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Dataset for "Laser-Driven Ion Surfing via Ponderomotive Self-Injection"
No full textDataset for the publication "Laser-Driven Ion Surfing via Ponderomotive Self-Injection". This simulation study demonstrates through particle-in-cell simulations a novel, hybrid ion acceleration scheme based on optically tailored plasma density profiles. In this approach, ions are initially pre-accelerated in a near-critical density plasma slab via the hole-boring regime of Radiation Pressure Acceleration, before being self-injected into an electrostatic field, co-propagating with the driving laser pulse, formed in a relativistically underdense rear-surface density gradient. This phase matched configuration enables sustained ion acceleration over an extended plasma length. Using Bayesian Optimisation, we tailor the density profile for a fixed laser power, achieving significantly enhanced maximum ion energies, of 2 GeV protons with current laser technologies. Compared with circularly polarised laser acceleration of ultrathin foils, the maximum proton energy exhibits a markedly steeper scaling with laser intensity, highlighting the potential of target density tailoring for next-generation laser-driven ion sources. Simulations were performed on the ARCHER2 cluster using the particle-in-cell code EPOCH. EPOCH is available from the Warwick Plasma GitHub repository. Two- and three-dimensional simulations were investigated and each input deck is supplied for each laser power sampled in the paper and for both, the proposed acceleration scheme and a benchmark acceleration scheme utilising a circular polarised laser pulse irradiating an ultrathin target. Accompanying python scripts are included which, once simulations are completed, recreate each figure (Figure 1-5) in the published paper. The EPOCH code used in this work was in part funded by the UK EPSRC grants EP/G054950/1, EP/G056803/1, EP/G055165/1, EP/ M022463/1 and EP/P02212X/1. HPC resource time thanks to Plasma HPC Grant: EP/X035336/1. UK Ministry of Defence © Crown owned copyright 2026/AW
Five Point Check©-based management of goat health can be self-sustainable without long-term public funding: a 5-year retrospective study of Malawi smallholdings
No full textFailure to manage goat nutrition or control gastrointestinal nematode parasites (GINs) can lead to low performance and livestock losses on smallholdings. Programs to improve smallholder goat health can have an immediate positive impact but often depend on external expertise and resources such as anthelmintic interventions. As a result, programs may fail to support smallholders once external resources, such as grant funding, are removed. With this in mind, a low-resource targeted-selective treatment (TST) program based on a hands-on Five Point Check© (FPC) scoring system was undertaken from 2020 to 2021 in rural Central Malawi. Participating smallholders were educated and equipped to perform goat health scoring and provide interventions on an as needed basis. In April 2025, five years after the study began, original participants were surveyed alongside control non-participants to determine the impact, uptake, and dissemination of TST using the FPC. 97.5 % of participants remembered the FPC and 73.8–92.9 % still used FPC tests on their goats. Practicing the FPC increased farmers’ confidence and success and decreased the likelihood of being impacted by disease or ill health. As a result of the FPC, targeted beneficial plant supplementation and anthelmintic use to treat sick goats was maintained among study participants. Non-study controls were unanimously in favour of using the FPC, but gaps exist in supporting dissemination of training and materials (such as FAMACHA cards and anthelmintic) to the wider smallholder community. Overall, this study shows that education and sustainable practices can be adopted and self-sustained in low-resource areas following initial investment.<br/
Robustor3D: robust multimodal 3D object detector for autonomous driving by vision-language knowledge blending
No full textMultimodal 3D object detection for autonomous driving, a task for real-world application, poses substantial challenges in maintaining robust performance under various perturbations and complex environmental conditions. However, most existing approaches primarily focus on performance optimization under relatively ideal scenarios or focus on one or few disturbing conditions (interference or adverse conditions), lacking systematic exploration of robustness against real-world factors, including high class imbalance, adverse weather conditions, sensor jitter and failures, and significant scene variations. To address this issue, we propose a robust multimodal 3D detector, termed RobusTor3D, which integrates robustness at both the structural and supervisory levels by blending the knowledge from Vision-Language Models(VLMs). Structurally, textual descriptions are incorporated to enhance the semantic richness and diversity of rare classes. This novel semantic injection operation compensates for the inherent class imbalance and modality weakness in conventional visual features. Furthermore, semantic alignment capability and robust representation by Vision-Language Knowledge Extraction (V-LKE) serve as semantic priors to complement modality-specific representations, significantly improving model adaptability. At the supervisory level, we propose a Scene-level Multimodal Consistency Learning (SMCL) strategy, which jointly enforces global semantic constraints across modalities, encouraging the learning of stable and abundant semantic representations. This special design specifically reduces the impact of spatial alignment, while notably enabling semantic compensation under modality-loss conditions. Extensive robustness experiments conducted on KITTI, KITTIC, and CADC benchmarks evaluate five robustness aspects, including long-tail problem, adverse weather (rain, snow, fog, strong sunlight), sensor spatial misalignment and motion blur, modality loss, and cross-domain scenarios. The results show that the proposed RobusTor3D demonstrates superior robustness across all five evaluated aspects. It consistently outperforms the state-of-the-art methods under various challenging conditions
Decoding enzyme–substrate specificity with EZSpecificity
No full textIn a recent issue of Nature, Zhao and co-workers introduce EZSpecificity, an enzyme-substrate-specificity prediction model built on a curated enzyme-substrate database and integrating sequence and structural information. Benchmark studies across representative enzyme families demonstrate that EZSpecificity outperforms existing machine-learning approaches, including enzyme-substrate prediction (ESP) and compound-protein interaction (CPI), in predicting enzyme-substrate specificity
Dataset for "Polar Discontinuities, Emergent Conductivity, and Critical Twist-Angle-Dependent Behaviour at Wafer-Bonded Ferroelectric Interfaces"
No full textAtomic Force Microscopy data associated with the submitted paper: "Polar Discontinuities, Emergent Conductivity, and Critical Twist-Angle-Dependent Behaviour at Wafer-Bonded Ferroelectric Interfaces", Nature Communications. Abstract for paper: "Probing novel functional properties, arising from twisted interfaces, has traditionally relied on the stacking of exfoliated 2D materials and the spontaneous formation of van der Waals (vdW) bonds. So far, investigations involving more intimate covalent or ionic bonds have not been a major focus. Yet, we show here that an established technique, involving high temperature thermocompressional bonding of bulk single crystalline wafers, works well for creating twisted non-vdW interfaces. We have successfully bonded z-cut lithium niobate single crystals to deliberately create ferroelectric oxide interfaces with strong polar discontinuities and have mapped the associated emergent interfacial conductivity. In some instances, a dramatic change in microstructure occurs, involving local dipolar switching. Such behaviour implies a twist-induced collapse in the capability of the system to effectively screen interfacial bound charge. Importantly, this phenomenon only occurs around specific moiré twist angles which have sparse coincident lattices and associated short-range aperiodicity. In quasicrystals, aperiodicity is known to induce pseudo-bandgaps and we suspect a similar phenomenon here.
The influence of plantation forest legacy on blanket bog hydrology
No full textHuman activities in headwater blanket bogs can lead to downstream flooding due to changes in land cover; however, the effects of the geographic distribution of these land cover modifications, especially the role of legacy of plantation forestry on hydrological regime, remains poorly characterized. Therefore, the focus of this research is to estimate the impact of legacy of plantation forestry on streamflow in small (21 ha) blanket bog catchment of Ireland. A network of groundwater monitoring and hydro-meteorological stations were installed to collect high-resolution (15 min to 1 h) hydro-meteorological and groundwater level data. Generalized Multistep Dynamic (GMD) TOPMODEL was calibrated using high resolution (1 m × 1 m) Light Detection and Ranging (LiDAR) and hydro-meteorological data in intact blanket bog watershed. The calibrated model was validated before simulating in degraded (legacy of plantation forestry) catchment. The effect of legacy of plantation forestry on streamflow was examined by comparing observed and simulated streamflow series at various timescales (monthly, seasonal, and yearly). The results indicated that streamflow increased by 106 % annually due to legacy of plantation forestry, with the highest monthly increase recorded in February (275 %) and the lowest in September (16 %) when compared to intact blanket bog. Seasonal analysis revealed an increase in streamflow attributed to legacy of plantation forestry, with the highest increase observed in winter (237 %) and the lowest in summer (24 %). Minimal interception losses, reduced evapotranspiration, and compact bog contribute to elevated runoff relative to undisturbed conditions. The results of this study assist water managers, stakeholders, and policymakers in facilitating effective planning and decision-making
Innovation grant (s)hopping: unpacking SMEs’ support choices between multiple potential funding sources
No full textIn many national contexts, firms encounter a complex support landscape for research and development (R&D) and innovation, which includes national and local grant schemes. How do small and medium enterprises (SMEs) navigate these landscapes? What factors influence their decision-making processes and choices regarding funding applications? Understanding these processes is crucial for creating more effective and precisely targeted innovation support systems. Using frameworks for contingent and hedonic decision-making, we conceptualise how SMEs choose between different innovation funding options. Interview data indicate a strong experiential element in SMEs' decision-making. Decisions between alternative funding sources tend to be reactive and driven by intuition in emerging SMEs, more planned and hedonic in early-trading SMEs, and based on strategic and hedonic reasoning in mature, revenue-generating SMEs. The findings provide valuable insights into the dynamics of SMEs' innovation funding strategies and offer practical implications for designing funding programmes that meet the needs of SMEs at various stages of development.<br/
Typology of online mental health peer support for young people: a systematic scoping review
No full textBackgroundYoung people are the age group with the highest prevalence of mental health problems, yet they are the least likely to engage with traditional treatments for their symptoms. Online peer support can support youth mental health as a supplementary strategy. While there is a growing body of research focusing on specific forms of online peer support and their effectiveness, a clear classification of the types of online peer support is under-developed.ObjectiveThe aim of this systematic scoping review was to identify and synthesise the existing peer-reviewed literature on online mental health peer support for young people to better understand the main characteristics of online peer support and develop a possible typology.MethodsThe IBSS, SSCI, Scopus, PsycINFO, Medline and Social Policy and Practice databases were searched using title and abstract. Retrieved studies (n = 12,093) were double screened and 49 articles met the criteria to be included in the review.ResultsThe systematic scoping review identified seven main characteristics and twenty-two sub-characteristics of online peer support. Based on those characteristics, three key distinguishing characteristics were identified which enabled a typology to be developed. It was therefore found that online peer support for youth mental health could be categorised into eight main types.ConclusionsThe identified characteristics and typology provide an overall description of current online mental health peer support for young people. This typology can facilitate research on effectiveness and further developments in online peer support. It may also help young people explore the types of online support available to them. Further research should explore the mechanisms and effectiveness of online peer support.<br/