Browse Articles

Efficiency of anchorage systems for RC beams strengthened in flexure using basalt fiber reinforced polymers

Abstract Recently, Basalt Fiber Reinforced Polymer (BFRP) composites emerged as a new FRP type, in addition to the commonly used glass, carbon, and aramid. The common premature debonding failure of externally bonded fiber-reinforced polymer (FRP) composites, when applied to reinforced concrete (RC) structures, has made searching for efficient anchorage systems an inevitable and challenging issue. Many studies through experimental testing and numerical modeling verified that anchorages applied to FRP systems not only enhance the member’s ductility and strength but also prevent the typical debonding of the FRP at a low strain level compared to the rupture strain. Research is needed, however, to understand the efficiency of different anchorage systems when applied to relatively high-strain BFRP sheets to strengthen concrete members. This research presents an experimental study aimed at investigating the efficiency of using anchorage systems in enhancing the flexural behavior of concrete beams strengthened with BFRP sheets. A total of eight concrete beams measuring 3100 mm length, 150 mm width and 350 mm depth were constructed and tested up to failure. The test parameters were the number of BFRP layers, the development length, and anchorage systems. The beam specimens were designed in accordance with ACI 440.2R-17 and tested under four-point bending over a clear span of 2800 mm until failure. The results showed that BFRP strengthening enhanced the flexural capacity of beams by up to 33% compared to the control specimen. However, increasing the number of BFRP layers without proper anchorage did not significantly improve strength due to premature debonding. The use of U-wrap anchorage successfully changed the failure mode from debonding to BFRP rupture, leading to more efficient utilization of the composite material, with anchorage effectiveness factor k fab  = 2.36, while spike anchors with anchor dowels 150 mm inside the concrete have an anchorage effectiveness factor k fab  = 1.97 which showed limited effectiveness depending on embedment depth. In addition, strengthened beams exhibited a reduction in ductility of approximately 28% compared to the control beam. The findings highlight the critical role of anchorage systems in achieving optimal performance of BFRP-strengthened RC beams.

The role of reduced aerosol masking from air pollutant emission reductions in recent global warming acceleration (2013–2023)

In recent years, the Earth has likely experienced an accelerated warming trend, raising growing interest in the possible contributing factors. From 2013 to 2023, global anthropogenic air pollutant emissions declined significantly and brought enormous public health benefits, but the contribution of reduced aerosol masking of greenhouse warming to recent trends remains uncertain. Using two state-of-the-art global climate models, we show that global air pollutant emission reductions during 2013–2023 caused a global effective radiative forcing of 0.16 W/m 2 (90% CI: 0.13 to 0.20), with international shipping, China, and other land regions contributing 0.05 W/m 2 (0.00 to 0.09), 0.07 W/m 2 (0.03 to 0.11), and 0.05 W/m 2 (0.00 to 0.09), respectively. International shipping contributes disproportionately to radiative forcing relative to its emission reductions, highlighting its high forcing efficiency. The combined forcings are estimated to have contributed a warming of 0.044 °C (0.012 to 0.076) over 2013–2023, accounting for 52% (14 to 90%) of the observed warming acceleration (0.084 °C/decade) relative to the 1970–2012 trend. Especially strong reductions in aerosol–cloud interactions are found over the North Pacific, driven primarily by the downwind impacts of East Asian emission reductions. Aerosol unmasking contributes to the recent acceleration of warming and highlights the importance of accurately quantifying air pollutant emission changes for future climate projections.

Correction: The impact of maternal versus paternal imprisonment on their children’s health: A scoping review

Eco-friendly synthesis of coumarins using lemon juice as a natural catalyst and application as disperse dyes on polyester fabric

Abstract An efficient, low-cost, and eco-friendly protocol has been carried out for the synthesis of two coumarin derivatives using lemon juice as an eco-friendly acidic catalyst. The chemical structures of these derivatives were characterized using melting points as well as spectral data (IR, NMR, and MS). By optimizing dyeing factors like time, temperature, and pH, the study’s main goal was to ascertain how dispersion dyes 10 and 7 react when dyeing polyester fabrics. The colored polyester samples varied in color from light brown to yellowish brown to reddish brown to dark brown, depending on the coupler moieties at a depth of 5%. To achieve excellent colour strength in value (K/S = 21.7), the ideal dyeing conditions for dye 10 were 30 min, pH of 2, and 130 °C at shade 5%. While the ideal dyeing conditions for disperse dyes dye 7 (K/S = 20.8) were 30 min, pH of 4, and 130 °C at a shade of 5%. When everything is considered, synthetic dyes appear to be good choices for adding a variety of colors to polyester textiles.

Correction for Sava-Segal et al., Narrative “twist” shifts within-individual neural representations of dissociable story features

Spatial disparities and multilevel determinants of childhood diarrhea in Mozambique: Evidence from the 2022–2023 Demographic and Health Survey (DHS)

Background Childhood diarrhea remains a major public health problem, particularly in sub-Saharan Africa, contributing substantially to morbidity and mortality and hindering progress toward Sustainable Development Goal 3 (SDG 3), which aims to end preventable under-five deaths. Marked regional variations in diarrhea burden highlight the need for updated analyses to guide public health planning and resource allocation. This study examines the spatial distribution and key determinants of diarrhea among under-five children to inform targeted interventions. Methods Data from 9,799 under-five children in the 2022–2023 Mozambique Demographic and Health Survey were analyzed to estimate diarrhea prevalence and identify associated determinants. Weighted analysis, spatial scan statistics (SaTScan), hotspot mapping, and multilevel logistic regression were used to assess individual- and community-level factors. Significant predictors were identified using adjusted odds ratios (AORs) with 95% confidence intervals (CIs) and p ≤ 0.05. Model variation was assessed using the intra-class correlation coefficient (ICC), median odds ratio (MOR), and proportional change in variance (PCV), and spatial patterns were mapped using ArcGIS. Results The weighted prevalence of diarrhea among under-five children in Mozambique was 8.8% (95% CI: 7.8–9.6%), highest in Niassa (14.5%), Cabo Delgado (14.0%), and Maputo City (13.4%), and lowest in Maputo Province (5.1%), Zambézia (5.5%), and Manica (5.8%). Multilevel analysis showed that children aged 12–23 months had higher odds of diarrhea (AOR = 1.36, 95% CI: 1.11–1.66). In contrast, children aged 24–59 months (AOR = 0.49, 95% CI: 0.41–0.59), maternal education (AOR = 0.77, 95% CI: 0.63–0.96), and rural residence (AOR = 0.69, 95% CI: 0.52–0.91) were associated with lower odds. Children residing in Nampula, Zambézia, Manica, Sofala, and Maputo Province had significantly lower odds of diarrhea compared to those in Niassa. Health-seeking behavior was strongly associated with reported diarrhea (AOR = 4.85, 95% CI: 4.10–5.74), possibly reflecting reporting bias. Conclusions Childhood diarrhea in Mozambique exhibits marked regional variation, with the highest burden in Niassa, Cabo Delgado, and Maputo City, and the lowest in Maputo Province, Zambézia, and Manica. Key determinants include child age, maternal education, and geographic region, while rural residence appears protective. These findings highlight the need for targeted, age- and region-specific interventions and strengthened maternal and community support to reduce childhood diarrhea and accelerate progress toward SDG 3.

Risk-aware tactical path planning in partially observable environments via trajectory-value factorized recurrent PPO

Quality of patient safety indicators in intensive care units: Protocol for a systematic review

Patient safety is an important issue in intensive care units. Patient safety indicators are often incorporated without undergoing the proper process of development and validation, which leads to problems with construct validity, measurement reliability, feasibility, and comparability across institutions and countries. This study reports a protocol for a systematic review that aims to identify and assess the validity of patient safety indicators used in the intensive care unit context. This protocol was previously registered in PROSPERO (CRD42024617125). We will search for original studies in the following databases: PubMed (Medline), Scopus, EMBASE (Elsevier), CINHAL (EBSCO), Web of Science, Cochrane Database and Google Scholar for grey literature. We will include methodological or observational studies that report the construction and/or validation of patient safety indicators. Two reviewers will independently screen and assess the studies, and disagreements will be resolved by a third reviewer. We will assess the quality of the studies using the COnsensus-based Standards for the selection of health status Measurement INstruments (COSMIN) checklist. To assess indicator validity, we will use the Appraisal of Indicators through Research and Evaluation (AIRE) instrument. We will classify the indicators according to Donabedian attributes of structure, process and outcomes, as well as the contexts of intensive care, such as pediatric, neonatal or cardiac units, for example. We will also perform descriptive analysis of each category assessed. We expect that our review will contribute to providing a valid set of indicators and help to identify gaps regarding patient safety dimensions that need to be assessed by new indicators.

Predictive metacognition: a neuro-computational framework for self-monitoring in large language models

Abstract Large Language Models demonstrate remarkable capabilities but suffer from critical metacognitive deficits, manifesting as overconfidence and hallucination, which severely limit their deployment in high-stakes applications. We introduce Predictive Metacognition, a neurobiologically-inspired framework that integrates principles of predictive processing and anterior cingulate cortex monitoring into transformer architectures. Our approach implements Error-Driven Learning and Dual-Process Monitoring through specialised fine-tuning that trains models to simultaneously generate responses and assess their own performance reliability. We fine-tuned Llama-3-8B-Instruct and Phi-3-Mini-4k-Instruct using LoRA (rank=8, $$\alpha =16$$ ) on 4,000 strategically constructed examples spanning varying confidence levels. Comprehensive evaluation against state-of-the-art baselines, including GPT-4o and Claude-3.5-Sonnet, revealed statistically significant improvements in confidence calibration. Our metacognitive models achieved substantial reductions in Brier Score (11.6% and 17.2% respectively) and Expected Calibration Error ( $$p < 0.023$$ , Cohen’s $$d = 1.456$$ ). Critically, these improvements generalised robustly to out-of-domain tasks while maintaining competitive task accuracy. This work establishes a computationally tractable implementation of biologically-inspired metacognitive architecture for large language models, offering a principled pathway towards AI systems capable of reliable intrinsic self-monitoring that can more accurately assess their own knowledge boundaries and express appropriate uncertainty.

Reversible superdeformability of hiPSC epithelial cortinoids

Epithelial cortinoids, fluid-filled shells formed from induced pluripotent stem cells (iPSCs), must accommodate large deformations during growth and morphogenesis. Using inflation–deflation assays and high-resolution imaging, we find that these fluid-filled shells are weakly pressurized and achieve extreme deformability through reversible soft modes of deformation accommodated by the cytoskeleton. We show that cytoskeletal elements such as actin localized along lateral cell edges undergo tilt and bend instabilities that buffer mechanical load by decoupling apico–basal stretching from lateral extension. These reversible instabilities act as elastic safety valves, permitting large shape changes without loss of epithelial hydraulic and topological integrity. A minimal theoretical and computational model demonstrates how tilt and bend reduce effective resistance to radial thinning and explains the observed pressure–strain softening. Thus, iPSC shells exploit reversible cytoskeletal instabilities as mechanical buffers, enabling robust tolerance of large deformations in developing epithelia.

Determinants of maternal postnatal care utilization in Bangladesh: A machine learning and SHAP-based analysis of BDHS 2022 data

Postnatal care (PNC) plays a crucial role in minimizing maternal and neonatal morbidity and mortality, but the uptake of services in Bangladesh remains below the recommended level. Although logistic regression has been widely used, it may miss complex nonlinear interactions among social, economic, and healthcare factors. This study contributes to the body of knowledge by using machine learning (ML) to identify the most significant determinants of PNC and to enhance prediction accuracy. We compared logistic regression to several ML models, including Random Forest, XGBoost, CatBoost, Support Vector Machine, AdaBoost, and Gradient Boosting, using nationally representative data from the 2022 Bangladesh Demographic and Health Survey (BDHS) with ADASYN oversampling to correct class imbalance. Among all models, Random Forest achieved the highest AUC (0.9050), closely followed by XGBoost (0.9036) and CatBoost (0.9028), all of which substantially outperformed logistic regression (AUC = 0.8470). SHAP analysis of the Random Forest model indicated that delivery place, husband’s occupation, rural residence, wealth index, and media exposure were the most influential predictors of PNC utilization, alongside maternal education, women’s occupation, and age-related factors. The results indicate that ML is more effective than classical procedures for revealing latent patterns and making accurate predictions. Policy implications include encouraging facility-based deliveries, improving maternal education, reducing wealth disparities, and enhancing media coverage of health, particularly among rural and low-income groups. This paper not only identifies key drivers of PNC in Bangladesh but also demonstrates how ML can supplement traditional methods to reinforce maternal health policy and interventions.

Multi-agent collaboration for coherent long-video music synthesis

Reply to Guido et al.: The importance of credibility in outreach interventions

Characteristics and outcome of congenital mesoblastic nephroma: A report of 376 patients registered in the SIOP 93-01, SIOP WT 2001, UK-IMPORT, and AIEOP protocols

Background Congenital mesoblastic nephroma (CMN) is the most common renal neoplasm diagnosed in the very first months of life. Complete nephrectomy only is the gold standard treatment. Objectives and methods This retrospective study aimed to explore the characteristics and outcome of CMN patients registered in the SIOP 93–01, SIOP WT 2001, UK-IMPORT, and AIEOP studies (1993–2019). Results A total of 376 CMN cases were identified, with a median age at diagnosis of 28 days. Stage information was available for 337 patients: 92/337 (27.4%) were diagnosed with stage I, 177/337 (52.6%) with stage II, and 67/337 (20%) with stage III. Among 272 patients with available histological data, 113/272 (41.5%) had classic, 105/272 (38.6%) cellular, and 54/272 (19.9%) mixed subtype. Treatment details were available for 314 patients; 248 (79%) underwent initial surgery, and 66 (21%) received preoperative chemotherapy. Among the latter group, 60% of patients showed a measurable reduction in tumor volume, indicating a favorable response to chemotherapy. The 5-year event-free survival rate was 93.8%, and the overall survival rate was 96.9%. The cumulative 5-year incidence of relapse was 5.3%, with a median time to recurrence of 4 months. Of the 16 relapse cases, 8 were in the cellular subtype, 5 in the mixed subtype, and 3 in the classical subtype. Conclusions This study confirms that CMN patients have an excellent outcome, with complete surgical resection being curative in the majority of cases. Chemosensitivity is observed in a significant proportion, suggesting that neoadjuvant chemotherapy may be a viable option in selected cases. While age at diagnosis, histological subtype, and survival outcomes are consistent with previous reports, we highlight that recurrences, though infrequent, tend to occur early and are not restricted to the cellular subtype. Further prospective studies and molecular investigations are required to refine clinical management strategies and update treatment recommendations.

The impact of vaginal bromocriptine on reducing pain and menstrual bleeding in women with adenomyosis: a randomized controlled trial

Directed interactions between electrophysiological, vascular, and fluid dynamics in the sleeping brain

Retraction: A novel primary stability test method for artificial acetabular shells considering vertical load during level walking and shell position

Retraction Note: Artificial intelligence-augmented smart grid architecture for cyber intrusion detection and mitigation in electric vehicle charging infrastructure

Genomic diversity and the domestication history of cotton ( <i>Gossypium hirsutum</i> )

Gossypium hirsutum is the leading fiber crop globally, but its origin as a domesticated plant and patterns of diversity in the wild remain to be elucidated. Here, we use extensive sampling of wild populations and comparative genome sequence data to illuminate the scope and patterning of wild cotton diversity across its native range. Analyses confirm the hypothesis that the Yucatán Peninsula (México) is the center of domestication, from which the original perennial forms and later modern annualized cultivars were derived. Population structure and phylogenomic analyses indicate that northwestern Yucatán harbors greater genetic diversity relative to smaller, geographically dispersed populations in northeastern Yucatán and the Caribbean basin. Genetic load and transposable element burden also are the lowest in northwestern Yucatán relative to other regions, consistent with its greater diversity and reflecting the effects of historical genetic bottlenecks in other populations. Populations from Florida and elsewhere in the Caribbean basin maintain unique pockets of diversity. Analyses of selection suggest that cotton domestication entailed long-term accumulation of mutations with relatively minor phenotypic effects, as opposed to a more punctuated process involving major domestication genes. Our study quantifies the scope and scale of genomic diversity in wild cotton, the origin of the cultivated gene pool, and the likely ecological and anthropogenic processes that shaped extant diversity and modern geographic patterning.

Knowledge of HPV and HPV vaccine and its association with vaccination willingness among female undergraduates: A comparative cross-sectional study between healthcare and non-healthcare majors in Chengdu, China

Purpose This study aimed to assess levels of knowledge about human papillomavirus (HPV) and its vaccine among female undergraduates compare these levels between healthcare and non-healthcare majors, and examine their associations with vaccination willingness. Methods A cross-sectional survey was conducted among 1,293 female undergraduate students from two universities in Chengdu. Knowledge was measured using a self-designed questionnaire, categorized into basic and advanced domains. Vaccination willingness was assessed via a 5-point Likert scale. Data were analyzed using descriptive statistics, t-tests, analysis of variance and hierarchical multiple regression to identify associations and compare the two student groups. Results A total of 1191 valid questionnaires were analyzed. Participants demonstrated moderate basic knowledge of HPV (mean score = 5.21 ± 1.91/8) and its vaccine (mean score = 2.99 ± 1.05/5), but low advanced knowledge of HPV (mean score = 1.02 ± 1.03/6) and its vaccine (mean score = 2.00 ± 1.53/6). Students in healthcare majors demonstrated significantly higher scores in HPV basic knowledge (p = 0.023),HPV vaccine basic knowledge (p = 0.012), and advanced HPV vaccine knowledge (p &lt; 0.001) compared to their non-healthcare peers. Overall vaccination willingness was higher among healthcare majors (p = 0.011), students from urban areas (p &lt; 0.001), and those with higher monthly living expenses (p &lt; 0.001). Hierarchical multiple regression analysis revealed that higher scores in basic knowledge were significantly associated with greater vaccination willingness (p &lt; 0.001, △R 2  = 0.127). Conclusions The study confirms a significant knowledge and intention gap between healthcare and non-healthcare students. Basic knowledge of HPV and its vaccine acts as an effective peripheral cue that boosts vaccination willingness, aligning with the Elaboration Likelihood Model (ELM). However, widespread deficits in advanced knowledge, even among healthcare students, impede central-route processing and durable attitude formation. Public health efforts should prioritize clear core messaging while simplifying and disseminating advanced knowledge to narrow knowledge gaps across student students with different academic backgrounds.