Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati

due to the presence of chemoresistance and the risk of tumor recurrence and metastasis. There is a pressing necessity to develop efficient treatments to improve response for treatment and increase prolong survival of breast cancer patients. Photodynamic therapy (PDT) has attracted interest for its features as a noninvasive and relatively selective cancer treatment. This method relies on light-activated photosensitizers that, upon absorbing light, generate reactive oxygen species (ROS) with powerful cell-killing outcomes. Nuclear factor kappa B (NF-κB), a transcription factor, plays a key role in cancer development by regulating cell proliferation, differentiation, and survival. Inhibiting NF-κB can sensitize tumor cells to chemotherapeuti

The consumption of fossil fuels has caused many challenges, including environmental and climate damage, global warming, and rising energy costs, which has prompted seeking to substitute other alternative sources. The current study explored the microwave pyrolysis of Albizia branches to assess its potential to produce all forms of fuel (solid, liquid, gas), time savings, and effective thermal heat transfer. The impact of the critical parameters on the quantity and quality of the biofuel generation, including time, power levels, biomass weight, and particle size, were investigated. The results revealed that the best bio-oil production was 76% at a power level of 450 W and 20 g of biomass. Additionally, low power levels led to enhanced

Tetradentate complexes type [M (HL) 2] were prepared from the reaction of 2-hydroxy -1, 2-diphynel-ethanone oxime [H2L] and KOH with ( Mn II, Fe II, Co II, Ni II , Cu II and Hg II ), in methanol with (2:1) metal: ligand ratio. The general formula for Cu II and Mn II complexes are [M (HL) 2 Cl.H2O] K, for Co II [Co (HL) 2. H2O] and [M (HL) 2] for the rest of complexes. All compounds were characterised by spectroscopic methods, I.R, U.V-Vis, H.P.L.C, atomic absorption and conductivity measurements chloride content. From the data of these measurements, the proposed molecular structures for Fe II and Hg II complexes are tetrahedrals, while Mn II and Cu II complexes are octahedrals, Ni II complex adopting square planar structure and the complex

When writing a text, such as a newspaper article, various types of discourse markers are frequently used to group sentences into paragraphs and parts in order to establish a discourse with certain functions, such as coordination, orientation, emphasizing the concepts presented, etc. It should also be noted that this type of mark exists in both written and spoken language. Therefore, it is convenient to dedicate a chapter to these linguistic elements to clarify their use and their classification, which is mainly based on Jose Portolés (2001), as well as the main features, specifically their features (prosodic, morphological, semantic and pragmatic).

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