Purpose – The purpose of this study is to identify the key labour-market skills, the challenges graduates face and recommendations for aligning higher education with employer expectations in Hungary, a Central European country. This study underscores the importance of soft skills, such as adaptability, problem-solving and independence, for graduates in the Hungarian labour market. Design/methodology/approach – A cross-sectional survey was conducted among all students of a Hungarian university involved in work placements (n = 1, 556). The research subjects were the organisations where undergraduate students from a Hungarian university completed their practical semester, and a total of 1, 556 student evaluations were processed. The study analysed 15 distinct skills suggested by NACE and identified four factors: agility, professional knowledge, interpersonal skills and generic skills. Findings – The study's findings indicate that agility, encompassing adaptability, problem-solving skills and independence, emerged as the paramount criterion in employers' evaluations. The findings indicate substantial disparities in the perceived significance and assessment of skills across diverse academic disciplines. The research findings show that, in the labour market, soft skills may be more significant than technical expertise. The subsequent development of the skills and competence measurement tool identified in the literature review is proposed, particularly with respect to the hard and soft skills of the field of study. Research limitations/implications – The main limitation of this research is the use of a non-validated measurement instrument developed for internal quality management, which may lack scientific rigour. Additionally, the application of a uniform competency framework across all disciplines prevents the study from capturing the specific skill nuances required by different professional fields. Practical implications – Universities should move beyond simply adding soft skills modules and instead embed cognitive and interpersonal development across all curricula. Key mechanisms for this include structured industry partnerships, work-integrated learning and a shared competency framework that aligns academic content with specific labour-market expectations. Social implications – By addressing the skills mismatch, these findings foster a more efficient transition from education to employment, ultimately enhancing graduate career prospects. Recognising the hierarchical structure of skills, where technical knowledge is the baseline but agility and interpersonal skills drive advancement, helps society better prepare a workforce capable of long-term professional growth. Originality/value – This study underscores the significance of soft skills in the Central European/Hungarian labour market context, offering direct evidence from employer evaluations of student work placements. The implications of this phenomenon extend to the need for educational reform that integrates soft skills training. Furthermore, there is a compelling need for enhanced collaboration between universities and employers. Additionally, policy adjustments are imperative to ensure the successful implementation of these changes. Aligning educational curricula with employer expectations can help mitigate the skills gap and stimulate economic growth in Central Europe.

Purpose – This study aims to explore how the Human Development Index (HDI) is associated with students’ perceived academic, personal and skill-development outcomes related to the integration of generative artificial intelligence, particularly ChatGPT, into higher education. From a knowledge management perspective, the research examines adaptive use of AI tools, structuring of information and support of autonomous learning in countries with varying development. Design/methodology/approach – The study draws on 11, 910 valid responses from the 2024 Global ChatGPT student survey, covering 58 countries. Based on 33 Likert-scale items, three reflective constructs were identified. To explore the relationships between HDI, usage intensity and perceived impacts, the analysis combined descriptive statistics, K-means clustering and a partial least squares structural equation modeling (PLS-SEM) mediation model. Findings – The regression analysis showed a weak but statistically significant negative correlation between HDI and perceived impacts: students from lower-HDI countries tended to view ChatGPT’s impacts more positively. The PLS-SEM results indicated that higher national development is associated with lower perceived academic, developmental and skill-related benefits. This relationship appears both direct and indirect, as students in more developed countries report using ChatGPT less frequently and less creatively for academic purposes. Practical implications – The findings highlight the need for context-sensitive, pedagogically grounded artificial intelligence strategies, particularly in highly developed countries and in the support of students from disadvantaged backgrounds. Originality/value – This study is among the first to examine how national development levels shape perceived ChatGPT impacts in higher education. By combining HDI, cluster analysis and mediation modeling, it offers a novel perspective on digital inequality.

Purpose – The study aimed to examine family-friendly practices of employers in Hungary and compared public and private sector organisations to better understand their approaches to promoting the work–life balance of employees. Design/methodology/approach – A cross-sectional, quantitative survey was carried out between April and June 2023, involving 702 organisations certified as family-friendly workplaces in Hungary, of which 101 managers responded. The data were analysed using descriptive statistics and Pearson’s chi-squared tests to examine associations between sector and the prevalence of family-friendly practices. Findings – The findings indicate sectoral variation in the implementation of family-friendly practices. Private sector organisations more frequently reported flexible working arrangements, whereas public sector employers more often reported traditional measures such as childcare services and child-friendly work environments. Teleworking was available in 87.3% of private organisations, compared with 67.4% of public organisations (p = 0.016). Similarly, part-time work was offered by 87.3% of private organisations and 63.3% of public organisations (p = 0.004). Conversely, on-site childcare (52.2% vs. 21.8%, p = 0.002) and child-friendly workplaces (58.7% vs 23.6%, p < 0.001) were more prevalent in the public sector. Research limitations/implications – The study is geographically limited to Hungary and focuses mainly on certified family-friendly workplaces, which may not represent all organisations uniformly. However, it provides a basis for benchmarking international research on family-friendly workplace policies. In addition, it does not include a qualitative study to provide more in-depth insight or to capture the views of employees, but identifies further research directions in this way. Practical implications – Based on these findings, organisations should consider implementing family-friendly policies that better promote work–life balance. The study recommends that the public sector extend flexible working arrangements and increase family benefits to improve recruitment and retention. Conversely, private sector employers should focus on developing childcare facilities on-site and fostering family-friendly work environments to support their employees’ needs effectively, thereby increasing job satisfaction. Social implications – A better understanding of family-friendly workplace policies can help to raise awareness of the importance of promoting work–life balance. The implementation of these policies has the potential to improve the well-being of employees and contribute to wider societal goals, including gender equality, family stability and the development of a more sustainable society. Originality/value – The study provides a comprehensive analysis of family-friendly workplace policies in the various sectors in Hungary, highlighting sectoral strategies and practical recommendations for better promoting work–life balance and organisational efficiency.

Low-carbon agricultural (LCA) practices, including nutrient, water, and soil management, present viable strategies for mitigating greenhouse gas (GHG) emissions while enhancing agricultural productivity. However, their long-term impacts on food security and emission reduction at the national scale require further investigation. This study employs scenario-based analysis to assess the role of LCA in reducing carbon dioxide, nitrous oxide, and methane emissions while evaluating its effects on food production, accessibility, and availability in India. By conceptualizing LCA as a baseline scenario, the study examines the influence of technology adoption, government policies, and sustainable agricultural practices in enhancing food security and mitigating climate change. A systematic literature review, following the PRISMA protocol, was conducted using keyword co-occurrence analysis from major global databases, including Scopus, ScienceDirect, Web of Science, and government and organizational sources. The findings indicate that efficient resource and nutrient management significantly strengthen food security while reducing annual GHG emissions, supporting India’s progress toward food self-sufficiency and climate resilience. These insights provide a foundation for strengthening national and global food policies and climate mitigation strategies, aligning with multiple Sustainable Development Goals (SDGs), including SDG 2 (Zero Hunger), SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production), SDG 13 (Climate Action), SDG 15 (Life on Land), and SDG 17 (Partnerships for the Goals). This study underscores the critical role of LCA in integrating food security with environmental sustainability, offering a policy-driven approach to climate adaptation and sustainable agricultural development in India.

Background: Chronic hepatitis B virus (HBV) infection is a well-recognized cause of hepatic injury through prolonged viral replication, inflammation, and oxidative stress. Existing antiviral drugs limit viral replication but cannot eliminate viral transcription or even totally preclude liver injury, thus reemphasizing the significance of drugs with combined antiviral and hepatoprotective effects. Objectives: To evaluate the effects of wedelolactone on HBV replication, gene expression, inflammation, and oxidative stress in an in-vitro model of HBV plasmid transfection with human hepatic cells. Methods: Human hepatocellular carcinoma cells (Huh7) were transfected with a 1.3-mer plasmid and treated with wedelolactone (2.5 - 10 µM). Luciferase assays for HBV promoter activity, Northern blotting and Southern blotting for transcripts and replicative intermediates, qPCR for extracellular HBV DNA, and western blotting for viral antigens such as HBx were performed. Cell cytotoxicity was measured. NF-κB/IκB, inflammatory cytokines (TNF-α, IL-6), and antioxidant markers (Nrf2, HO-1, Keap1) were assessed to evaluate inflammatory and oxidative responses. Results: Wedelolactone significantly suppresses HBV promoter activity, RNAs, core particle formation, and extracellular HBV DNA. It reduced the expression of HBcAg and HBsAg. It inhibited NF-κB activation and cytokine release, while simultaneously enhancing Nrf2/HO-1 signaling, including induction of heme oxygenase-1 by lowering levels of Keap1. Conclusions: Wedelolactone exerts dual antiviral and hepatoprotective actions by inhibiting HBV replication and modulating inflammatory and oxidative stress pathways.

This study presents a comprehensive investigation of optical solitary waves governed by a third-order complex modified Korteweg-de Vries (higher-order nonlinear Schrödinger-type, mKdV-NLS) equation incorporating stochastic effects. Initially, the methodology outlines the general procedure of this approach. Subsequently, by applying the traveling waves transformation to the given equation, it is reformulated into nonlinear ordinary differential equations (NLODEs). These NLODEs are then decomposed into their imaginary and real components. Furthermore, the proposed methodology is implemented to derive new solutions for optical solitary waves within the mKdV-NLS type model, encompassing stochastic breather-like waves, singular solitons, periodic waves, and various wave interactions. Additionally, numerical visualizations of the exact analytical solitary waves are provided, facilitating an examination of the stochastic term’s influence on wave dynamics. This study advances the understanding of optical wave behavior and clarifies the effects of stochastic contributions, offering valuable insights for both theoretical studies and practical applications in optics and related fields.

This paper introduces a novel method for the enhancement of automated vehicle safety and efficiency during critical manoeuvres. The fundamental of the presented method is the observer design architecture, in which lateral dynamic states of the vehicle are evaluated. The novel observer consists of both model-based and machine-learning-based methods to ensure the selected design performances, such as efficient trajectory tracking and safety evaluation of the autonomous vehicle. In contrast to the already introduced and applied stability index-based methods, the proposed safety evaluation process is able detect stability loss and performance degradation of the autonomous vehicle. In the proposed observer-based safety evaluation method, stability and performance loss detection is based on the comparison of model-based and learning-based state observation. The main novelty of the paper is the design of the reinforcement learning (RL) based observer in a guaranteed structure that results in small observation error even under nonlinear vehicle dynamics. Furthermore, a lateral safety index is defined based on the value of the improvement vector representing the addition to the model-based estimation. By this means, with the proposed safety evaluation method both safety and performance loss hazards can be identified simultaneously.

Microplastic (MP) pollution in river systems has become an increasing environmental concern, particularly in transboundary rivers such as the Danube. This study provides the first detailed assessment of microplastic contamination in the Szigetköz section of the Danube and its major tributary, the Mosoni-Danube. Depth-resolved pumped water samples were collected at three locations (Rajka, Mecsér and Gönyű) and analysed using Fourier Transform Infrared (FTIR) spectroscopy combined with automated spectral evaluation. MP concentrations showed a clear downstream increase, with average values of 83.8 particles/m³ at Rajka, 237.6 particles/m³ in the Mosoni-Danube at Mecsér, and 795.9 particles/m³ at Gönyű. Polyethylene (PE) was the dominant polymer in the tributary (70.6%), whereas both PE and alkyd resins were prevalent at the main Danube sites (Rajka: alkyd 37.7%, PE 31.8%; Gönyű: alkyd 39.9%, PE 37.3%). Particle size distribution also shifted downstream, with a higher proportion of smaller (50–100 μm) particles detected at Gönyű compared to upstream sites. The results suggest that the tributary may represent an important input to the main Danube channel in this section, while differences in polymer composition point to varying source characteristics within the study area. These findings provide an important baseline for future monitoring and support the development of targeted mitigation strategies in this transboundary river system.

This study examines the alignment between the Sustainable Development Goals (SDGs) and the Environmental, Social, and Governance (ESG) pillars through the lens of the European Sustainability Reporting Standards (ESRS) taxonomy, complemented by the Global Reporting Initiative (GRI). The research introduces a policy-relevant framework that categorizes SDG targets within ESG pillars, offering structured guidance for policymakers and regulatory bodies to harmonize global sustainability goals with corporate reporting practices. By mapping 199 GRI and 201 ESRS accounting entries to the 17 SDGs, the study identifies significant opportunities to address thematic and procedural gaps in existing reporting systems. The findings demonstrate that SDG 8 (“Decent Work and Economic Growth”) exhibits the highest linkage rate to ESRS accounting items, reinforcing its relevance for policy-driven frameworks that integrate economic resilience with social equity. This harmonized approach underscores the role of policy in fostering alignment between corporate ESG strategies and broader sustainability objectives, mitigating greenwashing risks, and advancing standardization across regions and sectors. The study advocates for policy interventions that leverage this framework to enhance transparency, accountability, and long-term decision-making for sustainable development.