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Marangoni convection is very useful in coating flow technology, surfactant replacement therapy for neonatal children, microfluidics, drying of semi-conductor vapors in microelectronics, foams, and film drainage in emulsions. The behavior of gyrotactic microorganisms and chemical reaction on the Marangoni convected Carreau-Yasuda liquid flowing over Riga plate with thermophoretic particle deposition is reported in this research. The Riga plate is self-possessed of magnets and electrodes. The fluid conducted electricity and the vertical Lorentz force has been exponentially increased. Thermal and mass species phenomena are investigated within the context of Dufour and Soret impacts. The PDEs are transformed into ODEs by the implication of suitable transformations. The resulting system of equations is solved by using homotopy analysis method (HAM). Using tables and graphs, the effects of dimensionless parameters on flow fields are described. The wall drag coefficient and pertinent flow rates are organized and stated. The results revealed that the temperature, concentration, and microorganisms profiles decay but the velocity profile augmented as the Marangoni ratio parameter increases.

The rising incidence of malaria on a global scale poses a substantial public health concern, necessitating effective and innovative ways for tackling it. The review paper explores the capability of Artificial Intelligence (AI) in aiding India’s attempt to eliminate malaria by 2030. Totally, 62 research articles published between 2014 and 2025 are systematically reviewed, covering AI applications in diagnosis (e.g., image-based parasite detection), treatment optimization (predictive analytics), and outbreak prediction. The main findings from research articles indicate that AI models have attained better diagnostic accuracies and significantly decreased diagnostic time as well as human error. Even though there are developments, poor data interoperability, limited rural infrastructure, and gaps in healthcare worker training are some of the major limitations. The review also analyses various AI techniques currently employed globally, which can be adapted for use in India. The paper analyses various AI techniques currently employed globally, which can be adapted for use in India. It also highlights the associated limitations that need to be addressed and suggests areas for future research. This review follows a structured and transparent approach to select, evaluate, and present the role of AI in malaria elimination.

The comparative analysis of non-Newtonian nanofluids with Newtonian conditions are addressed in this research. Oldroyd-B and Casson fluids are adopted as the non-Newtonian fluids (NNF). The generation of flow is due to bidirectionally movement of magnetized surface. Radiation and chemical reactive processes are accounted in energy and mass transportation equations. Buongiorno’s theory of nanoparticles is developed for the nanofluids analysis. The basic formulas of fluid dynamics are incorporated to formulate the physical model. The assumption of boundary-layer is utilized for the simplification of mathematical model. The arising nonlinear model of three independent variables are converted into one independent variable model using similarity constraints. The simplified mathematical model is treated analytically through the implementation of homotopic approach. The convergence of this scheme is verified through numerical benchmark and graphic illustration. The results of versatile constraints on physical quantities are addressed numerically and graphically. The comparison of results with previous published outcomes is provided in limiting approach.

Air quality has a significant influence on the environment and health. Instruments that efficiently and inexpensively detect air quality could be extremely valuable in detecting air quality indices. This study presents a robust deep learning model named AQE-Net, for estimating air quality from mobile images. The algorithm extracts features and patterns from scene photographs collected by the camera device and then classifies the images according to air quality index (AQI) levels. Additionally, an air quality dataset (KARACHI-AQI) of high-quality outdoor images was constructed to enable the model’s training and assessment of performance. The sample data were collected from an air quality monitoring station in Karachi City, Pakistan, comprising 1001 hourly datasets, including photographs, PM2.5 levels, and the AQI. This study compares and examines traditional machine learning algorithms, e.g., a support vector machine (SVM), and deep learning models, such as VGG16, InceptionV3, and AQE-Net on the KHI-AQI dataset. The experimental findings demonstrate that, compared to other models, AQE-Net achieved more accurate categorization findings for air quality. AQE-Net achieved 70.1% accuracy, while SVM, VGG16, and InceptionV3 achieved 56.2% and 59.2% accuracy, respectively. In addition, MSE, MAE, and MAPE values were calculated for our model (1.278, 0.542, 0.310), which indicates the remarkable efficacy of our approach. The suggested method shows promise as a fast and accurate way to estimate and classify pollutants from only captured photographs. This flexible and scalable method of assessment has the potential to fill in significant gaps in the air quality data gathered from costly devices around the world.

Grape is a type of fruit widely grown globally and in Türkiye thanks to its importance in human nutrition and diversity of usage areas. Türkiye has a long history of grape cultivation, and the genetic diversity of local grapes grown in some regions has still not been revealed. This study showed the genetic diversity between 60 local grape genotypes selected from north Central Anatolia and nine reference grape cultivars;10 inter simple sequence repeats (ISSR) and 7 inter-primer binding site (IPBS) retrotransposon primers were used. The mean values of genetic diversity indices in ISSR and IPBS retrotransposon primers were calculated as expected allelic frequency (p) 0.476/0.195, observed allelic frequency (q) 0.524/0.805, number of effective alleles (Ne) 1.326/1.378, Shannon’s information index (I) 0.308/0.367, expected heterozygosity (He) 0.199/0.232 and unbiased expected heterozygosity (uHe) 0.201/0.234, respectively. Unweighted pair group method with arithmetic mean (UPGMA) and model-based STRUCTURE analysis divided the studied germplasm into two groups. However, local genotypes were not grouped per the regions where they grew. As a result of the analysis of molecular variance (AMOVA) analysis, the inter-population variation was determined to be 11%, and the intra-population variation was determined to be 89%. The mean genetic differentiation value (Fst) between populations was 0.303. The results showed that ISSR and IPBS retrotransposon primers effectively explained the genetic diversity.

Real-time quantitative polymerase chain reaction (qRT-PCR) has been widely used in gene expression analyses due to its advantages of sensitivity, accuracy and high throughput. The stability of internal reference genes has progressively emerged as a major factor affecting the precision of qRT-PCR results. However, the stability of the expression of the reference genes needs to be determined further in different cells or organs, physiological and experimental conditions. Methods for evaluating these candidate internal reference genes have also evolved from simple single software evaluation to more reliable and accurate internal reference gene evaluation by combining different software tools in a comprehensive analysis. This study intends to provide a definitive reference for upcoming research that will be conducted on fruit trees. The primary focus of this review is to summarize the research progress in recent years regarding the selection and stability analysis of candidate reference genes for different fruit trees.

Marangoni convection is discovered by varying gradients of surface tension. Marangoni induced flow plays a vital role in melting of coating flow technology, drying wafers, crystals, soap film stabilization, wielding and microfluidics, in which the flow creates unwanted impacts under gravity on micro-level in the same manner as buoyancy-induced natural convection. The Magneto-Marangoni convective flow of Walter-B fluid over a vertical permeable surface is addressed in the current research. The Dufour–Soret effects are taken into account along with activation energy and radiation. Flow through a porous media is modeled via Darcy and Forchheimer theory. The surface tension gradient becomes stronger by increasing the Marangoni convection parameter, which results in stronger induced flows and more efficient heat and mass movement inside the liquid. The result is a more uniform distribution of these qualities throughout the liquid as the temperature and concentration profiles drop. With higher viscoelastic parameter levels, the fluid accelerates and the velocity profile increases due to decreased viscosity. Due to an augmentation in the Dufour and Soret number, the thermal and concentration of the Walter-B fluid boost up respectively.

A bstract We derive the response function for a comoving, pointlike Unruh-DeWitt particle detector coupled to a complex scalar field ϕ , in the (3 + 1)-dimensional cosmological de Sitter spacetime. The field-detector coupling is taken to be proportional to ϕ † ϕ . We address both conformally invariant and massless minimally coupled scalar field theories, respectively in the conformal and the Bunch-Davies vacuum. The response function integral for the massless minimal complex scalar, not surprisingly, shows divergences and accordingly we use suitable regularisation scheme to find out well behaved results. The regularised result also contains a de Sitter symmetry breaking logarithm, growing with the cosmological time. Possibility of extension of these results with the so called de Sitter α -vacua is discussed. While we find no apparent problem in computing the response function for a real scalar in these vacua, a complex scalar field is shown to contain some possible ambiguities in the detector response. The case of the minimal and nearly massless scalar field theory is also briefly discussed.

Water deficiency and temperature extremes, exacerbated by climate change events, lead to depletion in plant physiology and fruitfulness in most part of the world. Studies demonstrated that foliar seaweed (SW) treatment can promote plant growth and mitigate the adverse effects of climate change. Therefore, the effects of SW spraying (0.5%) on grapevine physiology, vine yields and quality of ‘Alphonse Lavallée’ have been investigated under both full irrigation (FI; maintaining water holding capacity of soilless medium at 100%) and deficit irrigation (DI; irrigation amount at 50% of FI) conditions in soilless culture under glasshouse condition. Foliar SW treatments applied three times during vegetation significantly improved the stomatal conductance, leaf relative water content and leaf growth of vines for both irrigation conditions. In particular, shoot growth and vine yield of SW treated vines were remarkably higher than nontreated ones under DI condition. SW also improved the berry and cluster weights under DI. Berry detachment and skin rupture forces increased after SW pulverization in DI vines. SW in DI subjected vines also accelerated the berry ripening with increased soluble solid content. Overall, foliar SW treatment could be recommended for sustainable grape production under the effects of water deficit in the face of climate change.

The complexes of Co(II), Ni(II), Cu(II) and Zn(II) metal ions has been synthesized through template method by the condensation of succinic acid dihydrazide with 5-chloroisatin in alcoholic medium. Complexes were characterized by C H N analysis, molar conductance, thermal analysis, magnetic susceptibility, mass spectrometry, FTIR, EPR, 1H NMR, UV–Visible spectroscopy. These studies suggest an octahedral geometry for all the complexes. The compounds were found active against B. subtilis and S. aureus and P. aeruginosa and E. coli bacteria. The Zn(II) complex showed significant anticancer activity against Squamous Cell Carcinoma cells tested by the MTT assay method. Molecular docking studies with EGFR tyrosine kinase were also carried out. All these results show that some of the synthesized compounds have remarkable antibacterial and anticancer property.