University of Warwick

Biological soil crusts (BSCs) are formed by phototrophic organisms at the soil surface and play a key role in structuring microbial communities and biogeochemical processes in dryland ecosystems. Similar surface associated communities occur in temperate agricultural soils, but their development, assembly dynamics and functional significance remain poorly understood. We investigated the temporal development of the soil surface microbiome following tillage and during subsequent growth of a winter wheat crop, integrating multi-kingdom amplicon sequencing with metagenomic analysis to track phototrophic, bacterial, fungal and protist communities, together with co-amplified macroscopic phototrophs. Distinct surface communities of phototrophs, bacteria and protists established rapidly, within 4 weeks of tillage, and underwent marked succession from early dominance by yellow-green algae (Xanthophyceae) to cyanobacteria, charophytes and ultimately mosses. Across all taxonomic groups, community assembly at the soil surface increasingly shifted towards dispersal limitation over time, whereas bulk soil communities were predominantly shaped by ecological drift. By the end of the growing season, the soil surface had developed a functional profile distinct from bulk soil, characterised by a greater representation of photosynthetic processes, largely due to eukaryotic algal carbon fixation, alongside increased genetic potential for heterotrophic carbon, nitrogen, phosphorus and sulphur cycling. These functional shifts were associated with enrichment of Actinobacteria, Bacteroidetes and Proteobacteria. Our results demonstrate that the soil surface of temperate agricultural systems represents a dynamic and functionally differentiated microbial habitat, which shares key biological features with dryland BSCs while exhibiting distinct functional and successional trajectories, revealing an overlooked component of managed temperate ecosystems • Soil surface communities establish rapidly in temperate agricultural soil • Dispersal limitation structures surface communities, while drift dominates in bulk soil • Surface soils show a distinct functional signature from phototrophs and heterotrophs

We consider adaptive increasingly rare Markov chain Monte Carlo (MCMC) algorithms, which are adaptive MCMC methods, where the adaptation concerning the “past” happens less and less frequently over time. Under a contraction assumption with respect to a Wasserstein-like function we deduce upper bounds of the convergence rate of Monte Carlo sums taking a renormalisation factor into account that is “almost” the one that appears in a law of the iterated logarithm. We demonstrate the applicability of our results by considering different settings, among which are those of simultaneous geometric and uniform ergodicity. All proofs are carried out on an augmented state space, including the classical non-augmented setting as a special case. In contrast to other adaptive MCMC limit theory, some technical assumptions, like diminishing adaptation, are not needed.

This study introduces a novel pipeline for converting surface electromyography (sEMG) signals into muscle activations using the Hilbert-Huang Transform. Traditional approaches in this context often apply low-pass filters that suppress high-frequency components, potentially discarding physiologically relevant signal information. In contrast, the proposed method leverages Empirical Mode Decomposition and Hilbert spectral analysis to preserve the nonstationary and multi-frequency nature of sEMG data. Activation outputs are then mapped through physiologically inspired dynamics, yielding time-resolved muscle activations. Comparative analyses were conducted across three muscles (EDC, FDS, FDP) using data from 10 subjects each performing 5 cylindrical grasps. Intra-subject comparisons using Wilcoxon signed-rank tests revealed statistically significant improvements (p < 0.001) in nearly all trials. Linear mixed-effects analysis of log-transformed activations showed that the new pipeline yields significantly higher muscle activations within each muscle: EDC GMR = 1.31 (95% CI: 1.255–1.359), FDS GMR = 1.35 (95% CI: 1.296–1.396), and FDP GMR = 1.29 (95% CI: 1.248–1.342), all p < 0.001. These results suggest that the choice of sEMG processing pipeline can meaningfully alter activation estimates and potentially influence musculoskeletal model estimation. The method presented provides a robust and physiologically consistent alternative for applications in biomechanics, prosthetic control, and neuromuscular modelling.

While teacher agency in curriculum reform is well-studied, its development during initial teacher education (ITE), a formative phase for developing competencies for standards-based teaching, remains under-explored. Informed by Priestley et al.'s (2015) ecological model, this qualitative multi-case study breaks new ground by examining how student teachers from two Chinese normal universities enacted agency in implementing the 2022 English Curriculum Standards during a full-responsibility internship. Analysis of focus group and individual interview data from 13 ITE graduates shows that implementation-oriented agency was shaped through the interaction of university preparation, internship conditions, and future professional trajectories. Agency was enabled when reform principles were integrated through sequenced curricula, reform-aligned pedagogical modelling, and structured school mentoring. Specifically, coherent feedback, professional learning opportunities, and curriculum-aligned resources supported the enactment of standards-aligned practices, whereas fragmented or absent support prompted compensatory adaptation. A particularly salient finding concerns the positioning of student teachers as legitimate learners during full-responsibility internships, which legitimised experimentation, reflection, and pedagogical risk-taking during professional transition. By integrating a pre-service perspective into the ecological model, this study identifies mechanisms through which ITE programmes shape agency in implementing new standards and offers insights for strengthening ITE design in reform contexts.

The bulk lifetime (τ bulk ) of high-quality silicon wafers is becoming ever more important as the efficiency of the solar cells increases (i.e. >27 %). As such there is a growing necessity to measure τ bulk directly. In this work, we showcase a non-destructive technique to infer τ bulk of high-quality wafers, termed the Charge Decoupling Method. This method is very simple and only requires atomic layer deposited (ALD) aluminium oxide (Al 2 O 3 )—or any other highly charged film (e.g. >10 12 q cm −2 )—and corona charging. By measuring the decay in the effective lifetime as the net negative charge decreases—due to the sequential deposition of positive corona charges—we can quantify the shape of the curve—analogous to the fill factor for a solar cell—and from this, determine the injection-dependent τ bulk and surface recombination velocity S . To experimentally verify the method, we apply the charge decoupling method to Al 2 O 3 passivated Czochralski-grown 5 Ω cm, n -type, 150 μm thick silicon wafers. From this we obtain a τ bulk of ∼30 ms and a corresponding S of 0.2 cm −1 at an injection level of ∼10 15 cm −3 . Mathematically, we demonstrate that the charge decoupling method depends solely on the ratio of surface to bulk recombination and thus does not depend on the doping type, resistivity, charge density, wafer thickness, interface defect density and the injection-dependent bulk lifetime. • We showcase a method to infer the bulk lifetime of high-quality silicon wafers, termed the Charge Decoupling Method (CDM). • The method only requires a non-leaky dielectric layer and corona charging. • We measure a bulk lifetime of ∼30 ms (at Δ n = 10 15 cm −3 ) on Cz, 5 Ω cm, n -type, 150 μm thick silicon wafers. • Mathematically, we demonstrate that CDM depends solely on the ratio of surface to bulk recombination. • The CDM method can be used without calibrating the corona charger from time to deposited charge.