A specific, sensitive and simple method was used for the determination of: vitamin B9 (Folic acid) in pure and pharmaceutical formulations using continuous flow injection analysis. The method is based on formation of ion pair compound between folic acid and ammonium molybdate in an aqueous medium to obtain a gray precipitate complex, using homemade; Ayah-6SX1-ST-2D solar cell CFI Analyzer. Optimum parameters was studied to increase the sensitivity for developed method. The linear range for the calibration graph was 0.01-0.6 mMol.L-1 of vitamin B9 and LOD was 131.994 ng/sample with correlation coefficient ( r ) of 0.9810, RSD% was lower than 0.1%, (n=9) for the determination of vitamin B9 at concentration (0.07and 0.5) mMol.L-1 respectiv

Diazotization reaction between quinolin-2-ol and (2-chloro-1-(4-(N-(5-methylisoxazol-3-yl)sulfamoyl)phenyl)-2l4-diazyn-1-ium was carried out resulting in ligand-HL, this in turn reacted with the next metal ions (Ni²⁺, Pt⁴⁺, Pd²⁺, and Mn²⁺)  forming stable complexes with unique geometries such as (tetrahedral for both Ni²⁺ and Mn²⁺, octahedral for Pt⁴⁺ and square planer for Pd²⁺ ). The creation of such complexes was detected by employing spectroscopic means involving ultraviolet-visible which proved the obtained geometries, fourier transfer proved the formation of azo group and the coordination with metal ion through it. Pyrolysis (TGA &

Dyspepsia is a significant public health issue that affects the entire world population. In this work, we formulate and analyze a deterministic model for the population dynamics of Gut bacteria in the presence of antibiotics and Probiotic supplements. All the possible equilibria and their local stability are obtained. The global stability around the positive equilibrium point is established. Numerical simulations back up our analytical findings and show the temporal dynamics of gut microorganisms.

Concrete pavements are essential to modern infrastructure, but their low tensile and flexural strengths can cause cracking and shrinkage. This study evaluates fiber reinforcement with steel and carbon fibers in various combinations to improve rigid pavement performance. Six concrete mixes were tested: a control mix with no fiber, a mix with 1% steel fiber (SF1%), a mix with 1% carbon fiber (CF1%), and three hybrid mixes with 1% fiber content: 0.75% steel /0.25% carbon fiber (SF0.75CF0.25), 0.25% steel /0.75% carbon fiber (SF0.25CF0.75), and 0.5% steel /0.5% carbon fiber ((SF0.5CF0.5). Laboratory experiments including compressive, flexural, and splitting tensile strength tests were conducted at 7, 28, and 90 days, while Finite Element Analys

Microalgae present much usefulness for antimicrobial research because of its enormous biodiversity and rapid growth rate. From this study results it is reaveled that Chlamydomonas reinhardtii were isolated from a pond of water in the province of Diwaniyah. The culture supernatants were obtained when extracted with methanol solvent. Antimicrobial activity of extracts was tested for pathogens, and the best inhibition zone obtained was against Candida albicans (32mm), S.aureus (15mm), and to E.coli (9mm). While it showed no effect against both S.epidermidis and Klebsiella spp. Biofilm was formed by all tested isolates with differences in its strength formation. The C. reinhardtii

Schiff bases are versatile compounds synthesized from the condensation of primary amino compounds with aldehydes or ketones. The high thermal of many Schiff base and their complexes were useful attributes for their application as catalysts in reactions involving at high temperatures. This thermal behavior of Schiff bases and their complexes was evaluated by TGA/DTG and DTA curves with 10 mass losses related to dehydration and decomposition. This review summarizes the developments in the last decade for thermal analysis of Schiff bases. Therefore, synthesis of Schiff bases and their complexes are reviewe

  This paper deals  the prediction of the process of  random spatial data of two properties, the first is called  Primary variables  and the second is called secondary  variables ,   the method  that were used in the  prediction process for this type  of data is technique Co-kriging  , the method is usually used when the number of primary variables  meant to predict for one of its elements is measured in a particular location a few (because of the cost or difficulty of obtaining them) compare with secondary variable which is the number of elements  are available and  highly correlated with primary variables, as was the&nbs

Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network

Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv