Trends in breastfeeding indicators across Indian states and Union Territories (1993-2021): Estimating progress towards the 2030 Global Nutrition Target.

Blood pressure (BP) control is a core quality metric in value-based care (VBC). The Healthcare Effectiveness Data and Information Set (HEDIS) Controlling High Blood Pressure (CBP) measure uses the final BP reading of the calendar year, a method that overlooks well-documented seasonal variation-BP declines in summer and rises in winter. We evaluated the impact of this pattern on measured performance in a large health system. We conducted a retrospective analysis of monthly BP control rates (July 2019 to December 2025) across the Jefferson Health-Lehigh ambulatory network, totaling 78 months and approximately 7.6 million patient-months. Summer (June to August) and winter (December to February) rates were compared using paired t-tests and ordinary least square regression with seasonal adjustment. Year-end performance was assessed using both the HEDIS final-reading (December rate) and a rolling Q4 average (October to December mean). Standard VBC quality improvement initiatives with Q4 intensification were in place. BP control rates were significantly higher in summer (75.2%; 95% confidence interval [CI]: 73.5%-77.0%) than winter (73.1%; 95% CI: 71.2%-75.1%), a 2.1-percentage-point difference (paired t = 5.13, P = 0.002). This pattern was consistent across all 7 years. Within-year peak-to-trough amplitude averaged 2.8 percentage points in nonpandemic years. The rolling Q4 average exceeded the December-only rate in all years, with differences of 0.06-0.59 percentage points, reclassifying 60-520 additional patients as controlled annually. Seasonal BP variation is robust and inadequately addressed by current quality measures. Multi-reading or seasonally adjusted methods would improve measurement accuracy and fairness. Engagement with NCQA and CMS to pilot redesigned measures is recommended.

Automatic selection of optical coherence tomography images for prognostic prediction models in age-related macular degeneration.

Tobacco retailer density and smoking prevalence following a hypothetical 500-meter buffer around schools in South Korea.

Impact of concurrent COPD and cardiovascular disease on mortality.

Accurate and rapid identification of corn diseases is a prerequisite for precision spraying in the field. Yet the highly variable outdoor environment, together with the computational cost of deep models, still constrains real-world deployment. To address these challenges, we propose Dycorn-YOLO11, a deployable corn disease detector built on a dual-dynamic feature capture architecture design. First, the online convolutional reparameterization block (OREPA) is embedded in the backbone to reduce training and inference complexity. Second, a dual-dynamic feature capture architecture is constructed, where v3-Dyhead and Dysample work in concert to achieve deformable alignment and content-adaptive sampling, strengthening the representation of small, low-contrast lesions. In addition, a “channel pruning + knowledge distillation” lightweight pipeline compresses the model substantially while preserving the backbone’s feature expressiveness. Experiments show that the improved model attains a precision (P) of 88.2%, recall (R) of 73.9%, and mAP of 81.5%, representing gains of 0.8, 2.1, and 3.4 percentage points over YOLO11n. The parameter count and model size are reduced by 41.5% and 40.0%, respectively, and the inference speed increases to 113.2 f/s, achieving a balanced trade-off among accuracy, compactness, and efficiency. The model also maintains high stability on an external, complex dataset, and delivers strong real-time performance in both static and moving field experiments. Overall, Dycorn-YOLO11 demonstrates robust, deployable performance and provides a feasible technical foundation for precision spraying in corn fields.

Unmanned tobacco curing using a novel adaptive decision support system

Leakage-safe diffusion augmentation with KAN-based models for imbalanced microarray gene-expression classification.

Apple flower detection based on dynamic slicing with YOLO-FRNet

The cost of digital convenience: Food delivery platform entry, health, and medical spending.

• Developed a multimodal vision framework using root and leaf–flower images • Proposed a YOLOv11-PST model with improved fine-grained phenotypic recognition • Implemented scale–seed ensembling and probability-level fusion for stability • Achieved 98.56% accuracy and 97.77% Macro-F1 across 12 P. lactiflora varieties • Integrated SHAP and Grad-CAM++ to reveal biologically meaningful visual cues The quality of Radix Paeoniae Alba (Baishao), a widely used traditional Chinese medicinal material, is closely linked to its geo-authentic origins, resulting in distinct regional varieties. Conventional assessment methods typically depend on chemical or molecular profiling, which, despite accuracy, are destructive, time-consuming, and unsuitable for large-scale screening. In this study, a computer vision-based framework was established using images of the original plant ( Paeonia lactiflora Pall.) cultivated under uniform conditions. Images of root and leaf-flower organs were captured to extract structural, textural, and chromatic features relevant to varietal differentiation. Machine learning models based on handcrafted features and deep learning models utilizing an enhanced YOLOv11 architecture were systematically compared. A variety-level multimodal fusion strategy integrating root and leaf-flower data through probability-space weighting further improved robustness and balance. Results indicated that root images yielded higher accuracy, whereas leaf-flower images provided more balanced classification across varieties. The multimodal fusion model consistently outperformed single-modality models, achieving a macro-F1 score of 98.56±0.57%. This represented an improvement of approximately 5 percentage points over the best unimodal deep learning models and substantially surpassed traditional machine learning baselines. Interpretability analysis employing SHAP and Grad-CAM++ revealed that the models effectively captured biologically relevant traits such as root branching patterns, contour structures, leaf venation, and petal margins. These findings suggest that image-based phenotypic information can reliably identify P. lactiflora varieties, offering a scalable and interpretable approach to modernizing quality control in traditional Chinese medicine.

Quantifying trunk influence on vibration response of Camellia oleifera branches via dynamic equivalence

Alcoholic cardiomyopathy presenting with severe circulatory failure requiring mechanical circulatory support: A systematic review.

Cooperation of general practitioners in referral networks: Impact on health outcomes and costs in chronic care.

Changing socio-demographic determinants of seasonal influenza acceptance in England during the pandemic and a framework for predicting future acceptance.

Proximal policy optimisation based black-box optimizer for tailoring inhalation instructions of an inhaler for minimising mouth-throat deposition.

Efficacy and safety of enpatoran, a Toll-like receptor 7/8 inhibitor, in patients with skin manifestations of cutaneous lupus erythematosus or systemic lupus erythematosus: findings from Cohort A of a multicentre, international, double-blind, placebo-controlled, dose-finding phase 2 trial.

To determine tuberculosis prevalence among health-care facility patients and to assess the effectiveness of chest radiography in facility-based tuberculosis screening. Our cross-sectional analysis used individual-level data collected during 2020-2023 from adults presenting at 796 health-care facilities participating in a public-private partnership in 15 provinces of Viet Nam. We constructed tuberculosis care cascades stratified by symptomatic presentation according to the World Health Organization (WHO) four-symptom screening and chest radiography. We reported diagnostic yield, number needed to screen and positivity. Among 1 423 818 participants, 22 598 had bacteriologically confirmed tuberculosis. Diagnostic yields were 2.2% (19 289/892 894) among symptomatic individuals with cough, 1.0% (1869/191 677) among symptomatic individuals without cough and 0.4% (1440/339 247) among asymptomatic individuals. Tuberculosis-suggestive chest radiograph results compared with normal results increased bacteriologically confirmed positivity by 9.4 percentage points in symptomatic individuals with cough (17.3%; 18 746/108 650 versus 7.9%; 543/6851), by 4.6 percentage points in symptomatic individuals without cough (12.6%; 1748/13 831 versus 8.0%; 121/1515) and by 7.6 percentage points in asymptomatic individuals (15.0%; 1328/8862 versus 7.4%; 112/1511). Without chest radiography, the number of individuals requiring testing to detect tuberculosis among symptomatic individuals with cough and without a cough would have been 6.5 (1 084 571/165 679) and 5.4 (892 894/165 679) times higher, respectively. Chest radiograph screening can reduce the number of expensive molecular tests used in symptomatic patients and enable tuberculosis diagnosis in asymptomatic patients. Future research should analyse cost and cost-effectiveness of using chest radiography in active and intensified case finding.

Dietary vitamin A inadequacy remains a serious public health problem, especially among young children. Food and condiment fortification programs and policies are in place in many countries to address this issue, but degradation of the vitamin A added via fortification can reduce the quantity of vitamin A reaching consumers. We modeled the impacts of vitamin A degradation on program effectiveness and cost-effectiveness in fortified wheat flour, sugar, and (hypothetical) bouillon cubes in Nigeria. We used secondary data to estimate the prevalence of vitamin A inadequacy among young children (6-59 months), and the programs' modeled contributions to reducing vitamin A inadequacy at selected levels of vitamin A degradation. The Lives Saved Tool was used to estimate child-lives saved. Program costs were estimated using activity-based models. Vitamin A degradation had a large negative impact on program effectiveness. Over the 0% to 80% vitamin A degradation range, accounting for other existing programs, fortification of sugar (7.5 mg/kg), wheat flour (2 mg/kg), and bouillon cubes (96 mg/kg) would reduce inadequacies among children by 2.9 to 0.7 percentage points, 3.9 to 0.7 percentage points, and 20.6 to 9.6 percentage points, respectively. Over the same vitamin A degradation range, average annual child-lives saved ranged from 3984 to 769 (sugar), 3036 to 739 (wheat flour), and 15 301 to 7153 (bouillon cubes); estimated cost/child-life saved ranged from US$ 550 to US$ 2848 (sugar), US$ 1039 to US$ 4271 (wheat flour), and US$ 944 to US$ 2018 (bouillon cubes). Vitamin A fortificant selection, technological innovations in vitamin A fortificants, and/or changes in premix and fortified food handling and storage could reduce degradation; these options could increase program costs, but merit consideration.

• Firms’ experiences with corruption outside tax authority have significant adverse spillovers on tax evasion. • Bribes for operating licenses raise firm tax evasion by up to 24.2 percentage points. • Bribes for government contracts increase tax evasion by 2.1 percentage points per contract value percent. • Working capital depletion mediates the corruption–tax evasion link in firms. • Anti-corruption in tax only is insufficient; multisectoral action is needed to curb tax evasion. This study examines the direct and spillover effects of corruption on firms’ tax evasion in sub-Saharan Africa (SSA), a region plagued by both phenomena. Firm-level data on 17 SSA economies spanning 2008–2014 were sourced from the World Bank’s Enterprise Survey. I instrument for endogeneity of corruption using five variables, namely the number of days it takes to (i) clear exports, (ii) clear imports, (iii) obtain an operating license, (iv) time spent by senior management on regulatory compliance, and (v) the extent to which business licenses and permits are an obstacle the firm’s operation. I implemented a battery of endogeneity-correcting estimators: traditional instrumental-variable two-stage least squares (2SLS), Lewbel’s 2SLS, Oster’s bounding analysis, propensity score matching, and Kinky Least Squares. I find that corruption of tax officials (i.e., bribe expected/requested in exchange for a favourable tax inspection) significantly increases tax evasion. More critically, this study challenges prevailing assumptions from European and Central Asian contexts by demonstrating that corruption outside tax authorities—specifically bribes expected/requested in exchange for operating licenses and government contracts—also exerts substantial adverse spillover effect on tax compliance. Firms that perceived/experienced bribe requests in exchange for obtaining operating licenses evaded taxes at rates 24.2 percentage points higher than their counterparts who did not perceive/experience bribe requests in exchange for obtaining operating licenses. In contrast, a percent increase in perceived bribe rates for government contracts corresponded to a 2.1 percentage-point increase in tax evasion. Mediation analysis identifies working capital depletion as a key transmission channel. These findings underscore the need for multisectoral anti-corruption strategies to effectively combat tax evasion and enhance domestic revenue mobilisation in SSA.