Physical properties of soil in terms of calculating the gravitational water percentage, calculating moisture in the soil, and calculating porosity by calculating the apparent and true density.
Enteral feeding is preferred route of nutrition support in critically ill adults when GIT function is good. Enteral nutrition is recommended method to be used when oral feeding fails, so the nutrition is delivered through a tube inserted into the sto
mach. Enteral nutrition has some complications; Mechanical complications are represented by pulmonary aspiration. Pulmonary aspiration is defined as inhalation of the contents of the mouth, pharynx or stomach into the respiratory tract. So it's important to evaluate pulmonary aspiration occurrence, this may help in prevention care. This study aimed to evaluate pulmonary aspiration among critically ill patients who have Enteral feeding by using nasogastric tube. Descriptive study was performed using convenience sample of (n=15) patients at intensive care unit in tishreen university hospital in lattakia, Syria. Data were collected during the period of 16/2 to 16/5 2022. A structured questionnaire used in the study was developed by researcher, this tool was tested for reliability and validity, a pilot study was done for 3 nurses to test the tool applicability. This study results show the presence blue colure (which added to feeding meal) in the aspirated secretion in the first day at the third suction trial. This study recommended applying an evidenced based practice written protocol about enteral feeding in ICU, to decrease the incidence of pulmonary aspiration.
This scientific study aims to evaluate the effects of bowel preparation on the outcomes of scheduled colorectal surgery. The study included a group of 83 patients, 37 without bowel preparation and 46 with bowel preparation. Perioperative outcomes of
patients were evaluated, including surgical site infection (SSI) rates, postoperative complications, and length of hospital stay.
The results concluded that bowel preparation before scheduled colorectal surgery has no superiority in reducing SSI and postoperative complications (anastomotic leakage, occurrence of abdominal or pelvic abscesses), as well as shortening the length of hospital stay, and did not show any clear advantage over the patients without mechanical bowel preparation.
In this research, the effect of different concentrations of Lavender oil on the growth of was studied Fusarium oxysporum،Acremonium strictum and all studied concentrations showed a clear inhibitory effect against this fungus.The inhibitory activity v
aried according to the different concentrations
The concentrations (0.06-0.04-0.03-0.02-0.01 ml/g) ) showed 100% inhibition against A. strictum and the inhibition percentage was 64.51% at 0.002ml/g and 58.04% ،35.48% 12.9at a concentration of (0.004،0.002،0.001 ml/g) on the seventh day of incubation. The concentrations (0.06-0.04-0.03-0.02-0.01-0.006-0.004-0.002 ml/g) showed 100% inhibition against Fusarium oxysporum and the inhibition percentage was38.82% at 0.001ml/g on the seventh day of incubation.
The inhibitory activity varied according to the different concentrations (0.06-0.04-0.03-0.02-0.01-0.006-0.002-0.001 ml/g) ) showed 100% inhibition against A. strictum and the inhibition
The lethal concentration (MBC) value of Lavender oil against A. strictum was 0.01 ml/g
And the inhibitory concentration (MIC) was 0.02 ml/g while the inhibitory concentration (MIC)and the lethal concentration (MBC) against F.oxysporum were 0.002 ml/g
The study aimed to identify the difficulties of using the Moodle platform from the point of view of members of the teaching staff at the Faculty of Education at Tishreen University, where the study sample consisted of (50) members of the teaching sta
ff at the Faculty of Education at Tishreen University. A questionnaire consisting of three axes (difficulties related to members of the educational staff, difficulties related to students, difficulties related to infrastructure), each axis includes a number of items, the study used the descriptive approach, and the results showed that the most difficult difficulties experienced by members of the educational staff from their point of view The lack of conviction in the effectiveness of the Moodle platform for the member of the educational staff, and the difficulty of the student's inability to understand the study material through the platform, which came with a high degree. (Academic degree, number of years of experience, gender ) .
Brain Computer Interface (BCI), especially systems for recognizing brain signals using deep learning after characterizing these signals as EEG (Electroencephalography), is one of the important research topics that arouse the interest of many research
ers currently. Convolutional Neural Nets (CNN) is one of the most important deep learning classifiers used in this recognition process, but the parameters of this classifier have not yet been precisely defined so that it gives the highest recognition rate and the lowest possible training and recognition time.
This research proposes a system for recognizing EEG signals using the CNN network, while studying the effect of changing the parameters of this network on the recognition rate, training time, and recognition time of brain signals, as a result the proposed recognition system was achieved 76.38 % recognition rate, And the reduction of classifier training time (3 seconds) by using Common Spatial Pattern (CSP) in the preprocessing of IV2b dataset, and a recognition rate of 76.533% was reached by adding a layer to the proposed classifier.
Indebtedness is considered one of the most important problems facing Arab countries, due to its negative dimensions on the process of economic development in these countries and its threat to the stability of their financial system. which prompted th
ese countries to borrow, which constituted a huge burden on the borrowing Arab countries in paying the installments agreed upon by the creditor and the interest arising from these loans, and of course, these burdens that are paid are at the expense of the basic services provided by these countries to their citizens, which It leaves negative effects on social and political conditions, in addition to stifling economic growth rates. This research aims to shed light on the factors that played an important role in exacerbating the external indebtedness crisis of Arab countries, and to identify ways that can mitigate the impact of external indebtedness at the local level. Arab and international
The current research aims to know the prevalence of marital compatibility among married female students at Tishreen University, and know the differences in marital compatibility according to some variables (method of marriage, place of residence, pre
sence of children). The research was applied to a sample of married students at Tishreen University, whose number was (100) students. To achieve this goal, the marital compatibility scale prepared by (Ammar, 2015) was used, which includes dimensions (intellectual, affectionalemotional, sexual, and social compatibility) distributed within (54) items. The researcher conducted the psychometric study of the scale to ensure its validity and reliability in relation to the current research sample is high, and there are no statistically significant differences in the marital compatibility of the research sample according to the variable of the place of residence and the presence of children. As for the variable of the method of marriage it was found that there were statistically significant differences in favor of marriage after a love story.
The cities of the Canaanite civilization flourished on the eastern coast of the Mediterranean, and its centers extended from the Iskenderun region in northern Syria to Palestine, and it was famous for its cities: Ugarit, Arwad, Jbeil, Beirut, Tyre, J
ericho, Acre and Gaza as major cities, with the presence of other smaller civilized centers. Part of this civilization has been spread in Syria and Lebanon. For example, the archaeological discovery of the centers of the Canaanite civilization, but the archaeological data provided by the discovered cities on the level of human civilization were very important, and it is an issue that raises the need for archaeological excavations, and the beginning of the historical Canaanite presence in its Syrian cultural and civilizational milieu. And if the Canaanite civilization left in its mother land, Syria, many achievements and cultural and cultural data, which is a rich field for historical and archaeological studies, but its cultural and civilizational radiation was not limited to the Syrian land, as it spread throughout the known ancient world, specifically in the West, where The Greeks knew it at the beginning of their civilization, and they called the Canaanites the name of the Phoenicians and their civilization, the Phoenician civilization, where their oldest historical and written sources spoke about the Canaanites, and provided a lot of important information about the Canaanite civilization. Hence, looking at the information related to the information contained in the original (Greek) sources, shedding light on it, and dealing with it with a scientific methodology to clarify it and present it to researchers and postgraduate students to benefit from it in its history and archaeology.
The purpose of this paper is to extract roads from satellite images, based on developing the performance of the deep convolutional neural network model (Deeplabv3+) for roads segmentation, and to evaluate and test the performance of this mode
l after training on our data.This experimental study was applied at Google Colab cloud platform, by software instructions and advanced libraries in the Python.We conducted data pre -processing to prepare ground truth masks,then we trained the model.The training and validation process required (Epochs=4), by(Patch Size=4images).The Loss function decreased to its minimum value (0.025). Training time was three hours and ten minutes, aided by the advanced Graphics Processing Unit (GPU) and additional RAM.We achieved good results in evaluating the accuracy of the predictions of the trained model (IoU = 0.953). It was tested on two different areas, one of which is residential and the other agricultural in Lattakia city. The results showed that the trained model (DeepLabv3+) in our research can extract the road network accurately and effectively.But its performance is poor in some areas which includes tree shadows on the edges of the road, and where the spectral characteristics are similar to the road, such as the roofs of some buildings, and it is invalid for extracting side and unpaved roads. The research presented several recommendations to improve the performance of the (Deeplabv3+) in extracting roads from high-resolution satellite images, which is useful for updating road maps and urban planning works.
