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Predicting the corrosion fatigue life of austenitic stainless steel (AusSS) in high-temperature, high-pressure water environments remains a complex task due to the intricate interaction of thermal, mechanical, and environmental factors, along with the scarcity of comprehensive experimental data. Traditional empirical fatigue models often fail to capture these multifactorial effects, limiting their predictive accuracy. This study presents a novel machine learning framework using a Genetic Algorithm Optimized Neural Network (GAONN) to enhance corrosion fatigue life prediction. The proposed model is applied across five AusSS grades, 316, 316LN, 316NG, 304, and 308L, offering generalized predictions across different alloy compositions and operational scenarios. Key input parameters include environmental factors such as temperature, pressure, and dissolved oxygen (DO), mechanical properties like strain rate and amplitude, and metallurgical attributes such as stacking fault energy (SFE). The GAONN model demonstrates excellent predictive accuracy on the test set, achieving an R 2 value of 94.4%, a mean-squared error of 0.014, a root mean-squared error of 0.120, a mean absolute error of 0.105, and a mean absolute percentage error of 3.6%. These results represent a significant improvement over classical corrosion fatigue life models. Additionally, Shapley Additive Explanations (SHAP) analysis identifies temperature, pressure, and strain amplitude as primary contributors to corrosion fatigue life, in agreement with metallurgical theory. This work establishes GAONN as a transparent, accurate, and scalable tool for assessing corrosion fatigue life in next-generation nuclear energy systems.

Fruits and vegetables are the highly used food products amongst the horticultural crops. These items are consumed uncooked, nominally cooked or fully cooked, according to their nature and cooking process. With the change in diet habits and rising population, the production, as well as the processing of horticultural crops, has exponentially improved to meet its increasing demand. A large amount of peel waste is generated from fruit and vegetable-based industries and household kitchen and has led to a big nutritional and economic loss and environmental problems. Processing of fruits and vegetables alone generates a significant waste, which amounts to 25–30% of the total product. Most common wastes include pomace, peels, rind and seeds, which are highly rich in valuable bioactive compounds such as carotenoids, enzymes, polyphenols, oils, vitamins and many other compounds. These bioactive compounds show their application in various industries such as food to develop edible films, food industries for probiotics and other industries for valuable products. The utilization of these low-cost waste horticultural wastes for producing the value-added product is a novel step in its sustainable utilization. The present review intends to summarize the different types of waste originating from fruits as well as vegetables peels and highlight their potential in developing edible films, probiotics, nanoparticles, carbon dots, microbial media, biochar and biosorbents.

Fruit extracts have natural bioactive molecules that are known to possess significant therapeutic potential. Traditionally, metallic nanoparticles were synthesized via chemical methods, in which the chemical act as the reducing agent. Later, these traditional metallic nanoparticles emerged as the biological risk, which prompted researchers to explore an eco-friendly approach. There are different eco-friendly methods employed for synthesizing these metallic nanoparticles via the usage of microbes and plants, primarily via fruit extract. These explorations have paved the way for using fruit extracts for developing nanoparticles, as they eliminate the usage of reducing and stabilizing agents. Metallic nanoparticles have gained significant attention, and are used for diverse biological applications. The present review discusses the potential activities of phytochemicals, and it intends to summarize the different metallic nanoparticles synthesized using fruit extracts and their associated pharmacological activities like anti-cancerous, antimicrobial, antioxidant and catalytic efficiency

The intake of microbial-contaminated food poses severe health issues due to the outbreaks of stern food-borne diseases. Therefore, there is a need for precise detection and identification of pathogenic microbes and toxins in food to prevent these concerns. Thus, understanding the concept of biosensing has enabled researchers to develop nanobiosensors with different nanomaterials and composites to improve the sensitivity as well as the specificity of pathogen detection. The application of nanomaterials has enabled researchers to use advanced technologies in biosensors for the transfer of signals to enhance their efficiency and sensitivity. Nanomaterials like carbon nanotubes, magnetic and gold, dendrimers, graphene nanomaterials and quantum dots are predominantly used for developing biosensors with improved specificity and sensitivity of detection due to their exclusive chemical, magnetic, mechanical, optical and physical properties. All nanoparticles and new composites used in biosensors need to be classified and categorized for their enhanced performance, quick detection, and unobtrusive and effective use in foodborne analysis. Hence, this review intends to summarize the different sensing methods used in foodborne pathogen detection, their design, working principle and advances in sensing systems.

Microgreens have been used for raw consumption and are generally viewed as healthy food. This study aimed to optimize the yield parameters, shelf life, sensory evaluation and characterization of total aerobic bacteria (TAB), yeast and mold (Y&M), Escherichia coli , Salmonella spp., and Listeria spp. incidence in mungbean ( Vigna radiata (L.) Wilczek), lentil ( Lens culinaris Medikus subsp. culinaris ), and Indian mustard ( Brassica juncea (L.) Czern & Coss.) microgreens. In mungbean and lentil, seeding-density of three seed/cm 2 , while in Indian mustard, eight seed/cm 2 were recorded as optimum. The optimal time to harvest mungbean, Indian mustard, and lentil microgreens were found as 7 th , 8 th , and 9 th day after sowing, respectively. Interestingly, seed size was found highly correlated with the overall yield in both mungbeans (r 2 = .73) and lentils (r 2 = .78), whereas no such relationship has been recorded for Indian mustard microgreens. The target pathogenic bacteria such as Salmonella spp. and Listeria spp. were not detected; while TAB, Y&M, Shigella spp., and E . coli were recorded well within the limit to cause any human illness in the studied microgreens. Washing with double distilled water for two minutes has shown some reduction in the overall microbial load of these microgreens. The results provided evidence that microgreens if grown and stored properly, are generally safe for human consumption. This is the first study from India on the safety of mungbean, lentils, and Indian mustard microgreens.

Heavy metal accumulation in plants is a severe environmental problem, rising at an expeditious rate. Heavy metals such as cadmium, arsenic, mercury and lead are known environmental pollutants that exert noxious effects on the morpho-physiological and biological attributes of a plant. Due to their mobile nature, they have become an extended part of the food chain and affect human health. Arbuscular mycorrhizal fungi ameliorate metal toxicity as they intensify the plant’s ability to tolerate metal stress. Mycorrhizal fungi have vesicles, which are analogous to fungal vacuoles and accumulate massive amount of heavy metals in them. With the help of a pervasive hyphal network, arbuscular mycorrhizal fungi help in the uptake of water and nutrients, thereby abating the use of chemical fertilizers on the plants. They also promote resistance parameters in the plants, secrete a glycoprotein named glomalin that reduces the metal uptake in plants by forming glycoprotein–metal complexes, and improve the quality of the soil. They also assist plants in phytoremediation by increasing the absorptive area, increase the antioxidant response, chelate heavy metals and stimulate genes for protein synthesis that reduce the damage caused by free radicals. The current manuscript focuses on the uptake of heavy metals, accumulation, and arbuscular mycorrhizal impact in ameliorating heavy metal stress in plants.

We present early-phase panchromatic photometric and spectroscopic coverage spanning the far-ultraviolet to near-infrared regime of the nearest hydrogen-rich core-collapse supernova (SN) in the last 25 yr, SN 2023ixf. We observe early “flash” features in the optical spectra due to confined dense circumstellar material (CSM). We observe high-ionization absorption lines (Fe ii, Mg ii) in the ultraviolet spectra from very early on. We also observe a multipeaked emission profile of Hα in the spectrum beginning at ∼16 days, which indicates ongoing interaction of the SN ejecta with a preexisting shell-shaped CSM having an inner radius of ∼75 au and an outer radius of ∼140 au. The shell-shaped CSM is likely a result of enhanced mass loss ∼35–65 yr before the explosion assuming a standard red supergiant wind. The UV spectra are dominated by multiple highly ionized narrow absorption and broad emission features from elements such as C, N, O, Si, Fe, and Ni. Based on early light-curve models of Type II SNe, we infer that the nearby dense CSM confined to 7 ± 3 × 1014 cm (∼45 au) is a result of enhanced mass loss (10−3.0±0.5 M ⊙ yr−1) two decades before the explosion.

Numerous abiotic stresses trigger the overproduction of reactive oxygen species (ROS) that are highly toxic and reactive. These ROS are known to cause damage to carbohydrates, DNA, lipids and proteins, and build the oxidative stress and results in the induction of various diseases. To resolve this issue, antioxidants molecules have gained significant attention to scavenge these free radicals and ROS. However, poor absorption ability, difficulty in crossing the cell membranes and degradation of these antioxidants during delivery are the few challenges associated with both natural and synthetic antioxidants that limit their bioavailability. Moreover, the use of nanoparticles as an antioxidant is overlooked, and is limited to a few nanomaterials. To address these issues, antioxidant functionalized nanoparticles derived from various biological origin have emerged as an important alternative, because of properties like biocompatibility, high stability and targeted delivery. Algae, bacteria, fungi, lichens and plants are known as the producers of diverse secondary metabolites and phenolic compounds with extraordinary antioxidant properties. Hence, these compounds could be used in amalgamation with biogenic derived nanoparticles (NPs) for better antioxidant potential. This review intends to increase our knowledge about the antioxidant functionalized nanoparticles and the mechanism by which antioxidants empower nanoparticles to combat oxidative stress.

Green synthesis has gained wide attention as a sustainable, reliable, and eco-friendly approach to the synthesis of a variety of nanomaterials, including hybrid materials, metal/metal oxide nanoparticles, and bioinspired materials. Plant flowers contain diverse secondary compounds, including pigments, volatile substances contributing to fragrance, and other phenolics that have a profound ethnobotanical relevance, particularly in relation to the curing of diseases by ‘Pushpa Ayurveda’ or floral therapy. These compounds can be utilized as potent reducing agents for the synthesis of a variety of metal/metal oxide nanoparticles (NPs), such as gold, silver, copper, zinc, iron, and cadmium. Phytochemicals from flowers can act both as reducing and stabilizing agents, besides having a role as precursor molecules for the formation of NPs. Furthermore, the synthesis is mostly performed at ambient room temperatures and is eco-friendly, as no toxic derivatives are formed. The NPs obtained exhibit unique and diverse properties, which can be harnessed for a variety of applications in different fields. This review reports the use of a variety of flower extracts for the green synthesis of several types of metallic nanoparticles and their applications. This review shows that flower extract was mainly used to design gold and silver nanoparticles, while other metals and metal oxides were less explored in relation to this synthesis. Flower-derived silver nanoparticles show good antibacterial, antioxidant, and insecticidal activities and can be used in different applications.