Wayne Community College is a public community college in Goldsboro, North Carolina. It offers more than 70 credit programs on campus with nine buildings and over 287,000 square feet (27,000 m²). Over 14,000 curriculum and extension students are enrolled at the college per year.
The imbibition phenomenon is prevalent in both natural settings and applied industries. Studying the mechanism of imbibition and comprehending the laws that govern the influence of related factors holds tremendous significance. This study employs the classical Darcy’s equation to examine the imbibition process in a heterogeneous hydrocarbon reservoir. Due to the highly nonlinear nature of the governing equations, analytical solutions are rare. In this study, we introduce the Homotopy Analysis Method (HAM) to solve the Counter-current spontaneous imbibition problem, providing an explicit series solution with adjustable convergence. HAM is particularly advantageous as it does not depend on small parameters and offers greater flexibility compared to traditional analytical methods. The method proposed in this study offers a more direct, accurate, and user-friendly approach for computing spontaneous imbibition performance compared to previously available methods. We assert its generality concerning functional forms for relative permeability and capillary pressure, making it applicable across the entire range of wettability, provided that these effects are appropriately considered in the parameterization of capillary pressure and saturation normalization. This study analyzes counter-current spontaneous imbibition in fractured heterogeneous porous media, primarily characterized by spatial variations in porosity and absolute permeability. Effects of the viscosity ratio, wettability of the medium, and inclined planes on the normalized water saturation are analyzed.
Cardiovascular diseases are the world’s leading cause of death; therefore cardiac health of the human heart has been a fascinating topic for decades. The electrocardiogram (ECG) signal is a comprehensive non-invasive method for determining cardiac health. Various health practitioners use the ECG signal to ascertain critical information about the human heart. In this article, swarm intelligence approaches are used in the biomedical signal processing sector to enhance adaptive hybrid filters and empirical wavelet transforms (EWTs). At first, the white Gaussian noise is added to the input ECG signal and then applied to the EWT. The ECG signals are denoised by the proposed adaptive hybrid filter. The honey badge optimization (HBO) algorithm is utilized to optimize the EWT window function and adaptive hybrid filter weight parameters. The proposed approach is simulated by MATLAB 2018a using the MIT-BIH dataset with white Gaussian, electromyogram and electrode motion artifact noises. A comparison of the HBO approach with recursive least square-based adaptive filter, multichannel least means square, and discrete wavelet transform methods has been done in order to show the efficiency of the proposed adaptive hybrid filter. The experimental results show that the HBO approach supported by EWT and adaptive hybrid filter can be employed efficiently for cardiovascular signal denoising.
This article presents an argument on the importance of teaching science with a feminist framework and defines it by acknowledging that all knowledge is historically situated and is influenced by social power and politics. This article presents a pedagogical model for implementing a special topic class on science and feminism for chemistry students at East Carolina University, a rural serving university in North Carolina. We provide the context of developing this class, a curricular model that is presently used (including reading lists, assignments, and student learning outcomes), and qualitative data analysis from online student surveys. The student survey data analysis shows curiosity about the applicability of feminism in science and the development of critical race and gender consciousness and their interaction with science. We present this work as an example of a transformative pedagogical model to dismantle White supremacy in Chemistry.
Now a days, electric power infrastructure is an essential section of the world due to the increase in power demand and industrialization. The smart grid is also one of the profoundly evolved innovations, which influences the synchronization between demand and renewable energy reactions. The smart grids contain many operations with power calculations such as smart functions, assurance, and control techniques to provide steadiness and proficiency to the system performance. However, the quality of power such as voltage deviation minimization, sag/swell, power loss minimization, and Total Harmonic Distortion (THD) appear to be the major issue. Therefore, in this paper, a novel Generalized Approximate Reasoning Intelligent Control along with Multi-objective African Buffalo Optimization is proposed to control the imperatives of the smart grid. In the grid, current controllers are upgraded by the proposed Optimal Pseudospectral Bang Bang Control technique, and voltage controllers are improved by the proposed Bessel Filter Sallen Key Topology. The simulation of the proposed method is actualized with MATLAB/Simulink. Consequently, the projected results are compared with the traditional control techniques and the outcomes show that the projected replica improved system efficiency concerning power quality problems in terms of reduced 14 MW of power loss and 2.18% of THD.
Low-oral bioavailability as a consequence of low-water solubility of drugs is challenging for formulation scientists in the development of new pharmaceutical products. This review aims to highlight relevant considerations when implementing a rational strategy for the development of lipid-based oral drug delivery systems and to discuss shortcomings and challenges to the current classification of these delivery systems such as nanoemulsion, Solid lipid nanoparticle (SLN), Nanostructured lipid carriers (NLC), Self-emulsifying drug delivery system (SEDDS). Lipid-based drug delivery systems consist of a diverse group of formulations, each consisting of varying functional and structural properties that are amenable to modifications achieved by varying the composition of lipid excipients and other additives thereby facilitating the bioavailability of poorly water-soluble drugs. In addition, lipid nanoparticles may also protect the loaded drugs from chemical and enzymatic degradation and gradually release drug molecules from the lipid matrix into the blood, resulting in improved therapeutic profiles compared to free drugs. Therefore, due to their physiological and biodegradable properties, lipid molecules may decrease adverse side effects and chronic toxicity of the drug-delivery systems when compared to others of polymeric nature. Accordingly, the present review is mainly centred on the various lipid-based drug delivery system and excipients used in lipid-based drug delivery systems (LBDDS).
