Peer-reviewed international research papers published open-access with EOI assignment and global indexing across engineering, computer science, environmental science, social sciences, and more.
Background: Proteus mirabilis is a bacterium of medical importance in infections of urinary sewers and is a major cause of associated diseases such as kidney stones and others. It is also resistant to many antibiotics, so the study resorted to the use of natural substances to study their effectiveness towards these bacteria. Methodology: Bacteria were collected from patients with urinary sewage inflammation and diagnosed by chemical and microscopic methods. They then attended water extracts of these substances and various concentrations (10, 20, 50, 100 g/mL). The bacteria were planted in the middle of the Mueller Hunton Acar and treated with these extracts to study the areas of inhibition. Results: The highest incidence among males aged 40-70 was 22% of the total samples, and the effect of olibanum was most on the 15-40 age group in males, while the least influential on this group was cardamom, while the 40-70 age group in males clove was most influential in its different concentrations while cardamom was least, the synergistic and antagonistic effectiveness of all extracts as the synergistic effectiveness was at its highest level when the extracts (cardamom+clove) were combined. Conclusion: Combining cardamom, and clove extracts with each other has had a high synergistic effect and therefore the use of these substances with each other by humans may reduce the incidence of urinary tract infections caused by proteus mirabilis.
Today, more than ever, our society has become obsessed with technology and people surround themselves with smart devices designed to improve their lifestyle. Communications have benefited of this rise of the gadgets the most, and reality shows that most adults in the urban environment own a smartphone with the help of which they can connect to the Internet. The Internet of Things (IoT) has emerged as a transformative force in the contemporary digital landscape, ushering in the Smart Era characterized by interconnected devices and pervasive data exchange. While IoT promises enhanced convenience, efficiency, and innovation, it also raises profound concerns regarding security and privacy. This paper examines the multifaceted implications of IoT on security and privacy in the Smart Era, exploring the challenges, vulnerabilities, and potential solutions to mitigate risks. Drawing upon a comprehensive review of existing literature and case studies, this paper provides insights into the evolving landscape of IoT security and privacy, offering recommendations for stakeholders to navigate this complex terrain effectively. Keywords: Era, Smart Era, Security, Internet, Smart Phone, Internet of Things (IoT), security challenges. Top of Form
This study investigates the effects of Naira Depreciation on the Nigerian economy, with a specific focus on the period from 1990 to 2022. Utilizing Ordinary Least Squares (OLS) analysis, the research examines the relationship between Naira Depreciation, Inflation Rate, and Gross Domestic Product (GDP). The findings reveal a significant negative impact of Naira Depreciation and inflation on GDP, underscoring the importance of implementing policies to stabilize the currency and control inflation for sustainable economic growth. The study contributes empirical evidence to the existing literature on the adverse consequences of currency devaluation in Nigeria, providing insights for policymakers and stakeholders to navigate economic challenges effectively
Background: The Covid-19 pandemic had a huge impact on various industries worldwide, and one of them the personal care services which includes the beauty industry. This industry was declared a non-essential service and only allowed to open under advanced lockdown level 3. For the first time the question about essential versus non-essential services was raised. Aim: The aim of this study was to investigate whether therapeutic health care, provided by somatologist may be classified as essential services to assist in the prevention of non-communicable diseases to alleviate the overburdened health systems. Methodology: A non-interventional quantitative research approach was employed. The study was conducted in Western Cape – Stellenbosch at two clinics, two spas and two salons. The study included 366 participants who completed online surveys. A pilot study was completed to test the validity and reliability of the study. Participants completed and submitted the surveys on the Survey Monkey App. Results: Most of the participants that took part in the study were females (79.8%) who were between the ages of 18 – 29 (26.9%). A significant portion about 67.6% of the population indicated that the reason for visiting their spa, salon, or clinic is for relaxation purposes. Figures showed that (0.52%) of the visits to these institutes were for purchases. The number of responses to how individuals would describe the term wellbeing indicates that a significant number of participants agrees that the term well – being has a relationship with being healthy. 0.81% of the population indicated that to them the term well – being involves health. Conclusion: Based on the current statuses that not only individuals are in, but also the status of the health care sector and the impact of COVID – 19 on the world, it is evident that full operations of the health and wellness sector including the beauty industry should be categorised as essential. 36.2% Of participants that was included in the study indicated that the closure of the health and well – ness industry had a small negative effect on their health and well – being and 30% indicated that it had a large negative effect on their health and well – being.
The focus of this article is to demonstrate that change is constant in the educational system. Education especially for children with disabilities has been a call for concern. This is so because, many have tackled the problem of education for children with disabilities from diverse angles. Some just like Louise Mbibeh thinks that these children can only be taught in an inclusive classroom reason being that special education is a form of divide learning or segregation. But others in the other hand just like Marry Warnock thinks that special education is necessary in the field of education especially for children with severe levels of disabilities. For inclusive education does not only means learning under the same roof but receiving all children despite their nature and placing them where they can learn best. But that will not be our point of focus. In this article, we want to demonstrate that neither special education nor inclusive education only can provide appropriate education for children with disabilities. The two of them must come together with their different strategies and provide a better education for these children. Both inclusive and special education are important non should be abandoned or valued above the other. Inclusive nor special education cannot function well without the other. Both needs each other so as to provide appropriate education for children with disabilities. What is the way forward now? inclusive special education is our way forward as a means to promote equality, quality and best education for children with disabilities. It is also a means through which controversies that exist between special and inclusive education are addressed and quality education established.
This research paper investigates the influence of user-generated content (UGC), particularly online reviews and ratings, on consumer trust and brand loyalty. Through a case study analysis of a prominent e-commerce platform, the study explores how UGC shapes consumer perceptions and behaviors.The findings reveal that positive UGC significantly impacts consumer trust. Consumers view online reviews and ratings as credible sources of information, and positive reviews act as social proof, reinforcing brand credibility and product quality. While negative reviews can potentially erode trust, addressing them constructively can demonstrate a commitment to customer satisfaction. The study also highlights the role of UGC in fostering brand loyalty. Positive UGC fosters emotional connections with the brand, and engagement with UGC platforms creates a sense of community. These factors contribute to a positive feedback loop, where increased trust leads to heightened loyalty, which in turn generates more positive UGC. The research offers practical implications for businesses seeking to leverage UGC. Recommendations include embracing transparency, actively engaging with customers, incentivizing UGC contributions, and integrating UGC into marketing campaigns. By effectively utilizing UGC, businesses can build trust, foster brand loyalty, and achieve long-term customer engagement.
This chapter delves into the transformative integration of Artificial Intelligence (AI) and the Internet of Things (IoT) to revolutionize corrosion mitigation strategies in Chemical Engineering Processes. The significance of effective corrosion control is emphasized, addressing challenges such as material degradation, safety risks, and increased maintenance costs. This necessitates innovative, proactive, and data-driven solutions. The chapter provides a comprehensive overview of AI and IoT applications, highlighting their real-time monitoring, predictive analytics, and adaptive control capabilities. The impact of corrosion on various components and systems within chemical engineering processes is explored, emphasizing the economic and environmental consequences, including maintenance costs, energy inefficiency, and material waste. The synergies between AI and IoT enable not only continuous monitoring but also early detection and prediction of corrosion trends. The adaptive learning mechanisms of AI are discussed, showcasing how these technologies optimize maintenance schedules and contribute to the development of customized corrosion prevention strategies. Specific AI applications, such as machine learning models for corrosion prediction and anomaly detection, are elucidated with real-world examples from diverse industries, including oil and gas, chemical processing, and renewable energy. IoT devices in corrosion monitoring, coupled with advanced sensor technologies for real-time data collection, enhance the granularity and accuracy of corrosion-related information. Challenges associated with data security, interoperability, and sensor reliability have been discussed, while presenting avenues for addressing these concerns. It also points toward ongoing research in advanced sensor technologies, explainable AI, and the potential use of quantum computing for corrosion modeling. In conclusion, the chapter underscores the transformative potential of leveraging AI and IoT for effective corrosion mitigation in Chemical Engineering processes. The proactive, real-time, and data-driven nature of these technologies not only ensures the longevity and safety of critical infrastructure but also aligns with broader sustainability goals. Keywords: Corrosion Mitigation; Artificial Intelligence (AI); Internet of Things (IoT); Environmental Sustainability; Predictive Maintenance.
A numerical solution for one-dimensional diffusion of chemicals under coupled chemical and thermal potentials is presented. The theoretical formulation considered includes thermal conduction and chemical diffusion due to molecular and thermal diffusion potentials. The investigation quantifies the spatio-temporal variations of the solute and studies the effects of the associated characteristic parameters. Established nonlinear and variable coefficient equations describing heat and mass transfer processes are solved using the MATLAB pdepe solver. The numerical prediction of solute movement is compared to the reference analytical solution from the literature and good performances are presented. Comparisons with the steady state heat transfer model were also carried out to study the influence of the soret effect and the temporal variation of temperature on chemical transport due to a thermal gradient. The analysis presented shows that the Soret effect significantly influences solute transport in unsteady regime. Compared to this regime, solute transfer responses with stationary thermal transfer suggest that the solute present in a subspace can be underestimated or overestimated as a function of time. It was also found that a temporal variation in the temperature of the medium affects the migration of solutes in the medium. For example, for an initial concentration of the solute at the surface C_0=100 mol/m^3 , the concentration gap between the two regimes can go up to 8 mol/m^3 . Similarly, an increase in average soil temperature induces rapid movement of solute in the domain. A large difference is observed between the forecasts in the steady and unsteady heat transfer regime when the average temperature increases from 323°K to 373°K. So, for an initial concentration C0= 100 mol/m3; the concentration at a depth of 0.5m at the 40-years date is 45.58 mol/m^3 and 60.67 mol/m^3 for the case of thermal diffusion in steady state with Tm = 323 °K and Tm = 373 °K, respectively. However in unsteady regime, at the same position and on the same date, the concentration is 49.74 mol/m^3 and 73.86 mol/m^3 with Tm = 323 °K and Tm = 373 °K, respectively. From the present numerical study, we observed that the temperature profiles increase with increasing initial surface concentration.
This qualitative research study examined "The impact of teaching history in a language students understand better in a bilingual setting" . This study is carried out to investigate whether the language of instruction as a result of regulation in the bilingual curriculum is impeding to attain set goals and also whether it has any influence on academic achievements of this discipline included as a core subject in the curriculum. Further, the study is determined to gather details with regard to language capability of students who enroll in the bilingual system of education to understand the subject content . The subject is included in the curriculum expecting to inculcate many competencies, this study will also examine whether the language of instruction play an integral part in making this a success. Therefore, This study is carried out to understand if, the language of instruction is a barrier that hinders the acquisition of the goals and competencies expected to be inculcated among students through this discipline. The population of the study included students , parents and teachers who are directly linked to the bilingual system of education in the urban region. The sample for the study was drawn from the population, it consisted of about 30 students, 10 parents and 10 teachers. The feedback of students, parents and teachers were gathered through a field survey questionnaire to analyze the impact of the language of instruction. The objectives of the study are reached through qualitative techniques mainly. The objective number 01,02 and 04 are addressed using qualitative techniques such as elaboration ,comparison, explanation and content analysis. The objective number three is determined using close ended question in the questionnaire. These questionnaires were analyzed using percentage analysis. The results indicated among the respondents around 30-40 % of the sample agrees to the fact that History should be taught in English for students in the bilingual setting. However, an equal number of respondents strongly believe that history should be taught in the first language to be more effective. The study further found that a significant level of academic achievement could be attained if the subject is taught in a language student prefers. The findings of the study, conclusion reached, implications for decision makers and the limitation faced are discussed comprehensively.
The study examined the impact of drug and substance abuse on the academic performance of school students. Specifically, the study aimed to investigate the correlation between drug use and academic achievement. The study employed a quantitative research approach and adopted an exploratory research design. A total of 100 participants, including school children, parents, and teachers, were selected for the study using convenience sampling technique. A validated questionnaire was used to collect data from the participants, and the gathered data was ultimately analysed using quantitative methods The study found a significant positive correlation between drug use and academic achievement. Specifically, the study found that students who report using drugs have lower academic achievement scores compared to those who do not use drugs. Additionally, the study found that parents and teachers perceive drug use as a significant predictor of poor academic performance. The study's findings suggest that drug and substance abuse can have a negative impact on the academic performance of school children. The study's conclusions support the idea that drug use can impair cognitive functioning and impact academic achievement.The study's recommendations include the implementation of drug prevention and intervention programmes in schools, as well as increased awareness campaigns targeting parents and teachers. Additionally, the study recommends further research to explore the longitudinal effects of drug use on academic performance. Recommendations for future research include examining the impact of specific drugs on academic performance and investigating the role of risk and protective factors in the relationship between drug use and academic achievement
Diabetes mellitus is still one of the age-long chronic diseases confronting the human race. Its frontiers are expanding by the day and has become a growing problem in the world today. Sequel to this, robust researches into it with an aim of developing more appropriate drugs for its management have been encouraged in recent times. In this study, the effects of Nauclea latifolia extracts on some biochemical and haematological parameters in diabetic rats were investigated. Thirty male Wistar albino rats were divided into six groups of 5 rats each (Groups A – F). Group A (normal control) and Group B (diabetic control) were administered 1 ml distilled water. Groups C, D and E were diabetic rats treated with 500mg / kg. b.wt of extracts of Nauclea latifolia while group F received 5mg/ kg. b.wt of glibenclamide. Serum total protein, albumin, urea and creatinine were determined using kits based on standard methods. Haematological parameters were determined using Mindray B C 2800 Veterinary Auto Haematology Analyser. The extracts raised non-significantly total protein and albumin levels while causing non-significant reduction in urea and creatinine. Packed cell volume (PCV), platelets, red blood cells (RBC) and white blood cells (WBC) were significantly increased in the diabetic treated rats. While the extracts do not affect the biochemical parameters significantly, they caused significant increase in the haematological parameters. The significant increase of PCV and RBC by the extracts shows that they have the potential for remedying anaemic condition in diabetes mellitus. The significant increase in platelets by the extracts indicates that they might have beneficial effect in bleeding disorders when used in clinical medicine in addition to having potential to boost immunity since they significantly increased the white blood cells count in the diabetic treated rats.
The algae growth and nutrition values like total phosphorous and total nitrogen have been increasing by disposing sewage waste in the ponds of Kathmandu valley. Due to which water become eutrophic and microbiologically unsafe for agricultural and aquacultural reuse; It's necessary to find out the low cost and environmentally friendly substances for the removal of algae and phosphorous from eutrophic pond to recover oxygen depletion and ecological damage. The principle of flocculation has been considered as the removal of algae and phosphorous with effect on nitrogen, turbidity and pH. This study investigates the calcium-magnesium containing burned dolomite powder as a inorganic coagulant has been used to remove the algae and phosphorous simultaneously. For the removal of algae and phosphorous, the dolomite powder was calcined at 1000°C for 2Hr and from 2.5g/l to 15g/l was used in this experiment as Jar test. The water samples with algae was collected from Nagdaha and Godawari Kund. A series of experimental investigations such as pH and turbidity after Jar test was done using pH meter and turbidity meter showed that algae was removed sufficiently. In addition, TP and TN analyses at different amount of doses were done by UV/Vis Spectrophotometer (UVmini-1240). In the present analysis shows an effective removal of turbidity caused by algae at optimum dose of 2.5g/l at turbidity range of 5-12NTU and 7.5g/l at range of 20-30NTU. At optimum dose pH was raised upto 11 due to release of OH- ions in the solution. Experiment also showed that the phosphorous was almost removed at 7.5g/l dose, but in case of nitrogen no obvious effect was observed. From the present work it can be concluded that burned dolomite as a low cost coagulant is found efficient in flocculation of algae and phosphorous from wastewater.
Corrosion and human interference in pipes, vessels, and equipment. Traditionally, the control of metal properties relied on physical methods, such as visual inspection aided by magnifying glasses. Various physical techniques, such as Ultrasonic, Acoustic Emission, Eddy Current, Magnetic Flux Leakage, and radiographic methods, are employed to measure the wall thickness of pipes, vessels, and tanks in oil and gas systems thereby aiding in the detection of corrosion. Artificial intelligence (AI) finds applications across various domains, addressing classification, diagnosis, selection, and prediction challenges in Oil and gas facilities. Artificial Intelligence was modeled to detect corrosion on pipes using Deep learning (DL) algorithms like Convolutional Neural Network (CNN) which focuses on the texture of the image. Artificial Intelligence (AI) can help sustain oil and gas assets by predicting e, which detects the texture of corroded regions of pipes, vessels and correctly classify them. The process is implemented using python and the TensorFlow deep learning framework. The techniques involve data collection from primary and secondary sources, data preprocessing, feature selection, model development, instantaneous prediction, and continuous improvement. The dataset were trained, validated and tested using improved convolutional Neural Network (CNN), where classes are labeled as Corrosion and No Corrosion. The CNN Model developed performed very when compared with other DL models such as the conventional CNN, Resnet-50, VGG-19 and Inception-v3 models. Although, multiple executions of the model were conducted with various epochs, and it was concluded that between 4 and 5 epochs with three convolutional layers, the best results were obtained in terms of training and validation accuracy, achieving overall accuracy of 99.4%, which outperformed other works existing in the literature. KEY WORDS; Artificial Intelligence, Convolutional Neural Network, Deep Learning, Prediction Resnet-50, VGG-19 and Inception-v3, epoch.
Seeds are important inputs for agricultural productivity. The Government of Ethiopia has progressed and applied seed sector policies to improve the country’s seed industry and increase overall crop production. However, there are constraints that hampered the development of the seed sector in the country. There is also limited awareness about the seed legal issues among the various stakeholders in the value chain. The objective of this review is to assess the improvement areas of the new seed proclamation (1288/2023). To achieve the objectives of this research reviewing and to compare the existing seed legal framework, recent literature and personal communications were used. The new seed proclamation number 1288/23 offers strategic direction for the seed regulatory framework in Ethiopia. Seed proclamation accommodates the needs of various components that has to be functional in the seed industry and addresses most of private sector challenges in the country. Awareness creation on new seed proclamation and strengthening implementers at all levels is critical in the future.
This study explores the significance of modular distance learning in the professional development of teachers enrolled in Enthusiastic College Inc.'s graduate program in Upper Dinganen, Buldon Maguindanao. The study's goal is to investigate the effect of modular distance learning on teacher knowledge acquisition, instructional methods, and overall growth. The study employs a mixed-methods approach, integrating both quantitative and qualitative data collection methods. The study included 50 teachers from the graduate program. Participants are given modular distance learning modules that are specifically tailored to promote their professional growth in many areas of teaching and pedagogy. A questionnaire is distributed to collect quantitative data on the participants' perceptions of the modules' effectiveness and usefulness. Additionally, interviews are undertaken to collect qualitative data about the teachers' experiences and ideas about the impact of modular distance learning on their professional progress. Thematic analysis and statistical techniques are used to analyze the study's findings. The findings show that modular distance learning provides flexibility and convenience, allowing teachers to combine their teaching responsibilities while continuing their professional development. Participants indicate significant information acquisition, enhanced instructional practices, and a beneficial impact on their teaching methods and student outcomes. The study also highlights the specific modules and learning experiences that have had the greatest impact on their professional development. According to the data, modular distance learning plays an important role in the professional development of instructors in the Enthusiastic College, Inc. graduate program. It provides teachers with a flexible and accessible platform for expanding their knowledge, refining their instructional approaches, and improving their teaching talents. The study proposes that modular distance learning be continued as a beneficial technique for ongoing professional development in education. This study contributes to the current literature on modular distance learning and its significance in the context of teacher professional development. The findings can help educational institutions, policymakers, and teacher training programs understand the benefits and effectiveness of implementing modular remote learning as a way to promote and enhance teachers' professional growth. Keywords: Modular Distance Learning, Significance, Professional, Development, Teacher.
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