The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

We prepared polythiophene (PTH) with single wall carbon nanotube (SWCNT) nanocomposite thin films for Nitrogen dioxide (NO2) gas sensing applications. Thin films were synthesized via electrochemical polymerization method onto (Indium tin oxide) ITO coated glass substrate of thiophene monomer with magnesium perchlorate and different concentration from SWCNT (0.012 and 0.016) % in the presence130mL of Acetonitrile used. X-ray diffraction (XRD), Field Emission Scanning Electron microscopy (FE-SEM), Atomic Force Microscope (AFM) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to characterized these nanocomposite thin films. The response of these nanocomposite for NO₂ gas was evaluated via monitoring the change

The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ

The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

Empirical equations for estimating thickening time and compressive strength of bentonitic - class "G" cement slurries were derived as a function of water to cement ratio and apparent viscosity (for any ratios). How the presence of such an equations easily extract the thickening time and compressive strength values of the oil field saves time without reference to the untreated control laboratory tests such as pressurized consistometer for thickening time test and Hydraulic Cement Mortars including water bath ( 24 hours ) for compressive strength test those may have more than one day.

In this study, the hydromorphodynamic simulation of a stretch of the Euphrates River was conducted. The stretch of the Euphrates River extended from Haditha dam to the city of Heet in Al-Anbar Governorate and it is estimated to be 124.4 km. Samples were taken from 3 sites along the banks of the river stretch using sampling equipment. The samples were taken to the laboratory for grain size analysis where the median size (D₅₀) and sediment load were determined. The hydromorphodynamic simulation was conducted using the NACY 2DH solver of the iRIC model.  The model was calibration using the Manning roughness,    sediment load, and median particle size and the validation process showed that the error between th

The study presents the test results of stabilizing gypseous soil embankment obtained from
Al- Faluja university Campus at Al-Ramady province. The laboratory investigation was divided
into three phases, The physical and chemical properties, the optimum liquid asphalt (emulsion)
requirements (which are manufactured in Iraq) were determined by using one dimensional
unconfined compression strength test.in the first phase , The optimum fluid content was 11%
(6% of emulsion with 5% water content).. At phase two, the effect of Aeration technique was
investigated using both direct shear and permeability test. At phase three for the case of static
load , the pure soil embankment model under dry test condition was investigated

This research presents experimental and theoretical investigation of 15 reinforced concrete spliced and nonspliced girder models. Splices of hooked dowels and cast in place joints, with or without strengthening steel plates were used. Post-tensioning had been used to enhance the splice strength for some spliced girders. The ANSYS computer program was used for analyzing the spliced and non-spliced girders. A nonlinear three dimensional element was used to represent all test girders. The experimental results have shown that for a single span girder using steel plate connectors in the splice zone has given a sufficient continuity to resist flexural stresses in this region. The experimental results have shown that the deflection of hooked do