佩奇大学

Kis-Balaton is regarded as the largest marshland in Central Europe. Its small mammal communities consist of several protected shrews and rodents, including the Pannonian Root Vole Alexandromys oeconomus mehelyi, a postglacial relict subspecies. Small mammals play a variety of fundamental roles in ecological networks; thus, they are commonly chosen as indicators in wetland studies. Our study was carried out in two areas of the Kis-Balaton wetland in the period between 2007 and 2024. First, we examined the difference in the community structure of small mammals using PERMANOVA and NMDS analysis. Then, we investigated the co-occurrence pattern of species. In addition, Generalized Additive Models were used to determine the occurrence probability of six water-tolerant species as a function of spatial and temporal predictor variables in Kis-Balaton. Our results showed that the community structure of small mammals was similar in both monitored areas. The co-occurrence analysis revealed a positive association between numerous species. According to the GAM modeling, the occurrence probability significantly differed for several species in the comparison of investigated areas, with the partial main effects of years and areas being determining factors. A direct partial effect of monthly rainfall was shown in the case of the Common Shrew and Short-tailed Field Vole, for which species the change of occurrence probability was correlated with the variation of rainfall. Monthly rainfall had a significant effect on the occurrence probability of the Striped Field Mouse and the Harvest Mouse as a predictor in tensor product interaction models.

Our model explores supplier selection within an inventory management framework, integrating regional considerations and the impact of the made-in effect on demand. The firm optimizes product pricing, geographic sourcing distribution, and batch sizes. Our analytical results suggest that firms should expand local sourcing when product origin strongly influences consumer value or when demand is relatively inelastic to price. Additionally, leveraging smaller batch production can optimize cost efficiency while maintaining responsiveness, making local sourcing a strategic advantage in markets with uncertain demand or high service levels. In the fashion industry, the made-in effect plays a crucial role in shaping sourcing strategies, as a product’s country of origin significantly impacts consumer perceptions, brand reputation, and pricing dynamics. In line with observed sourcing strategies, we show that in the luxury segment, known for its significant pricing power and high service level, brands benefit from outsourcing manufacturing domestically. In contrast, economy brands, which operate under tighter margins and serve highly price-sensitive markets, should rely on offshore sourcing, leading to larger safety stocks and reduced responsiveness to demand uncertainty. Finally, a dual sourcing strategy—combining local and offshore suppliers—may be optimal, allowing firms to balance cost efficiency with responsiveness. This approach is commonly adopted by fast fashion companies to manage short product life cycles and volatile demand.

Mental fatigue induced by prolonged task performance (time-on-task [ToT]) is typically perceived as an unpleasant state and is associated with compromised performance. Operations requiring cognitive control, such as resolving response conflicts, are particularly sensitive to ToT-related detrimental effects. As cognitive control is critical for precise movements, ToT likely impacts movement performance. Two experiments explored this by examining the resolution of response conflicts in pointing movement with increasing ToT. In Experiment 1, participants performed a flanker task with congruent, neutral, and incongruent pointing trials. The results revealed slower movement initiation and execution, especially in incongruent trials, and ToT-related impairments in leftward movements possibly due to rightward attentional bias under fatigue. Experiment 2 introduced ‘leap trials,’ where spatial target locations shifted unexpectedly. While leap trials required high cognitive control, they resisted ToT-related deterioration, suggesting that phasic changes in spatial orientation resist fatigue. The performance of frequent normal trials with stable target locations declined over time, indicating that reduced tonic vigilance may worsen movements. Across both experiments, motivation manipulations after ToT periods mitigated declines in performance, reflecting the compensatory role of increased task engagement. These findings highlight the interplay between fatigue and cognitive control in motor tasks, offering insights into mechanisms underlying performance under mental strain.

Handheld devices have become popular to determine epidermal contents of UV-A absorbing compounds in intact leaves. For the comparability of the results between different labs, it is important that all instruments show the same or at least similar results. Therefore, the signals from seven different Dualex Scientific optical leaf clips from five laboratories were compared to each other, alongside a prototype of an LSA-2050 leaf state analyzer and a UV-A-PAM fluorometer. The values of the Flav index, which is used to quantify epidermal UV-A absorbing compounds such as flavonoids, corresponded well with each other (r2 > 0.989), except for one instrument. A higher variability among instruments was found for the chlorophyll (Chl) index, again with one instrument showing a significant offset. Although one Dualex instrument showed an excellent linear calibration for the anthocyanin (Anth) index relative to extract concentrations when red hazelnut leaves were investigated (r2 = 0.969), the Dualex instruments had all an offset against each other and at Chl index values below 30, erroneous Anth index values were observed. While Flav index results appeared quite reliable, it is recommended to calibrate a Dualex instrument against leaf extracts for exact determination of chlorophyll and anthocyanin contents. Simple tests for the functionality of a Dualex instrument are suggested.

Artificial Intelligence (AI) is transforming human resource management (HRM), introducing new efficiencies in recruitment, evaluation, and decision-making. However, its effect on diversity, equity, and inclusion (DEI) remains debated. This systematic literature review (SLR) compiles findings from 43 peer-reviewed articles published between 2016 and 2024 to critically assess AI’s dual role in HRM as both a potential promoter of fairness and a source of embedded bias. Rooted in ethical principles like fairness and accountability, organizational viewpoints such as HRM implementation challenges and best practices, and technological factors including algorithmic transparency and data quality, this review highlights four main themes: (1) AI’s ability to improve standardization, objectivity, and accessibility in HR processes; (2) risks related to algorithms and data that could perpetuate systemic bias and lessen accountability; (3) the human, data, and algorithmic origins of these issues; and (4) strategies for mitigation including participatory design, explainability, human oversight, and ethical governance. Despite growing interest in AI integration within HRM, previous studies have mostly treated fairness and effectiveness as separate issues, providing limited insight into how AI simultaneously impacts DEI outcomes. Additionally, the current literature often neglects the practical difficulties of implementing ethical principles, leaving HR professionals with scattered guidance. This review addresses these gaps by providing a timely, interdisciplinary overview that connects academic discussions with the urgent need for ethically responsible AI use in real-world HR environments. Practical implications are provided for HR professionals, developers, and organizational leaders, highlighting the importance of transparent implementation and inclusive design. Additionally, the review highlights theoretical and methodological gaps, suggesting that future research should focus on employee perceptions, contextual moderators, and the long-term effects of AI in various organizational settings. By presenting a comprehensive, multidisciplinary synthesis, this study advances the ongoing discussion on the ethical integration of AI in HRM. It provides practical guidance on aligning technological progress with inclusive organizational values. JEL Codes: M12; O33; J71; M14