University of Oxford

Urban tunnelling projects pose significant risks to the integrity of nearby structures due to ground movements induced by the excavation process. Embedded walls are commonly employed as a protective measure to mitigate these adverse effects. This paper presents a comprehensive numerical investigation into the effects of embedded walls on tunnelling-induced ground displacements, aiming to provide insights and recommendations for optimal embedded wall design. The study assesses the impact of varying embedded wall length and horizontal distance from the tunnel on soil settlement and horizontal displacements. Results demonstrate the complex interplay between embedded wall length, horizontal distance, and ground movement patterns, and the highly non-linear influence of key parameters on embedded wall efficiency (i.e. its ability to reduce settlements). A preliminary design chart is proposed to guide engineers in determining the appropriate horizontal location and depth of embedded walls to effectively reduce tunnelling-induced ground displacements. The findings contribute to a better understanding of embedded wall performance in the context of tunnelling and provide valuable guidance for the practical design and implementation of protective measures in urban areas.

Achieving amplification with high gain and quantum-limited noise is a difficult problem to solve. Parametric amplification using a superconducting transmission line with high kinetic inductance is a promising technology not only to solve this problem but also adding several benefits. Compared to other technologies, they have the potential to improve power saturation, achieve larger fractional bandwidths, and operate at higher frequencies. In this type of amplifier, the selection of the proper transmission line is a key element in its design. Given current fabrication limitations, traditional lines such as coplanar waveguides (CPW), are not ideal for this purpose, since it is difficult to make them with the proper characteristic impedance for good matching and slow enough phase velocity for making them more compact. Capacitively loaded lines, also known as artificial lines, are a good solution to this problem. However, few design rules or models have been presented to guide their accurate design. This fact is even more crucial considering that they are usually fabricated in the form of Floquet lines that have to be designed carefully to suppress undesired harmonics appearing in the parametric process. In this article we present, first, a new modeling strategy, based on the use of electromagnetic-simulation software, and, second, a first-principles model that facilitate and speed the design of CPW artificial lines and of Floquet lines made out of them. Then, we present comparisons with experimental results that demonstrate their accuracy. Finally, the theoretical model allows one to predict the high-frequency behavior of the artificial lines, showing that they are good candidates for implementing parametric amplifiers above 100 GHz.

GaToroid is a novel configuration of a beam delivery system for charged particles therapy based on a steady-state, axis-symmetric field configuration. The basic idea is to use fixed toroidal magnets, producing an axis-symmetric (or periodical axis-symmetric) field configuration that can bend beams from several directions onto the patient location. In principle, neither magnets nor patient need to be moved. In addition, the field of the magnets of this toroidal gantry is static. Such system is perfectly adapted to FLASH therapy, a novel method of beam dose delivery that has shown benefits for electrons and potential for hadrons. In this paper we describe the magnetic design of a “compact GaToroid”, which could be built with iron-dominated magnets, suitable for 200 MeV electron beams, as well as protons at 70 MeV. The gantry profits from the use of toroidal quadrupoles, which greatly simplify the beam transmission. An additional novelty is the use of a resonant kicker as the vector magnet. Starting from the requirements for beam transmission, we derive first the magnet main characteristics (strength, aperture, size and mass) and report the detailed magnetic field calculations in support of the design.

Background: One Health focuses on sustainable health for humans, animals, and ecosystems. The approach has been well demonstrated, yet most efforts have not been scaled up. Understanding the organisations involved in scaling up processes is critical to translating research into practice. The Lao People's Democratic Republic has successfully implemented One Health projects for multiple decades; however, the organisational network has not been described and scaling up efforts have been limited. Methods: Data from organisations involved in One Health projects over the past five years were collected by key-informant interview or workshop. The network was investigated using a mixture of quantitative network analysis and qualitative thematic analysis. Results: The organisational network was quantitatively described as sparse and centralised. Organisations were required to harness pre-existing relationships to maximise scarce resources and make coordination and alignment of priorities more efficient. A lack of international organisations in the top 10% of resource sharing metrics suggests a potential disconnect between donors. This was reflected in the challenges faced by national organisations and a feeling of being stretched thin over numerous externally funded projects with donor-driven priorities. Conclusions: It appears that high-level political support for country ownership of development and aid priorities remains unrealised. Developing network capacity and capability may assist scaling up efforts and build resilience in the network and its core organisations. This may allow for the inclusion of more development, education, environment, and water, sanitation, and hygiene organisations that were perceived to be lacking. Future One Health programmes should focus on practical activities that do not overload staff capacity. There is much for One Health to learn about the art of scaling up and organisations are encouraged to include implementation science in their research to inform future scaling up efforts.

Key epidemiological parameters, including the effective reproduction number, R(t), and the instantaneous growth rate, r(t), generated from an ensemble of models, have been informing public health policy throughout the COVID-19 pandemic in the four nations of the United Kingdom of Great Britain and Northern Ireland (UK). However, estimation of these quantities became challenging with the scaling down of surveillance systems as part of the transition from the “emergency” to “endemic” phase of the pandemic. The Office for National Statistics (ONS) COVID-19 Infection Survey (CIS) provided an opportunity to continue estimating these parameters in the absence of other data streams. We used a penalised spline model fitted to the publicly-available ONS CIS test positivity estimates to produce a smoothed estimate of the prevalence of SARS-CoV-2 positivity over time. The resulting fitted curve was used to estimate the “ONS-based” R(t) and r(t) across the four nations of the UK. Estimates produced under this model are compared to government-published estimates with particular consideration given to the contribution that this single data stream can offer in the estimation of these parameters. Depending on the nation and parameter, we found that up to 77% of the variance in the government-published estimates can be explained by the ONS-based estimates, demonstrating the value of this singular data stream to track the epidemic in each of the four nations. We additionally find that the ONS-based estimates uncover epidemic trends earlier than the corresponding government-published estimates. Our work shows that the ONS CIS can be used to generate key COVID-19 epidemiological parameters across the four UK nations, further underlining the enormous value of such population-level studies of infection. This is not intended as an alternative to ensemble modelling, rather it is intended as a potential solution to the aforementioned challenge faced by public health officials in the UK in early 2022.

Artificial neural networks (ANNs) have emerged as an essential tool in machine learning, achieving remarkable success across diverse domains, including image and speech generation, game playing, and robotics. However, there exist fundamental differences between ANNs’ operating mechanisms and those of the biological brain, particularly concerning learning processes. This paper presents a comprehensive review of current brain-inspired learning representations in artificial neural networks. We investigate the integration of more biologically plausible mechanisms, such as synaptic plasticity, to improve these networks’ capabilities. Moreover, we delve into the potential advantages and challenges accompanying this approach. In this review, we pinpoint promising avenues for future research in this rapidly advancing field, which could bring us closer to understanding the essence of intelligence.

In today's digital landscape, the Web has become increasingly centralized, raising concerns about user privacy violations. Decentralized Web architectures, such as Solid, offer a promising solution by empowering users with better control over their data in their personal `Pods'. However, a significant challenge remains: users must navigate numerous applications to decide which application can be trusted with access to their data Pods. This often involves reading lengthy and complex Terms of Use agreements, a process that users often find daunting or simply ignore. This compromises user autonomy and impedes detection of data misuse. We propose a novel formal description of Data Terms of Use (DToU), along with a DToU reasoner. Users and applications specify their own parts of the DToU policy with local knowledge, covering permissions, requirements, prohibitions and obligations. Automated reasoning verifies compliance, and also derives policies for output data. This constitutes a ``perennial'' DToU language, where the policy authoring only occurs once, and we can conduct ongoing automated checks across users, applications and activity cycles. Our solution is built on Turtle, Notation 3 and RDF Surfaces, for the language and the reasoning engine. It ensures seamless integration with other semantic tools for enhanced interoperability. We have successfully integrated this language into the Solid framework, and conducted performance benchmark. We believe this work demonstrates a practicality of a perennial DToU language and the potential of a paradigm shift to how users interact with data and applications in a decentralized Web, offering both improved privacy and usability.

Aim Quantifying the relative contribution of environmental filtering versus limiting similarity in shaping communities is challenging because these processes often act simultaneously and their effect is scale‐dependent. Focusing on caves, island‐like natural laboratories with limited environmental variability and species diversity, we tested: (i) the relative contribution of environmental filtering and limiting similarity in determining community assembly in caves; (ii) how the relative contribution of these driving forces changes along environmental gradients. Location Europe. Time period Present. Major taxa studied Subterranean spiders. Methods We used data on distribution and traits for European cave spiders ( n = 475 communities). We estimated the trait space of each community using probabilistic hypervolumes, and obtained estimations of functional richness independent of the species richness of each community via null modelling. We model functional diversity change along environmental gradients using generalized dissimilarity modelling. Results Sixty‐three percent of subterranean spider communities exhibited a prevalence of trait underdispersion. However, most communities displayed trait dispersion that did not depart significantly from random, suggesting that environmental filtering and limiting similarity were both exerting equally weak or strong, yet opposing influences. Overdispersed communities were primarily concentrated in southern latitudes, particularly in the Dinaric karst, where there is greater subterranean habitat availability. Pairwise comparisons of functional richness across caves revealed these effects to be strongly scale‐dependent, largely varying across gradients of cave development, elevation, precipitation, entrance size and annual temperature range. Conversely, geographical distance weakly affected trait composition, suggesting convergence in traits among communities that are far apart. Main conclusions Even systems with stringent environmental conditions maintain the potential for trait differentiation, especially in areas of greater habitat availability. Yet, the relative influence of environmental filtering and limiting similarity change with scale, along clear environmental gradients. The interplay of these processes may explain the assembly of species‐poor subterranean communities displaying high functional specialization.

The difluoromethyl functionality has proven useful in drug discovery, as it can modulate the properties of bioactive molecules. For PET imaging, this structural motif has been largely underexploited in (pre)clinical radiotracers due to a lack of user‐friendly radiosynthetic routes. This Minireview provides an overview of the challenges facing radiochemists and summarises the efforts made to date to access ¹⁸F‐difluoromethyl‐containing radiotracers. Two distinct approaches have prevailed, the first of which relies on ¹⁸F‐fluorination. A second approach consists of a ¹⁸F‐difluoromethylation process, which uses ¹⁸F‐labelled reagents capable of releasing key reactive intermediates such as the [¹⁸F]CF2H radical or [¹⁸F]difluorocarbene. Finally, we provide an outlook for future directions in the radiosynthesis of [¹⁸F]CF2H compounds and their application in tracer radiosynthesis.

Introduction An important mechanism of research waste is inadequate incorporation of, and references to, previous relevant research. Identifying references for a research manuscript can be challenging, in part due to the exponential rise in potentially relevant literature to consider. For large research projects, such as developing or updating reporting guidelines, it may be helpful to construct a supportive topic‐specific bibliographic database. Methods In support of updating the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 2013 and the CONsolidated Standards Of Reporting Trials (CONSORT) 2010, we developed the SPIRIT‐CONSORT Evidence Bibliographic database (SCEBdb): a freely available topic‐specific bibliographic database of publications providing an evidence foundation for the updates. We searched multiple sources of potential publications and tagged included ones with database‐specific keywords. For context, we also formulated 10 core considerations for constructing topic‐specific bibliographic databases and identified and described 5 illustrative other databases. Results As of April 2024, the SCEBdb included 846 publications. The database proved useful as a supplementary information source for our scoping review of published comments on SPIRIT 2013 and CONSORT 2010, for a supplementary Delphi process, and in the writing phase of the guidance documents. We expect that the database will be useful for future projects within the fields of clinical research methodology, bias, evidence synthesis, and randomized trials. Conclusion The methods involved in constructing the SCEBdb, and our suggested core considerations for topic‐specific bibliographic databases, could be helpful for researchers reflecting on whether, and how, to develop a topic‐specific bibliographic database.

Slowing and/or reversing brain ageing may alleviate cognitive impairments. Previous studies have found that exercise may mitigate cognitive decline, but the mechanisms underlying this remain largely unclear. Here we provide unbiased analyses of single‐cell RNA sequencing data, showing the impacts of exercise and ageing on specific cell types in the mouse hippocampus. We demonstrate that exercise has a profound and selective effect on aged microglia, reverting their gene expression signature to that of young microglia. Pharmacologic depletion of microglia further demonstrated that these cells are required for the stimulatory effects of exercise on hippocampal neurogenesis but not cognition. Strikingly, allowing 18‐month‐old mice access to a running wheel did by and large also prevent and/or revert T cell presence in the ageing hippocampus. Taken together, our data highlight the profound impact of exercise in rejuvenating aged microglia, associated pro‐neurogenic effects and on peripheral immune cell presence in the ageing female mouse brain.

By bringing together a large group of participants with diverse skillsets, hackathons aim to make good headway into a particular research topic over a short period of time. This collaborative approach supports relationship building, cross team working and the development of technical skills across different areas. image

Business reliance on algorithms is becoming ubiquitous, and companies are increasingly concerned about their algorithms causing major financial or reputational damage. High-profile cases include Google’s AI algorithm for photo classification mistakenly labelling a black couple as gorillas in 2015 (Gebru 2020 In The Oxford handbook of ethics of AI, pp. 251–269), Microsoft’s AI chatbot Tay that spread racist, sexist and antisemitic speech on Twitter (now X) (Wolf et al. 2017 ACM Sigcas Comput. Soc. 47, 54–64 (doi:10.1145/3144592.3144598)), and Amazon’s AI recruiting tool being scrapped after showing bias against women. In response, governments are legislating and imposing bans, regulators fining companies and the judiciary discussing potentially making algorithms artificial ‘persons’ in law. As with financial audits, governments, business and society will require algorithm audits; formal assurance that algorithms are legal, ethical and safe. A new industry is envisaged: Auditing and Assurance of Algorithms (cf. data privacy), with the remit to professionalize and industrialize AI, ML and associated algorithms. The stakeholders range from those working on policy/regulation to industry practitioners and developers. We also anticipate the nature and scope of the auditing levels and framework presented will inform those interested in systems of governance and compliance with regulation/standards. Our goal in this article is to survey the key areas necessary to perform auditing and assurance and instigate the debate in this novel area of research and practice.

We describe our efforts to access a compound with an Al=P double bond by reaction of Al(Nacnac) towards [H2CN(Dipp)]2P(PCO) (Nacnac=HC[C(Me)N(Dipp)]2; Dipp=2,6‐ⁱPr2C6H3). Our observations are consistent with the formation of a transient phosphanyl‐phosphaalumene at low temperatures (−70 °C), however this species was found to readily undergo intramolecular C−H activation of the β‐diketiminato ligand upon warming to room temperature. The reactivity of the transient complex toward small molecules including dihydrogen, carbon dioxide, phosphaketenes, amines and silanes could be explored at low temperatures, showcasing that the target compound can react as both a frustrated Lewis pair (via the pendant phosphanyl moiety) or in hydroelementation reactions of the Al=P bond. The elusive target molecule could be trapped by addition of a Lewis base (tetrahydrofuran) affording an isolable molecular species that reacts in an analogous fashion to the base‐free compound.

Background Non-toxic approaches to enhance radiotherapy outcomes are beneficial, particularly in ageing populations. Based on preclinical findings showing that high-fibre diets sensitised bladder tumours to irradiation by modifying the gut microbiota, along with clinical evidence of prebiotics enhancing anti-cancer immunity, we hypothesised that dietary fibre and its gut microbiota modification can radiosensitise tumours via secretion of metabolites and/or immunomodulation. We investigated the efficacy of high-fibre diets combined with irradiation in immunoproficient C57BL/6 mice bearing bladder cancer flank allografts. Result Psyllium plus inulin significantly decreased tumour size and delayed tumour growth following irradiation compared to 0.2% cellulose and raised intratumoural CD8⁺ cells. Post-irradiation, tumour control positively correlated with Lachnospiraceae family abundance. Psyllium plus resistant starch radiosensitised the tumours, positively correlating with Bacteroides genus abundance and increased caecal isoferulic acid levels, associated with a favourable response in terms of tumour control. Psyllium plus inulin mitigated the acute radiation injury caused by 14 Gy. Psyllium plus inulin increased caecal acetate, butyrate and propionate levels, and psyllium alone and psyllium plus resistant starch increased acetate levels. Human gut microbiota profiles at the phylum level were generally more like mouse 0.2% cellulose profiles than high fibre profiles. Conclusion These supplements may be useful in combination with radiotherapy in patients with pelvic malignancy. C3P3Z-i-BEWcsPG8U_9P4fVideo Abstract

The molecular and cellular basis of health in human tendons remains poorly understood. Among human tendons, hamstring tendon has markedly low pathology and can provide a prototypic healthy tendon reference. The aim of this study was to determine the transcriptomes and location of all cell types in healthy hamstring tendon. Using single nucleus RNA sequencing, we profiled the transcriptomes of 10 533 nuclei from four healthy donors and identified 12 distinct cell types. We confirmed the presence of two fibroblast cell types, endothelial cells, mural cells, and immune cells, and identified cell types previously unreported in tendons, including different skeletal muscle cell types, satellite cells, adipocytes, and undefined nervous system cells. The location of these cell types within tendon was defined using spatial transcriptomics and imaging, and potential transcriptional networks and cell–cell interactions were analyzed. We demonstrate that fibroblasts have the highest number of potential cell–cell interactions in our dataset, are present throughout the tendon, and play an important role in the production and organization of extracellular matrix, thus confirming their role as key regulators of hamstring tendon homeostasis. Overall, our findings underscore the complexity of the cellular networks that underpin healthy human tendon function and the central role of fibroblasts as key regulators of hamstring tendon tissue homeostasis.

This work presents a proposed extension to the International Union of Pure and Applied Chemistry (IUPAC) International Chemical Identifier (InChI) standard that allows the representation of isotopically-resolved chemical entities at varying levels of ambiguity in isotope location. This extension includes an improved interpretation of the current isotopic layer within the InChI standard and a new isotopologue layer specification for representing chemical intensities with ambiguous isotope localization. Both improvements support the unique isotopically-resolved chemical identification of features detected and measured in analytical instrumentation, specifically nuclear magnetic resonance and mass spectrometry. Scientific contribution This new extension to the InChI standard would enable improved annotation of analytical datasets characterizing chemical entities, supporting the FAIR (Findable, Accessible, Interoperable, and Reusable) guiding principles of data stewardship for chemical datasets, ultimately promoting Open Science in chemistry.

Knowledge graph reasoning (KGR) aims to infer new knowledge or detect noises, which is essential for improving the quality of knowledge graphs. Recently, various KGR techniques, such as symbolic- and embedding-based methods, have been proposed and shown strong reasoning ability. Symbolic-based reasoning methods infer missing triples according to predefined rules or ontologies. Although rules and axioms have proven effective, it is difficult to obtain them. Embedding-based reasoning methods represent entities and relations as vectors, and complete KGs via vector computation. However, they mainly rely on structural information and ignore implicit axiom information not predefined in KGs but can be reflected in data. That is, each correct triple is also a logically consistent triple and satisfies all axioms. In this paper, we propose a novel NeuRal Axiom Network (NeuRAN) framework that combines explicit structural and implicit axiom information without introducing additional ontologies. Specifically, the framework consists of a KG embedding module that preserves the semantics of triples and five axiom modules that encode five kinds of implicit axioms. These axioms correspond to five typical object property expression axioms defined in OWL2, including ObjectPropertyDomain, ObjectPropertyRange, DisjointObjectProperties, IrreflexiveObjectProperty and AsymmetricObjectProperty. The KG embedding module and axiom modules compute the scores that the triple conforms to the semantics and the corresponding axioms, respectively. Compared with KG embedding models and CKRL, our method achieves comparable performance on noise detection and triple classification and achieves significant performance on link prediction. Compared with TransE and TransH, our method improves the link prediction performance on the Hits@1 metric by 22.0% and 20.8% on WN18RR-10% dataset, respectively.