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Integrating Artificial Intelligence into Fuzzy Decision Analytics: A Novel Approach to Mitigating Stereotype Threat in Sustainable Business Environments

Gergely Czukor Dragan Pamucar Hasan Dincer Serhat Yuksel Serkan Eti

Publication Name: Journal of Fuzzy Extension and Applications

Publication Date: 2025-06-01

Volume: 6

Issue: 2

Page Range: 371-390

Description:

Preventing the threat of stereotyping is critical for business performance improvements. Because of this situation, businesses must take the necessary precautions. However, these actions have an impact on cost increase for the businesses. The number of studies in the literature performing priority analysis for these factors is quite limited. This situation increases the need for a new study that prioritizes the analysis of these variables. Accordingly, this study aims to evaluate the factors against the stereotype threat in the sustainable business environment. An artificial intelligence model is implemented in the first stage to weigh the experts. In the following stage, selected criteria are evaluated with the help of T-Spherical fuzzy DEMATEL. Thirdly, a comparative analysis was performed using different values. Finally, selected industries are ranked by Spherical Fuzzy RATGOS with respect to the stereotype threat. The weights of the experts can be identified in the analysis process. This situation has a strong contribution to the effectiveness of the findings. It is concluded that training activities are critical to minimizing the threat of stereotypes in companies.

Open Access: Yes

DOI: 10.22105/jfea.2025.480001.1641

Omega-3 Fatty Acid Consumption Alters Uterine Contraction: A Comparative Study on Different Breeds of Rats

Tamás Tóth George Bázár Reza Samavati Kalman F. Szucs Annamaria Schaffer Dora Vigh Henrik Baranyay Seyedmohsen Mirdamadi Tamara Barna Róbert Gáspár

Publication Name: International Journal of Molecular Sciences

Publication Date: 2025-06-01

Volume: 26

Issue: 11

Page Range: Unknown

Description:

Polyunsaturated fatty acids (PUFAs) play roles in several physiological and pathophysiological processes, but their effects on reproductive function are controversial. The aim of the study was to investigate the effect of n-3 PUFA-rich fish oil and n-6-rich sunflower oil on sex hormone status, in vivo and in vitro uterine contractility, and endometrial remodeling. Female Sprague Dawley, Lister hooded, and Wistar rats were treated orally for 20 days with 1 mL of tap water, sunflower oil, or fish oil. Blood samples were taken for gonadotropic and sex hormone analysis. In vivo smooth muscle contractions were measured weekly by electromyography. Isolated uterine and cecal contractions were measured after sacrificing the animals. Endometrial remodeling was detected based on the presence of αvβ3 integrin by optical imaging. In Sprague Dawley rats, fish oil increased the LH level and progesterone/estradiol (P4/E2) ratio compared to the sunflower oil-treated group. Uterine contractions were reduced both in vitro and in vivo. Endometrial αvβ3 integrin activity was increased in the fish oil group. In Lister hooded rats, neither sunflower nor fish oil treatments modified the investigated parameters. However, in Wistar rats, both oils increased only the in vivo contractions and reduced the P4/E2 ratio, along with αvβ3 integrin fluorescence. n-3 PUFA-rich fish oil induces a breed-dependent effect on sex hormone status and uterine contractions in rats. The response to PUFA intake may vary significantly within a given species, which may have importance both in animal feeding and human nutrition.

Open Access: Yes

DOI: 10.3390/ijms26115221

Overview on the Sustainable and Responsible Educational Technology Efforts Using Artificial Intelligence for the Workers of the Future

Márta Konczos Szombathelyi Viktória Kövecses-Gősi Zita Kaszalik Viktória Gősi Kövecses

Publication Name: Journal of Sustainability Research

Publication Date: 2025-06-01

Volume: 7

Issue: 2

Page Range: Unknown

Description:

The purpose of the research is to review how artificial intelligence is integrated into the education of employees, emphasizing that the rapid application of artificial intelligence significantly affects the development of the workforce and the achievement of sustainability goals. The European Commission also continuously monitors changes in the field of digitization and artificial intelligence. Among other things, the European Union uses ESG (environmental, social, governance) aspects to measure sustainability performance, relying on domestic and international literature to reveal how education, investments and international cooperation can lead to social development and market competitiveness. As a research method, we use the analysis of annual reports, training and conference reports, company websites, and databases on corporate ESG commitment, employee development, and digitalization. Based on the decision of the European Commission, the continuous and rapid progress of the development of digitization and artificial intelligence is an issue to be monitored with reporting obligations. Analyzes of ESG reports help to understand the sustainability practices and environmental effects of a given organization, help to reveal social responsibility, interpret the company's long-term value creation potential and risks, measure and compare the sustainability performance of different companies and organizations. Analyzing ESG reports is key to promoting transparency and responsible business practices. Based on the developments, in addition to the economic results, the realization of the sustainability goals is becoming more and more tangible in the context of the ESG framework, the investigation of digitalization and artificial intelligence, as well as the labor market and education.

Open Access: Yes

DOI: 10.20900/jsr20250039

Comparison of ultrasound-assisted extraction and modified QuEChERS technique for extraction of hesperidin from lemon peel (Citrus limon L.) as determined by HPLC

E. Lakatos Székelyhidi Rita Beatrix Sik Laura Végh Zsolt Ajtony

Publication Name: Journal of Food Composition and Analysis

Publication Date: 2025-06-01

Volume: 142

Issue: Unknown

Page Range: Unknown

Description:

Hesperidin (HSP) is a bioflavonoid known for its notable health benefits. Recent extraction strategies have aimed to minimize hazardous solvent use and simplify procedures to improve cost-effectiveness. This study compares ultrasound-assisted extraction (UAE) with a modified “quick, easy, cheap, effective, rugged, and safe” (QuEChERS) method for the recovery of HSP. High-performance liquid chromatography with diode array detection (HPLC-DAD) was used for quantification. The modified QuEChERS method resulted in the highest extraction efficiency while significantly reducing processing time. The validated method demonstrated excellent sensitivity (LOQ: 10.0 µg/mL), high accuracy (recovery >93 %), and good precision (RSD <3.4 %), making it a reliable and cost-effective approach for routine HSP analysis in citrus peel. These findings indicate that the modified QuEChERS technique offers a promising alternative to UAE for the rapid and efficient extraction of HSP.

Open Access: Yes

DOI: 10.1016/j.jfca.2025.107553

How does intergenerational transmission affect green innovation? Evidence from Chinese family businesses

Irum Shahzadi Peijun Xie Shiyi Tang Jian Wang Irum Shahzadi Yuriy Bilan

Publication Name: Structural Change and Economic Dynamics

Publication Date: 2025-06-01

Volume: 73

Issue: Unknown

Page Range: 158-169

Description:

Green innovation in family businesses is a significant yet underexplored area of research, particularly with regard to the influence of dynamic succession characteristics on intergenerational inheritance and its impact on innovation. This study, integrating the social-emotional wealth theory (SEW) and the agency theory, examines 505 Chinese listed family firms spanning from 2011 to 2020. Employing the Difference-in-Differences (DID) method, we investigate how intergenerational inheritance affects green innovation investment over time. Our findings reveal that initially, intergenerational transmission tends to inhibit green innovation investment in family businesses; however, this effect diminishes as the intergenerational process unfolds, indicative of the maturation of the second generation. Notably, we observe that a higher education level among second-generation heirs weakens the inhibitory effect of intergenerational inheritance on green innovation investment. This study addresses a gap in green innovation research by considering intergenerational transmission dynamics in family businesses, thus enhancing our understanding of innovation behaviors within this context. By synthesizing SEW and agency theory, this research offers novel insights into the varying impacts of intergenerational inheritance on firm innovation, shedding light on approaches to reconcile the willingness-ability paradox in family business innovation and promoting effective governance of succession processes.

Open Access: Yes

DOI: 10.1016/j.strueco.2024.12.022

Assessing the Impact of IT, Trade Globalisation, and Economic Complexity on Carbon Emissions in BRICS Economies

Mahwish Zafar Md Billal Hossain Hamza Akram Tuba Rasheed

Publication Name: Economies

Publication Date: 2025-06-01

Volume: 13

Issue: 6

Page Range: Unknown

Description:

The escalating threat of climate change has placed carbon dioxide (CO2) emissions at the forefront of global environmental policy. The relationship between carbon dioxide (CO2) emissions and information technology (IT) is crucial in shaping international climate change strategies. This study investigates the impact of information technology, trade globalisation (TG), and economic complexity (EC) on CO2 emissions in BRICS countries using panel data from 1996 to 2018. The analysis applies the CUP-FM estimator to assess long-run relationships and the Dumitrescu–Hurlin panel causality test to evaluate directionality. The results show that information technology significantly reduces CO2 emissions. This effect is primarily driven by the promotion of the service sector, reduced material use, and improved energy efficiency. In contrast, trade globalisation has an inconsistent impact. While it can lower emissions through technology diffusion and efficiency gains, it can also increase them due to Scale Effects and the relocation of polluting industries. This study also identifies a U-shaped relationship between economic complexity and CO2 emissions, indicating that emissions initially rise with complexity but decline as innovation and clean production practices improve. These findings suggest that developing digital infrastructure and green technologies and trade Globalisation can promote sustainable development in BRICS economies. Therefore, policymakers should prioritise strengthening the IT environment, fostering international trade partnerships, and integrating clean technologies to balance economic growth with environmental protection.

Open Access: Yes

DOI: 10.3390/economies13060153

Method of fundamental solutions formulations for biharmonic problems

Andreas Karageorghis Csaba Gáspár

Publication Name: Engineering Analysis with Boundary Elements

Publication Date: 2025-06-01

Volume: 175

Issue: Unknown

Page Range: Unknown

Description:

We consider various method of fundamental solution (MFS) formulations for the numerical solution of two-dimensional boundary value problems (BVPs) governed by the homogeneous biharmonic equation. The motivation for employing the proposed techniques comes from the corresponding boundary integral representations. These are carefully analyzed in the case the domain of the BVP under consideration is a disk. The results of this analysis detect a potentially troublesome case in one of the proposed MFS approaches. Numerical results confirm the analytical findings for more general domains.

Open Access: Yes

DOI: 10.1016/j.enganabound.2025.106180

Performance Analysis of MPT-GRE Multipath Networks Under Out-of-Order Packet Arrival

Naseer Al-Imareen G. Lencse

Publication Name: Electronics Switzerland

Publication Date: 2025-06-01

Volume: 14

Issue: 11

Page Range: Unknown

Description:

Network packets may arrive out of their original order due to network delays, transmission speed variations, congestion, or uneven resource distribution. These factors cause significant challenges to network performance. These challenges result in jitter, packet loss, and reduced throughput, negatively affecting the efficient arrangement of packets. The Multipath tunnel-Generic Routing Encapsulation (MPT-GRE) architecture addresses this issue through a packet reordering mechanism designed for multipath GRE with User Datagram Protocol (UDP) encapsulation networks. This study investigates and analyses the path-specific delays, jitter, and transmission speed constraints to evaluate the influence of out-of-order packets on the MPT-GRE tunnel throughput aggregation capability. By comparing scenarios with and without the re-ordering mechanism, the results demonstrate that the reordering mechanism substantially improves the traffic throughput in symmetric and asymmetric channel configurations. Additionally, the study emphasizes the critical role of optimizing the reordering window parameter for effective performance. These findings confirm that packet reordering mechanisms significantly enhance MPT-GRE network performance by reducing the negative effects of delays and out-of-order arrivals.

Open Access: Yes

DOI: 10.3390/electronics14112138

Knowledge flows in industry 4.0 research: a longitudinal and dynamic analysis

Edit Süle Abdo Hassoun John G. Keogh Abderahman Rejeb Karim Rejeb

Publication Name: Journal of Data Information and Management

Publication Date: 2025-06-01

Volume: 7

Issue: 2

Page Range: 123-145

Description:

Industry 4.0 represents a significant shift in industrial practices, presenting unique opportunities to improve manufacturing via advanced digital technologies and sustainable processes. The rapid growth of Industry 4.0 research has uncovered a significant knowledge gap and emphasized the need for studies adopting dynamic and longitudinal perspectives to understand this field’s evolution comprehensively. This study meticulously analyzes 10,176 articles to investigate the thematic evolution and knowledge transfer mechanisms within Industry 4.0. The examination reveals four distinct sub-periods, each characterized by thematic transitions, starting with foundational themes such as simulation and cyber-physical systems, progressing to later focuses on cloud computing, convolutional neural networks, and digital twin technologies. As research progresses, themes like production facilities, monitoring, and security highlight the shift towards automation, real-time monitoring, and strong data security measures. Five primary thematic domains are identified: (1) core enablers of sustainable smart manufacturing, (2) innovation and strategic transformation, (3) smart and secure manufacturing systems, (4) advanced data-driven manufacturing technologies, and (5) AI-driven real-time monitoring and production. These domains illustrate a transition from fundamental enablers like the Internet of Things (IoT) to more intricate AI-based applications. The main path analysis indicates a shift in emphasis, moving from essential digital integration towards sustainability, digital transformation, and resource efficiency applications. The findings reveal significant implications and highlight Industry 4.0 as a driving force for sustainable and resilient industrial ecosystems.

Open Access: Yes

DOI: 10.1007/s42488-025-00146-3