In this paper, based on the E. Study map, clear terms are oered for the dierential equations
of one-parameter Lorentzian spatial kinematics that are coordinate system-independent. This cancels
the request of demanding coordinate transformations that are typically required in the determination of
the canonical systems. With the suggested technique, new proofs of the Disteli formulae of a spacelike
line trajectory are instantly gained and their spatial equivalents are studied in detail. As a consequence,
we address the kinematic geometry of a point trajectory for the one-parameter Lorentzian spherical
and planar movements.

In this paper, we study the singularities on a non-developable ruled surface according to
Blaschke’s frame in the Euclidean 3-space. Additionally, we prove that singular points occur on this
kind of ruled surface and use the singularity theory technique to examine these singularities. Finally,
we construct an example to confirm and demonstrate our primary finding.

The dilute HCl pretreatment of the calcareous red alga, Liagora viscida, either at room temperature or 100 °C, produced Ca²⁺/carrageenan-containing extracts. Dipping strawberries in these extracts for 10 s demonstrated their ability to maintain various quality and nutritional traits during cold storage. The weight loss of the fruits after 7 days at 4 °C was reduced to 2.48–2.63 % in the treatments, compared to 3.26 % in the control. The treatments were effective in retaining the contents of vitamin C, titratable acidity, and phenolics, compared to marked reductions in the control. Additionally, the levels of anthocyanins, flavonoids, and the total antioxidant capacity were enhanced during cold storage. The treated fruits also showed higher chitinase activities, while the activities of cellulase, polygalacturonase, and pectin methylesterase (PME) showed remarkable reductions. The application of the extract derived at 100 °C reduced the decay caused by Botrytis cinerea decay to 34 % and 63.26 % after 3 and 4 days of infection, respectively, compared to 55.09–97 % in the untreated control. This reduction was concomitant with higher anthocyanins, flavonoids, and chitinase, and lower cellulase and PME in this treatment. The levels of malondialdehyde indicated less stressed fruits during both cold storage and fungal infection. Overall, the treatments promoted systemic resistance in the fruits, enhancing their ability to defend against pathogens. These results suggest the promising utilization of calcareous macroalgae as a sustainable biomass for developing a cost-effective and eco-friendly preservative to extend the shelf-life of strawberries during cold storage and enhance their resistance to pathogens.

The name kojic acid was acquired from “Koji”, a fungus or starter inoculum consumed in Japanese oriental food. It is a secondary metabolite organic acid secreted by several species of Aspergillus. Their chemical structure was determined as 5-hydroxy-2-hydroxymethyl-δ-pyrone and produced industrially by Aspergillus species in aerobic fermentation. It has various applications in several fields as antimicrobial, anticancer, tyrosinase inhibitor, insecticide and pesticide organic compounds. It applied in some cosmetic, medicine, food, agriculture and chemical industries. The production of kojic acid is increasing because of its commercial value in various industries. The needing for kojic acid has been constantly increasing. This chapter is to shed light on the history, properties, producer fungi and biosynthetic pathway of this important organic acid. Also, the advance in kojic acid fermentation, medium as well as optimization of nutritional and environmental production conditions are discusses. Some derivatives and diverse applications of kojic acid in industries are described. Future prospects of kojic acid also discussed through this chapter.

We all know that the drug discovery process takes years to discover a new drug. Identifying potential drug targets requires years of preclinical research to identify and validate the most promising targets. Artificial intelligence (AI) has emerged as a potent tool for harnessing anthropomorphic knowledge and providing quick solutions to complex problems. Amazing advancements in AI technology and machine learning (ML) present a game-changing opportunity to increase efficiency and accuracy in drug discovery and development. Researchers can identify disease-associated targets and predict their interactions with potential drugs by using AI algorithms that analyse large amounts of biological data, such as genomics and proteomics. This allows for a more efficient and targeted approach to drug discovery from microbes, increasing the likelihood of drug approval success. ML algorithms can predict the bioactivity and toxicity of drug candidates and aid in experimental design. Besides, AI can aid in predicting the mechanism of action, adverse reactions and also play a great role in designing clinical trials and predicting the outcomes. This capability enables lead compound prioritization and optimization, reducing the need for extensive and costly animal testing. AI algorithms can help with personalized medicine approaches, resulting in more effective treatment outcomes and improved patient adherence. This chapter discusses the diverse applications of AI and ML to improve the efficiency of drug discovery, drug screening, designing drug molecules, prediction of the mechanism of action, prediction of the maintenance and quality control, prediction of adverse events, and clinical trial design.