PHARMACOKINETICS AND BIOAVAILABILITY OF TYLVALOSIN AFTER ORAL, INTRAMUSCULAR AND INTRAVENOUS ADMINISTRATION IN TURKEYS

Objective: Tylvalosin, is a new macrolide antibiotic, it is highly effective against a range of important diseases in many different veterinary species specially pigs and poultry. The pharmacokinetics and bioavailability of Tylvalosin were investigated in healthy turkeys.Methods: Tylvalosin was orally, intramuscularly, and intravenously administrated to turkeys in a single dose of (25 mg/kg b.w.), and the blood samples were analyzed by using a microbiological assay method.Results: After intravenous injection, the serum concentration-time curves were best described by a two compartment-open model. The distribution and elimination half–life t 0.5 α and t 0.5 β were (0.076±0.0014 h, 0.788±0.107 h), respectively. The volume of distribution Vdss was (1.155±0.183 L/kg), with body clearance Cl (B) of (1.489±0.143 ml/kg/h). Following oral administration, Tylvalosin was absorbed with t 0.5 ab (0.283±0.012 h) and eliminated, with t 0.5 el (5.309±0.542 h). The peak serum concentration was (0.637±0.018 µg/ml) at Tmax of (1.293±0.024 h). Following intramuscular administration, Tylvalosin was absorbed with t 0.5 ab (0.076±0.003 h) and eliminated with t 0.5 el (0.467±0.058 h). The peak serum concentration was (1.446±0.121 µg/ml) at Tmax of (0.282±0.008 h). The systemic bioavailability of Tylvalosin following oral administration was 33.84% and 14.06% after intramuscular administration.Conclusion: These results indicate that, after oral and intramuscular administration, Tylvalosin was rapidly absorbed and distributed to tissues of turkeys. However, repeated doses are necessary to maintain Tylvalosin serum concentration above the MIC for most susceptible microorganisms.Â

Saad Elkhadem's The Plague in English: A Study of the Translation Strategies used to Recreate the Egyptian Ethos

This thesis focuses on translation as a transcultural activity. It studies the foreignizing and domesticating translation strategies used to recreate the Egyptian ethos in the translation of Elkhadems The Plague from Arabic to English. Five theories are incorporated in the analysis. These are Venutis Domesticating and Foreignizing Theory; Tourys DTS; Genettes Paratexts; Pedersens taxonomy of strategies for rendering culture-bound references and his classification of culture-bound elements; and Vermeers Skopos Theory. Three types of analysis are conducted: a literary analysis of the source text; a microanalysis of the target text, further divided into an analysis of the novel's paratexts and a descriptive analysis of ninety-eight culture-bound references; and finally, a macro-analysis of the overall norms and of the skopos of the translation showing how both affect the transmission of the Egyptian ethos. Overall, this thesis provides some insight into the influence of translation on cultural identity

Microbial Quality of Paddy fields at Alfurat Alawsat Area, Iraq and the Effect of Milling Process on the Rice Contamination Level

شملت الدراسة تحليل اربعة وخمسون عينة شلب، خمسة واربعون عينة تربة، وتسع عينات مياه ري اخذت من منطقة الفرات الاوسط/ العراق. حللت من الناحية المايكروبية وشملت تحليل العدد البكتيري الكلي، عدد الخمائر والاعفان، عدد بكتريا القولون، وعدد بكتريا E. coli. تم تصنيع عينات الشلب على مستوى مختبري لانتاج رز ذا درجة بياض 32 و 36 وتم تحديد المحتوى المايكروبي للرز المصنع. اظهرت النتائج ان كل عينات مياه الري تجاوزت الحد المسموح به لمنظمة الغذاء والدواء الامريكية (FDA)  لبكتريا E. coli  وان كل عينات الشلب تجاوزت الحد الجيد للعدد الكلي للبكتيريا بينما لم تتجاوت اي عينة الحد المسموح به للعدد الكلي للبكتريا. معظم عينات الشلب تجاوزت العدد المسموح به للخمائر والاعفان وعدد قليل من النماذج تجاوزت العدد الكلي لبكتريا القلولون. قللت العملية التصيعية للشلب الحمل المايكوبي لبعض عينات الشلب بينما التاثير لم يكن واضحا مع عينات اخرى وزداد المحتوى المايكروبي لعينات اخرى بعد العملية التصنيعية. عشر عينات رز على درجة بياض 32 وثمان عينات رز على درجة بياض 36 من اصل 13 عينة تجاوت الحد المسموح به للخمائر والاعفان بالنسبة لمواصفة الغذاء والدواء الامريكية والمواصفة القياسية العراقية. كل عينات الرز المصنة تجاوت الحد المسموح به لبكتريا القولون بالنسبة للمواصفة القياسية العراقية بينما فقط ستة عينات وثلاث عينات من اصل 13 عينة تجاوز الحد المسموح به لذات البكتريا بالنسبة لمواصفة منظمة الغذاء والدواء الامريكية لرز على درجة بياض 32 و36 على التوالي. نستنتج من الدراسة ان عينات الشلب الماخوذة من حقول الشلب في منطقة الفرات الاوسط تجاوزت بعض الحدود المايركروبية من الحقل دون تاثير للعملية التصنيعية او الخزن عليها وان مياه الري اعتبرت المصدر الرئيسي لتلوث الحقول لذلك يجب مراقبة حقول الشلب للسيطرة على التلوث المايكروبي.  Fifty-Four paddy samples, 45 soil samples, and nine irrigation water samples of some paddy fields at Alfurat Alawsat Area, Iraq were collected to investigate the microbial quality including total count bacteria (TCB), molds and yeast, total coliform (TC), and E. coli bacteria. Paddy samples were processed at the laboratory level to produce rice at 32 and 36 whiteness, and the microbial quality of the produced rice was conducted too. The results showed that all irrigation water samples were overpassed the FDA limit for E. coli. All paddy samples were exceeded the good limit of TCB, but no sample exceeded the acceptable limit. Most paddy samples were exceeded the FDA limit for molds and yeast, and few paddy samples exceeded the total coliform limit. The milling process reduced microbial levels for some samples, while the effect was undetectable for other samples. Ten rice samples at 32 whiteness and eight rice samples at 36 whiteness out of 13 paddy samples overpassed FDA and Iraqi Quality Standardization (IQS) for molds and yeast. All produced rice at both whiteness levels was exceeded the total coliform of IQS, while only six and three samples out of 13 rice samples at 32 and 36 whiteness respectively overpassed the FDA limit. In conclusion, paddy samples taken from Alfurat Alawsat fields were overpassed some microbial levels from fields without the effect of storage or milling processing. Irrigation water was probably the main source of fields’ contamination, therefore, the paddy fields need to be monitored and controlled in terms of their microbial contamination

Partial Replacement of Cement by Solid Wastes as New Materials for Green Sustainable Construction Applications

The manufacturing of ordinary Portland cement is an energy-intensive process that results in pollution and CO2 emissions, among other issues. There is a need for an environmentally friendly green concrete substitute. Waste products from a variety of sectors can be recycled and used as a green concrete substitute. This decreases the environmental effects of concrete manufacturing as well as energy consumption. The use of solid waste materials for green building is extremely important now and in the future. Green concrete is also in its infancy in terms of manufacturing and application. Academics must intervene by encouraging business implementation. The aim of this review paper is to raise awareness about the importance of repurposing recycled materials and to highlight new technologies for producing green, sustainable concrete

Optimized Cooperative Localization Technique Based on Linear Intersection over Wireless Sensor Networks

Localization is one of the significant techniques in wireless sensor networks. The localization approaches are different in several applications. Localization offers geographical information for managing the topology. In this paper, we propose optimized cooperative localization technique based on trilateration, multilateration and linear intersection. The approach reduces the error rates, communication cost and energy consumption for maintaining the high accuracy. Furthermore, the approach is implemented for controlling air craft system to avoid the landing and takeoff delays. To demonstrate the strength of the approach, we used network simulator ns-2 to validate the estimation errors, computational latency, energy consumption and error tolerance. Based on the simulation results, we conclude that the presented approach outperforms other existing cooperative scheduling approaches in terms of accuracy, mobility, consumed power

Some Numerical Methods for Solving Linear Two-Dimensional Volterra Integral Equation

In this paper, the existence and uniqueness of solution of the linear twodimensional Volterra integral equation of the second kind(LT-DVIE) with Continuous Kernel are discussed and proved. Trapezoidal rule and Simpson's rule are used to solve this type of two dimensional Volterra integral equation of the second kind. Numerical examples are considered to illustrate the effectiveness of the proposed methods and the error is estimated

Deep Learning-aided Brain Tumor Detection: An Initial ‎Experience based Cloud Framework ‎

Lately, the uncertainty of diagnosing diseases increased and spread due to the huge intertwined and ambiguity of symptoms, that leads to overwhelming and hindering the reliability of the diagnosis ‎process. Since tumor detection from ‎MRI scans depends mainly on the specialist experience, ‎misdetection will result an inaccurate curing that might cause ‎critical harm consequent results. In this paper, detection service for brain tumors is introduced as ‎an aiding function for both patients and specialist. The ‎paper focuses on automatic MRI brain tumor detection under a cloud based framework for multi-medical diagnosed services. The proposed CNN-aided deep architecture contains two phases: the features extraction phase followed by a detection phase. The contour ‎detection and binary segmentation were applied to extract the region ‎of interest and reduce the unnecessary information before injecting the data into the model for training. The brain tumor ‎data was obtained from Kaggle datasets, it contains 2062 cases, ‎‎1083 tumorous and 979 non-tumorous after preprocessing and ‎augmentation phases. The training and validation phases have been ‎done using different images’ sizes varied between (16, 16) to ‎‎ (128,128). The experimental results show 97.3% for detection ‎accuracy, 96.9% for Sensitivity, and 96.1% specificity. Moreover, ‎using small filters with such type of images ensures better and faster ‎performance with more deep learning.

DiaMe: IoMT deep predictive model based on threshold aware region growing technique

Medical images magnetic resonance imaging (MRI) analysis is a very challenging domain especially in the segmentation process for predicting tumefactions with high accuracy. Although deep learning techniques achieve remarkable success in classification and segmentation phases, it remains a rich area to investigate, due to the variance of tumefactions sizes, locations and shapes. Moreover, the high fusion between tumors and their anatomical appearance causes an imprecise detection for tumor boundaries. So, using hybrid segmentation technique will strengthen the reliability and generality of the diagnostic model. This paper presents an automated hybrid segmentation approach combined with convolution neural network (CNN) model for brain tumor detection and prediction, as one of many offered functions by the previously introduced IoMT medical service “DiaMe”. The developed model aims to improve extracting region of interest (ROI), especially with the variation sizes of tumor and its locations; and hence improve the overall performance of detecting the tumor. The MRI brain tumor dataset obtained from Kaggle, where all needed augmentation, edge detection, contouring and binarization are presented. The results showed 97.32% accuracy for detection, 96.5% Sensitivity, and 94.8% for specificity