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Automated plant disease detection has become an essential application of deep learning, supporting early diagnosis and effective crops and ornamental plant management. Recent advancements in the You Only Look Once (YOLO) family of object detection models have improved both accuracy and efficiency, making them suitable for real-time deployment. This paper presents a comparative analysis of YOLOv8, YOLOv9, and YOLOv11 for classifying diseased and healthy leaves of Ixora and Bougainvillea, two widely grown ornamental species. A curated dataset of annotated leaf images covering multiple disease conditions was used to train and evaluate the models under consistent experimental settings. To capture both accuracy and real-time feasibility, performance was evaluated using standard detection metrics like mean Average Precision (mAP), precision, recall, and F1-score in addition to inference speed (FPS). The assessment also highlights environmental robustness and subtle disease localization parameters, which are important for monitoring ornamental plants in unrestricted outdoor environments. Results indicate that YOLOv11 achieves the highest detection accuracy, especially in capturing subtle disease patterns, while YOLOv8 and YOLOv9 demonstrate competitive performance with faster inference, making them preferable for resource-limited applications. The findings highlight practical trade-offs between accuracy and efficiency across YOLO versions, offering valuable insights for real-world deployment. By extending research beyond staple crops to ornamental plants, this work underscores the broader applicability of AI-driven disease detection and establishes a benchmark for evaluating next-generation YOLO architectures in horticulture.

The worldwide emerging cases of various respiratory viral diseases and the current escalation of novel coronavirus disease (COVID‐19) make people considerably attentive to controlling these viruses through innovative methods. Most re-emerging respiratory diseases envelop RNA viruses that employ attachment between the virus and host cell to get an entry form using the host cell machinery. Emerging variants of COVD-19 also bring about a constant threat to public health as it has wide infectivity and can quickly spread to infect humans. This review focuses on insights into the current investigations to prevent the progression of incipient variants of Severe Acute Respiratory Syndrome Coronavirus (SARS-COV-2) along with similar enveloped RNA viruses that cause respiratory illness in humans and animals. Nanotheranostics is a trailblazing arena of nanomedicine that simultaneously helps prevent or treat diseases and diagnoses. Nanoparticle coating and nanofibers were extensively explored, preventing viral contaminations. Several studies have proven the virucidal activities of metal nanoparticles like copper, silver, and titanium against respiratory viral pathogens. Worldwide many researchers have shown surfaces coated with ionic nanoparticles like zinc or titanium act as potent antiviral agents against RNA viruses. Carbon nanotubes, quantum dots, silica nanoparticles (NPs), polymeric and metallic nanoparticles have also been explored in the field of nanotheranostics in viral detection. In this review, we have comprehensively discussed different types of metallic, ionic, organic nanoparticles and their hybrids showing substantial antiviral properties to stop the progression of the novel coronavirus disease focused on three key classes: prevention, diagnostics, and treatment.

The motion of a surfactant-laden viscous droplet in the presence of background non-isothermal Poiseuille flow is studied analytically and numerically. Specifically, the effect of interfacial Marangoni stress due to non-uniform distribution of surfactants and temperature at the droplet interface on the velocity and direction of motion of the droplet along the centerline of imposed Poiseuille flow is investigated in the presence of linearly varying temperature field. In the absence of thermal convection, fluid inertia and shape deformation, the interfacial transport of bulk-insoluble surfactants is governed by the surface Peclet number which represents the relative strength of the advective transport of surfactant over the diffusive transport. We obtain analytical solution for small and large values of the surface Peclet number. Numerical solution is obtained for arbitrary surface Peclet number, which compares well with the analytical solution. Depending on the direction of temperature gradient with respect to the imposed Poiseuille flow, the surfactant-induced Marangoni stress affects the droplet velocity differently. When the imposed temperature increases in the direction of imposed Poiseuille flow, surfactants retard the droplet motion as compared with a surfactant-free droplet. However, when the imposed temperature decreases in the direction of imposed Poiseuille flow, presence of surfactants may increase or decrease the magnitude of droplet velocity depending on the relevant governing parameters. Further, for particular values of governing parameters, we observe change in direction of droplet motion due to presence of surfactants, which may bear significant consequences in the design of droplet based microfluidic systems.

The motion of a viscous droplet in unbounded Poiseuille flow under the combined influence of bulk-insoluble surfactant and linearly varying temperature field aligned in the direction of imposed flow is studied analytically. Neglecting fluid inertia, thermal convection and shape deformation, asymptotic analysis is performed to obtain the velocity of a force-free surfactant-laden droplet. The present study is focused on two limiting situations of surfactant transport: (i) small surface Peclet number, and (ii) high surface Peclet number. Thermocapillary-induced Marangoni stress, strength of which relative to viscous stress is represented by thermal Marangoni number, has strong influence on the distribution of surfactant on the droplet surface. Temperature field not only affects the axial velocity of the droplet but also has significant effect on the cross-stream velocity of the droplet in spite of the fact that the temperature gradient is aligned with the Poiseuille flow direction. When the imposed temperature increases in the direction of Poiseuille flow, the droplet migrates towards the flow centerline. The magnitude of both axial and cross-stream velocity components increases with the thermal Marangoni number. However, when the imposed temperature decreases in the direction of Poiseuille flow, the magnitude of both axial and cross-stream velocity components may increase or decrease with the thermal Marangoni number. Most interestingly, the droplet moves either towards the flow centerline or away from it. Present study shows a critical value of the thermal Marangoni number beyond which the droplet moves away from the flow centerline which is in sharp contrast to the motion of a surfactant-laden droplet in isothermal flow for which droplet always moves towards the flow centerline.