The research aims at integrating the disclosure of the business models with the qualitative characteristics of accounting information. To achieve this, the elements of the business model should be identified and disclosed, and then study the possibility of integrating the disclosure of the business model with the qualitative characteristics of accounting information.

To achieve this objective, the research was based on the indicators of disclosure of the business model of the International Accounting Standards Board to measure the disclosure of the business model.

The research reached a number of conclusions, the most important of which were as follows:

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An Investigation of estimated Mechanical Properties of AL-Alloys 2024-T3, which is the most commonly used in industrial applications, been established experimentally. A new novel Plasma Peening techniques had applied for the whole surfaces of the material by CNC-Plasma machine for 48 specimen, and then a new investigation were toke over to figure the amount of change in mechanical properties and estimated fatigue life. It found that improvement was showing a nonlinear behavior according to peening duration time, speed, peening distance, peening number, and amount of effected power on the depth of the material thickness. The major improvement was at medium speed long duration time normal peening distance. Which shows up t

It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

Polyhydroxyalkanoates (PHAs) have gained much attention as biodegradable polymers, many efforts are being made to minimize the cost of PHAs by finding cheap carbon source depending on the type of microorganism and fermentation conditions. The aims of this study were to evaluate the effects of different glucose concentrations and other important conditions on the PHA production by Bacillus cereus isolated from soil. Polyhydroxyalkanoates PHAs accumulated by soil microorganisms were examined by screening the isolated bacteria using Sudan B Black and Nile Blue staining process. A Gram positive strain was identified using the 16s rRNA gene, deposited in the NCBI GenBank sequence database. Different growth conditions (favorite glucose concentrat

The mixed ligand complexes of Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II) with alanine and 8-hydroxyqinoline (Oxine) were synthesized and characterized by FT-IR ,spectra electronic, flam-AAS] along with conductivity measurements , solubility , melting point, magnetic susceptipibility.The synthesized complexes were tested in vitro for antimicrobial activity. The results obtained indicated that some of these complexes are more active than with others.

Corncob is an agricultural biomass waste that was widely investigated as an adsorbent of contaminants after transforming it into activated carbon. In this research carbonization and chemical activation processes were achieved to synthesize corncob-activated carbon (CAC). Many pretreatment steps including crushing, grinding, and drying to obtain corncob powder were performed before the carbonization step. The carbonization of corncob powder has occurred in the absence of air at a temperature of 500 °C. The chemical activation was accomplished by using HCl as an acidic activation agent. Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) facilitate

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

Experimental research was carried out to investigate the effect of fire flame (high temperature) on specimens of short columns manufactured using SCC (Self compacted concrete). To simulate the real practical fire disasters, the specimens were exposed to high
temperature flame, using furnace manufactured for this purpose. The column specimens were cooled in two ways. In the first the specimens were left in the air and suddenly cooled using water, after that the specimens were loaded to study the effect of degree of
temperature, steel reinforcement ratio and cooling rate, on the load carrying capacity of the reinforced concrete column specimens. The results will be compared with behaviour of columns without burning (control specime