Nanocomposite of carbon nanotube add to epoxy resin material of weight fraction ( 0.25, 0.5, 0.75 1.0, 1.25, 1.5, 1.75 , 2 & 2.5 wt. % ) were fabricated by dispersing within an epoxy resin using a Ultrasound machine followed by mechanical stirring. The samples were heat treated at temperature ( 80 °C for 3 hrs) The mechanical properties of the composites were investigated. Wear and hardness properties measurements indicated higher wear rate and hardness with increasing concentration of MWCNTs . The MWCNTs significantly improved the wear resistance and hardness when compare than the pure epoxy. These note show too after heat treatment of composite with ( 80 oC for 3 hrs ).

This research studied the effects of modified BaTiO₃ (BT) nanoparticles with coupling agent γ-APS (0.5wt. %) on the tensile and thermal conductivity of epoxy nanocomposites with respect to content (0.25, 0.5, 0.75, 1, 3 and 5wt. %). Multiwall carbon nanotubes (MWCNTs) at different concentration (0.2, 0.4, 0.8 and 1 wt. %) were added to the BaTiO₃/epoxy nanocomposites. The influence of MWCNTs on the tensile properties and thermal conductivity was investigated. The tensile strength and Young’s modulus of BaTiO₃/epoxy nanocomposites film were increased at up to 3 wt. % of added BT, but  adding BT at more than 3 wt.% decreased the strength of epoxy. The tensile strength was increased with incre

Objective :.
1-Find out the prevalence of alcohol and drugs addiction in two different years before and after the last
war i.e. in 2002 and in 200. 2-Study the association between the addiction
and some variables. 3-Identify the prescribed drugs and other substances that
have been abused
Methodology : A retrospective study has been conducted involving the in-patients at addiction unit-IbnRushd
psychiatric hospital in Baghdad by applying the semi-structured form based on ICD-10 criteria
of addiction and dependency with the confirmation of the specialist psychiatrist diagnosis of
dependency. Data concerning each patient admitted in the hospital was gathered to have an idea about
the problem of addiction (drugs an

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

In this work Laser wireless video communication system using intensity modualtion direct
detection IM/DD over a 1 km range between transmitter and receiver is experimentally investigated and
demonstrated. Beam expander and beam collimeter were implemented to collimete laser beam at the
transmitter and focus this beam at the receiver respectively. The results show that IM/DD communication
sysatem using laser diode is quite attractive for transmitting video signal. In this work signal to noise
ratio (S/N) higher than 20 dB is achieved in this work.

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Air pollution is one of the important problems facing Iraq. Air pollution is the result of uncontrolled emissions from factories, car exhaust electric generators, and oil refineries and often reaches unacceptable limits by international standards. These pollutants can greatly affect human health and regular population activities. For this reason, there is an urgent need for effective devices to monitor the molecular concentration of air pollutants in cities and urban areas. In this research, an optical system has been built consisting of aHelium-Neonlaser,5mWand at 632.8 nm, a glass cell with a defined size, and a power meter(Gentec-E-model: uno) where a scattering of the laser beam occurs due to air pollution. Two pollutants were examin

A nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na

  Numerous integral and local electron density’s topological parameters of significant metal-metal and metal-ligand bonding interactions in a trinuclear tetrahydrido cluster [(Cp* Ir) (Cp Ru)₂ (μ₃-H) (μ-H)₃]1 (Cp = η⁵ -C₅Me₅), (Cp* = η⁵ -C₅Me₄Et) were calculated and interpreted by using the quantum theory of atoms in molecules (QTAIM). The properties of bond critical points such as the delocalization indices δ (A, B), the electron density ρ(r), the local kinetic energy density G(r), the Laplacian of the electron density ∇²ρ(r), the local energy density