Impact of silver substitution on the structural, magnetic, optical, and antibacterial properties of cobalt ferrite.

Silver-doped Cobalt Ferrite nanoparticles AgxCo1-xFe2O4 with concentrations (x = 0, 0.05, 0.1, 0.15) have been prepared using a hydrothermal technique. The XRD pattern confirms the formation of the spinel phase of CoFe2O4 and the presence of Ag ions in the spinel structure. The spinel phase AgxCo1-xFe2O4 nanoparticles are confirmed by FTIR analysis by the major bands formed at 874 and 651 cm-1, which represent the tetrahedral and octahedral sites. The analysis of optical properties reveals an increase in band gap energy with increasing concentration of the dopant. The energy band gap values depicted for prepared nanoparticles with concentrations x = 0, 0.05, 0.1, 0.15 are 3.58 eV, 3.08 eV, 2.93 eV, and 2.84 eV respectively. Replacement of the Co2+ ion with the nonmagnetic Ag2+ ion causes a change in saturation magnetization, with Ms values of 48.36, 29.06, 40.69, and 45.85 emu/g being recorded. The CoFe2O4 and Ag2+ CoFe2O4 nanoparticles were found to be effective against the Acinetobacter Lwoffii and Moraxella species, with a high inhibition zone value of x = 0.15 and 8 × 8 cm against bacteria. It is suggested that, by the above results, the synthesized material is suitable for memory storage devices and antibacterial activity.

Breast Cancer Classification through Meta-Learning Ensemble Technique Using Convolution Neural Networks.

This study aims to develop an efficient and accurate breast cancer classification model using meta-learning approaches and multiple convolutional neural networks. This Breast Ultrasound Images (BUSI) dataset contains various types of breast lesions. The goal is to classify these lesions as benign or malignant, which is crucial for the early detection and treatment of breast cancer. The problem is that traditional machine learning and deep learning approaches often fail to accurately classify these images due to their complex and diverse nature. In this research, to address this problem, the proposed model used several advanced techniques, including meta-learning ensemble technique, transfer learning, and data augmentation. Meta-learning will optimize the model's learning process, allowing it to adapt to new and unseen datasets quickly. Transfer learning will leverage the pre-trained models such as Inception, ResNet50, and DenseNet121 to enhance the model's feature extraction ability. Data augmentation techniques will be applied to artificially generate new training images, increasing the size and diversity of the dataset. Meta ensemble learning techniques will combine the outputs of multiple CNNs, improving the model's classification accuracy. The proposed work will be investigated by pre-processing the BUSI dataset first, then training and evaluating multiple CNNs using different architectures and pre-trained models. Then, a meta-learning algorithm will be applied to optimize the learning process, and ensemble learning will be used to combine the outputs of multiple CNN. Additionally, the evaluation results indicate that the model is highly effective with high accuracy. Finally, the proposed model's performance will be compared with state-of-the-art approaches in other existing systems' accuracy, precision, recall, and F1 score.

Bio-fabrication of Zinc Oxide nanoparticles to rescue Mung Bean against Cercospora leaf spot disease.

Plant disease management using nanotechnology is evolving continuously across the world. The purpose of this study was to determine the effect of different concentrations of green synthesized zinc oxide nanoparticles (ZnO NPs) using Trachyspermum ammi seed extract on Cercospora leaf spot disease in mung bean plants under in-vitro and in-planta conditions. Additionally, the effects on mung bean agronomic and physiological parameters were also assessed. The green synthesized ZnO NPs were characterized using UV-visible spectroscopy, Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and Scanning electron microscopy (SEM). Green synthesized NPs were tested for their ability to inhibit fungal growth at five different concentrations under in-vitro experiment. After 7 days of inoculation, ZnO NPs (1200 ppm) inhibited mycelial growth substantially (89.86% ± 0.70). The in-planta experiment showed statistically significant result of disease control (30% ± 11.54) in response to 1200 ppm ZnO NPs. The same treatment showed statistically significant improvements in shoot length, root length, number of leaves, number of pods, shoot fresh weight (28.62%), shoot dry weight (85.18%), root fresh weight (38.88%), and root dry weight (38.88%) compared to the control. Our findings show that green synthesized ZnO NPs can control Cercospora canescens in mung bean, pointing to their use in plant disease control and growth enhancement.

Green synthesis and application of GO nanoparticles to augment growth parameters and yield in mungbean (Vigna radiata L.).

Plant growth promotion has long been a challenge for growers all over the world. In this work, we devised a green nanomaterial-assisted approach to boost plant growth. It has been reported that carbon nanomaterials are toxic to plants because they can inhibit the uptake of nutrients if employed in higher concentrations, however this study shows that graphene oxide (GO) can be used as a regulator tool to improve plant growth and stability. Graphene oxide in different concentrations was added to the soil of mungbean. It is proved that when a suitable amount of graphene oxide was applied, it had a good influence on plant growth by enhancing the length of roots and shoots, number of leaves, number of root nodules per plant, number of pods, and seeds per pod. We presume that the use of bio-fabricated graphene oxide as a strategy would make it possible to boost both plant growth and the significant increase in the number of seeds produced by each plant.

Incorporation of engineered nanoparticles of biochar and fly ash against bacterial leaf spot of pepper.

In agriculture, the search for higher net profit is the main challenge in the economy of the producers and nano biochar attracts increasing interest in recent years due to its unique environmental behavior and increasing the productivity of plants by inducing resistance against phytopathogens. The effect of rice straw biochar and fly ash nanoparticles (RSBNPs and FNPs, respectively) in combination with compost soil on bacterial leaf spot of pepper caused by Xanthomonas campestris pv. vesicatoria was investigated both in vitro and in vivo. The application of nanoparticles as soil amendment significantly improved the chili pepper plant growth. However, RSBNPs were more effective in enhancing the above and belowground plant biomass production. Moreover, both RSBNPs and FNPs, significantly reduced (30.5 and 22.5%, respectively), while RSBNPs had shown in vitro growth inhibition of X. campestris pv. vesicatoria by more than 50%. The X-ray diffractometry of RSBNPs and FNPs highlighted the unique composition of nano forms which possibly contributed in enhancing the plant defence against invading X. campestris pv. vesicatoria. Based on our findings, it is suggested that biochar and fly ash nanoparticles can be used for reclaiming the problem soil and enhance crop productivity depending upon the nature of the soil and the pathosystem under investigation.