R. S. Rimal Isaac

Breast cancer is a highly prevalent malignancy among women globally and arises from the uncontrolled proliferation of abnormal cells in breast tissue. Timely and precise diagnosis is critical for effective treatment and enhanced survival. Histopathological image analysis is considered the gold standard; nevertheless, manual assessment is labor-intensive and prone to variability. Existing deep learning and transformer-based approaches demonstrate strong effectiveness; however, they incur significant computational complexity and limited efficiency in capturing multi-scale features. To address these challenges, this research presents a framework that integrates ConvMixer, multi-scale patch learning, and an Adaptive Combined Runge–Kutta–Harris Hawks Optimization (AC-RUNHHO) algorithm. The model effectively captures both fine-grained cellular patterns and global tissue structures, while adaptive optimization improves convergence and hyperparameter tuning. The framework is evaluated on a breast cancer histology dataset comprising 4000 histopathological images across four classes. Experimental results demonstrate robust performance under the evaluated experimental conditions, achieving 98.63% accuracy, 98.63% precision, 98.62% recall, and 98.62% F1-score. Ablation and cross-validation analyses further confirm the generalization capability of the model. Overall, the developed framework demonstrates promising performance in computer-aided breast histopathological image classification, achieving high predictive accuracy and providing interpretable visual explanations.

Mesoporous Ga ₂ O ₃ -integrated γ-Al ₂ O ₃ nanocomposites with high dispersion of Ga ₂ O ₃ species produced by a sol–gel synthesis route are high-performing bifunctional oxide catalysts for the hydrogen production by dimethyl ether (DME) steam reforming.

Flower-like copper–cobalt Prussian blue analogue sulfide is synthesized via pulsed laser irradiation in liquid and its formation mechanism is investigated by acoustic levitation coupled with in situ Raman spectroscopy.

Introduction: Nano-priming with metal oxide nanomaterials is an emerging strategy for improving seed germination and early seedling vigour. This study evaluates the effect of nickel oxide (NiO) nanoparticle priming on germination and early physiology traits of Black gram (Vigna mungo L., VBN 8). Methods: NiO nanoparticles were synthesised using a solution combustion method with ascorbic acid as fuel and nickel nitrate as precursor, followed by calcination at 500 °C for 1 hour. Characterisation was performed using XRD, UV–Vis spectroscopy, FTIR, and FESEM-EDAX. Seeds were primed with NiO Nanoparticle suspensions at 10, 15, 25, 50, and 100 ppm; distilled water served as the control. Germination was assessed for 7 days, and parameters including germination percentage, Mean Emergence Time (MET), root and shoot length, Seedling Vigour Index (SVI), moisture content, biomass, and water uptake were recorded. Results: All NiO treatments enhanced germination and early seedling growth compared with the control. The 50-ppm treatment resulted in the highest water uptake (27.6%) and moisture content (68.3 %). The 100-ppm treatment produced the highest SVI (1945) and biomass, demonstrating superior seedling vigour. NiO nano-priming did not induce toxicity even at 100 ppm. Discussion: Enhanced physiological responses appear to result from improved water absorption, metabolic activation, and surface-hydroxyl-mediated hydration associated with NiO nanoparticle priming. Conclusion: NiO nano-priming at 50-100 ppm significantly improved germination and early seedling performance in Vigna mungo, offering a safe and cost-effective approach for sustainable seed enhancement.

Molybdenum trioxide nanoparticles were synthesised via a simple and cost-effective solution combustion method. XRD confirmed an orthorhombic crystalline phase with an average crystalline size of 56.6 nm. UV-Vis spectroscopy indicated a direct bandgap of 2.9 eV, while RAMAN spectra revealed Mo = O and Mo-O stretching vibrations. SEM-EDAX analysis confirmed nanoscale morphology and a uniform Mo-O distribution. Photocatalytic studies, under direct sunlight, degraded 92% methylene blue dye within 120 min, following pseudo-first-order kineticsS. Furthermore, dose-dependent antibacterial activity was exhibited against E. coli and S. aureus. These findings highlight MoO3 NPs for sustainable agriculture by degrading pollutants and controlling microbes in irrigation systems.

Background: The research outlines a study utilizing zinc oxide (ZnO) as a nano-priming agent synthesized through combustion. ZnO nanoparticles are of significant attraction because of their distinct properties and combustion synthesis proves to be a versatile and effective method for their preparation. The exothermic nature of a combustion reaction offers a rapid and energy-efficient route to obtain nanoparticles with specific properties. Mung beans are rich in nutrients, easy to digest, with low glycemic index and show antioxidant and versatility as sprouted form, soup, dal, dessert and processed products like starch for noodles and flours. Mung beans are a globally traded commodity and may generate an income source for farmers. Methods: In this work, at 500oC, ZnO nanoparticles were prepared using zinc nitrate and ascorbic acid. Characterization techniques, including UV-vis spectroscopy, XRD, RAMAN and FE SEM, confirmed ZnO nanoparticles. The experiment involved seed priming with varying concentrations of the ZnO nanoparticle (from 1 ppm to 5 ppm) suspension, with a control group that was left untreated. Result: The results revealed that treating mung bean (Vigna radiata) seeds with a concentration of 5 ppm ZnO nanoparticles positively influenced seed germination, improved shoot and root lengths and overall biomass, compared to unprimed seeds and suggested ZnO nanoparticles as an effective nano-priming agent for promoting seedling growth and development.

The expanding urbanization, population growth, and climate emergency have stimulated the development of sustainable energy technologies for a greener future. Hydrogen energy is viewed as a key solution to meet the ever‐increasing energy demand. The evolution of electrocatalysts for hydrogen production plays a crucial role in this context. Sustainable and low‐cost materials with excellent catalytic performance are highly preferred for both photocatalytic and electrocatalytic hydrogen production. Graphitic carbon nitride (g‐C₃N₄) is a versatile layered two‐dimensional material used in the hydrogen evolution reaction (HER). However, a comprehensive review investigating the effects of doping on both photocatalytic and electrocatalytic HER is lacking in the literature. This gap motivates the writing of a detailed review on g‐C₃N₄‐based catalysts for sustainable hydrogen production through both photocatalysis and electrocatalysis. This review encompasses the key features of g‐C₃N₄‐based electrocatalysts, the doping of g‐C₃N₄, their HER activities, and performance evaluations. It is concluded that doping is an effective approach to enhance the catalytic performance of g‐C₃N₄‐based catalysts for sustainable hydrogen production.

The synthesis of Zn1-x-yCoxNiyFe2O4 (0 ≤ x & y ≤ 0.25) nanoparticles has been carried out using a microwave combustion technique. The X-ray diffraction analysis of ZnFe2O4 samples, as well as ZnFe2O4 samples doped with Co2+ and Ni2+, indicated the presence of a spinel structure with a crystallite size ranging from 11 to 29 nm. The lattice and crystallite were established using XRD analysis. The FE-SEM picture reveals a uniform grain morphology. The UV-Vis spectra indicated a rise in band gap values along with an increase in the concentration of Co2+ and Ni2+. The VSM spectra demonstrate ferromagnetic behaviour in all of the samples.