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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 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Performance Analysis for Hybrid Massive MIMO FSO/RF Links Based on Efficient Channel Codes
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Publication Date
Sat Sep 21 2013
Journal Name
Nonlinear Dynamics
BER performance enhancement for secure wireless optical communication systems based on chaotic MIMO techniques
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
IoT System on Dynamic Fish Feeder Based on Fish Existence for Agriculture Aquaponic Breeders
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Maintaining and breeding fish in a pond are a crucial task for a large fish breeder. The main issues for fish breeders are pond management such as the production of food for fishes and to maintain the pond water quality. The dynamic or technological system for breeders has been invented and becomes important to get maximum profit return for aquaponic breeders in maintaining fishes. This research presents a developed prototype of a dynamic fish feeder based on fish existence. The dynamic fish feeder is programmed to feed where sensors detected the fish's existence. A microcontroller board NodeMCU ESP8266 is programmed for the developed h

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Publication Date
Fri Dec 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Airborne Computer System Based Collision-Free Flight Path Finding Strategy Design for Drone Model
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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Fri Jul 01 2022
Journal Name
Optical Fiber Technology
Highly sensitive fiber Bragg grating based gas sensor integrating polyaniline nanofiber for remote monitoring
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Publication Date
Tue Sep 17 2013
Journal Name
International Journal Of Engineering And Innovative Technology (ijeit)
Study of Optical Properties (Linear and Nonlinear) and Structures for CdS Thin Film Preparation in Spray Pyrolysis Technique
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Publication Date
Wed Apr 01 2020
Journal Name
Groundwater For Sustainable Development
Hydrochemistry of shallow groundwater and its assessment for drinking and irrigation purposes in Tarmiah district, Baghdad governorate, Iraq
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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Emotional deprivation and its relation with the behavioral and nervous problems for adolescents
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