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Resolving the Late Pleistocene (MIS3–1) Sedimentary Sequence from Doniford, UK: Implications for British-Irish Ice Sheet extent, megafaunal history and hominin occupation
No full textWe present a new Optically Stimulated Luminescence (OSL) chronology, detailed sedimentological evidence, new palynological data and a new Palaeolithic artefact from a classic site known for over 100 years. The fluvioperiglacial sedimentary sequence and chronology irrevocably indicates that the BIIS did not reach the north shore of the SW peninsular of the British Isles in MIS 3–2. Both the sedimentology and palynology suggests cool–cold steppic conditions rather than polar desert. The discovery during this project of a new unrolled bout coupé biface is significant since it adds another westerly example of this characteristic Middle Palaeolithic form associated with Neanderthals, that is relatively common in Britain (compared to Europe). The chronology and sedimentology also confirm the likely reworking of the cold fauna and Acheulian artefacts from regional floodplains prior to MIS 3. The site highlights the archaeological potential of actively eroding cliffs for expanding knowledge of hominin occupations of south–western Britain, near to an ‘edge’ of the Middle Palaeolithic world.</p
Long-term effectiveness of iGlarLixi treatment in people with type 2 diabetes in the United States: The soli-durability 24-month observational study.
No full textAIM: To evaluate the effectiveness and safety of a fixed-ratio combination of insulin glargine 100 U/mL and lixisenatide (iGlarLixi) over 24 months in people with type 2 diabetes (T2D). METHODS: In this retrospective, observational study, data were collected from the Optum Market Clarity® database in the United States. People with T2D aged ≥18 years, previously treated with oral antidiabetic drugs ± basal insulin or glucagon-like peptide-1 receptor agonists, who initiated iGlarLixi between 1 January 2017 and 31 March 2020 and received ≥1 iGlarLixi prescription were included. The primary outcome was change in HbA1c 24 months after starting iGlarLixi. Secondary outcomes included change in HbA1c from baseline, achievement of HbA1c </p
Risk of relapse: TB treatment outcome associates with differentially culturable M. tuberculosis counts in sputum samples.
No full textNo abstract</p
The unfolded protein response influences therapy outcome and disease progression in chronic lymphocytic leukaemia
No full textSince genomics, epigenomics and transcriptomics have provided only a partial explanation of chronic lymphocytic leukaemia (CLL) heterogeneity, and since concordance between mRNA and protein expression is incomplete, we related the CLL proteome to clinical outcome. CLL samples from patients who received fludarabine-containing chemoimmunotherapy were analysed by mass spectrometry (SWATH-MS). One dataset compared pre-treatment samples associated with an optimal versus suboptimal response, while another compared paired samples collected before treatment and at disease progression. eIF2 signalling (pivotal to the unfolded protein response (UPR)), was identified as the most enriched pathway in both datasets (respective z-scores: − 6.245 and 3.317; p < 0.0001), as well as in a fludarabine-resistant CLL cell line established from HG3 cells (z-score: − 2.121; p < 0.0001). Western blotting revealed that fludarabine-resistant HG3 cells expressed higher levels of PERK, which phosphorylates the regulatory eIF2α subunit, and lower levels of BiP, an HSP70 molecular chaperone that inactivates PERK but preferentially binds to misfolded proteins during ER stress. The PERK inhibitor, GSK2606414, sensitised resistant, but not sensitive, HG-3 cells to fludarabine without affecting background cell viability or cytotoxicity induced by the BCL-2 inhibitor venetoclax. These findings identify the UPR as a novel determinant of therapy outcome and disease progression in CLL.</p
Determinants Of Successful Peacekeeping In Civil Wars: A Qualitative Comparative Analysis
No full textPeacekeeping is a significant tool for promoting the settlement of civil wars in the post-Cold War period. Qualitative comparative analysis (QCA) was applied to a comprehensive dataset of peacekeeping operations between 1946 and 2014 that includes not only United Nations missions, but missions led by regional intergovernmental organizations and ad hoc coalitions. The conditions evaluated in the QCA were drawn from the literature on civil war initiation, duration, and termination. Results of the QCA indicate that characteristics that alter belligerent behaviour consistent with rationalist explanations for war are related to peacekeeping success. Multidimensional missions are most successful and traditional peacekeeping operations are least effective due to the importance of addressing the reconstruction of the state after war and the delivery of public goods, particularly security. Security sector reform and a large peacekeeping contingent are a sufficient cause of success in some cases, however, when the central state has collapsed peacekeeping operations are likely to fail. Geographic conditions that hinder the exercise of sovereignty are a malign condition, however physiographic conditions conducive to sustaining an insurgency less so. Island nations constitute the easier cases of peacekeeping, being the opposite of a hinterland country. The policy implications are that (1) unarmed observation missions are successful in pacific contexts with a high level of commitment to peace among the belligerents or when monitoring a robust mission for compliance with international norms, (2) great powers are better suited for robust missions, but the intervention must further state interests, (3) UN multidimensional missions are the most effective at establishing a durable peace even if liberal peacebuilding fail to result in liberal governance, (4) intervention in some cases, principally failed states, are unlikely to be successful and should be considered a tool for the management of the negative externalities of the conflict.</p
G-Adaptivity: optimised graph-based mesh relocation for finite element methods
No full textWe present a novel, and effective, approach to achieve optimal mesh relocation in finite element methods (FEMs). The cost and accuracy of FEMs is critically dependent on the choice of mesh points. Mesh relocation (r-adaptivity) seeks to optimise the mesh geometry to obtain the best solution accuracy at given computational budget. Classical r-adaptivity relies on the solution of a separate nonlinear “meshing” PDE to determine mesh point locations. This incurs significant cost at remeshing, and relies on estimates that relate interpolation- and FEM-error. Recent machine learning approaches have focused on the construction of fast surrogates for such classical methods. Instead, our new approach trains a graph neural network (GNN) to determine mesh point locations by directly minimising the FE solution error from the PDE system Firedrake to achieve higher solution accuracy. Our GNN architecture closely aligns the mesh solution space to that of classical meshing methodologies, thus replacing classical estimates for optimality with a learnable strategy. This allows for rapid and robust training and results in an extremely efficient and effective GNN approach to online r-adaptivity. Our method outperforms both classical, and prior ML, approaches to r-adaptive meshing. In particular, it achieves lower FE solution error, whilst retaining the significant speed-up over classical methods observed in prior ML work.</p
Reliable Indoor Localization in Multi-Building Environments: Leveraging Environment-Invariant and Position-Related Features
No full textReceived Signal Strength Indicator (RSSI)-based indoor localization offers a cost-effective solution for autonomous mobile robot navigation in 3D indoor environments, including cross-floor and multi-building structures. However, localization accuracy is fundamentally constrained by the low sampling density and unstable measurement of RSSI data. So far, existing methods neglect cross-environment RSSI coherence (e.g., repeated signal patterns in geometrically similar areas), resulting in unreliable fingerprint databases. What’s more, most approaches fail to model the spatial hierarchy of buildings, floors, and coordinates, which leads to lower accuracy in indoor positioning model predictions. To address these issues, we propose EP-3DLoc, a novel 3D indoor localization framework that combines an Environment-Invariant feature-based Data Completion (EIC) method with a Position-Related feature-based Localization (PRL) method. The EIC enhances data quality by filling in sparse RSSI data using environment-invariant features, which are recurring RSSI patterns found in similar environmental structures. The PRL module combines multi-scale RSSI signal processing (raw data and image-like data) with a multi-task network that analyzes location relationships, enhancing localization accuracy in 3D environments. Experimental results on public datasets (TUT2018, UTSIndoorLoc, and UJIIndoorLoc) have demonstrated that EP-3DLoc achieves state-of-the-art performance on indoor localization in multi-building environments. Further testing on the self-constructed dataset HZAUIndoorLoc have revealed that EP-3DLoc not only outperforms existing methods in localization accuracy but also maintains low energy consumption and strong resistance to interference.</p
The reason for the widespread energetic storm particle event of 13 March 2023
No full textContext. On 13 March 2023, when the Parker Solar Probe spacecraft (S/C) was situated on the far side of the Sun as seen from Earth, a large solar eruption took place, which created a strong solar energetic particle (SEP) event observed by multiple S/C all around the Sun. The energetic event was observed at six well-separated locations in the heliosphere, provided by the Parker Solar Probe, Solar Orbiter, BepiColombo, STEREO A, near-Earth S/C, and MAVEN at Mars. Clear signatures of an in situ shock crossing and a related energetic storm particle (ESP) event were observed at all inner-heliospheric S/C, suggesting that the interplanetary coronal mass ejection (CME)-driven shock extended all around the Sun. However, the solar event was accompanied by a series of pre-event CMEs.
Aims. We aim to characterize this extreme widespread SEP event and to provide an explanation for the unusual observation of a circumsolar interplanetary shock and a corresponding circumsolar ESP event.
Methods. We analyzed data from seven space missions, namely Parker Solar Probe, Solar Orbiter, BepiColombo, STEREO A, SOHO, Wind, and MAVEN, to characterize the solar eruption at the Sun, the energetic particle event, and the interplanetary context at each observer location as well as the magnetic connectivity of each observer to the Sun. We then employed magnetohydrodynamic simulations of the solar wind in which we injected various CMEs that were launched before as well as contemporaneously with the solar eruption under study. In particular, we tested two different scenarios that could have produced the observed global ESP event: (1) a single circumsolar blast-wave-like shock launched by the associated solar eruption, and (2) the combination of multiple CMEs driving shocks into different directions.
Results. By comparing the simulations of the two scenarios with observations, we find that both settings are able to explain the observations. However, the blast-wave scenario performs slightly better in terms of the predicted shock arrival times at the various observers.
Conclusions. Our work demonstrates that a circumsolar ESP event, driven by a single solar eruption into the inner heliosphere, is a realistic scenario.</p
What can open research learn from the open source movement in computing?
No full textFor a long time, two aspects of my professional life were disconnected, but no doubt informing each other. Although, I have been a long proponent of open research, I have an older interest (from about 1993) in the open source movement in computing. I will discuss the two fields, and what one can learn from the other.Presented at Midlands Innovation Open Research Week, 09/05/2025.</p
Improving biomedical research using an industry-academic open research collaborative
No full textBiomedical research has a high rate of replication failure, making the drug and diagnostic development pipelines slow, expensive and risky. In preclinical research, antibodies are an important reagent used to identify proteins, validate drug targets and investigate disease mechanisms. However, they are also a common driver of replication failure, with some antibodies exhibiting poor selectivity for their intended target. To overcome this barrier, we have established an open research collaboration with industry. We use this open ecosystem to conduct consensus-endorsed antibody quality control experiments. Our collaboration has shown that >50% of research antibodies (n=614), were poorly selective for their intended target in 3 commonly used applications. This work has led to:• The removal of unsuitable reagents from the market.• Open data that improves the reproducibility of biomedical research.• The development of new antibodies that are more reliable.The work is supported by the Only Good Antibodies community, which maximises impact by including stakeholders from commercial databases, research institutions, research funders, publishers and experts in antibody production. This collaboration has used open data to successfully advocate for:• A review of guidelines for applicants at a research funding agency.• New funding calls for reagent validation.• Funding for an education and awareness program informed by the open data.Presented at Midlands Innovation Open Research Week, 07/05/2025.</p