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Big-medical-data classification and image detection are crucial tasks in the field of healthcare, as they can assist with diagnosis, treatment planning, and disease monitoring. Logistic regression and YOLOv4 are popular algorithms that can be used for these tasks. However, these techniques have limitations and performance issue with big medical data. In this study, we presented a robust approach for big-medical-data classification and image detection using logistic regression and YOLOv4, respectively. To improve the performance of these algorithms, we proposed the use of advanced parallel k-means pre-processing, a clustering technique that identified patterns and structures in the data. Additionally, we leveraged the acceleration capabilities of a neural engine processor to further enhance the speed and efficiency of our approach. We evaluated our approach on several large medical datasets and showed that it could accurately classify large amounts of medical data and detect medical images. Our results demonstrated that the combination of advanced parallel k-means pre-processing, and the neural engine processor resulted in a significant improvement in the performance of logistic regression and YOLOv4, making them more reliable for use in medical applications. This new approach offers a promising solution for medical data classification and image detection and may have significant implications for the field of healthcare. [ABSTRACT FROM AUTHOR]

A library of N-benzylpyridinium-based compounds, 7a-j and 8a-j, was designed and synthesised as potential acetylcholinesterase) AChE (inhibitors. An in vitro assay for the synthesised compounds showed that most compounds had significant AChE inhibitory activities at the nanomolar and submicromolar levels. The benzyl (8a) and fluoro (8b) derivatives were the most active, with IC50 values ≤56 nM. Compound 7f, which had a benzyl moiety, showed the highest potency among all the target compounds, with an IC50 value of 7.5 ± 0.19 nM against AChE, which was higher than that of the activities of tacrine (IC50 = 30 ± 0.2 nM) and donepezil (IC50 = 14 ± 0.12 nM). Compounds with vanillin moieties exhibited antioxidant activity. Among the tested compounds, four derivatives (7f, 7 g, 8f, and 8 g) exhibited superior AChE inhibitory activity, with Ki values of 6–16 nM, which were potent in the same range as the approved drug, donepezil. These compounds showed moderate antioxidant activities, as indicated by the results of the ABTS assay. [ABSTRACT FROM AUTHOR]

To generate high-yielding cultivars with favorable fiber quality traits, cotton breeders can use information about combining ability and gene activity within a population to locate elite parents and potential F1 crosses. To this end, in the current study, twelve cotton parents (eight genotypes as female parents and four testers) and their F1 crosses obtained utilizing the linex tester mating design were evaluated for their general and specialized combining abilities (GCA and SCA, respectively) of yield traits. The findings showed that for all the investigated variables, variances owing to genotypes, parents, crosses, and parent vs cross showed extremely significant (P ≤ 0.01) differences. Additionally, throughout the course of two growing seasons, the mean squares for genotypes (parents and crosses) showed strong significance for all the variables under study. The greatest and most desired means for all the examined qualities were in the parent G.94, Pima S6, and tester G.86. The best crossings for the qualities examined were G.86 (G.89 × G.86), G.93 × Suvin, and G.86 × Suvin. The parents' Suvin, G89x G86 and TNB were shown to have the most desired general combining ability effects for seed cotton yield/plant, lint yield/plant, boll weight, number of bolls/plants, and lint index, while Suvin, G.96 and pima S6 were preferred for favored lint percentage. For seed cotton yield, lint percentage, boll weight, and number of bolls per plant per year, the cross-G.86 x (G.89 × G.86) displayed highly significant specific combining ability impacts. The crosses G.86 × Suvin, Kar x TNB, G.93 × Suvin, and G.93 × TNB for all the studied traits for each year and their combined were found to have highly significant positive heterotic effects relative to better parent, and they could be used in future cotton breeding programs for improving the studied traits. [ABSTRACT FROM AUTHOR]

Natural fibre–reinforced epoxy composites have been increasingly utilised in construction and building applications. These materials introduce cost-effective alternatives to conventional materials and their utilisation often has related to financial advantages that are immediate and can be expected over the structure service life. In this work, the results of thermal, dynamic-mechanical, and thermal-mechanical properties of date palm fibre (DPF)/bamboo fibre (BF) hybrid composite were compared to bamboo fibre-reinforced epoxy to demonstrate the importance of hybridization. The thermal stability was improved when DPF/BF fillers were added in epoxy resin comparatively to BF reinforced epoxy. The glass transition temperature (T g) was increased by incorporating the date palm fibre/bamboo hybrid composite in epoxy compared to the BF reinforced epoxy. The thermal expansion was enhanced by modifying the hybrid composites in epoxy in contrast to the single fibre composites, without hybridisation. Hence, the hybridisation technique of date palm fibre with bamboo has improved the thermal and thermal-mechanical properties suitable for several applications including non-structural applications. [ABSTRACT FROM AUTHOR]

In this research NaOH treated date palm fibres were used as reinforcement in phenolic based composites. The composites were prepared by hot press technique and evaluated tensile flexural, structural, thermo gravimetric dynamic mechanical properties. Overall properties of modification/treatment of fibers' surface enhanced, that have been studied as compared to untreated samples. The treated samples of 50% DPF composites showed highest Tensile properties among all composites but flexural properties declined compared to the untreated composites but this decline is very less. Fibre treatment showed declined properties of three point bending of DPF composites. Scanning Electron Microscopy studied the behavior of fibre and matrix bonding before and after treatment. Treated 50% DPF showed better fibre distribution, 60% DPF showed void content however 40%DPF showed poor fibre/matrix interfacial bonding. Thermogravimetric analysis studied the behavior of Treated DPF/Phenolic composites at high temperature, and found thermal stability enhanced because good interfacial bonding. Dynamic mechanical analysis showed that stability at stress of material with temperature and also studied the energy dissipation and internal friction. Treated 50%DPF showed better properties due to the ratio of mixing of fibre/matrix and better interfacial bonding. DPF composite have potential to use for exterior applications and false wall and roof. [ABSTRACT FROM AUTHOR]