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Formulation And Evaluation of Miconazole Pharmacosome by Using Solvent Evaporation Method to Enhance Solubility of Miconazole
Get PDFThis study aims to improve the solubility, bioavailability, and safety profile of miconazole through the development of a pharmacokinetic, a type of vesicular drug delivery system known for its advantages over with conventional methods. Using a solvent evaporation technique, miconazole is encapsulated in a soy lecithin-based pharmacokinetics. The pharmacokinetics obtained showed significant improvements in drug solubility, concentration uniformity and stability. One specific formulation, rated F1, with an exact ratio of miconazole to soy lecithin showed an impressive drug release rate of 94.25% within 60 minutes, in stark contrast to the release rate of only 28.90% achieved by free miconazole. This improved release profile shows the potential to improve treatment efficacy. In addition, both the standard F1 and miconazole formulations exhibited significant antifungal activity against Candida albicans, as evidenced by the minimum inhibitory concentrations (MICs) of 144.23 ?g/ml and 143.31 ?g/ml respectively. The innovative approach of complexing miconazole with soy lecithin through the formation of pharmacokinetics not only enhances drug solubility and bioavailability, but also contributes to minimizing potential toxic effects. These results highlight a promising pharmaceutical role as a means of improving the pharmacological properties of miconazole and other potential drugs with similar solubility challenges. This study has important implications for the development of more effective and safer therapeutic interventions in the field of antifungal therapy
Recent Advancement in Current Challenges and Opportunities for Civil Engineers: “Expansive Soil Stabilization Using Fly Ash as Stabilizing Agent”
No full textExpansive soils are challenges for engineering applications in virgin state because of their shrink-swell nature with moisture variation. Numerous stabilizers and number of methods have been used to stabilize expansive soils as an effort to make them more practical for construction purposes. Searching for suitable stabilizers to overcome soil difficulties caused by the expansive nature of soil is the key issue, not only in terms of achieving the required soil engineering characteristics but also in terms of environmental and economic concerns. The purpose of this article was to assess the current trends, challenges, and opportunities of various admixtures utilized for expansive soil improvement, as well as their economic and environmental consequences. A critical use of various admixtures commonly as soil stabilizers, including marble waste powder, fly ash, eggshell powders, stone waste, and lime powder is conducted. Furthermore, this paper is also focused to analyze the offered stabilizers in terms of soil geotechnical properties and sustainability in the field application. Sustainable and eco- friendly challenges overcome by the various techniques used in geotechnical field. One of them expansive soil stabilization with fly ash. Main objective of this paper is that waste from thermal power plant utilized as stabilizing agent for expansive soil stabilization
Management and Governance Issues Discussion in Vietnam and Asian Pacific Corporate Governance Standards
Get PDFThis paper mainly concentrates on empirical research for findings in Management and Governance Issues Discussion in Vietnam and Asian Pacific Corporate Governance Standards. First, it comes up with findings on corporate governance subjects in the post-crisis and post-scandal time. It found out that companies in these periods have certain corporate governance issues such as how to better organize an information disclosure system. Second,this paper provide with a short summary of evaluation of current corporate governance principles in these four countries which can enable corporations to seek and to compare to their current codes. Last but not least, Vietnam SSC also informed set of documents was developed with technical support from the International Finance Corporation, a member of the World Bank Group, and the support of the Swiss State Department of Economic Affairs (SECO), and includes the following criteria: standards higher than the minimum legal requirements, encouraging businesses to move towards international best practices
Time Study and Motion Analysis using Basi Maynard Operation Sequence Technique (MOST) in Pro Time Estimation Software: A Case Study of the Button Making Process in SIUE MakerLab
Get PDFEfficiency and productivity are vital aspects of any assembly process, and time study and motion analysis play a crucial role in optimizing these factors. This research presents a detailed study of the button making process in the Southern Illinois University Edwardsville’s MakerLab using ProTime Estimation Software. The objective of this project is to understand the concept of time studies otherwise known as work measurements, build proficiency in the usage of the ProTime Estimation Software, evaluate the efficiency and productivity of the button making process in the MakerLab, identify potential areas for improvement and contribute valuable insights. ProTime Estimation Software was employed as a powerful tool for real time data acquisition and analysis because this software allows for precise measurement and observation of each step in the process, enabling the establishment of accurate time standards for different work elements. The project outcome concludes that the button making process in the SIUE MakerLab is relatively efficient and productive, but there is room for improvement by reducing the setup time, minimizing the idle time, and optimizing the layout and workflow
Evaluation of Butea monosperma & Boerhaavia diffusa In Experimentally Induced Neuropathic Pain
No full textAim: The aim of the present investigation is to study the Evaluation of Butea monosperma & Boerhaavia diffusa In Experimentally Induced Neuropathic Pain. Material & Methods: Wistar albino rats weighing between 200-250 grams were selected for the study. The extracts and gallic acid (GA) suspensions were administered to the animals once a day through oral gavage. The suspension of extracts was prepared using 0.5% Na CMC and distilled water. An ideal neuropathic pain model should produce consistent sensory symptoms such as allodynia, hyperalgesia, and spontaneous pain over an extended duration, making it feasible for comprehensive evaluation. The Tibial and Sural Transection Injury model is a surgical technique commonly utilized in experimental settings to induce neuropathic pain in animal subjects, particularly rodents. This model involves the precise transection of the tibial and sural nerves, branches of the sciatic nerve, to elicit neuropathic pain symptoms. In parallel, the surrounding muscular tissue was homogenized with phosphate buffer (pH 7.4) and employed for the determination of myeloperoxidase (MPO) levels. Results: The multifaceted nature of neuropathic pain, coupled with the inadequacies of existing treatments, underscores the importance of exploring alternative interventions, and this study aims to contribute valuable insights to this complex field. Conclusion: These directions are crucial for advancing our understanding, translating findings into clinical applications, and ensuring the sustainability of therapeutic interventions
A Deep Learning Model for Decision Making in Healthcare Systems
No full textDecision Making (DM) is one of the domains that provide decisions based on improvement in business without the involvement of humans. This is mainly focused on giving suggestions to various companies to increase their online product, disease prediction, and also in many applications. Decision-making is used in many research applications such as the medical domain, online marketing, E-commerce, Filtering of Email, and other types of domains that help experts to get better decisions. It is identified that machine learning (ML) algorithms have several disadvantages in finding accurate decisions on various applications. Huge research is done on ML algorithms to find accurate patterns in decision-making algorithms to take automated decisions. ML algorithms are very weak in the processing of large datasets and also in statistical analysis. In this domain, deep learning (DL) plays a significant role in finding accurate patterns in detecting decision-making in multiple domains. In this paper, a deep learning model is introduced to find the disease patterns from the medical data to take the correct decisions and also to predict the risk based on the status of the disease. The proposed deep learning model is the combination of several models. Thus the decision-making is applied to know the status of the disease. Experiments are conducted on Heart-2 Dataset, Haberman’s Survival dataset, and Pima Indians Diabetes datasets and show the comparative performance
IOT Based Smart Irrigation System Using Arduino
No full textAgriculture is a crucial part of many national economies, but traditional irrigation techniques often fall short in terms of water efficiency and control. To address these limitations, this project presents an IoT-driven smart irrigation system. The system utilizes a network of sensors and actuators to continuously monitor factors like soil moisture, temperature, humidity, and weather conditions. This data is analyzed by a central control unit, which applies algorithms to determine the most efficient irrigation schedules and water usage. Designed to be both energy-efficient and cost-effective, the system operates using a standard power source. This smart irrigation system offers several advantages over conventional methods, including reducing water wastage and conserving resources, which ultimately leads to increased crop yields and cost savings. The system is also user-friendly, simple to install, and easy to maintain, with customization options for various crops and soil types. Furthermore, its scalability allows it to be extended to larger areas or multiple fields. In summary, this IoT-based irrigation solution represents a significant advancement over traditional systems, providing modern agriculture with a sustainable, efficient, and flexible tool. Its energy efficiency, scalability, and adaptability make it an ideal option for farmers seeking to improve their irrigation practices through innovative technology
Iron Oxide and Graphene Oxide nanocomposite with Polymethyl Methacrylate as innovative Pour Point Depressant for Waxy Crude Oil of North-East India
No full textThis paper focuses on the transportation challenges associated with waxy crude oil found in the North-Eastern region of India, particularly in Assam. The high paraffin and wax content in the crude oil leads to issues such as high pour point and viscosity, which can obstruct the flow of oil and cause disruptions in the transportation process. In this study, a composite material consisting of Graphene Oxide (GO) and Iron Oxide (Fe3O4) was synthesized and evaluated in crude oil rheology test. This study includes the characterization of the waxy crude oil sample e.g., specific gravity, API gravity, pour point, water content, wax content, FTIR analysis and SARA distribution. The dispersion stability of the rGO-Fe3O4 composite material was tested in polar (water) and nonpolar (xylene) solvents. The composite material showed high hydrophobicity and remained insoluble in water, while it dissolved in xylene. The rheological test for the crude oil and Pour Point depressant (PPD) such as viscosity, shear stress, storage modulus, loss modulus etc., were also performed. The crude oil sample's pour point was effectively reduced by 18°C with the application of a 500-ppm dosage. The findings of this research contribute to a better understanding of the challenges associated with transporting waxy crude oil and offer insights into the potential use of nanocomposite PPDs (NPPD) for improving the flow properties of the oil
NIDS Based False Positive Alert Screening Approach Using Machine Leaning
No full textOne of the most crucial security challenges of the modern day is detecting cyber attacks, and a network monitoring system to detect any intrusion commonly known as Network Intrusion Detection System (NIDS) are essential for this. Various machine learning approaches have been used in numerous research to build robust NIDS that can identify cyberthreats. While the majority of NIDS research focuses on developing novel AI/ML models to increase classification/detection accuracy, every model generates a percentage of false positive (FP) alarms in the real world. The mechanism for handling FP alarms is rarely covered in studies. Managing the volume of FP alarms on a busy network takes a lot of time for security staff. Automation of FP alert filtering is crucial because of this. In this research, we leverage kernel density estimation to present an automated FP alert filtering technique. Regardless of the NIDS that is in place, our suggested plan can help security staff with the alert verification process. Our tests demonstrate that, in terms of error ratio, our suggested system performs 32% to 60% better than alternative algorithms. Additionally, our suggested plan cuts down on the alert verification process's duration by 73%.
 
Effect of wt% of Reinforcement on Tribological Properties of Epoxy/Al2O3 Polymer Nanocomposites
No full textBy using an immediate cross-linking procedure, five samples were created. Neat epoxy and epoxy filled with 0.5, 1.0, 1.5 and 2.0 wt% of Al2O3 nanorods. At four different sliding distances of 15, 30, 45 and 60 meters friction and wear tests were performed on all samples using a ‘linearly reciprocating ball on flat tribometer’ against an ASE 304 stainless steel counter surface at room temperature with a constant load of 15 N. It was found that when epoxy is reinforced with 2 wt% of Al2O3, the coefficient of friction decreases by 70% and volume loss decreases by 52% compared to that of pure epoxy for a total sliding distance of 60 meters. It was also found that as the wt% of Al2O3 nanorods increases in epoxy, average surface roughness decreases, resulting in a lower coefficient of friction. Scanning electron microscopic tests were also performed on all samples. It was found that epoxy containing 2.0 wt% of Al2O3 nanorods is smoothest among other images, which is evidence of wear resistance. It is the subject of further research what will happen if the wt% of Al2O3 nanorods in epoxy increases beyond 2 wt% but it is clear from this research that the minimum wt% of Al2O3 nanorods in epoxy should be at least 2 wt% to achieve efficient wear resistance