Widespread adoption of occupational exoskeletons (OEX) depends on various human and environmental factors. This systematic review aimed to provide an overview of facilitators and barriers influencing OEX implementation, according to users and interest holders. A systematic search of PubMed and EMBASE identified 28 studies on active or passive OEX and opinions on acceptance or rejection during implementation. Facilitators were reported slightly more often than barriers (128 times vs. 110 times), with 70 facilitators and 67 barriers identified. Barriers were most frequently associated with the Device domain (36.4
Ransomware is a cybersecurity threat that holds organizations' data hostage until a ransom is paid. Past research has mainly focused on the technical aspects of prevention or the ransom payment when an attack occurs. Little attention has been devoted to the strategies of organizations that lead to this payment. In this study, we analyze 41 authentic chat logs from 16 private and 25 open-source ransomware incidents, focusing on the phases of ransomware negotiations and the influence strategies employed by both threat actors and victims. The analysis identifies three distinct phases in ransomware negotiations: the proof-of-life phase, the bargaining phase, and the support phase. Across these stages, threat actors predominantly use being credible and direct pressure, while victims rely on rational persuasion and kindness to secure favorable terms. Both parties adapt their strategies as the negotiation progresses and phases change, moving from establishing what data is stolen to exchanging offers about the ransom amount. This analysis was complemented by a qualitative exploration of how these strategies manifest in ransomware negotiations. This paper provides key insights into the dynamics between threat actors and victim companies by outlining negotiation strategies and stages. Understanding these dynamics better prepares decision-makers and cybersecurity experts for the negotiation communication process with the threat actors following ransomware attacks.
This work is concerned with the limiting spectral distribution of rank-based dependency measures in high dimensions. We provide distribution-free results for multivariate empirical versions of Kendall's τ and Spearman's ρ in a setting where the dimension p grows at most proportionally to the sample size n. Although rank-based measures are known to be well suited for discrete and heavy-tailed data, previous works in the field focused mostly on the continuous and light-tailed case. We close this gap by imposing mild assumptions and allowing for general types of distributions. Interestingly, our analysis reveals that a non-trivial adjustment of classical Kendall's τ is needed to obtain a pivotal limiting distribution in the presence of tied data. The proof for Spearman's ρ is facilitated by a result regarding the limiting eigenvalue distribution of a general class of random matrices with rows on the Euclidean unit sphere, which is of independent interest. For instance, this finding can be used to derive the limiting spectral distribution of sample correlation matrices, which, in contrast to most existing works, accommodates heavy-tailed data.
Face-voice association in multilingual environment challenge 2026 aims to investigate the face-voice association task in multilingual scenario. The challenge introduces English-German face-voice pairs to be utilized in the evaluation phase. To this end, we revisit the fusion and orthogonal projection for face-voice association by effectively focusing on the relevant semantic information within the two modalities. Our method performs favorably on the English-German data split and ranked 3rd in the FAME 2026 challenge by achieving the EER of 33.1.
In this review, we introduce granular materials as a condensed matter system and briefly discuss their general properties. We then focus on particle segregation in rapid, dense granular flows, a phenomenon that occurs more readily in granular materials than in other condensed matter systems. Our primary emphasis is on the development of continuum models to describe segregation in these systems. Over the years, numerous approaches have been proposed, each offering different perspectives on how to construct such models. Rather than providing an exhaustive review of any single approach, we compare and contrast various modeling strategies, highlighting their commonalities and respective advantages. By doing so, we aim to establish a clearer connection between different approaches, facilitating closer comparisons and potential synergies between them. We believe that bridging these approaches is essential for advancing our understanding and improving predictive capabilities in granular segregation modeling in the future.
