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Development and Validation of HPLC Method For the Detection of Fusidic Acid Loaded in Non-ionic and Cationic Nanoemulsion-Based Gels
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Fusidic acid (FA) is a well-known pharmaceutical antibiotic used to treat dermal infections. This experiment aimed for developing a standardized HPLC protocol to determine the accurate concentration of fusidic acid in both non-ionic and cationic nano-emulsion based gels. For this purpose, a simple, precise, accurate approach was developed. A column with reversed-phase C18 (250 mm x 4.6 mm ID x 5 m) was utilized for the separation process. The main constituents of the HPLC mobile phase were composed of water: acetonitrile (1: 4); adjusted at pH 3.3. The flow rate was 1.0 mL/minute. The optimized wavelength was selected at 235 nm. This approach achieved strong linearity for alcoholic solutions of FA when loaded at a serial concentration ranging from 12.5 to 400 µg/ml. Furthermore, the approach showed good stability and achieved full recovery and an effective separation for FA from the abovementioned formulation. Besides, the protocol validation revealed good robustness at a temperature range of 23 to 27, pH 3.0 to 3.5, detection wavelength 230 to 240 nm, flow rate 0.8 and 1.2 and mobile phase contents of (78:22 to 82:18 acetonitrile/ water). The limit of Detection was obtained 1.33 µg/ml and limit of Quantification was 4.04 µg/ml for FA that uploaded through mentioned formulations. All the validation parameters were within the acceptance criteria, as per ICH , US Pharmacopeia requirements. Overall, an affordable and reproducible method could be achieved for the detection and quantification of fusidic acid within the nano-emulsion based gels formulas.

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Publication Date
Fri Dec 15 2023
Journal Name
Bionatura
Evaluation of the Drinking water in some Hospitals in Baghdad
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Due to the significance of hospital drinking water, a study was done to assess the water in three hospitals in Baghdad (Al-Yarmouk Teaching Hospital, Ibn Sina Hospital, and Ibn-Al-Nafis Hospital) for its nature and quality, compare it to other hospitals in terms of its physical, chemical, and bacterial specifications, and compare it to international standards. According to Iraqi standards from 2009 and WHO standards from 2011, Chemical factors were measured, which included pH, Total Dissolved Solids (TDS), and Calcium Ion (Ca+2). Reported readings are all within acceptable ranges for drinking water. In contrast, turbidity, total hardness (T.H.), chlorides (Cl-), magnesium (Mg+2), the number of aerobic plates (APC), total coliform (T

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Logic in the philosophy of ethical behavior in business organizations
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Logic in the philosophy of ethical behavior in business organizations

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Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
The Role of Patnership Approuch in Facilitating Housing in Iraq
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Publication Date
Sun Sep 04 2016
Journal Name
Baghdad Science Journal
Survey of Keratinophilic Fungi in the Tigris River in Baghdad
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The present study includs the isolation and identification of Keratinophilic fungi in fresh water samples collected from Tigris river in Baghdad, Iraq. Samples were collected from different districts of Baghdad (Al-Rustumia, Madina Al-Teb, Al-Azamia, Al-Kadimia, Al-Dorha and Al-Kanah). The water samples were examined for keratinophilic fungi by the plating method culturing and Hair Baiting Technique. A total number of 18 genera are recorded, in which the Tigris water indicates an impressive diversity of fungi. A variety of fungal strains were isolated from river water, out of 814 fungal colonies, Aspergillus terrus (5.5%) was the most frequent species, followed by Asperg

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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
The Cost of Technology Transfer in Construction Companies (In Iraq)
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The construction sector is considered an important and influential pivot in the national economy of any country.  Nations are working to develop this sector, receiving modern and developed techniques. So, this sector can be a carrier or a receiver of modern technologies. The cost of technology transfer between the international companies that sponsor this sector is a matter of great importance, especially since different factors affect the need for this advanced technology. The cost of technology transfer in construction is related to multiple factors presented by Knowledge, equipment, plant, hardware and software. The lack of distinguishing and evaluating the direct and indirect costs in the construction sector during

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Publication Date
Fri Jan 01 2016
Journal Name
Iraqi Journal Of Agricultural Sciences
Effect of extraction of sheep manure with warm water on the growth and nutrients content of tomato plants under cultivation of plastic houses
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Publication Date
Mon Jan 01 2024
Journal Name
Dental Hypotheses
Effect of Surface Treatments with Plasma and Chemical Bond on Shear Bond Strength of Acrylic Denture Teeth to Flexible and Heat-Cured Denture Base Material: An In Vitro Study
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Introduction: We aimed to evaluate the shear bond strength of acrylic denture teeth to flexible and heat-cured denture base material after surface treatments with argon plasma, chemical bonding agent (PALFIQUE universal), and combination. Methods: A total of 80 incisor acrylic denture teeth were treated with a argonplasma, chemical bond (PALFIQUE universal bond), and a combination with 10 samples for each group. The neck (gingival portion) of teeth was cut at a 45° angle, and the teeth were attached to heat-cured acrylic resin and flexible denture base material. All the specimens were stored in artificial saliva for 7 days in an incubator (37 °C). A shear

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Spectroscopic Study for Resonance Effects on the Carbonyl Double Bond Order in Urea Schiff Bases Which Contain Conjugated System
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In this work we prepared some schiff bases by condensation urea and benzaldehyde or its derevative ( bromo benzaldehyde or hydroxy benzaldehyde ) as ( 1 : 1 ) mole ( urea : benzaldehyde or its substitution ) to prepare compounds ( A1 , B1 , C1 , D1 , E1 , F1 , G1 ) and ( 1 : 2 ) mole ( urea : benzaldehyde or its substitution ) to prepare compounds ( A2 , B2 , C2 , D2 , E1 , F2 , G2 ) . The prepared compounds identified spectroscopic by infrared spectroscopy FT-IR and Thin layer chromotography T.L.C . The force constant calculated from the wave number for the carbonyl stretching from FT-IR chart and by using the following equation K = 4?2C2?'2? The change in double bond order for carbonyl deteremined in according with some past re

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Publication Date
Thu Dec 01 2016
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
NEW HOST PLANTS RECORD FOR THE BROWN SOFT SCALE COCCUS HESPERIDUM LINNAEUS, 1758 (HEMIPTERA: COCCIDAE) IN BAGHDAD PROVINCE, IRAQ
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    An investigation was provided in this work for the host range of brown soft scale Coccus hesperidum Linnaeus in Baghdad Province.  Five plant species were found infected by this insect, three of these species, Citrusaurantium L. (Rutaceae); Nerium oleander L. (Apocynaceae); Ficuscarica L. (Moraceae) reported earlier, and the remaining two, Dahlia pinnata Cav. (Asteraceae) and Myrtuscommunis L. (Myrtaceae) are recordedhere for the first time as host plants for this pest.

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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