Long-term animal re-identification (ReID) must remain robust to gradual morphological evolution and seasonal appearance shifts. Although recent vision–language models provide strong pretrained visual representations, adapting them to longitudinal ecological settings remains challenging, particularly under identity and temporal distribution shifts. We present a parameter-efficient CLIP adaptation framework for animal ReID and introduce a continuous metadata-conditioning mechanism that incorporates numerical attributes directly into the prompt representation during training. While low-rank visual adaptation, prompt-based supervision, and cross-modal alignment provide the adaptation framework, the proposed metadata-conditioning strategy constitutes the primary methodological contribution. By preserving the continuous structure of numerical metadata rather than discretizing it into textual categories, the proposed approach enables smooth modulation of the embedding space during training while maintaining a purely visual inference pipeline. Experiments on a seven-year longitudinal fish dataset and multiple wildlife benchmarks demonstrate improved performance under closed-set, open-set, and time-aware evaluation protocols. The results demonstrate that continuous metadata conditioning improves robustness to longitudinal appearance variation and temporal distribution shifts, while parameter-efficient adaptation enables a purely visual inference pipeline without requiring metadata at test time. Code and evaluation splits can be found at: https://github.com/AnilOsmanTur/MetaPrompt-ReID.
In the context of Industry 5.0, scheduling heterogeneous resources, such as humans and robots, has become increasingly critical. Task allocation must balance human comfort, ergonomics, and trust with productivity and responsiveness to customer demands. This review explores recent advances and prospects in the automatic generation of schedules and action plans, particularly Behavior Trees (BTs), to improve human–robot collaboration. We examine the application of artificial intelligence techniques to classical production management problems, such as Job Shop Scheduling Problem (JSSP) and Assembly Line Balancing Problems (ALBP), for autonomous task scheduling and robotic behavior design. This includes highlighting innovative scheduling approaches and the advantages of Behavior Trees over traditional models such as Hierarchical Task Networks (HTN) and Finite-State Machines (FSM). Behavior Trees offer a modular and reactive programming structure essential for executing complex tasks assigned to robots. The review also discusses human operators’ perception of robotic actions and identifies best practices for implementing collaborative solutions that prioritize both efficiency and safety.
The social care sector across the globe is increasingly witnessing customer mistreatment incidents that pose significant personal and work-related challenges for frontline employees. Extant research suggests that human resource management (HRM) can be instrumental in extending support to the frontline to overcome the adversities of such mistreatment. In this study, we first develop a comprehensive account of the types of customer mistreatment prevalent in social care. Then, drawing on psychological contract theory, we outline the frontline's expectations of support from HRM practices to deal with such incidents. We further elaborate on gaps in social care that inhibit extending such support through HRM practices to the frontline and establish how the HR co-creation approach can be utilized to plug these gaps. In this multistage qualitative study, we collect data in three stages from 51 frontline employees and 15 HR professionals working in the social care sector who have witnessed customer mistreatment. Based on our study's findings, we propose a novel framework called "FRESH against mistreatment" (Frontline Expectations for Support from HRM), which can aid HR professionals in identifying expectations, gaps, and possibilities for extending support through HRM practices to the frontline in social care to handle incidents of customer mistreatment.
This study examined the evolving landscape of green entrepreneurship (GE) research through a comprehensive analysis that combined bibliometric and systematic literature reviews. Analysis of 88 articles retrieved from the Web of Science (WoS) mapped the research trajectory, identifying key authors, journals and research themes. Findings revealed a growing interest in GE research, with a discernible shift toward six themes. The themes were drivers and motivators, pro-environmental behaviours (PEB) and practices, business models and strategies, entrepreneurial intentions and orientation and the crucial role of innovation and technology. Thus, we identified key gaps, with suggestions for future research directions. These included exploring the interplay between technology and green entrepreneurial activity, the impact of enabling policy frameworks and the influence of consumer behaviour driving green entrepreneurial activity. This study contributes to a more nuanced understanding of the GE field, providing a strategic roadmap for future research endeavours.
People with attachment anxiety frequently experience problems in social relationships and tend to form a strong attachment toward material objects as a substitute for their interpersonal insecurities. However, the underlying mechanism linking attachment anxiety with material values is not well-defined. We propose that anxiously attached people are more prone to avoid thoughts, feelings, and experiences, thereby leading to greater material values. In three correlational studies and a preregistered experiment conducted across Russian, Turkish, Polish, and U.S. samples (N = 1,397), we investigated whether experiential avoidance mediates the link between attachment anxiety and material values. The indirect effect of attachment anxiety on material values through experiential avoidance was consistently significant across all studies. In Study 4, we also demonstrated that inducing attachment anxiety (vs. negative affect) led to a suppression of unwanted experiences, feelings, and thoughts, resulting in more material values. We suggest that interventions focused on secure relationships may enhance anxiously attached individuals’ action strategies, potentially reducing their material values, with implications for the literature on attachment styles and material values as well as broader models of social and clinical psychology.
