Ascorbic acid (AsA), an antioxidant form of vitamin C, helps the plants in photosynthesis as an enzyme’s cofactor. It also increases the rate at which plants grow, produce, and germinate. The main goal of this study was to find out how ascorbic acid affects the growth of maize (Zea mays L.) while applying on rooting medium. First, a trial experiment was performed to determine the most effective dose of AsA application for maize plants to adopt in the main experiments. A single variety of maize, Golden, was grown in sand under pot conditions. Hoagland’s nutrient solution was applied every week and four doses of AsA (0, 0.5, 1, 1.5, and 2 mM) were applied in root medium of maize seedlings every three days for two weeks. Then, in the main experiment conducted at the Botanical Garden at the University of Agriculture Faisalabad, two cultivars of maize i.e., Golden and Sadaf, were grown in the soil inside a wire house. The selected optimal dosage of vitamin C from trial experiment (1 mM) was applied to roots of maize plants for five weeks after every three days at seedling stage. Growth and physiological parameters were measured and statistically analyzed with the help of COSTAT software using analysis of variance (ANOVA) technique. When compared with the control plants, all plant parameters (root length, shoot length, leaf area, fresh and dry biomass, chlorophyll a and b content, soluble carbohydrates, osmotic potential, Potassium, Calcium, and Phosphorus content) were observed to be enhanced with AsA treatment. On the other hand, application of ascorbic acid decreased the sodium content of both roots and shoots of the treated plants. Moreover, genotype Sadaf demonstrated relatively better results in comparison to genotype Golden.

In modern healthcare, patient satisfaction is widely recognized as a cornerstone of healthcare quality assessment, influencing not only clinical outcomes but also institutional reputation and patient loyalty. Yet, its inherently subjective and multifaceted nature makes it difficult to capture with conventional tools. This study introduces an inference system, developed within the framework of artificial intelligence, to provide a more nuanced evaluation of patient-centered care. The model examines eight qualitative indicators of patient experience, including communication, accessibility, staff competence, and perceived treatment outcomes, translating them into measurable outputs through linguistic variables. Relying on a Mamdani approach combined with centroid defuzzification, the system generates an interpretable satisfaction score on a 0–10 scale. Applied to real-world clinical data, this approach proves effective in managing uncertainty, improving decision support, and offering a refined perspective for patient experience evaluation, ultimately supporting more responsive and human-centered healthcare delivery.

This study analyses the anthropometric characteristics of young Senegalese handball players (U18 and U20 categories) in order to determine the extent to which their morphological profile is compatible with the demands of high-level handball. Based on measurements of height, weight, body mass index (BMI), wingspan and hand span, the data collected from a representative sample were compared with data from young international handball players who participated in the 10thWorld Youth Handball Championship (U19) in Croatia in 2023. The results show that while the height and wingspan of Senegalese players are broadly in line with African and European benchmarks, their weight, BMI and hand span are lower. The study concludes that a morpho-functional approach is needed in the detection and training of young handball players.