Publications

European forests  play a crucial role in  climate change mitigation and biodiversity conservation, though they are continuously adapting to rapid and continuous variations in environmental conditions. Ensuring their health and resilience requires timely detection of changes in forest status, functioning, and provided ecosystem services. However, accurate predictions of their future ecological, economic and social contributions depend on a well-coordinated approach that brings together ground-based forest inventory and monitoring networks, community science, and key stakeholders. 

A new paper published by Guerrieri and colleagues from the CLEANFOREST Cost Action core group highlights the urgent need for stronger synergies among these players. The authors advocate for a new era of forest monitoring and inventorying, where networks collaborate and coordinate their efforts to systematically track and assess the state and long-term changes of European forests. This can be achieved with the creation of an ‘alliance’ of forest monitoring and inventorying programs, which should fall under the auspices of international political bodies. The alliance could serve as the pan-European research infrastructure that centralizes discussion on protocols for data collections and data harmonization, priority needs for current and future monitoring and accessibility to the data from relevant end users, thus strengthening the European forest monitoring system.. The alliance is timely and essential to support the proposed EU Forest Monitoring Law, as well as other relevant European policy targets.

This Perspective paper is the result of debate during and after the panel discussion on ‘Building a common vision on forest monitoring amid global change: challenges and opportunities’ during the first annual meeting of the CLEANFOREST COST Action in Thessaloniki in 2023.

Plants, People, Planet is a multi-disciplinary Open Access journal, owned by the New Phytologist Foundation and published by Wiley. The journal publishes outstanding plant-based research in its broadest sense and celebrates everything new, innovative and exciting in plant-focused research that is relevant to society and people’s daily lives. The New Phytologist Foundation is an independent, not-for-profit organisation dedicated to the promotion of plant science.

In the past decade, metal-organic frameworks (MOFs) have been extensively researched for biomedical applications, particularly drug storage, after proving to be excellent substitutes for traditional porous materials. Biomedical applications of MOFs have been greatly expedited with the recent integration of data science and molecular modelling approaches to experimental research, establishing them as essential elements in medical imaging, diagnostics, and regenerative medicine. In this review, to demonstrate the potential of MOFs in cutting-edge treatments for neurological and cancer diseases, we examined the molecular interactions between MOFs and biological systems and discussed the field’s opportunities and challenges.

The Internet of Things (IoT) is transforming industries with its plethora of applications, from smart cities to healthcare. However, this rapid proliferation comes with a pressing need for additional cybersecurity needs to ensure stable and resilient operations. Resource-constrained IoT devices often rely on basic cryptographic mechanisms, allowing innovative solutions like Radio Frequency Fingerprinting (RFF) to thrive and enhance physical layer security. As part of European Union COST Action, this study dives into the current state-of-the-art in RFF, a technique that utilizes unique hardware characteristics for device authentication and classification.  Key Takeaways:  Challenges in Real-World Deployment: While RFF has shown promise in academic settings, its practical applications are limited by technological barriers.   There is a burgeoning need to deliberate the potential CONOPS (concept of operation) and operational scenarios encountered in real world deployment. The research sheds light on critical performance metrics and the complexities of evaluating RFF systems.  By addressing these challenges, the study lays a foundation for advancing RFF from theory and controlled environment to practical implementation, enabling its integration into secure IoT ecosystems.  By connecting this work to the COST action, we aim to foster collaboration across Europe to develop cutting-edge security solutions for networks of the future.

We developed a lightweight 1D Convolutional Neural Network (CNN) model optimized for edge devices, reducing inference latency while maintaining high classification accuracy. Using an open-source dataset of 30 LoRa devices, we evaluated preprocessing methods (Short Time Fourier Transform (STFT) and Fast Fourier Transform (FFT)). Our approach demonstrated: A significant reduction in inference latency, making deployment on real-time edge devices feasible. Comparable classification accuracy when benchmarked against a 2D CNN model. This work not only bridges a crucial gap in the literature but also propels the adoption of RFF for edge devices—an essential step for secure IoT networks in 6G. By aligning this effort with COST Action, we aim to foster collaboration across Europe to achieve secure, resilient, and trustworthy 6G systems.

This review highlights recent advancements in combining metal–organic frameworks (MOFs) with carbohydrate chemistry to create biocompatible systems for biomedical applications. MOFs offer unique properties like biodegradability, low toxicity, and high surface area, enabling functionalization with biological ligands and  the loading of active cargos, from small drugs to biomacromolecules. Recent research focuses on leveraging carbohydrate chemistry to functionalize and modify MOF structures, aiming for efficient and naturally inspired designs. The review discusses the field’s progress over the past five years, addressing both its potential and challenges, including sustainability and real-world applicability.

A sustainable and eco-friendly ligand for diverse nanoparticles functionalization is reported. The ligand is synthesized through a photochemical reaction between lecithin and cysteine, followed by the addition of mannose, a sugar beneficial for biomedical targeting. The environmental impact of the ligand is assessed through green metrics, demonstrating superior sustainability compared to conventional ligands. The ligand is successfully applied to various nanoparticle platforms, including the MOFs MIL-101(Fe), PCN-222, UiO-66, and iron nanoparticles, highlighting its potential for safer and more effective applications in nanomedicine.

The significant increase in the number of IoT devices has also brought with it various security concerns. The ability of these devices to collect a lot of data, including personal information, is one of the important reasons for these concerns. The integration of machine learning into systems that can detect security vulnerabilities has been presented as an effective solution in the face of these concerns. In this review, it is aimed to examine the machine learning algorithms used in the current studies in the literature for IoT network security. Based on the authors’ previous research in physical layer security, this research also aims to investigate the intersecting lines between upper layers of security and physical layer security. To achieve this, the current state of the area is presented. Then, relevant studies are examined to identify the key challenges and research directions as an initial overview within the authors’ ongoing project.

Scientists have known about microplastics in nature since the 1970s, but lately they are finding these tiny plastics almost everywhere they look – in the air, lakes, rivers, oceans, on land, and even in remote places like Arctic lakes and snow! This article will introduce young audiences to the hidden universe of microplastics, the tools scientists use to analyse them, and how people can do their own experiments to analyse microplastics from a nearby beach.

With their variable active sites Metal–organic frameworks (MOFs) can achieve visible-light absorption and efficient charge separation for photocatalytic, and conductivity for electrocatalytic  CO₂   reduction into value added chemicals. This work illustrates the importance of porous carbon fiber layers (CFLs) on the activity and selectivity of MOF based  photocathodes towards the CO₂ reduction reaction (CO₂RR) in a zero-gap gas phase photoelectrolyzer. The wettability of the CFL modulates the local environment on the metal organic framework catalyst (UiO-66-NH₂, yellow coloured). Hydrophobic CFL-based MOF photocathodes lead to CO₂RR, producing liquid hydrocarbons ( CxHyOz) such as formate, methanol and ethanol. In contrast, hydrophilic, wetted CFL-based photocathodes favor the Hydrogen Evolution Reaction (HER).The results are a step further in understanding how the design and composition of the photoelectrodes in photoelectrochemical electrolyzers can impact the  CO₂  reduction efficiency and selectivity.