Aim: The present study aims to improve the poor water solubility of zaltoprofen which is a non-steroidal anti-inflammatory drug (NSAIDs) with a potent analgesic effect using solid dispersion then formulate it as a hollow type suppository to be more convenient for geriatric patients. Materials and Method: Zaltoprofen solid dispersions were prepared by solvent evaporation technique in different zaltoprofen: Soluplus® ratios. Results: Among the formulations tested, zaltoprofen solid dispersion preparation using 1:5 (zaltoprofen: Soluplus®) ratio showed the highest solubility and selected for further investigation. Solid dispersion characterization was evaluated by differential scanning calorimetry (DSC), X-ray diffraction study (XRD) and Fou

Laser-Induced Breakdown Spectroscopy (LIBS) has been documented as an Atomic Emission Spectroscopy (AES) technique, utilising laser-induced plasma, in order to analyse elements in materials (gases, liquids and solid). The Nd:YAG laser passively Q-switched at 1064nm and 9ns pulse duration focused by convex lens with focal length 100 mm to generates power density 5.5×1012 Mw/mm2 with optical spectrum in the range 320-740 nm. Four soil samples were brought from different northern region of Iraq, northern region (Beiji, Sherkat, Serjnar and Zerkary).
The soil of the Northern region of Beige, Sherkat, Serjnar and Zarkary has abundant ratios of the elements P [0.08, 0.09, 0.18, 0.18] and Ca [0.61, 0.15, 0.92, 0.92] while it lack of Si [0.0

As population growth increases the demand for crops increases and their quality improves, and it becomes necessary to find innovative and modern solutions to enhance production. In this context, artificial intelligence plays a pivotal role in developing new technologies to improve crop sorting and increase agricultural yields. The present review discusses the main differences between manual and mechanical potato harvesting, explaining the advantages and disadvantages of each method. Manual harvesting is highlighted as a traditional method that allows for greater precision in handling the crop, but it requires more time and effort. In contrast, mechanical harvesting provides greater efficiency and speed in the process, but it may damage some

This research aims to study the important of the effect of analysis of covariance manner for one of important of design for multifactor experiments, which called split-blocks experiments design (SBED) to deal the problem of extended measurements for a covariate variable or independent variable (X) with data of response variable or dependent variable Y in agricultural experiments that contribute to mislead the result when analyze data of Y only. Although analysis of covariance with discussed in experiments with common deign, but it is not found information that it is discussed with split-Blocks experiments design (SBED) to get rid of the impact a covariance variable. As part application actual field experiment conducted, begun at

ew sports technologies have highlighted the importance of perceptual – cognitive training in order to optimize performance in sports e.g., dynamic team sport such as basketball. Augmented motor reality AMR is a new training model based on realistic movement combined with interactive virtual cues that may be useful to enhance spatial orientation and decision making. The purpose of this study was to investigate the effects of an AMR-based training program on spatial awareness and skill-based decision making in youth basketball players. Twenty-four male young basketball players aged 15.2±0.8 years were randomized to the experimental group n=12, receiving AMR training, and control group n=12, performing conventional practice. The interventio

New sports technologies have highlighted the importance of perceptual – cognitive training in order to optimize performance in sports e.g., dynamic team sport such as basketball. Augmented motor reality AMR is a new training model based on realistic movement combined with interactive virtual cues that may be useful to enhance spatial orientation and decision making. The purpose of this study was to investigate the effects of an AMR-based training program on spatial awareness and skill-based decision making in youth basketball players. Twenty-four male young basketball players aged 15.2±0.8 years were randomized to the experimental group n=12, receiving AMR training, and control group n=12, performing conventional practice. The interventi

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

Catalytic reforming of naphtha occupies an important issue in refineries for obtaining high octane gasoline and aromatic compounds, which are the basic materials of petrochemical industries. In this study, a novel of design parameters for industrial continuous catalytic reforming reactors of naphtha is proposed to increase the aromatics and hydrogen productions. Improving a rigorous mathematical model for industrial catalytic reactors of naphtha is studied here based on industrial data applying a new kinetic and deactivation model. The optimal design variables are obtained utilizing the optimization process in order to build the model with high accuracy and such design parameters are then applied to get the best configuration of this pro