Advancing Open Science

Radio altimetry is important for sensing the near-ground altitude of airborne platforms operating at several-kilometre altitudes. In urban environments, multipath propagation and coherent superposition from buildings and ground surfaces can alter echo delay, energy, and waveform, thereby affecting downstream ranging and altitude-estimation decisions. Conventional echo models often cannot retain the geometric propagation delays, material properties, polarization transformations, and coherent phase relationships of individual scattering components in kilometer-scale three-dimensional scenes, limiting their ability to reconstruct physically consistent time-domain echoes. To address this, this study combines radio-altimetry echo simulation with electromagnetic simulation of urban environments and develops a finite-distance spherical-wave physical-optics method for modeling time-domain echoes in large-scale urban scenes. The method maps the scattering responses of urban surface facets to the received time-domain echo. Representative cases verify the accuracy of calculations of scattering amplitude, range attenuation, and two-way propagation delay. The results show that a uniform material assignment predominantly affects echo amplitude and energy while exerting only a limited influence on the delay structure. In contrast, variations in urban geometry alter the spatial locations and orientations of effective scattering facets and the coherence relationships among their complex fields, resulting in distinct main-peak positions, energy-delay distributions, and early- and late-arriving multipath structures.

Nigeria bears a substantial burden of prostate cancer, which represents the leading cause of cancer mortality and the most frequently diagnosed malignancy among its male population [...].

Microgrid scheduling is a nonlinear, multimodal, and highly constrained optimization problem that requires effective coordination among renewable generation, controllable distributed generators, energy storage, and grid interaction. To improve the search capability of the original Crayfish Optimization Algorithm (COA), this study proposes an Enhanced Crayfish Optimization Algorithm (ECOA) inspired by the coordination characteristics of cross-media performing arts. Rather than simply combining independent operators, ECOA constructs a state-aware and behavior-specific adaptive search framework around the intrinsic behavioral structure of COA. Specifically, a rhythm-guided adaptive search strategy is embedded into the summer-resort behavior to dynamically regulate search intensity, a multi-role collaborative guidance strategy reconstructs the competition behavior through time-varying information interaction, and a stagnation-aware stage-transition perturbation strategy selectively reactivates exploration when the search becomes stagnant. Extensive experiments are conducted on the CEC2014, CEC2017, and CEC2022 benchmark suites under six-dimensional settings, and the results are compared with those of nine representative metaheuristic algorithms. The results show that ECOA achieves highly competitive convergence accuracy and run-to-run stability on most benchmark functions. Wilcoxon rank-sum tests and Cliff’s delta effect-size analysis indicate that many of the observed improvements are statistically significant and practically meaningful, while the Friedman test ranks ECOA first in all six benchmark settings. Ablation experiments further demonstrate that all three mechanisms contribute positively to performance and that their coordinated integration is more effective than any individual strategy. Parameter-sensitivity analysis shows that ECOA maintains effective convergence over a relatively broad range of the disturbance coefficient , with providing a balanced setting across different landscapes. Finally, ECOA is applied to a deterministic day-ahead microgrid scheduling problem with explicit feasibility repair and power-balance penalty handling. Under the considered operating scenario, ECOA achieves the lowest mean operating cost of 1361.8028 among all compared algorithms and produces coordinated power-allocation schedules satisfying the modeled operational constraints. These results demonstrate the effectiveness of ECOA for complex numerical optimization and constrained engineering scheduling problems.

Hydrogel-based flexible sensors have emerged as a promising platform at the intersection of materials science, flexible electronics, and biomedical engineering, owing to their tissue-like mechanical compliance, tunable ionic conductivity, and versatile chemical functionalizability. To translate laboratory-scale hydrogel devices into durable, reliable wearable systems, this review critically summarizes recent progress in functional hydrogels and organogels, covering literature reported up to September 2026, and organizes the discussion along the complete chain from material synthesis and characterization to wearable deployment. We first outline the synthesis principles of gel network architectures, including double networks, semi-interpenetrating networks engineered with nanosheet crosslinkers, organohydrogels employing mixed solvent systems, and mechanically interlocked topologies, followed by MXene-based composite gel materials and advanced 3D printing fabrication strategies. Six representative sensing mechanisms, namely piezoresistive, capacitive, triboelectric, thermoelectric, electrochemical, and multimodal decoupling, are then qualitatively and, where possible, quantitatively compared regarding their performance characterizations. We also discuss signal processing and readout electronics for each sensing mechanism, which are critical for wearable deployment. Dedicated sections analyze performance enhancement strategies aimed at mechanical robustness and sensitivity, and summarize self-healing chemistries along with environmental adaptation approaches, such as solvent replacement and deep eutectic solvent engineering, which are essential for long-term operational stability. We further propose a minimum reporting checklist for standardization and benchmarking and provide a systematic evaluation of long-term stability, toxicity, degradation data, leachables, . Finally, we highlight application frontiers of these gel materials in health monitoring biosensing, electronic skin, and human–machine interaction, and conclude with a critical assessment of key challenges in scalable manufacturing, biocompatibility, multimodal crosstalk, energy autonomy, and environmental sustainability. A dedicated discussion of environmental impact and sustainability, covering bio-based polymers, biodegradability, recycling, and life-cycle assessment.

Post-COVID-19 balance and postural control alterations have been reported after SARS-CoV-2 infection, but individual-level phenotyping remains challenging because post-acute sequelae are heterogeneous and often lack clear clinical ground truths. We analyzed motion capture balance data from 140 participants, including 114 post-COVID-19 participants and 26 control-group participants, who completed sensory organization/postural balance tasks under single-task and cognitive dual-task conditions. Relative joint angle trajectories were transformed into 0–5 Hz frequency-domain spectra, from which 13 balance-derived task contrasts were constructed to capture cognitive dual-task versus single-task differences, closed-eyes versus open-eyes task condition differences, and related task condition changes. Joint-wise spectral contrast features were encoded using a vector-quantized variational autoencoder. Control-distant subgroup discovery was then formulated as a control-anchored, graph-based QUBO clustering problem and solved using a quantum annealing workflow. Simulated annealing and tabu search were applied to the identical BQM/QUBO formulation as classical solver-level references, whereas Gaussian mixture modeling was retained as an unconstrained classical clustering reference. Consistent with the control-anchored design of the QUBO objective, QUBO clustering identified a selective subset of post-COVID-19 participants with control-distant latent balance profiles while largely preserving the control-group reference structure. Across all task contrasts, quantum annealing assigned 1 of 307 control-group participant–contrast assignments (0.3%) and 118 of 1366 post-COVID-19 participant–contrast assignments (8.6%) to the control-distant group. Simulated annealing and tabu search produced slightly larger but similar control-distant post-COVID-19 subsets, assigning 143 of 1366 post-COVID participant–contrast assignments (10.5%) and 0 of 307 control-group participant–contrast assignments (0.0%) to the control-distant group. In contrast, GMM assigned 63 of 307 control-group participant–contrast assignments (20.5%) and 266 of 1366 post-COVID-19 participant–contrast assignments (19.5%) to the control-distant group. Parameter sensitivity analysis showed high overall assignment agreement for the same BQM/QUBO formulation, but the exact membership of the sparse control-distant subset was more variable. Simulated annealing sensitivity analysis showed overall agreement of 98.3–100.0% and control-distant Jaccard indices of 0.836–1.000 relative to the baseline, whereas a representative QPU sensitivity analysis showed overall agreement of 93.6–100.0% and control-distant Jaccard indices of 0.443–1.000. Frequency band profiles further suggested that QUBO-derived control-distant assignments corresponded to contrast-dependent and exploratory interpretable postural control patterns, particularly in low-frequency postural sway-dominant and mid–low-frequency postural control bands. These findings support the feasibility of objective-driven, control-anchored QUBO-based quantum-assisted clustering for exploratory subgroup discovery in heterogeneous, label-limited biomedical datasets. The proposed framework does not establish diagnostic criteria for long COVID or evidence of quantum speedup but provides a hypothesis-generating approach for interpretable post-COVID-19 neuromotor phenotyping and related medical data analysis applications.

Collaborating with service users with lived experience of systems and processes, including the Criminal Justice System, can help tailor services, which in turn might increase accessibility, engagement, and satisfaction. Despite domestic abuse survivors often expressing a desire to be involved in developing and improving services, opportunities to do so have traditionally been limited, and their experiences of providing a ‘victim voice’ have not been extensively explored. The present paper outlines findings from interviews conducted with five survivors who took part in a range of collaborative engagement activities with criminal justice practitioners and other service providers (e.g., housing and social services) as ‘experts by experience’. During the interviews they reflected on their experiences and considered opportunities for increased involvement of survivors in developing services and support provisions moving forward. Key themes from thematic analysis of the interview data included the importance of survivors’ voices being heard, with their experience acknowledged and their contributions valued, as well as the need for effective facilitation and management of collaborative opportunities. More broadly, notable personal benefits were described by all participants, including feeling empowered by being given the opportunity to have a voice in driving change.

The red-claw crayfish, Cherax quadricarinatus, is a commercially valuable freshwater aquaculture species, with muscle flavor representing a core trait driving consumer preference and market value. Under identical farming conditions, same-batch crayfish commonly develop marked size divergence within and between sexes, but the impacts of this variation on muscle volatile flavor profiles remain largely unexplored. Here, C. quadricarinatus reared under consistent environmental conditions were categorized into four groups by body weight and sex: large-size female (GUBF), large-size male (GUBM), small-size female (GUSF), and small-size male (GUSM). Headspace solid-phase microextraction–gas chromatography–mass spectrometry (HS-SPME/GC-MS) was employed to profile volatile organic compounds. Multivariate statistical analysis, relative odor activity value calculation, metabolic pathway and network analysis, and receiver operating characteristic (ROC) analysis were combined to dissect flavor variation patterns, identify key aroma compounds, reveal underlying metabolic mechanisms, and screen potential biomarkers. Proximate composition analysis showed significant size differences in crude protein, lipid, moisture, and meat yield, with no significant sex differences. One hundred thirty-six volatile metabolites across 15 chemical categories were identified in all samples. Multivariate statistical analyses revealed clear separation among the four groups, suggesting that both body size and sex shape muscle volatile metabolite profiles, with stronger effects observed in females. Thirty-eight shared aroma-active compounds were detected, mainly including alcohols, aldehydes, ketones, esters, and aromatic hydrocarbons. The overall sensory profile was dominated by sweet-like notes, followed by fruity and green notes. Sex-related flavor differences were relatively slight in large-size crayfish but pronounced in small-size individuals. Large-size female crayfish had simpler flavor composition, while small-size females showed higher diversity and abundance of flavor compounds; size variation had limited effects on male flavor. Butanoate metabolism was significantly enriched in both the small-size sex comparison and female size comparison. Core metabolic frameworks were generally conserved across groups, but key hub metabolites differed by comparison type. This study systematically characterized the volatile flavor profiles of C. quadricarinatus muscle across different body sizes and sexes under controlled farming conditions, providing preliminary references for quality evaluation and premium aquaculture optimization of C. quadricarinatus.

This article studies how narrativity, performativity and visuality are employed in Shakespeare comics: single-volume adaptations of individual Shakespeare plays in comic book, graphic novel or manga form. The cases studied include two Classics Illustrated titles (Julius Caesar, Hamlet), two No Fear Shakespeare Graphic Novels (Hamlet, Macbeth) and the Manga Classics Macbeth. These are all geared towards older children, but like most comics they can be enjoyed by readers of all ages. In discussions framed by adaptation theory and research on children’s editions of Shakespeare, I study how verbal content such as paraphrase, captions in text boxes and original Shakespearean verse interact with visual elements in these comics, and I argue that the legibility, aesthetic interest and reader engagement engendered by Shakespeare comics emerge primarily from their multimodal narrative design—which has literary, dramatic and visual arts qualities—whilst paraphrasing the verbal language is less effective. Scholarship on Shakespearean prose retellings for older children identifies cultural assumptions that underlie this genre of adaptation and demonstrates how narrative has been used to reinscribe problematic moral stances, worldviews and a form of bardolatry. Comics’ visual–verbal narrative design enables reinterrogations of the canon through comparing several Shakespeare comics. I show how the manner in which framing devices, drawing styles, character designs and settings interact and interblend with the verbal content, thus determining how Shakespeare comics create meaning, and how they help us reassess Shakespeare’s position in culture. At the same time, the conspicuous co-authorship seen in Shakespeare comics, between text, textual adaptation, mise-en-page and visual art, contributes towards subverting the notion of Shakespeare as singular genius.