks than for coffee (p < 0.001). Males and individuals engaging in anaerobic exercise expressed more positive expectations for energy drinks than females and those participating in aerobic or mixed exercise regimens. Additionally, high-frequency exercisers (≥4 sessions per week) reported greater positive expectations for both beverages and fewer negative expectations for coffee than low-frequency exercisers (≤3 sessions per week). Correlational analyses revealed weak but significant associations between expectations and variables such as exercise history, frequency, intensity, and age. Conclusions: The findings suggest that coffee is perceived as a more effective performance enhancer and exhibits greater placebo-inducing potential than energy drinks, which may elicit stronger nocebo effects. These group-specific perceptions should be considered by trainers, coaches, and researchers when addressing placebo–nocebo mechanisms in the context of sports and exercise.
Open Access: Yes
DOI: 10.3390/nu17040628
Towards Predicting Business Activity Classes from European Digital Corporate Reports †
Publication Name: Engineering Proceedings
Publication Date: 2024-01-01
Volume: 79
Issue: 1
Page Range: Unknown
Description:
Digital financial reporting enables automated analyses on vast datasets. This study illustrates the benefits of integrating XBRL and machine learning. XBRL, an open-source financial reporting language, was used to create a unified database of over 5600 IFRS-tagged reports. The IFRS taxonomy tags containing textual data on company activities were analyzed using the Zero-Shot Learning algorithm to identify specific activities. This study highlights how digital reporting and machine learning can extract and analyze textual data, offering insights into company activities and demonstrating the potential of these technologies in financial reporting.
Open Access: Yes
Legislation of forensic DNA analysis in Hungary - past, present and future
Publication Name: Forensic Science International Genetics Supplement Series
Publication Date: 2019-12-01
Volume: 7
Issue: 1
Page Range: 604-606
Description:
Ever since the first application of DNA analysis in criminal casework in 1992, the conditions under which forensic DNA analysis is performed within the Hungarian law have been developed and subsequently approved, in parallel with the establishment of a national database report of forensic DNA. Act XLVII of 2009 (on the Criminal Records System, on the Records of EU Member State Court Rulings against Hungarian Citizens as well as on the Records of Biometric Criminal and Law Enforcement Data) constituted the legal framework for this. Moreover, Act XXIX of 2016 (on Judicial Experts), Act CXII of 2011 (on the Right of Informational Self-Determination and on Freedom of Information), as well as Regulation 12/2016. (V.4.) of the Minister of Interior (on Rules of Taking Fingerprints, Palm prints, Photographs and DNA samples), as well as the Provisions of 31/2008. (XII. 31.) of the Minister of Local Government (on the work of forensic experts, respectively) went on to specify the professional requirements necessary for forensic DNA analysis. The regulations of the EU must also be taken into consideration. Of particular significance, are the escalations undertaken by the EU for the purpose of combating transnational crime as developed in the Prüm Treaty, and, under Council Decision 2008/615/JHA and Council Decision 2008/616/JHA, became ratified into its partial transformation into an EU-wide tool for cooperation. The General Data Protection Regulation (GDPR) has also introduced a new and seemingly far-reaching exemption to the general prohibitive conditions applied to the processing of genetic data. The question of whether, and which kind of, consent is required remains left to other applicable EU and national laws. The aim of this study is to provide an overview on how Hungarian legislation of forensic DNA has changed over the past 27 years, to illustrate the current legal context in addition to providing a conceptual theoretical framework for future legislation, including the rules of forensic DNA typing and legal regulation connected to DNA-databases.
Open Access: Yes
Impact of Big Four Audit Firms on Environmental Disclosure in China: Critical Role of Governance and Ownership Structure
Publication Name: Politicka Ekonomie
Publication Date: 2025-01-01
Volume: 73
Issue: 5
Page Range: 810-838
Description:
As the corporate world has recently been increasingly held accountable for its non-green behaviour, corporate environmental disclosures (CED) are crucial in informing the relevant stakeholders. Among the factors influencing CED, firm auditors play a pivotal role. Our research investigates the impact of Big Four audit firms on corporate environmental disclosure in China. With unique institutional factors and the most significant carbon emissions globally, China provides an exciting and compelling ground for studying this relationship. For this purpose, we use annual firm-level data of A-listed shares on the Shenzhen and Shanghai stock exchanges and employ the Poisson and negative binomial regression models for empirical analyses. Contrary to the common belief that Big Four audit firms lead to improved disclosure quality, we find that they negatively affect environmental disclosure in China. We also investigate the moderating role of corporate governance and ownership structure in this relationship. A high ratio of state ownership, male directors on the board and institutional investor holding worsen the disclosure quality. However, a high ratio of independent directors mitigates this issue. These findings open new avenues for further research and can guide future policy decisions regarding environmental disclosure in Chinese firms. The Big Four audit firms should be more stringent in their operations and supervise public firms regarding environmental disclosures.
Open Access: Yes
Utilizing machine learning and CMIP6 projections for short-term agricultural drought monitoring in central Europe (1900–2100)
Publication Name: Journal of Hydrology
Publication Date: 2024-04-01
Volume: 633
Issue: Unknown
Page Range: Unknown
Description:
Water availability for agricultural practices is dynamically influenced by climatic variables, particularly droughts. Consequently, the assessment of drought events is directly related to the strategic water management in the agricultural sector. The application of machine learning (ML) algorithms in different scenarios of climatic variables is a new approach that needs to be evaluated. In this context, the current research aims to forecast short-term drought i.e., SPI-3 from different climatic predictors under historical (1901–2020) and future (2021–2100) climatic scenarios employing machine learning (bagging (BG), random forest (RF), decision table (DT), and M5P) algorithms in Hungary, Central Europe. Three meteorological stations namely, Budapest (BD) (central Hungary), Szeged (SZ) (east south Hungary), and Szombathely (SzO) (west Hungary) were selected to forecast short-term agriculture drought i.e., Standardized Precipitation Index (SPI-3) in the long run. For this purpose, the ensemble means of three global circulation models GCMs from CMIP6 are being used to get the projected (2021–2100) time series of climatic indicators (i.e., rainfall R, mean temperature T, maximum temperature Tmax , and minimum temperature Tmin under two scenarios of socioeconomic pathways (SSP2-4.5 and SSP4-6.0). The results of this study revealed more severe to extreme drought events in past decades, which are projected to increase in the near future (2021–2040). Man-Kendall test (Tau) along with Sen's slope (SS) also revealed an increasing trend of SPI-3 drought in the historical period with Tau = −0.2, SS = −0.05, and near future with Tau = −0.12, SS = −0.09 in SSP2-4.5 and Tau = −0.1, SS = −0.08 in SSP4-6.0. Implementation of ML algorithms in three scenarios: SC1 (R + T + Tmax + Tmin ), SC2 (R), and SC3 (R + T)) at the BD station revealed RF-SC3 with the lowest RMSE RFSC3 -TR = 0.33, and the highest NSE RFSC3 -TR = 0.89 performed best for forecasting SPI-3 on historical dataset. Hence, the best selected RF-SC3 was implemented on the remaining two stations (SZ and SzO) to forecast SPI-3 from 1901 to 2100 under SSP2-4.5 and SSP4-6.0. Interestingly, RF-SC3 forecasted the SPI-3 under SSP2-4.5, with the lowest RMSE = 0.34 and NSE = 0.88 at SZ and RMSE = 0.34 and NSE = 0.87 at SzO station for SSP2-4.5. Hence, our research findings recommend using SSP2-4.5, to provide more accurate drought predictions from R + T for future projections. This could foster a gradual shift towards sustainability and improve water management resources. However, concrete strategic plans are still needed to mitigate the negative impacts of the projected extreme drought events in 2028, 2030, 2031, and 2034. Finally, the validation of RF for short-term drought prediction on a large historical dataset makes it significant for use in other drought studies and facilitates decision making for future disaster management strategies.
Open Access: Yes
