The exploitation of the metagenome for novel biocatalysts by functional screening is determined by the ability to express the respective genes in a surrogate host. The probability of recovering a certain gene thereby depends on its abundance in the environmental DNA used for library construction, the chosen insert size, the length of the target gene, and the presence of expression signals that are functional in the host organism. In this paper, we present a set of formulas that describe the chance of isolating a gene by random expression cloning, taking into account the three different modes of heterologous gene expression: independent expression, expression as a transcriptional fusion and expression as a translational fusion. Genes of the last category are shown to be virtually inaccessible by shotgun cloning because of the low frequency of functional constructs. To evaluate which part of the metagenome might in this way evade exploitation, 32 complete genome sequences of prokaryotic organisms were analysed for the presence of expression signals functional in E. coli hosts, using bioinformatics tools. Our study reveals significant differences in the predicted expression modes between distinct taxonomic groups of organisms and suggests that about 40% of the enzymatic activities may be readily recovered by random cloning in E. coli.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
The Dutch Environmental Vision and Mobility Vision 2050 promote climate-neutral urban growth around public transport stations, envisioning them as vibrant hubs for mobility, community, and economy. However, redevelopment often increases construction, a major CO₂ contributor. Dutch practice-led projects like 'Carbon Based Urbanism', 'MooiNL - Practical guide to urban node development', and 'Paris Proof Stations' explore integrating spatial and environmental requirements through design. Design Professionals seek collaborative methods and tools to better understand how can carbon knowledge and skills be effectively integrated into station area development projects, in architecture and urban design approaches. Redeveloping mobility hubs requires multi-stakeholder negotiations involving city planners, developers, and railway managers. Designers act as facilitators of the process, enabling urban and decarbonization transitions. CARB-HUB explores how co-creation methods can help spatial design processes balance mobility, attractiveness, and carbon neutrality across multiple stakeholders. The key outputs are: 1- Serious Game for Co-Creation, which introduces an assessment method for evaluating the potential of station locations, referred to as the 4P value framework. 2-Design Toolkit for Decarbonization, featuring a set of Key Performance Indicators (KPIs) to guide sustainable development. 3- Research Bid for the DUT–Driving Urban Transitions Program, focusing on the 15-minute City Transition Pathway. 4- Collaborative Network dedicated to promoting a low-carbon design approach. The 4P value framework offers a comprehensive method for assessing the redevelopment potential of station areas, focusing on four key dimensions: People, which considers user experience and accessibility; Position, which examines the station's role within the broader transport network; Place-making, which looks at how well the station integrates into its surrounding urban environment; and Planet, which addresses decarbonization and climate adaptation. CARB-HUB uses real cases of Dutch stations in transition as testbeds. By translating abstract environmental goals into tangible spatial solutions, CARB-HUB enables scenario-based planning, engaging designers, policymakers, infrastructure managers, and environmental advocates.
The CARTS (Collaborative Aerial Robotic Team for Safety and Security) project aims to improve autonomous firefighting operations through an collaborative drone system. The system combines a sensing drone optimized for patrolling and fire detection with an action drone equipped for fire suppression. While current urban safety operations rely on manually operated drones that face significant limitations in speed, accessibility, and coordination, CARTS addresses these challenges by creating a system that enhances operational efficiency through minimal human intervention, while building on previous research with the IFFS drone project. This feasibility study focuses on developing effective coordination between the sensing and action drones, implementing fire detection and localization algorithms, and establishing parameters for autonomous flight planning. Through this innovative collaborative drone approach, we aim to significantly improve both fire detection and suppression capabilities. A critical aspect of the project involves ensuring reliable and safe operation under various environmental conditions. This feasibility study aims to explore the potential of a sensing drone with detection capabilities while investigating coordination mechanisms between the sensing and action drones. We will examine autonomous flight planning approaches and test initial prototypes in controlled environments to assess technical feasibility and safety considerations. If successful, this exploratory work will provide valuable insights for future research into autonomous collaborative drone systems, currently focused on firefighting. This could lead to larger follow-up projects expanding the concept to other safety and security applications.
