A simple, precise, and sensitive spectrophotometric method has been established for the analysis of doxycycline. The method includes direct charge transfer complexation of doxycycline withp-Bromanil in acetonitrileto form a colored complex. The intensely colored product formed was quantified based on the absorption band at 377 nm under optimum condition. Beer’s law is obeyed in the concentration range of 1–50 μg.mL-1 with molar absorptivity of 1.5725x104 L.mol-1.cm-1, Sandell's sensitivity index (0.0283) μg.cm-2, detection limit of 0.1064 μg.mL-1, quantification limit 0.3224 μg.mL-1 and association constant of the formed complex (0.75x103). The developed method could find application in routine quality control of doxycycline and has

The increasing population growth resulting in the tremendous increase in consumption of fuels, energy, and petrochemical products and coupled with the depletion in conventional crude oil reserves and production make it imperative for Nigeria to explore her bitumen reserves so as to meet her energy and petrochemicals needs. Samples of Agbabu bitumen were subjected to thermal cracking in a tubular steel reactor operated at 10 bar pressure to investigate the effect of temperature on the cracking reaction. The gas produced was analyzed in a Gas Chromatograph while the liquid products were subjected to Gas Chromatography-Mass Spectrometry (GC-MS) analysis. Heptane was the dominant gas produced in bitumen cracking at all temperatures and the r

An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi

Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce

          Graphite Coated Electrodes (GCE) based on molecularly imprinted polymers were fabricated for the selective potentiometric determination of Risperidone (Ris). The molecularly imprinted (MIP) and nonimprinted (NIP) polymers were synthesized by bulk polymerization using (Ris.) as a template, acrylic acid (AA) and acrylamide (AAm) as monomers, ethylene glycol dimethacrylate (EGDMA) as a cross-linker and benzoyl peroxide (BPO) as an initiator. The imprinted membranes and the non-imprinted membranes were prepared using dioctyl phthalate (DOP) and Dibutylphthalate (DBP) as plasticizers in PVC matrix. The membranes were coated on graphite electrodes. The MIP electrodes using

<p>Recently, reconfigurable intelligent surfaces have an increasing role to enhance the coverage and quality of mobile networks especially when the received signal level is very weak because of obstacles and random fluctuation. This motivates the researchers to add more contributions to the fields of reconfigurable intelligent surfaces (RIS) in wireless communications. A substantial issue in reconfigurable intelligent surfaces is the huge overhead for channel state information estimation which limits the system’s performance, oppressively. In this work, a newly proposed method is to estimate the angle of arrival and path loss at the RIS side and then send short information to the base station rather than huge overhe

In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify fo

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n