Andre Henriques

Volume 1 of the FCC Feasibility Report presents an overview of the physics case, experimental programme, and detector concepts for the Future Circular Collider (FCC). This volume outlines how FCC would address some of the most profound open questions in particle physics, from precision studies of the Higgs and EW bosons and of the top quark, to the exploration of physics beyond the Standard Model. The report reviews the experimental opportunities offered by the staged implementation of FCC, beginning with an electron-positron collider (FCC-ee), operating at several centre-of-mass energies, followed by a hadron collider (FCC-hh). Benchmark examples are given of the expected physics performance, in terms of precision and sensitivity to new phenomena, of each collider stage. Detector requirements and conceptual designs for FCC-ee experiments are discussed, as are the specific demands that the physics programme imposes on the accelerator in the domains of the calibration of the collision energy, and the interface region between the accelerator and the detector. The report also highlights advances in detector, software and computing technologies, as well as the theoretical tools/reconstruction techniques that will enable the precision measurements and discovery potential of the FCC experimental programme. The content and structure of this report are guided by the scope and priorities defined in the mandate of the FCC Feasibility Study. It is therefore not intended to serve as an exhaustive review of the full physics potential of FCC. Several topics, already covered in earlier reports such as the FCC CDR, are not reiterated here or are addressed only briefly, in alignment with the study’s focus. This volume reflects the outcome of a global collaborative effort involving hundreds of scientists and institutions, aided by a dedicated community-building coordination, and provides a targeted assessment of the scientific opportunities and experimental foundations of the FCC programme.

Background: Public health events of international concern highlight the need for up‐to‐date evidence curated using sustainable processes that are accessible. In development of the Global Repository of Epidemiological Parameters (grEPI) we explore the performance of an agentic‐AI assisted pipeline (GREP‐Agent) for screening evidence which capitalizes on recent advancements in large language models (LLMs). Methods: In this study, the performance of the GREP‐Agent was evaluated on a data set of 2000 citations from a systematic review on measles using four LLMs (GPT4o, GPT4o‐mini, Llama3.1, and Phi4). The GREP‐Agent framework integrates multiple LLMs and human feedback to fine‐tune its performance, optimize workload reduction and accuracy in screening research articles. The impact on performance of each part of this Agentic‐AI system is presented and measured by accuracy, precision, recall, and F1‐score metrics. Results: The results show how each phase of the GREP‐Agent system incrementally improves accuracy regardless of the LLM. We found that GREP‐Agent was able to increase sensitivity across a broad range of open source and proprietary LLMs to 84.2%–88.9% after fine‐tuning and to 86.4%–95.3% by varying workload reduction strategies. Performance was significantly impacted by the clarity of the screening questions and setting thresholds for optimized workload reduction strategies. Conclusions: The GREP‐Agent shows promise in improving the efficiency and effectiveness of evidence synthesis in dynamic public health contexts. Further development and refinement of adaptable human‐in‐the‐loop AI systems for screening literature are essential to support future public health response activities, while maintaining a human‐centric approach.

This study presents an advanced airborne transmission risk assessment model that integrates both short- and long-range routes in the spread of respiratory viruses, building upon the CERN Airborne Model for Indoor Risk Assessment (CAiMIRA) and aligned with the new World Health Organization (WHO) terminology. Thanks to a two-stage exhaled jet approach, the model accurately simulates short-range exposures, thereby improving infection risk predictions across diverse indoor settings. Key findings reveal that in patient wards, the short-range viral dose is 10-fold higher than the long-range component, highlighting the critical role of close proximity interactions. Implementation of FFP2 respirators resulted in a remarkable 13-fold reduction in viral dose, underscoring the effectiveness of personal protective equipment (PPE). Additionally, the model demonstrated that an 8 h exposure in a poorly ventilated office can equate to the risk of a 15 min face-to-face, mask-less interaction, emphasizing the importance of physical distancing and source control. We also found in high-risk or low-occupancy settings, that secondary transmission is driven more by overall epidemic trends than by the presence of individual superspreaders. Monte Carlo simulations across various scenarios, including classrooms and offices, validate the model’s robustness in optimizing infection prevention strategies. These findings support targeted interventions for short- and long-range exposure to reduce airborne transmission.

Systematic Reviews are essential for synthesizing evidence from multiple studies, but the process, particularly the title and abstract screening phase, is time-consuming and labour-intensive. Traditional machine learning methods for automating this phase often fall short of the sensitivity required by Cochrane, which is set at greater than 0.99. This paper introduces a novel 5-tier prompting approach leveraging a foundational Large Language Model to automate the screening process. First, each study is assigned to one of five classes based on its likelihood of meeting predefined inclusion and exclusion criteria. Using a specified threshold, these classifications are then converted into binary decisions. This approach minimizes the risk of excluding relevant papers while automatically excluding the majority of irrelevant ones.Evaluation conducted on 5,643 records from four published systematic reviews resulted in zero wrong excludes when compared to human full-text screening decisions. The executed experiments resulted in a 68% average reduction in human workload, which enables a 50% decrease in the time needed to complete the screening process, all without compromising the accuracy of the results. These findings suggest that the 5-tier prompting approach offers a promising solution for enhancing the efficiency of systematic reviews.

BACKGROUND: Indoor aerosol transmission of SARS-CoV-2 has been widely recognised, especially in schools where children remain in closed indoor spaces and largely unvaccinated. Measures such as strategic natural ventilation and high efficiency particulate air (HEPA) filtration remain poorly implemented and mask mandates are often progressively lifted as vaccination rollout is enhanced. METHODS: We adapted a previously developed aerosol transmission model to study the effect of interventions (natural ventilation, face masks, HEPA filtration and their combinations) on the concentration of virus particles in a classroom of 160 m3 containing one infectious individual. The cumulative dose of viruses absorbed by exposed occupants was calculated. RESULTS: In the absence of interventions, the cumulative dose absorbed was 1.5 times higher in winter than in spring/summer, increasing chances of indoor airborne transmission in winter. However, natural ventilation was more effective in winter, leading to up to a 20-fold decrease in cumulative dose when six windows were fully open at all times. In winter, partly opening two windows all day or fully opening six windows at the end of each class was effective as well (2.7- to 3-fold decrease). In summer, good ventilation levels could be achieved through the opening of windows all day long (2- to 7-fold decrease depending on the number of windows open). Opening windows only during yard and lunch breaks had minimal effect (≤1.5-fold decrease). One HEPA filter was as effective as two windows partly open all day in winter (3-fold decrease) whereas two filters were more effective (5-fold decrease). Surgical face masks were very effective independently of the season (8-fold decrease). Combined interventions (i.e., natural ventilation, masks, and HEPA filtration) were the most effective (≥25-fold decrease) and remained highly effective in the presence of a super-spreader. INTERPRETATION: Natural ventilation, face masks, and HEPA filtration are effective interventions to reduce SARS-CoV-2 aerosol transmission. These measures should be combined and complemented by additional interventions (e.g., physical distancing, hygiene, testing, contact tracing and vaccination) to maximise benefit.

A high-quality, low-cost ventilator, dubbed HEV, has been developed by the particle physics community working together with biomedical engineers and physicians around the world. The HEV design is suitable for use both in and out of hospital intensive care units, provides a variety of modes and is capable of supporting spontaneous breathing and supplying oxygen-enriched air. An external air supply can be combined with the unit for use in situations where compressed air is not readily available. HEV supports remote training and post market surveillance via a Web interface and data logging to complement standard touch screen operation, making it suitable for a wide range of geographical deployment. The HEV design places emphasis on the ventilation performance, especially the quality and accuracy of the pressure curves, reactivity of the trigger, measurement of delivered volume and control of oxygen mixing, delivering a global performance which will be applicable to ventilator needs beyond the COVID-19 pandemic. This article describes the conceptual design and presents the prototype units together with a performance evaluation.

The COVID-19 pandemic has highlighted the need for a proper risk assessment of respiratory pathogens in indoor settings. This paper documents the COVID Airborne Risk Assessment methodology, to assess the potential exposure of airborne SARS-CoV-2 viruses, with an emphasis on virological and immunological factors in the quantification of the risk. The model results from a multidisciplinary approach linking physical, mechanical and biological domains, enabling decision makers or facility managers to assess their indoor setting. The model was benchmarked against clinical data, as well as two real-life outbreaks, showing good agreement. A probability of infection is computed in several everyday-life settings and with various mitigation measures. The importance of super-emitters in airborne transmission is confirmed: 20% of infected hosts can emit approximately two orders of magnitude more viral-containing particles. The use of masks provides a fivefold reduction in viral emissions. Natural ventilation strategies are very effective to decrease the concentration of virions, although periodic venting strategies are not ideal in certain settings. Although vaccination is an effective measure against hospitalization, their effectiveness against transmission is not optimal, hence non-pharmaceutical interventions (ventilation, masks) should be actively supported. We also propose a critical threshold to define an acceptable risk level.