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Titanium and its alloys are widely used for orthopedic and dental implants because of their favorable bone-matching elastic modulus, corrosion resistance, and biocompatibility. However, implant-associated infection and insufficient early osseointegration continue to compromise their long-term clinical performance. Here, inspired by natural micro- and nano-topography such as cicada wings and lotus leaves, we fabricated hierarchical surfaces comprising titanium micro-pillar arrays coated with TiO₂ nanotubes. Micro-pillar arrays with scanning pitches of 40, 60, and 80 μm were fabricated via femtosecond laser ablation, followed by in situ anodization to grow TiO₂ nanotubes approximately 100 nm in diameter. The hierarchical architecture integrates micro-pillars and TiO₂ nanotubes to enhance antibacterial performance and bioactivity: the micro-pillar arrays coated with nanotubes provide a three-dimensional microenvironment for cell adhesion, and the TiO₂ nanotubes show contact-killing antibacterial function. The 40-MNTs sample (40 μm micro-pillars coated with TiO₂ nanotubes) achieved the highest antibacterial efficiency while effectively supporting mesenchymal stem cell adhesion and proliferation. These findings show that combining micro-scale geometry with nano-topographical cues can improve antibacterial performance while maintaining cytocompatibility, providing a drug-free surface engineering strategy for titanium implants. Full article

Tropical pumpkin (Cucurbita spp.) is an underutilized, nutrient-dense vegetable crop with potential to enhance food and nutrition security and generate household income among farming communities. In Uganda, farmers primarily obtain pumpkin seed through informal seed systems, including farmer-produced and -managed sources where seed quality is largely undocumented. This study evaluated the quality of pumpkin seeds collected from 16 selected districts in Uganda and provides the first baseline assessment of tropical pumpkin seed quality within farmer-produced and farmer-managed systems. Seed quality in this study was defined as the ability of seeds to germinate, exhibit high vigor, and remain free of fungal growth. Pumpkin seeds were assessed at 0, 3, and 6 months of storage under conditions representative of local seed traders (25 ± 5 °C; 60 ± 5% RH). Seed-associated fungi recovered on PDA containing streptomycin sulfate after 14 days of incubation were identified morphologically. Seed purity ranged widely (43.8–99.5%), indicating substantial variability among seed sources. Seed germination varied among districts, with most seeds showing improved germination after storage, whereas seed vigor declined with storage duration. Five putatively seedborne fungal genera, Fusarium, Aspergillus, Colletotrichum, Alternaria, and Rhizopus spp., were identified. The findings demonstrate substantial heterogeneity in farmer-produced and -managed seed, which is a predominant seed source in Uganda. Full article

This study investigates the optimization of airflow distribution and pressure drops in H14 HEPA minipleat filters through the introduction of the hot-melt cell as the fundamental hydraulic unit governing local flow behavior. A coupled analytical framework integrating Falkner–Skan boundary-layer theory, Darcy–Weisbach channel friction, and Darcy porous-medium flow was developed and experimentally tested using velocity measurements obtained in a 600 m³/h test bench operating at a frontal velocity of 0.45 m/s under laminar-flow conditions. Ten primary geometric configurations and 21 hot-melt distribution scenarios (totaling 31 cases plus an optimized design case) were systematically evaluated by varying cell width (W), inlet height (H_i), and pleat length (L). Experimental and analytical results reveal significant velocity heterogeneity in the vicinity of the filter surface, which progressively decreases with distance from the filter, while localized velocity amplification is observed near the hot-melt separators. The analysis demonstrates that hydraulic diameter, pleat angle, and hot-melt spacing are the dominant parameters governing pressure drop generation and flow redistribution. Among the configurations investigated, a model-predicted optimized design (W = 46.25 mm, L = 55.00 mm, 230 pleats) yields a theoretical pressure drop reduction of up to 29.23% without significantly compromising the effective filtration area. These results provide an analytical framework for pre-prototyping optimization, although experimental verification of physical prototype validation for mechanical integrity and the preservation of initial efficiency, among other governing physical quantities, remains essential. The results demonstrate that the proposed hot-melt cell concept provides a practical engineering framework for the aerodynamic optimization of minipleat HEPA filters, enabling improved flow uniformity and reduced energy consumption in cleanroom applications. Full article

Background: Diet during pregnancy plays a crucial role in promoting healthy dietary behaviours and positive maternal and child health outcomes. However, evidence regarding the factors associated with healthy dietary behaviours among pregnant women is limited. The SaperePer study aims to assess the dietary behaviours of pregnant women and identify the sociodemographic, lifestyle, and health-related factors that influence their choices. Methods: This cross-sectional analysis included 1254 pregnant women recruited from two Northern Italian centres (Turin and Cuneo). Dietary behaviour was assessed using a questionnaire, which generated a diet-related scores. Associations between these scores and participants’ characteristics were investigated using multivariable regression models. Results: Overall, participants reported relatively favourable dietary habits and a low prevalence of risky behaviours. Higher socioeconomic position was found to be one of the strongest contributing factors to dietary behaviour (medium vs. low β (95% CI) = 1.18 (0.93, 1.42); high vs. low β (95% CI) = 1.57 (1.10, 2.04), both p < 0.001). Higher dietary behaviour scores were positively associated with older maternal age, moderate physical activity, and better perceived physical and psychological health, whereas smoking and alcohol consumption were associated with lower scores. Conclusions: Dietary behaviour during pregnancy appears to be shaped by a complex interplay of socioeconomic, behavioural, and health-related factors rather than by nutritional knowledge alone. These findings highlight the need for tailored interventions that address the social and contextual features of dietary behaviour to encourage healthier habits during pregnancy. Full article

Background/Objectives: Motivational interviewing (MI) is an established approach to addressing vaccine hesitancy, yet immediate changes following dedicated training for family physicians remain insufficiently documented in Romania. This study evaluated pre–post changes in physicians’ MI knowledge, self-reported communication behaviour, and self-perceived ability to counsel patients about vaccination, together with patient-level change following consultations delivered by trained physicians. Methods: This uncontrolled pre–post study used a voluntary, self-selected non-probability sample of 28 family physicians recruited through announcements distributed via county family medicine associations; participants completed paired assessments immediately before and after structured MI-based training. The three main physician-level outcomes were MI knowledge (MISI), corrected self-reported MI communication behaviour (MIBI), and self-perceived MI ability (SPMI). The linked component comprised 151 patients nested within 15 physicians. Patient changes were averaged within physician, and the physician-level mean patient composite change was used as the principal outcome of this component. Paired physician changes and physician-aggregated patient change were assessed using Wilcoxon tests, rank-biserial effect sizes, and bootstrap 95% confidence intervals (CIs), with Holm adjustment across the three physician outcomes. Results: Mean MISI increased by 39.80 percentage points (95% CI: 29.59–50.51), though the limited internal consistency of this seven-item composite requires item-level interpretation, and corrected MIBI by 0.44 points (95% CI: 0.20–0.68; r_rb = 0.75) and SPMI by 1.22 points (95% CI: 0.89–1.61; r_rb = 0.99); all Holm-adjusted p-values were <0.001. Across the 15 linked physicians, the mean patient composite change was 0.55 points (95% CI: 0.38–0.75; r_rb = 1.00; p < 0.001). No consistent association was observed between physician-level competency changes and mean patient change. Conclusions: Immediate post-training physician scores and post-consultation patient composite scores were higher. Controlled studies incorporating observed consultations and follow-up are required before causal or sustained effects can be inferred. Full article

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder whose clinical assessment relies mainly on behavioral and neuropsychological evaluation. This study evaluates a subject-wise machine learning framework for distinguishing children with ADHD from healthy controls using multichannel EEG-derived features. The public dataset comprised 121 participants (61 ADHD and 60 controls), with 19-channel EEG recordings sampled at 128 Hz. Signals were segmented into 4-s windows with 50% overlap, and statistical and spectral features were extracted, including mean, standard deviation, and theta-, alpha-, and beta-band power. Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting (GB), and Logistic Regression (LR) were evaluated using strict subject-wise separation. RF achieved the highest Accuracy (0.8099), F1-score (0.8160), Balanced Accuracy (0.8097), and MCC (0.6204), whereas SVM obtained the highest Sensitivity (0.8525) and ROC-AUC (0.8527). An additional subject-specific analysis based on individual alpha frequency (IAF) was performed to account for inter-individual spectral variability; mean IAF values were 8.8320 Hz for ADHD and 8.8833 Hz for controls, and the individualized-band analysis did not improve classification performance. Bootstrap confidence intervals and non-parametric tests indicated comparable performance among RF, SVM, and GB. Frontal and fronto-central channels, particularly Fz, showed the greatest model-derived contribution. Overall, the framework provides a reproducible subject-wise EEG classification approach, although external validation on independent cohorts remains necessary before clinical application. Full article

To address the limited endurance of unmanned underwater vehicles (UUVs) during long-duration missions, this study proposes a foldable and retractable wave energy converter (WEC) conformally integrated with the UUV hull. A two-degrees-of-freedom heave-coupled dynamic model of the float–UUV system is established, and parameter-matching relationships are derived using complex dynamic stiffness and impedance-matching theory. A bidirectionally coupled STAR-CCM+-AMESim co-simulation framework resolves the nonlinear viscous flow field, relative motion, and PTO dynamic response in closed loop. Under regular wave conditions defined based on a representative Bohai Sea state, the effects of the transmission ratio and spring stiffness on the coupled motion and equivalent resistive load power output are systematically investigated. Under the specified wave condition, average electrical power varies unimodally with both parameters, reaching 70.8 W at a transmission ratio of 15 and a spring stiffness of 4642 N/m; the corresponding peak power is 161.2 W. The system is more sensitive to increases than decreases in transmission ratio, suggesting a value slightly below the theoretical optimum for engineering design. The instantaneous power shows an asymmetric double-peak pattern, indicating a shift in dominance between direct float-driven generation and spring-mediated energy release. Agreement between theory and co-simulation provides numerical cross-validation and offers a theoretical basis and numerical methodology for designing and optimizing WECs on mobile UUV platforms. Full article

Sustainable reservoir-system management requires coordinated operation to balance economic benefits, sediment regulation, and ecological requirements while maintaining equitable and durable cooperation among participating reservoirs. Focusing on the Wanjiazhai, Sanmenxia, and Xiaolangdi reservoirs in the middle and lower Yellow River Basin, this study develops an integrated framework that links multi-objective reservoir operation, coordination-oriented scheme selection, and compensation allocation under representative dry, normal, and wet hydrological conditions. NSGA-II is used to identify Pareto trade-offs among sediment transport, electricity production, and ecological water-deficit control, while the coupling-coordination degree model is applied to select schemes with balanced overall performance. CRITIC-TOPSIS is then used to allocate compensation by integrating static engineering attributes with operation-induced dynamic responses. The results show that the maximum coupling-coordination degrees reach 0.81, 0.88, and 0.90 under dry, normal, and wet conditions, respectively. Compared with actual operation, the recommended schemes increase total electricity production while reflecting hydrologically dependent trade-offs in sediment transport and ecological water-deficit control. Xiaolangdi Reservoir consistently receives the largest compensation share, followed by Wanjiazhai Reservoir and Sanmenxia Reservoir, and this ranking remains consistent across alternative allocation methods. By linking operational trade-offs with reservoir-specific contributions and compensation priorities, the framework supports more adaptive and equitable joint operation and provides a quantitative decision-support approach for improving the long-term environmental, economic, and institutional sustainability of reservoir-system management in the Yellow River Basin. Full article

Background: Pancreatoduodenectomy (PD) is a complex surgical procedure with substantial postoperative morbidity and mortality. Postoperative outcomes following PD are typically determined by measuring preoperative liver function in the form of serum albumin and bilirubin levels. In this study, the prognostic value of the preoperative ALBI grade was compared with that of albumin and bilirubin alone in predicting postoperative complications and short-term mortality after PD. Methods: This retrospective cohort study included 1149 patients who underwent partial or total PD between 2014 and 2017 at a high-volume surgical center. The preoperative ALBI grade (I–III) was calculated in these patients as well as the preoperative levels of bilirubin and albumin. The associations between ALBI grade, albumin and bilirubin levels with postoperative complications and 30- and 90-day mortality were analyzed using univariate and multivariable logistic regression models. The predictive performance of the ALBI grade and albumin and bilirubin levels was assessed using receiver operating characteristic (ROC) curves and area under the curve (AUC) analysis. Results: Higher ALBI grades were significantly associated with worse perioperative outcomes, including increased incidence of liver perfusion failure (42.4%) and postpancreatectomy hemorrhage (15.2%). In a pre-specified reduced multivariable model adjusted for BMI, ASA physical status as well as surgical complexity, ALBI grade III remained associated with 30- and 90-day mortality (OR 6.21; 95% CI, 1.62–23.78; p = 0.008 and OR 8.97; 95% CI, 2.91–27.62; p < 0.001) but was attenuated compared to univariate analyses. Seven of the 8 patients with ASA grade IV physical status were in ALBI grade III and accounted for 5 of the 6 30-day and 6 of the 8 90-day deaths in this group; in a sensitivity analysis excluding these patients, the association between ALBI grade III and 30-day mortality was no longer statistically significant, and the univariable association with 90-day mortality was also attenuated to non-significance, although the BMI-adjusted 90-day estimate remained significant (OR 5.02; 95% CI, 1.07–23.54; p = 0.041). ROC analysis showed that the ALBI score (AUC, 0.74 and 0.74) did not outperform albumin alone (AUC, 0.69 and 0.70) in predicting 30- and 90-day mortality (DeLong p = 0.21–0.24), although both outperformed bilirubin alone (AUC, 0.54–0.56). Conclusions: Preoperative ALBI grade III is associated with short-term morbidity and mortality after PD, but this association is confounded in part by baseline surgical risk (ASA physical status), and the ALBI score does not outperform albumin alone as a predictor of mortality. As a simple, readily available composite marker, the ALBI grade may still help flag patients who warrant closer perioperative surveillance, although this retrospective study does not establish that correcting albumin or bilirubin levels before surgery improves outcomes. Full article

Air void content (Va) is a key volumetric parameter governing the performance of Stone Mastic Asphalt (SMA), yet its prediction becomes challenging when steel slag, fibers, and additives are incorporated. This study develops an interpretable machine learning framework for predicting Va using 74 mixtures collected from 16 published studies and nine mixture-related variables. XGBoost was optimized using Particle Swarm Optimization and Grey Wolf Optimizer (GWO), with the best configuration obtained by GWO at a population size of 40 and a minimum development-stage 5-fold cross-validation (CV) RMSE of 0.371%. On the principal 70/30 evaluation partition, the optimized model achieved R² = 0.944, RMSE = 0.397%, MAE = 0.262%, and MAPE = 0.054, outperforming the evaluated benchmark models in R², RMSE, MAE, and MAPE. Robustness analyses showed that prediction accuracy was sensitive to data partitioning and literature-source composition, indicating that the reported performance should be interpreted within the represented data domain. SHAP, permutation importance, and feature-ablation analyses consistently identified binder penetration as the most influential predictor, followed mainly by asphalt content and softening point. Overall, the proposed framework provides an interpretable tool for preliminary Va estimation and mixture screening, while independent laboratory and field validation remains necessary before practical deployment. Full article

The biological carbon pump plays a central role in regulating atmospheric CO₂ by transporting carbon from the surface ocean to depth. Although diel vertical migration and the Active Migrant Pump (AMP) are increasingly recognized as important components of carbon sequestration, previous reviews have focused primarily on carbon fluxes and individual migrant groups, with less attention to how taxonomic and functional biodiversity, community composition, biomass, and environmental forcing interact to shape active carbon transport. Here, we synthesize current knowledge on the biodiversity underlying the AMP and evaluate how organismal identity, functional traits, behavior, life history, and biomass influence the magnitude, pathways, and efficiency of active carbon export. We further examine major mechanisms of active carbon transport and their links to biodiversity across ocean basins, and assess how climate-driven changes in species composition, migratory behavior, and ecosystem structure may alter the AMP. The review identifies three major knowledge gaps: substantial uncertainty in the biomass of migrating organisms, insufficient taxonomic resolution of key migrant groups, and limited incorporation of biodiversity and functional traits into carbon-flux models. Active carbon transport is determined by interactions between biodiversity, biomass, organismal traits, migration behavior, and environmental factors. Explicit integration of these dimensions into biogeochemical models is therefore essential for improving estimates of the AMP and predicting its response to ocean change. Full article

Background: The widespread availability of over-the-counter (OTC) medicines supports self-care but also requires users to recognize medication-related risks and make safe decisions without direct professional supervision. Existing studies have often examined medication literacy, self-medication, or pharmacovigilance separately. To address this gap, we developed a questionnaire within the conceptual framework of OTC medication risk literacy to explore scenario-based OTC medicine risk recognition, self-assessed confidence, self-reported safety behaviours, information-seeking practices, and pharmacovigilance awareness among respondents recruited through an online survey in Romania. Methods: A cross-sectional observational study was conducted using an anonymous Google Forms questionnaire. Data were collected between June–July 2026. The questionnaire included scenario-based items addressing common OTC medicine risks, self-assessed confidence in medication-related decision-making, self-reported safety behaviours, information sources, chronic disease and medicine use, adverse effect experience, reporting behaviour, and pharmacovigilance awareness. Associations were evaluated using chi-square tests, effect-size measures, and multivariable regression analyses. Results: A total of 423 respondents completed the survey. Recognition of major medication-safety risks was high for persistent symptoms requiring medical evaluation (96.5%), severe allergic reactions (95.7%), severe cutaneous adverse effects (96.2%), OTC medicine use during pregnancy (95.7%), antibiotic misuse (89.8%), and contraindications associated with chronic disease or anticoagulant therapy (91.7–92.7%). In contrast, recognition was lower for the antihistamine–alcohol interaction scenario, for which only 53.9% selected the safest response. Confidence was highest for understanding information provided on medicine packaging and patient information leaflets, whereas lower confidence was reported for recognising unsafe medicine combinations and contraindications. Most respondents reported reading medicine packaging and following recommended dosage instructions. Doctors (69.0%), pharmacists (61.2%), and patient information leaflets (56.3%) were the most used information sources. Pharmacovigilance awareness was limited, although 45.1% of respondents agreed that they knew how to report a suspected adverse effect, 35.0% disagreed and 52.3% of eligible respondents reported having previously submitted a suspected adverse effect report. Healthcare background remained independently associated with higher recognition and confidence scores after adjustment. Conclusions: In this online convenience sample, respondents generally recognized major OTC medicine safety risks in structured scenarios and reported several safe-use behaviours, but practical gaps remained in interaction recognition, complex risk assessment, and pharmacovigilance awareness. The findings should be interpreted as exploratory and not as representative national estimates. Scenario-based assessment may help identify educational priorities, while pharmacist counselling, clearer information, and pharmacovigilance education remain plausible strategies that require further evaluation. Full article

To address the coexistence of random measurement delays and intermittent data loss in multi-UAV cooperative navigation under weak communication scenarios, an adaptive cooperative localization method based on online diagnosis is proposed. A timestamp-driven diagnosis mechanism first identifies the physical reachability and temporal validity of cooperative measurements and classifies the channel state as normal, delayed, or lost. The estimator then adaptively switches between timestamp-diagnosed multi-step augmented filtering for delayed packets and Gray Wolf Optimizer (GWO)-optimized Gated Recurrent Unit (GRU) virtual measurement reconstruction for complete dropouts. In a four-UAV hybrid-anomaly simulation with continuous random delays and a 10 s communication blackout, the proposed method reduces the mean east and north RMSE by 69.1% and 75.2%, respectively, and lowers the mean horizontal-channel RMSE from 2.200 m to 0.608 m. Ablation experiments isolate the contribution of each module (diagnosis and multi-step delayed filtering and GWO-GRU virtual reconstruction), and 20 paired Monte Carlo runs with paired significance tests confirm the improvement. Relative to the strongest delay-aware baseline, the full-trajectory mean accuracy is comparable, and the main advantage of the proposed method is its robustness during complete communication outages and fast post-outage recovery. The simulation scenarios are driven by flight data collected with the DJI Matrice 350 RTK platform; the communication anomalies are included in the simulation, and all evaluations are performed offline. These results indicate that the proposed diagnosis-driven scheduling strategy can improve cooperative localization robustness when delay and data loss occur simultaneously. Full article