Colorectal cancer (CRC) is the most common disease and cause of death globally. The aim of the study is investigation and detection of some bacterial interfering with CRC occurrence and progression. The study conducted between September 2022 till February 2023, a total of 50 specimens were collected from confirmed CRC patients. In addition, 50 stool specimens were collected from Healthy volunteers, considers as control group. Isolation and identification of bacteria in all collected specimens were done by using cultural and differential media (blood agar, macconkey agar and Pfizer agar), as well as the VITEK- 2 compact system. The bacterial species, in the specimens of control were ( Escherichia coli 50 (86.20%), Klebsiella Pneumoni

Abstract:
This research (The effect of information in Iraqi universities) wants to
explain the aims and the opinions of Iraqi universities lecturers during the
globalization era and information technology .
The results we have got about using the computers by the lecturers of
Iraqi universities just in illustration and statistic as depends on there works

The research acquires its importance by motivating the behavioural side of the employees to apply modern technology in the work, because of its great importance in increasing the efficiency of employees’ performance and excellence. The research was based on two main hypotheses to show the relationship and impact between the variables through the adoption of a questionnaire to collect data and information related to the research, which consisted of (50) people from administrators working at different levels, based on personal interviews and field visits to collect research data. The data collection process was subjected to statistical analysis using the statistical program (SPSS) (Statistical package for social science) to reach

Polish Academy of Sciences

Tin oxide was deposited by using vacuum thermal method on silicon wafer engraved by Computer Numerical Controlled (CNC) Machine. The inscription was engraved by diamond-made brine. Deep 0.05 mm in the form of concentric squares. Electrical results in the dark were shown high value of forward current and the high value of the detection factor from 6.42 before engraving to 10.41 after engraving. (I-V) characters in illumination with powers (50, 100, 150, 200, 250) mW/cm2 show Improved properties of the detector, Especially at power (150, 200, 250) mW/cm2. Response improved in rise time from 2.4 μs to 0.72 μs and time of inactivity improved 515.2 μs to 44.2 μs. Sensitivity angle increased at zone from 40o to 65o.

Eighteen new cyclic imides (maleimides) conncted to benzothiazole moiety through sulfonamide group were synthesized via multistep synthesis.The first step involved preparation of two maleamic acids N-phenylmaleamic acid and N-benzylmaleamic acid via reaction of maleic anhydride with aniline or benzyl amine.Dehydration of the prepared amic acids by treatment with acetic anhydride and anhydrous sodium acetate in the second step afforded N-phenylmaleimide and N- benzyl maleimide which in turn were treated with chlorosulfonic acid in the third step to afford 4-(N-maleimidyl) phenyl sulfonyl chloride and 4-(N-maleimidyl) benzyl sulfonyl chloride respectively.In the Fourth step of this work each one of the two prepared maleimidyl sulfonyl chlorid

In this study, we set up and analyze a cancer growth model that integrates a chemotherapy drug with the impact of vitamins in boosting and strengthening the immune system. The aim of this study is to determine the minimal amount of treatment required to eliminate cancer, which will help to reduce harm to patients. It is assumed that vitamins come from organic foods and beverages. The chemotherapy drug is added to delay and eliminate tumor cell growth and division. To that end, we suggest the tumor-immune model, composed of the interaction of tumor and immune cells, which is composed of two ordinary differential equations. The model’s fundamental mathematical properties, such as positivity, boundedness, and equilibrium existence, are exami

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c