The transition process from fossil fuels to environmentally friendly renewable energy sources carries the risk of creating new environmental damages. Photovoltaic technology represents one of the alternatives with the least risk of harmful environmental impact. However, this technology has two important drawbacks: the significant land occupation for the installation of PV systems and the uncontrollability of production. By constructing floating photovoltaic plants on hydroelectric reservoirs, both of these problems can be reduced to an acceptable level. Some artificial reservoirs, originally built for hydroelectric power plants, have acquired a significant secondary function as recreational areas and fish breeding sites. Therefore, there is justified resistance from the local community to change the existing appearance and purpose of such reservoirs. This paper proposes a completely new concept of integrating the interests of the local community into such objects. In addition to preserving existing uses, the concept also offers new features. This can make the entire system environmentally friendly and sustainable. This paper details the technology behind the construction of floating photovoltaic power plants on artificial reservoirs and emphasizes their various advantages. These benefits include the non-utilization of cultivable land, the ease of assembly and construction, integration into existing power grids, and the potential to address electricity storage issues. For instance, Buško Lake, covering an area of 55.8 km2, may host 2.93 km2 of installed floating photovoltaic (FPV) facilities, enabling a total installed capacity of 240 MW. With an average of 5.5 h of daily sunshine, this totals 2007 annual hours, equivalent to a 55 MW thermal power plant. An analysis showed that, with losses of 18.2%, the average annual production stands at 302 GWh, translating to an annual production value of 18 million € at 60 €/MWh. The integration of this production into an existing hydroelectric power plant featuring an artificial reservoir might boost its output by 91%. The available transmission line capacity of 237 MW is shared between the hydroelectric power plant (HPP) and FPV; hence during the FPV maximum power generation time, the HPP halts its production. HPP Orlovac operates a small number of hours annually at full capacity (1489 h); therefore in combination with the FPV, this number can be increased to 2852 h. This integration maintains the lake’s functions in tourism and fishing while expanding its capabilities without environmental harm.

Significance S-layer proteins (SLPs) are self-assembling, crystalline proteins coating the cell surfaces of many prokaryotes. This study presents experimental atomic resolution structures of lactobacilli SLPs, deriving functional insight into key probiotic Lactobacillus strains. The structures of SlpA and SlpX proteins highlight the domain swapping critical for SlpX integration, particularly in response to environmental stress. Two binding regions are identified as crucial for attachment of the S-layer to (lipo)teichoic acid. The structure of assembled S-layer provides a foundation for employing (designed) SLPs as a therapeutic agent in the treatment of inflammatory diseases. Additionally, it opens broad avenues for the use of SLPs in vaccine development and in crafting nanostructures with tailored properties, including those designed for targeted drug delivery.

Background The optimal anesthetic strategy for endovascular therapy (EVT) in acute ischemic stroke is still under debate. The aim of this study was to compare the clinical outcomes of patients with isolated posterior cerebral artery (PCA) occlusion stroke undergoing EVT by anesthesia modality with conscious sedation (non-GA) versus general anesthesia (GA). Methods Patients from the Posterior CerebraL Artery Occlusion (PLATO) study were analyzed with regard to anesthetic strategy. GA was compared with non-GA using multivariable logistic regression and inverse probability of weighting treatment (IPTW) methods. The primary endpoint was the 90-day distribution of the modified Rankin Scale (mRS) score. Secondary outcomes included functional independence or return to Rankin at day 90, and successful reperfusion, defined as expanded Thrombolysis in Cerebral Infarction (eTICI) 2b to 3. Safety endpoints were symptomatic intracranial hemorrhage and mortality. Results Among 376 patients with isolated PCA occlusion stroke treated with EVT, 183 (49%) had GA. The treatment groups were comparable, although the GA group contained more patients with severe stroke and lower posterior circulation Alberta Stroke Program Early CT Score (pc-ASPECTS). On IPTW analysis, there was no difference between groups with regard to ordinal mRS shift analysis (common OR 0.89, 95% CI 0.53 to 1.51, P=0.67) or functional independence (OR 0.84, 95% CI 0.50 to 1.39, P=0.49). There were greater odds for successful reperfusion with GA (OR 1.70, 95% CI 1.17 to 2.47, P=0.01). Safety outcomes were comparable between groups. Conclusion In patients with isolated PCA occlusion undergoing EVT, patients treated with GA had higher reperfusion rates compared with non-GA. Both GA and non-GA strategies were safe and functional outcomes were similar.

In our recent attempt to explain flavor hierarchies [1], a gauged SU(2) flavor symmetry acting on left-handed fermions provides a ground to introduce three independent rank-one contributions to the Yukawa matrices: a renormalizable one for the third family, a mass-suppressed one for the second family, and an additional loop-suppressed factor for the first family. Here, we demonstrate how minimal quark-lepton unification à la Pati-Salam, relating down-quarks to charged leptons, can significantly improve this mechanism. We construct and thoroughly analyze a renormalizable model, performing a comprehensive one-loop matching calculation that reveals how all flavor hierarchies emerge from a single ratio of two scales. The first signatures may appear in the upcoming charged lepton flavor violation experiments.

The Lithium-Ion battery at the end of life represents a valuable source of secondary raw materials such as lithium, nickel, cobalt etc. Deep discharging, as a part of battery recycling, is a time-consuming process in which the battery's thermal dependency on the discharge parameters and voltage recovery effect is manifested. Adjusting the discharging process adequately to address those two phenomena leads to a safety increase and discharging time decrease. This paper treats two aspects. It is observed the effect of the constant and variable discharging current along with the depth of the discharge in the form of discharge end voltage parameter on the maximal cell temperature reached during the process. The second aspect is the battery recovery voltage trend after the discharging process and its dependency on the same parameters. The impact of these parameters is demonstrated experimentally on two battery cell types.

Network slicing enables multiple virtual networks to share physical resources, allowing network operators to deliver highly customizable and efficient networking solutions that meet the diverse requirements of modern applications. The automated management of network slices has been studied in the last years to make such solutions more flexible, ready to support new applications, and capable of optimizing network resource utilization. Many works in the literature give a top-down approach, focusing on the high-level decision processes, and relying on abstracted infrastructure managers and simulation tools to apply/execute such decisions. In this work, we leverage components that we previously developed for network monitoring, flexible traffic shaping, and Software-Defined Time-Sensitive Networking control, to create a bottom-up approach toward automated slice management. We describe the intricate coordination of elements required for an automated control loop and present the results achieved with a proof-of-concept executed in a real testbed of wired and Wi-Fi nodes. The results show the capability of the system to correctly identify the bottleneck of a flow and apply corrective actions to reestablish its intended performance level.

Intent-driven network management has become an important part of autonomous systems in Beyond 5G (B5G) towards Sixth-Generation (6G) networks, by enabling flexibility in the interaction among applications, operators and users. Intents play an important role in the communication of road users like autonomous vehicles and pedestrians to edge computing services. As sensor technologies for modern vehicles are cheaper, smaller, diverse and computing capable, more demand for applications and services on the road is increasing. A flexible intent interpretation and coordination are needed to deal with the dynamic environment and constantly changing goals. This paper presents a proof-of-concept of Zero-touch Network and Service Management (ZSM) for vehicular communication services, using an Intent Management Entity (IME) to translate user objectives into actionable directives. This paper describes a realistic testbed setup at the Smart Highway, where a Deep Reinforcement Learning (DRL) algorithm is used to optimize the selection of Roadside Units (RSUs) for service orchestration. This paper also discusses the challenges and opportunities of enhancing the IME with time-based intent coordination, using Artificial Intelligence and Machine Learning (AI/ML) techniques to estimate the waiting time and priority in intent coordination. The paper aims to demonstrate the benefits of ZSM and Intent-driven Management for vehicular edge computing and B5G/6G autonomous network management frameworks.

The native integration of AI and ML algorithms in the next-generation mobile network architecture will allow for meeting the expectations of 6G. This aspect is targeted by the DAEMON project, which proposed a solution to natively manage Network Intelligence (NI) through novel architectural elements and procedures. In this paper, we discuss how NI solutions based on AI and ML can leverage NI native procedures implemented by the NI Orchestrator to improve their lifecycle management. We also discuss how the architectural procedures can be implemented in practice, using state-of-the-art software components.

The challenge of ensuring safety in autonomous driving or sailing involves predicting and replicating various potential scenarios on roads and waterways, posing difficulties and high costs. In response, the European project 5G-Blueprint addresses this by introducing a complementary technology, i.e., teleoperation, which leverages 5G connectivity to enable human interventions in complex situations beyond autonomous capabilities, thereby removing the physical link between the human operator and the remotely controlled vehicle/vessel. This operational mode brings stringent connectivity requirements, including high uplink bandwidth for transmitting video streams from onboard cameras to the teleoperation center, low latency, and an ultra-reliable connection for relaying commands from the teleoperator to the remote vehicle/vessel. Additionally, it emphasizes minimal interruption time when the teleoperated vehicle/vessel crosses international borders, ensuring seamless connectivity and uninterrupted remote operation. Therefore, this paper summarizes extensive evaluations of network and service performance, highlighting key results across pilot locations and providing conclusions and analysis of 5G-enhanced teleoperation in various use cases. Additionally, it outlines lessons learned from pilot activities.

The Transport and Logistics (T&L) sector faces numerous challenges, including the search for qualified personnel, as well as improving driver safety and work-life balance. Teleoperation emerges as the technology able to address these challenges. Thanks to 5G connectivity and network slicing, operating vehicles remotely from a Teleoperation Center (ToC) is becoming a reality. The European project 5G-Blueprint, funded by the European Union, has demonstrated the feasibility of 5G-based teleoperation, even in a cross-border context. Despite the fact that 5G and network slicing enable reliable and low-latency transmission of video data from cameras installed on Teleoperated Vehicles (ToVs) to ToC, the perception of the surrounding environment is different for the teleoperator compared to the driver who is physically present in the vehicle. In this paper, we introduce a real-world system that showcases synergy among different teleoperation elements, including intelligent traffic lights (iTL) and Vulnerable Road Users (VRU), aimed at supporting teleoperation by improving remote driver’s situational awareness. This synergy enhances the environmental perception of the teleoperator, bridging the gap between their experience and that of an in-vehicle driver. First, we evaluate the performance of a real-world 5G network with network slicing, based on actual data and testing scenarios conducted in both industrial and urban areas with 5G Standalone (5G SA) coverage. Then we validate the 5G capabilities for enabling a real-world system that showcases synergy among different teleoperation elements.

The International Transport Forum (ITF) predicts a significant increase in demand for transportation in the coming years, despite the shortage of drivers. To tackle this challenge, the Transport and Logistics (T&L) industry is increasingly relying on emerging technologies. While connected and autonomous driving offer promises of greater safety, efficiency, and environmental benefits, connected and autonomous driving face operational hurdles in complex environments. However, the existing limitations of autonomous vehicles, particularly in dense urban settings, highlight the need for complementary technologies, such as teleoperation. The European Horizon 2020 5G-Blueprint project aims to design and validate the technical architecture and business models for cross-border teleoperated transport, utilizing 5G technology. This study delves into the implementation of a real 5G Standalone (5G SA) network within a port environment, utilizing network slicing for teleoperation and Multi-Access Edge Computing (MEC) to enable real-time video processing at the network edge. Specifically focusing on Ultra-Reliable Low Latency Communications (URLLC) and enhanced Mobile Broadband (eMBB) slices, we conduct a comprehensive evaluation of a real-world 5G SA network. Our assessment examines key performance parameters such as Round-Trip Time(RTT) latency, Packet Delivery Rate (PDR), Reference Signals Received Power (RSRP), and corrupted frame rates, emphasizing the crucial role of 5G network slicing and MEC in enhancing operational reliability and efficiency in teleoperated transport systems.

This study offers experimental testing of commercial and laboratory inverters, utilized in a laboratory prototype of an urban microgrid. Operation of grid inverters supplied by PV arrays in urban environments, encounters challenges such as partial shading and soiling. Emulation of the current-voltage characteristics of PV arrays enables repeated and reliable testing of inverter operation under irregular supply conditions. It has been shown that finding the maximum power point can be challenging under conditions of partial shading and soiling. Additionally, meeting the grid quality standards for the delivered power represents a challenge. Satisfying these requirements can be achieved through careful design of LCL filters at inverter output terminals, but further improvement can be achieved only through an adequate selection of the primary controller. To further improve the quality of grid currents, the possibility of applying innovative control algorithms has been demonstrated for laboratory inverters. Application of sliding mode controllers, besides ensuring system robustness, can prevent overshoots and fault responses from the current protection circuit by introducing a specific anti-windup structure.

A generation of orthogonal signals in single-phase systems, crucial for various applications such as power converters synchronization, faces challenges in handling disturbances like DC offset and low order harmonics present in power grids. This paper presents an orthogonal signal generator based on the principles of adaptive noise canceller, offering immunity to low order harmonics and DC offset. By leveraging adaptive techniques, this novel generator surpasses traditional approaches, which lack disturbance rejection capabilities. Simulation results in MATLAB validate the performance and robustness of the proposed generator, marking a significant advancement in generating orthogonal signals for single-phase systems.

Building integrated microgrids and building integrated photovoltaic systems (BIPV) are emerging as a promising avenue for seamlessly integrating small scale renewable energy sources (RES) into the grid. Challenges arise as new ideas are being explored and implemented in this area, and one of them is maximizing self-consumption and self-sufficiency, for any energy policy, but especially while adhering to zero energy export (ZEE) policy restrictions. As a solution to enhance the utilization of BIPV system this paper proposes a load management (LM) technique. By combining on-grid photovoltaic (PV) system with controllable loads, this paper demonstrates how proactive LM can increase self-consumption and self-sufficiency factors, as well as mitigate PV produced energy dumping due to ZEE restrictions. A case study in the wood sector's industrial building illustrates the efficiency of this approach, showcasing reduced reliance on grid power during sunny periods and increased self-sufficiency through strategic load scheduling. Real-world data analysis validates the effectiveness of LM in aligning PV generation with building energy demands, offering insights into its potential for broader adoption in the renewable energy sector.