A novel self-curing active cold patch asphalt mixture: Performance evaluation and mechanism analysis

Cold patch asphalt mixtures (CPAMs) are increasingly favored for pothole repairs in asphalt pavements due to their environmental benefits and ease of construction. However, their low strength and durability have hindered broader application, necessitating the development of CPAMs with enhanced engineering performance. To address these challenges, this study proposes a novel self-curing active CPAM incorporating solvent naphtha (SN) as a diluent and polymerized methylene diphenyl diisocyanate (PMDI) as a polymer modifier. Various SN-to-PMDI ratios and SN-PMDI contents relative to virgin bitumen (VB) were evaluated to produce cold patch asphalt liquid (CPAL) and the corresponding CPAMs. Viscosity tests confirmed that SN effectively reduces VB viscosity, ensuring its workability. Specifically, adding 10 % SN reduced VB viscosity by approximately 30 %, while higher SN content (e.g., 30 %) significantly compromised mechanical performance. Mechanical evaluations, including Marshall stability, moisture susceptibility, crack resistance, freeze-thaw resistance, and rutting resistance, demonstrated that CPAM containing 20 % SN-PMDI with a 50:50 SN-to-PMDI ratio achieved excellent mechanical performance comparable to hot mix asphalt (HMA). Mechanism analysis through FTIR tests further revealed that PMDI reacts with atmospheric moisture, transforming isocyanate groups (-NCO) into carbamate groups (-NHCOO), and also interacts with hydroxyl groups on limestone aggregates, forming carbamate compounds, which contribute to a 20 % increase in strength development. Overall, this study introduces a novel approach for preparing high-performance CPAM, providing a promising solution for durable and efficient pothole repairs in practical engineering applications

Framework for uncertainty evaluation in optical surface topography measurement using a virtual instrument

Uncertainty evaluation in the measurement of surfaces with complex topography using optical techniques remains a challenge due to the complex interaction between light and the surfaces. The ISO 25178 part 600 specification standard simplifies uncertainty evaluation by introducing a set of agreed metrological characteristics that can be propagated through a mathematical model. To complement this, we developed a virtual coherence scanning interferometer to model error sources and provide task-specific uncertainty evaluation. This paper presents a framework for evaluating measurement uncertainty of areal surface texture parameters, using both the metrological characteristics approach and the virtual instrument method. We demonstrate this framework by assessing the uncertainty of the Sq parameter, which represents the root-mean-square of surface heights, for sinusoidal and quasi-random surfaces. By comparing the combined standard uncertainty from both approaches, we quantify the contribution of topography fidelity, a key but difficult-to-evaluate characteristic. The proposed method offers a comprehensive understanding of uncertainty in optical surface measurement, leading to improved tolerancing in manufacturing

Target product profiles for digital health technologies including those with artificial intelligence: a systematic review

Digital health technologies (DHTs), including those incorporating artificial intelligence (AI), have the potential to improve healthcare access, efficiency, and quality, reducing gaps between healthcare capacity and demand. Despite prioritisation in health policy, the adoption of DHTs remains limited, especially for AI, in part due to complex system requirements. Target product profiles (TPPs) are documents outlining the characteristics necessary for medical technologies to be utilised in practice and offer a way to align DHTs’ research and development with health systems’ needs. This systematic review examines current DHT TPPs’ methodologies, stakeholders, and contents. A total of 14 TPPs were identified, most targeted at low- and middle-income settings and communicable diseases. Only one TPP outlined the requirements for an AI device specifically. In total, 248 different characteristics were reported across the TPPs identified and were consolidated down to 33 key characteristics. Some considerations for DHTs’ successful adoption, such as regulatory requirements or environmental sustainability, were reported inconsistently or not at all. There was little standardisation in TPP development or contents, and limited transparency in reporting. Our findings emphasise the need for guidelines for TPP development, could help inform these, and could be used as a basis to develop future DHT TPPs. Systematic Review Registration: https://www.researchprotocols.org/2024/1/e50568/authors

Unravelling the Data Puzzle: A Total Survey Error Perspective on Adult Learning and Education Participation in the UK

This paper investigates the methodological discrepancies underlying the measurement of adult learning and education (ALE) participation in the UK by focusing on four major surveys—APiL, PIAAC, AES, and LFS. Grounded in the Total Survey Error (TSE) framework, we systematically examined the surveys’ documentation and compared their definitions, reference periods, and operationalization of ALE. Our review identified significant inconsistencies, including mismatched age ranges, divergent weighting schemes, and ambiguous question phrasing. These methodological differences potentially undermine data validity and complicate cross-survey comparisons. As a result, policymakers and researchers may be left with an uncertain evidence base for shaping adult education policies. To address these issues, we propose two scenarios: first, conducting qualitative interviews to refine how participation questions are conceptualized by adults, and second, implementing survey experiments to assess the effects of various reference periods, data collection modes, and question formats on reported participation rates. We suggest that strengthening the methodological foundations of ALE surveys can foster greater confidence in the reliability of adult education statistics, informing more nuanced policy interventions and advancing future research directions

Pattern formation on an ice surface

A linear stability model based on a phase-field method is established to study the formation of ripples on the ice surface. The pattern on horizontal ice surfaces, e.g. glaciers and frozen lakes, is found to be originating from a gravity-driven instability by studying ice–water–air flows with a range of water and ice thicknesses. Contrary to gravity, surface tension and viscosity act to suppress the instability. The results demonstrate that a larger value of either water thickness or ice thickness corresponds to a longer dominant wavelength of the pattern, and a favourable wavelength of 90 mm is predicted, in agreement with observations from nature. Furthermore, the profiles of the most unstable perturbations are found to be with two peaks at the ice–water and water–air interfaces whose ratio decreases exponentially with the water thickness and wavenumber

Quantifying diagnostic intervals and routes to diagnosis for children and young people with cancer in the UK (Childhood Cancer Diagnosis study, CCD): a population-based observational study

Background: Childhood cancer is a global disease burden, with early diagnosis a priority. We quantified diagnostic intervals and referral routes for children and young people (CYP 0–18 years) diagnosed with cancer in the UK. Methods: All CYP diagnosed between September 2020–March 2023 were eligible. Demographic, referral, and symptom data were collected prospectively. Patient interval (PI), diagnostic interval (DI), and total diagnostic interval (TDI) were calculated. Findings: 1957 CYP (mean age 7.4 years, 55% male, 78% white) participated. Median PI, DI, and TDI were 1.1 (IQR 0.1–4.0; range 0–164), 1.7 (IQR 0.4–5.9; range 0–310), and 4.6 weeks (IQR 2.0–11.4; range 0–310), respectively. Intervals were unaffected by sex, ethnicity or deprivation index (IMD). Median TDI was longest in 15–18 years (8.7 weeks, IQR 3.0–17.4) and bone tumours (12.6 weeks, IQR 6.6–23.4) and shortest in under ones (3.7 weeks, IQR 1.0–8.1) and renal tumours (2.3 weeks, IQR 0.9–5.0). 74% (n = 1438) had 1–3 pre-diagnostic healthcare contacts; 67% (n = 1312) presented emergently, with a median of 4.0 (range 0–26) symptoms. CYP with Langerhans Cell Histiocytosis were most likely to have ≥4 visits when compared with leukaemia (adjusted OR 7.48, 95% CI 3.54–15.82), followed by central nervous system, bone, and soft tissue tumours. Interpretation: This study highlights equal access to diagnosis for sex, ethnicity and IMD, but disparities for age and diagnostic groups. These data will inform professional and public health strategies and health policy to accelerate diagnosis for all. Funding: National Institute for Health and Social Care Research (NIHR) DRF-2018-11-ST2-055

Reimagining Qualitative Literature Reviewing Through Collaborative Feedback Poetry

This think piece contributes to qualitative inquiry and higher education by introducing collaborative feedback poetry as a theoretically and pedagogically grounded approach to literature reviewing. Co-authored by an education professor and a graduate student, this article explores how composing poetry in response to academic texts—specifically poetic inquiries by professors and graduate students—enriched their learning and fostered mutual understanding, intercultural exchange, and creative academic engagement. By shifting from summary and critique to affective, polyvocal engagement, this approach extends comprehension and connection with complex personal and social issues such as identity, exclusion, and belonging. The authors position collaborative feedback poetry as a developmental and educational tool that promotes epistemological diversity and subjective knowing as vital to vigorous qualitative research. Their conclusions suggest that integrating poetry can reshape how literature is read, interpreted, and taught—inviting researchers, educators, and students to experience emotionally resonant, polyvocal, and imaginative academic knowledge and practices

Blockchain in the pharmaceutical sector: empirical evidence on the associated challenges and countermeasures

The pharmaceutical sector is experiencing rapid growth in global medicine usage and spending. As the sector expands, so do risks. Blockchain technology promises significant benefits for addressing key issues in the pharmaceutical supply chains, such as enhancing traceability, preventing counterfeit drugs, and securing sensitive data. However, its adoption is not without criticism, facing challenges such as high implementation costs, regulatory uncertainties, and even skepticism about its purported benefits. This study provides the first empirical analysis of blockchain adoption challenges and countermeasures in the pharmaceutical industry. The research aims to identify key challenges and propose effective solutions to support broader implementation. A three-step methodology was employed: a systematic literature review to identify challenges, followed by a Delphi study to assess their relevance, and finally, a questionnaire collecting practical countermeasures. Seventeen major challenges and eight sets of countermeasures were identified and prioritized, with "IT security" being ranked as the most critical challenge and "Education and training" as the most effective countermeasure as it tackles more pressing challenges. The results were then analyzed using the Technology-Organization-Environment (TOE) framework and the Stakeholder Theory. The use of these complementary frameworks allowed to shed light on how different stakeholders can address the different challenges based on their roles, emphasizing the importance of their collective and collaborative efforts. This integration of theoretical frameworks provides valuable practical insights for addressing blockchain-related challenges and accelerating its adoption. Moreover, this research compares the pharmaceutical sector with other application areas, extending insights into blockchain adoption across industries