This paper is concerned with finding solutions to free-boundary inverse coefficient problems. Mathematically, we handle a one-dimensional non-homogeneous heat equation subject to initial and boundary conditions as well as non-localized integral observations of zeroth and first-order heat momentum. The direct problem is solved for the temperature distribution and the non-localized integral measurements using the Crank–Nicolson finite difference method. The inverse problem is solved by simultaneously finding the temperature distribution, the time-dependent free-boundary function indicating the location of the moving interface, and the time-wise thermal diffusivity or advection velocities. We reformulate the inverse problem as a non-

The two objectives of the current research are :-

1. Uncover the views and opinions of the students of Artistic Education Department about the relation between educational novelty and its relation with visual . 
2. Identifying the capabilities of the students of artistic education department .

            The society of the research is the  fourth class students of artistic education department -  College of Fine Arts  ( 83 students from both sexes ) .  It was chosen ( 60 ) students sample of  from both sexes by the researcher in order to conduct test upon them .The researcher has adopted descr

     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

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