Abstract
Recent research on online censorship has provided valuable insights into common censorship strategies and censors' tolerance for collateral damage. A consistent finding across these studies is that censors tend to favour cost-effective techniques such as proxy enumeration, active probing, and deep packet inspection (DPI), rather than more complex and non-deterministic methods such as deep learning-based traffic analysis. For example, a recent study on the Snowflake censorship evasion system reinforced this finding by demonstrating that authoritarian regimes primarily relied on DPI to target the system. However, as censorship techniques continue to evolve, two critical questions arise: (1) What future attack vectors are likely to emerge based on current research and observed censor capabilities? (2) How can these emerging threats, along with previously utilised censorship methods, be effectively mitigated? In this paper, we present Obscura, a censorship evasion system designed to resist cost-effective, historically grounded censorship techniques while also defending against a class of plausible future attacks within a cost-effective threat model targeting WebRTC-based censorship evasion systems. Obscura is built upon four core features: (1) encapsulation of traffic within WebRTC media streams, (2) the use of a reliability layer, (3) support for both browser-based and Pion-based clients and proxy instances, and (4) the use of ephemeral proxies. Each feature is intended to mitigate either a known attack observed in the wild or a theoretically plausible attack consistent with the capabilities of a cost-effective censor. We provide a security analysis to justify our design choices and a performance evaluation to demonstrate that Obscura maintains reasonable throughput for typical online activities.

Abstract
Circular Economy is based on implementation of R-strategies to narrow or close the loop of material flows and to minimize raw material consumption by extending the life cycle of materials. Since this approach is expanding from individual organizational actions to a collaborative approach, the objective of this paper is to analyse the role of digital technologies such as AI and cloud platforms in facilitating and changing the collaboration between stakeholders to improve sustainability. This study adopts a qualitative multi case study methodology, using surveys, interviews and document analysis from 10 new ventures in the agri-food ecosystem supported by the cascade funding programme. The results show that collaboration among actors is changed by the different technologies and strategic drivers of circular economy in the considered ecosystem.

Abstract
DIn the digital transformation of industrial sectors, data is a high-value business asset. How companies manage data between systems within the organization or through networks of business partners impacts their competitive factor. Technological maturity may imply several adversities, such as the lack of interoperability standards for simple and transparent data exchange. This paper presents an architecture that enables secure exchanges of supply chain orders between textile and clothing companies. This architecture is based on Electronic Business (eBIZ) 4.0 and International Data Spaces (IDS) frameworks, fostering trust and widespread adoption of platforms in the industry sector, particularly when handling sensitive supply chain information. The architecture was implemented and validated in 3 use cases with Enterprise Resource Plannings (ERPs) from the same vendor, different vendors, and communication from a ERP to a Web portal. Implementing the proposed architecture impacted efficiency, transparency, and accountability within the supply chain network. The lead times for purchases, provisioning, and the number of additional information requests in the ordering were reduced. In subcontracting, a reduction in non-conformities and an overall improvement in delivery times were verified. Moreover, logistics operations and communication with subcontractors were optimized, leading to faster order reception and reducing informal contacts.

Abstract
This study investigates the antifragility of organizations, especially in strategic sectors highly exposed to disruptive events. Based on a qualitative approach with case studies in the wine and textile sectors in Portugal, the findings indicate that financial and market strength, as resilience capabilities, operate interdependently and are reinforced by digital maturity and supply chain integration. Companies with financial robustness and strong market intelligence tend to be more agile in strategically investing and reallocating resources during crises. The research adopts an expanded definition of antifragility, which incorporates resilience, innovation, and strategic reconfiguration in the face of disruptions. It concludes that organizational antifragility results from the articulation of financial resources, market intelligence, and digital collaboration, offering a sustainable competitive advantage in the face of uncertainty. The study contributes to theoretical debates and provides practical recommendations for managers and policymakers.

Abstract
[No abstract available]

Abstract
The decoupling of temperature and refractive index measurements was achieved by exploiting the properties of the asymmetric spectrum generated by Fano resonance, resulting from the interference between the Bragg reflection of the grating and the Fresnel reflection at the fiber tip. This spectral asymmetry enabled the implementation of a combined wavelength-based and intensity-based interrogation scheme. By separating the influence of each parameter in the spectral response, it was possible to measure the refractive index independently, without interference from temperature variations. A refractive index sensor with a minimum detectable change of delta = 1.2 & times; 10(-4) RIU was demonstrated. In addition to introducing a novel structure that leverages Fano resonance, the sensor was also applied as an evaporation rate sensor. The results demonstrate its potential for a wide range of applications, serving as a foundation for the development of future optical sensing technologies.