Enhanced transformer long short-term memory framework for datastream prediction

In machine learning, datastream prediction is a challenging issue, particularly when dealing with enormous amounts of continuous data. The dynamic nature of data makes it difficult for traditional models to handle and sustain real-time prediction accuracy. This research uses a multi-processor long short-term memory (MPLSTM) architecture to present a unique framework for datastream regression. By employing several central processing units (CPUs) to divide the datastream into multiple parallel chunks, the MPLSTM framework illustrates the intrinsic parallelism of long short-term memory (LSTM) networks. The MPLSTM framework ensures accurate predictions by skillfully learning and adapting to changing data distributions. Extensive experimental assessments on real-world datasets have demonstrated the clear superiority of the MPLSTM architecture over previous methods. This study uses the transformer, the most recent deep learning breakthrough technology, to demonstrate how well it can handle challenging tasks and emphasizes its critical role as a cutting-edge approach to raising the bar for machine learning

Cytotoxic activity and phytochemical analysis of Arum palaestinum Boiss.

Objective: To evaluate the in vitro cytotoxic activity of the fractionated extract as well as isolated compounds of Arum palaestinum Boiss. (A. palaestinum) (black calla lily), and to identify the volatile components which may be responsible for the potential antitumor activity. Methods: A. palaestinum was collected from its natural habitats and subjected to phytochemical analysis for separation of pure compounds. In vitro cytotoxic activity was investigated against four human carcinoma cell lines Hep2, HeLa, HepG2 and MCF7 for the fractionated extract and isolated compounds. While, the diethyl ether fraction was subjected to GC–MS analysis as it exhibited the most potent cytotoxic effect to evaluate the active constituents responsible for the cytotoxic activities. Results: Four flavonoid compounds were isolated (luteolin, chrysoeriol, isoorientin, isovitexin) from the diethyl ether and ethyl acetate. The extracts and the pure isolated compounds showed a significant high antiproliferative activity against all investigated cell lines. The GC–MS analysis revealed the separation and identification of 15 compounds representing 95.01% of the extract and belonging to different groups of chemical compounds. Conclusions: The present study is considered to be the first report on the cytotoxic activities carried out on different selected fractions and pure compounds of A. palaestinum to provide evidences for its strong antitumor activities. In addition, chrysoeriol and isovitexin compounds were isolated for the first time from the studied taxa

Interactive Effects of Arbuscular Mycorrhizal Inoculation with Nano Boron, Zinc, and Molybdenum Fertilization on Stevioside Contents of Stevia (Stevia rebaudiana, L.) Plants

Stevia (Stevia rebaudiana, L.) is receiving increasing global interest as a diabetes-focused herb associated with zero-calorie stevioside sweetener glycoside production. This study was conducted to determine whether the arbuscular mycorrhiza (AM), as a biofertilizer integrated with nano boron (B), zinc (Zn), and molybdenum (Mo), would improve stevia growth and stevioside content. A factorial experiment with four replicates was conducted to evaluate the effect of AM at 0, 150, and 300 spore/g soil and three nano microelements B at 100 mg/L, Zn at 100 mg/L, and Mo at 40 mg/L on growth performance, stevioside, mineral contents, and biochemical contents of stevia. Results indicated that the combination of AM at 150 and B at 100 mg/L significantly increased plant height, number of leaves, fresh and dry-stem, and herbal g/plant during the 2019 and 2020 growing seasons. Chlorophyll content was increased by the combination between AM at 150 spore/g soil and B at 100 mg/L during both seasons. Stevioside content in leaves was increased by AM at 150 spore/g soil and B at 100 mg/L during the second season. In addition, N, P, K, Zn, and B in the leaf were increased by applying the combination of AM and nano microelements. Leaf bio constituent contents were increased with AM at 150 spore/g soil and B at 100 mg/L during both seasons. The application of AM and nano B can be exploited for high growth, mineral, and stevioside contents as a low-calorie sweetener product in stevia