The research aims to clarify the response of the GDP to the M1 shock. It includes access to the results using standard methods, where the standard model was built according to quarterly data using the program STATA 17. According to the joint integration model ARDL, the research found a long-term equilibrium positive for the relationship between GDP and the money supply in Iraq, as the change in the money supply by a certain percentage will lead to a change in GDP by about 71% of that percentage. In the event of a shock in the Iraqi economy, the impact of the M1 will differ from what it was before the shock, as the shock will increase its effectiveness towards GDP by about 10% more than before the shock. At the same time, the relationship

Origanum majorana (Majorana hortensis), an evergreen herbaceous plant belonging to the Lamiaceae family, has been well known for being used for gastrointestinal, cardiac, respiratory, rheumatologic and many other illnesses, but in wounds management hasn’t been qualified scientifically yet. The goal of the study was to evaluate the wound healing properties of sterols in n-hexane and phenols in ethyl acetate extract fractions of the Iraqi Origanum majorana L aerial parts by contrasting their wound healing abilities with those of commercially available MEBO ointment in a rat excised wound repair model. At various periods, the size of the wounds was measured and skin tissue samples were taken for histopathology. When compared to positive and

This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi

Abstract

Here we present the results of experiments involving cynomolgus macaques, in which a model of traumatic spinal cord injury (TSCI) was created by using a balloon catheter inserted into the epidural space. Prior to the creation of the lesion, we inserted an EMG recording device to facilitate measurement of tail movement and muscle activity before and after TSCI. This model is unique in that the impairment is limited to the tail: the subjects do not experience limb weakness, bladder impairment, or bowel dysfunction. In addition, 4 of the 6 subjects received a combination treatment comprising thyrotropin releasing hormone, selenium, and vitamin E after induction of experimental TSCI. The subjects tolerated the implantation of the recording devi

Since the emergence of the science of international relations as an independent academic scientific field,  various theories and trends have appeared and have tried to understand and explain the international reality and give a clear picture of what is happening within the international system of interactions and influences and the search for tools for stability and peace in international relations. Among these theories is the feminist theory, which is a new intellectual trend on the level of international relations theories,  which tried to give an explanation of what is happening in world politics and in international relations in particular. The main issue that feminist theory is concerned with is the lack of women’s subordination

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

Following model educational offenders in collection and Alasbaka of fifth grade students preparatory in history A. M. Dr Prepared by: Dr. Bashaer Mawloud Tawfeeq, The Center of Educational and Psychological Studies Baghdad University - There is no difference statistically significant at the 0.05 level of significance between the average scores of the following students studying using model and offenders and who are studying in the usual manner (traditional) in the collection - There is no difference statistically significant at the 0.05 level of significance between the mean scores for the following students studying using model and offenders and who are studying in the usual manner (traditional) in retention Find limits: Current search

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