Abstract
The transition to the water circular economy (WCE) requires several stakeholders' awareness, articulation, and action involving complex governance concerns. As a participatory approach to identifying problems, designing solutions, and implementing strategic actions, the co-creation process should support stakeholder involvement to adjust existing institutional arrangements to foster the WCE. This article designs and applies a co-creation process to analyse the perception of key stakeholders about institutional challenges for water reuse and explore their contributions to innovate policy, planning, and governance for the implementation of new water reuse technology in Almendralejo (Spain), Lecce (Italy), Omis (Croatia), and Eilat (Israel). The findings indicate that implementing a new water loop encounters complex institutional and production-related obstacles, which different stakeholders address in varying ways. Moreover, the proposed solutions to the on-site issues identified emphasise the need for actions that foster engagement and collaboration, particularly to enhance awareness, training, and regulation. Addressing these challenges associated with adopting new water loops, even when technical, may depend on non-technical solutions regarding the institutional framework. The co-creation processes highlight the importance of focusing on institutional arrangements and stakeholder awareness while implementing new water loops to ensure and promote symbiotic territories that consider the policy, producers', and users' strategies.

Abstract
Neonatal seizures represent a critical medical issue that requires prompt diagnosis and treatment. Typically, at-risk newborns undergo a Magnetic Resonance Imaging (MRI) brain assessment followed by continuous seizure monitoring using multichannel EEG. Visual analysis of multichannel electroencephalogram (EEG) recordings remains the standard modality for seizure detection; however, it is limited by fatigue and delayed seizure identification. Advances in machine and deep learning have led to the development of powerful neonatal seizure detection algorithms that may help address these limitations. Nevertheless, their performance remains relatively low and often disregards the non-stationary attributes of EEG signals, especially when learned from weakly labeled EEG data. In this context, the present paper proposes a novel deep-learning approach for neonatal seizure detection. The method employs rigorous preprocessing to reduce noise and artifacts, along with a recently developed time-frequency distribution (TFD) derived from a separable compact support kernel to capture the fast spectral changes associated with neonatal seizures. The high-resolution TFD diagrams are then converted into RGB images and used as inputs to a pre-trained ResNet-18 model. This is followed by the training of an attention-based multiple-instance learning (MIL) mechanism. The purpose is to perform a spatial time-frequency analysis that can highlight which channels exhibit seizure activity, thereby reducing the time required for secondary evaluation by a doctor. Additionally, per-instance learning (PIL) is performed to further validate the robustness of our TFD and methodology. Tested on the Helsinki public dataset, the PIL model achieved an area under the curve (AUC) of 96.8%, while the MIL model attained an average AUC of 94.1%, surpassing similar attention-based methods.

Abstract
In recent years, Positive Energy Districts (PEDs) have been interpreted in many—and often conflicting—ways. We recast PEDs as a vehicle for verifiable climate neutrality and present a declaration-ready assessment that integrates (i) a cumulative, science-based GHG budget per m2 gross floor area (GFA), (ii) full life-cycle accounting, and (iii) time-resolved conversion factors that include everyday motorized individual mobility and quantify flexibility. Two KPIs anchor the framework: the cumulative GHG LCA balance (2025–2075) against a maximum compliant budget of 320 kgCO2e·m-2GFA and the annual primary energy balance used to declare PED status with or without mobility. We follow EN 15978 and apply time-resolved emission factors that decline to zero by 2050. Its applicability is demonstrated on six Austrian districts spanning new builds and renovations, diverse energy systems, densities, and mobility contexts. The baseline scenarios show heterogeneous outcomes—only two out of six meet both the cumulative GHG budget and the positive primary energy balance—but design iterations indicate that all six districts can reach the targets with realistic, ambitious packages (e.g., high energy efficiency and flexibility, local renewables, ecological building materials, BESS/V2G, and mobility electrification). Hourly emission factors and flexibility signals can lower import-weighted emission intensity versus monthly or annual factors by up to 15% and reveal seasonal import–export asymmetries. Built on transparent, auditable rules and open tooling, this framework both diagnoses performance gaps and maps credible pathways to compliance—steering PED design away from project-specific targets toward verifiable climate neutrality. It now serves as the basis for the national labeling/declaration scheme klimaaktiv “Climate-Neutral Positive Energy Districts”.

Abstract

Abstract
In the coming years, a wide range of underwater applications, including resource mining, marine research, and military operations will play an increasingly important role. The Internet of Underwater Things (IoUT) extends IoT principles to underwater environments, enabling connectivity between underwater devices and the Internet. However, high latency, intermittent connectivity, and security risks, such as privacy breaches, data tampering, and unauthorized access, pose major challenges to IoUT adoption. Existing security mechanisms fail in Delay-Tolerant Networks (DTNs) due to their reliance on centralized trust models. Blockchain provides a decentralized, immutable, and transparent solution for securing underwater communications. This paper introduces the Blockchain-Based Underwater Messaging System (BUMS), an innovative solution that ensures message integrity, confidentiality, and resilience in DTNs. Messages are immutably stored in blockchain blocks, while malicious nodes are autonomously detected and excluded without the need for a central authority. To evaluate its feasibility, we developed the Underwater Blockchain Simulator (UBS), a custom-tailored open-source simulator designed to test blockchain algorithms in underwater networks. Simulation results demonstrate that BUMS enhances security and network reliability while maintaining efficiency in high-latency underwater environments, making it a viable solution for secure IoUT-based communications.

Abstract
Road safety is a global issue, with road-related accidents being one of the biggest leading causes of death. Motorcyclists are especially susceptible to injuries and death when there is an accident, due to the inherent characteristics of motorcycles. Accident prevention is paramount. To improve motorcycle safety, this paper discusses and proposes a preliminary architecture of a system composed of various sensors, to assist and warn the rider of potentially dangerous situations such as front and back collision warnings, pedestrian collision warnings, and road monitoring.