American Scientific Research Journal for Engineering, Technology, and Sciences

The Synergistic Effect of Two Remedial Plant Extracts on Hyperglycemia and Selected Associated Complications in Streptozotocin-induced Rats

Daniel Oyinloye, Adeleke Osho, Pranabendu Mitra — Tue, 18 Jun 2024 00:00:00 +0000

The study investigated the synergistic effects of remedial plant extracts from Musa accuminata (banana) and Momordica charantia (bitter melon) on hyperglycemia and associated complications in streptozotocin-induced diabetic rats—a widely accepted model for studying diabetes mellitus and its complications. Diabetes mellitus, characterised by elevated blood glucose levels and potential organ system complications, prompted the exploration of herbal remedies with minimal adverse effects. Rats induced with diabetes were treated with Musa accuminata extract, Momordica charantia extract, and a combination of both extracts. Blood glucose levels were monitored, and markers of complications, including blood pressure and weight management, were assessed.

Results revealed that the combined treatment demonstrated a synergistic effect, effectively lowering blood glucose levels (350.43±0.14 to 291.59±23.26) compared to individual extract treatments: Banana extract, Bitter melon extract and Glibenclamide (350.43±0.10 to 300.39±21.02, 347.34±0.06 to 292.23±24.53 and 348.30±0.12 to 287.64±24.06) respectively. Furthermore, the combined treatment exhibited significant improvements in blood pressure (127.92/91.25mmHg, 129.19/98.06, 127.20/99.58mmHg and 130.75/99.83mmHg, combined extract, banana bitter melon and Glibenclamide respectively) and weight management in the animal model, surpassing the outcomes of glibenclamide and untreated diabetic rats. The average weight gain across all the groups ranges from 250g to 321g per rat.These findings highlight the potent anti-hyperglycemic and anti-complication properties of the Musa accuminata and Momordica charantia extracts and their combination in streptozotocin-induced diabetic rats. It is suggested that additional research be done on the underlying mechanisms and clinical trials to confirm the plant extracts' medicinal potential in treating diabetes mellitus and its related problems.

Integration of Advanced Sensors in Smart Transportation Systems: Enhancing Efficiency and Safety

Tochukwu M. Ukaegbu, David Oweh, Kenneth O. Ogirri — Fri, 21 Jun 2024 00:00:00 +0000

The article examines how Smart Transportation Systems (STS) might revolutionize transportation, using Nigeria as a case study. It addresses worldwide urban transportation obstacles, such as traffic jams and safety concerns, and presents STS as a workable solution, outlining its main features and advantages. The study explores the classification of sensors in STS, including vehicle-based, traffic control, and supporting technologies, and clarifies how they contribute to traffic management, driving assistance, and safety improvements. The research delves into communication protocols as well, with a focus on wireless sensors and Vehicle Ad-hoc Networks (VANETs), which provide real-time data sharing between cars and infrastructure for enhanced traffic updates, route optimization, and safety precautions. The report highlights Nigeria's efforts and emphasizes the potential advantages of universal adoption, while admitting the limited implementation of STS in poor nations. In order to fully realize the advantages of STS in enhancing urban life and transportation systems, not just in Nigeria but also worldwide, it finishes by highlighting the need for ongoing research, legislative frameworks, and infrastructure investment.

Housing Affordability and Prototype Solutions for Middle-Income Group of Savar, Bangladesh

Sat, 13 Jul 2024 00:00:00 +0000

Addressing the housing needs of the middle class has been a key focus of national initiatives in emerging nations like Bangladesh. With a substantial portion of the population being middle-income individuals, this issue is particularly pressing, especially in various parts of the capital city of Dhaka. However, the area of Savar is notable for its high population of factory workers within the middle-income bracket, where housing affordability is a major concern. Surprisingly, this issue has remained largely unnoticed. To address this, an on-field investigation and survey were conducted to assess the affordability scenario. The application of the Price to Income Ratio (PIR) tool facilitated a numerical assessment of the situation. The findings reveal a significant gap between housing demand and supply, with most available options being unaffordable for the target group. Therefore, this research aims to identify potential solutions within the affordability range of the middle-income group, including exploring modular housing options as a cost-effective and flexible approach to meet their needs and offer a viable path toward improved living conditions for the target demographic, and to spark further investigations into the topic.

Use of Solar Photovoltaic Systems for Meeting the Power Demand in the Island of Crete, Greece Avoiding the Land Use Conflicts

John Vourdoubas — Sun, 26 May 2024 00:00:00 +0000

Solar photovoltaic systems are increasingly used for power generation worldwide replacing the use of fossil fuels and reducing the energy-related carbon emissions. The abundant solar energy resources in Crete can generate green electricity increasing the island’s energy security and self-sufficiency. Apart from installing them on the ground new configurations for siting solar photovoltaics have been developed avoiding the conflicts related with land use. Several unconventional configurations regarding the installation of solar photovoltaic modules in Crete meeting the annual power demand have been investigated. These configurations include their installation on rooftops of buildings, on the surface of water bodies, on cultivated and uncultivated land allowing the dual production of energy and food and on the fields vertically sited. Evaluation of power generation from solar photovoltaics sited on rooftops of buildings in Crete indicated that they could generate a significant amount of the annual electricity demand of the island while the floating solar photovoltaics could only generate a small amount of its annual power demand. The use of agrivoltaics and of vertical photovoltaics in Crete could generate significant amounts of electricity although quantitative estimations have not been implemented. In conclusion, solar electricity generation in Crete can meet the annual power demand in the island allowing the dual use of valuable and fertile land for electricity generation and food production.

Moving the Agriculture Value Chain Forward in Nigeria: A Review of Digital Technology Trends in Financing Agriculture

Mohammed Abdullahi — Wed, 10 Jul 2024 00:00:00 +0000

Nigeria’s telecommunication industry has developed since the privatization of the telecommunication industry in the early dispensation of the Fourth Republic in 1999. It has positive transformational development of some sectors of the economy with an impact on the growth, and improving the effectiveness and efficiency of businesses in banking and finance, oil and gas, taxation, and energy sectors with reliance on the development of software and programs and hardware. The neglect of digital technology for an internet economy in the agriculture sector financing can be argued to be a contributor to the negative effect of the overall social system in Nigeria. If there is an increase in digital technology financial services for the agricultural sector in the rural areas in Nigeria, then there will be an increase in agricultural financing agricultural productivity, and agricultural performance. The objectives of this paper are - 1. To examine the problems of digital technology limiting financial agricultural funds in private, public, and international financial institutions and agencies and agricultural sector productivity. 2. To identify the research gaps in digital technology financial services that limit agricultural funding in Nigeria. This paper is structured around multidimensional approaches with emphasis on the theories of development which include the Big Man Theory of Thomas Carlyle, the Management Theory of Frederick Taylor, the Structural Functional Theory of Talcott Parson and Robert K Merton, the Modernization Theory of Emile Durkheim, the Human Needs Theory of David McClelland and Maslow, and Integration Theory of Niemann and Bergmann. The method used for data collection is a secondary source and is based on the review of two journal papers and two international conferences published in journals and academic websites related to financing agriculture and seven digital technology papers that relate to the problem of financial exclusion for agricultural smallholder farmers.The findings reveal a lack of a structural framework that supports developed software and hardware and a lack of a universal API that provides financial services to marginalized rural farmers in rural areas. The absence of checks and balances in accounting and the absence of agricultural extension workers limits the services of monitoring and evaluation of agricultural funds and smallholder farmers. It is recommended that digital technology be applied to provide financial inclusion for marginalized farmers in rural areas.

Potential Health Consequences of the El Paso Smelter

Destiny R. Bacon — Tue, 23 Jul 2024 00:00:00 +0000

The city of El Paso, Texas previously had a smelter that employed a lot of individuals in surrounding areas. The smelter eventually closed, which led to public health officials investigating the health and environmental factors that the smelter had on the community. Testing has found that there were neurological, behavior, and blood lead levels elevated within children that were in the vicinity of the smelter. The smelter has created a lasting impact on the community, environment, and health of the individuals within that area.

Assessment of Mentorship Opportunities for Real Estate Developers in Ghana

Mon, 01 Jul 2024 00:00:00 +0000

Effective mentorship usually guides and steers young professionals towards path of success in their professional career development. Majority of infant real estate developers in the developing countries including Ghana do not tap into mentorship opportunity to sharpen their professional tools due to the limited knowledge they have in the concept of mentorship. In spite of the limited empirical research conducted in real estate mentorship, this study serves to break grounds by assessing the opportunities and challenges existing in real estate industry. To achieve this purpose, study materials such as books, academic articles, theses and other documented sources were gathered to examine literature on the subject matter. Interviews were further conducted among some selected real estate developers in Ghana with the basis to establish the key facts and factors associated with the challenges and opportunities mentorship provides to mentees. It was discovered through this study that majority of the real estate developers (mentees) lack funds to undertake projects due to the difficulty they face to secure affordable funding. They also frequently face land litigation issues. The study suggests that the emerging real estate developers in Ghana could build their capacities to remedy such findings through mentorship opportunities available to them.

Reliability Optimization in Healthcare Warehouses Through Advanced Quality Assurance Techniques

Phani Chandra Barla — Sun, 26 May 2024 00:00:00 +0000

“Big data” refers to extremely useful and extensive datasets. A lot of people have been paying attention to it over the last 20 years because of the promising future it holds. The goal of many public and private organizations is to improve customer service by the collection, storage, and analysis of massive volumes of data. The healthcare business extensively uses big data from a wide variety of sources, including patient medical records, test results, hospital records, and Internet of Things devices. Additionally, biomedical research generates a substantial quantity of big data that is relevant to public healthcare. Proper management and analysis of this data are prerequisites for extracting actionable insights from it. This is crucial because without it, using big data analysis to solve problems is like trying to find a needle in a haystack. The only way to overcome the many challenges of processing massive data at each phase is to use state-of-the-art computer tools for big data analysis. For this reason, healthcare professionals who wish to propose solutions that can enhance public health must possess the appropriate infrastructure to methodically generate and evaluate large data. When big data is properly managed, analyzed, and understood, it can open up new possibilities for modern healthcare. That is why numerous industries, healthcare included, are putting in a lot of effort to make the most of this chance and transform it into better services and more money. Medical therapy and personalized treatment stand to benefit greatly from the current healthcare industry's increased emphasis on biomedical data integration.

Leveraging Artificial Intelligence for Enhanced Personalization and Customer Experience in E-Commerce Platforms

Anand — Tue, 23 Jul 2024 00:00:00 +0000

Artificial Intelligence (AI) is revolutionizing the e-commerce industry by enabling unprecedented levels of personalization and enhancing customer experiences. This paper explores how AI technologies, such as machine learning, natural language processing (NLP), computer vision, and recommendation systems, are being leveraged to tailor e-commerce interactions to individual customer preferences and behaviors. Key personalization strategies include dynamic content adaptation, customized product recommendations, and personalized marketing campaigns. AI-powered chatbots, virtual assistants, and predictive analytics are transforming customer service, making it more efficient and responsive. Case studies from leading e-commerce platforms like Amazon and Netflix illustrate the practical applications and benefits of AI, including increased conversion rates, improved customer loyalty, and enhanced operational efficiency. The paper also addresses challenges such as data privacy, algorithm bias, and integration with existing systems. Looking forward, the integration of AI with emerging technologies like the Internet of Things (IoT) promises to further innovate the e-commerce landscape. This paper provides a comprehensive overview of the current state and future prospects of AI in enhancing personalization and customer experience in e-commerce.

Performance Metrics of a Grid Connected Photovoltaic Plant: A Practical Case of the 1.3MW Phakalane Plant in Gaborone, Botswana

Lista Gobodi, Ditiro Setlhaolo, Japhet D. Sakala — Sun, 02 Jun 2024 00:00:00 +0000

The performance of a solar photovoltaic plant can be analyzed using various key performance indicators such as performance ratio, capacity utilization factor, system efficiency, system availability etc. This paper is a presentation of the performance of a 1.3MW grid connected photovoltaic system in Gaborone, Botswana. The methodology utilizes the energy generated and supplied to the grid from January to December 2020 to compute the quality ratios: performance ratio, capacity utilization factor and the technical availability of the plant. During the period of study, the grid connected plant injected 2,245,505.00 kWh of energy to the national grid with the final yield, reference yield, performance ratio and the capacity utilization factor of: 1 724 peak sun hours; 2 196 peak sun hours; 78.5%; and 19.66% respectively. Comparing it with other plants this system’s performance is very good. However, the technical availability of the plant was only 57.4% with Mean Time Before Failure (MTBF) of 129 hours and Mean Time To Repair (MTTR) of 96 hours. Therefore, this paper reveals the impact of grid interference and prolonged downtime on the performance of grid tied PV systems. The study gives insight to engineers, researchers, decision makers and other stakeholders in this field so that focus must be directed to ensure the availability of such power plants especially in Africa where most grids experience frequent tripping.

Study to Improve Engineering Properties of the Mixtures of Cinder, Natural Pozzolana and Lateritic Soils for Construction of Surfacing Layers of Low Volume Roads in Mbeya Region Tanzania

Ally Seleman Mwita, Dr. Duwa Hamisi Chengula, Prof. Joseph John Msambichaka — Sun, 26 May 2024 00:00:00 +0000

The availability of suitable gravel materials for road construction that meet specified standards are becoming scarce and the use of available marginal materials shows challenges of not meeting engineering properties for construction of surfacing layers of Low Volume Roads (LVRs). This study aims at investigating the engineering properties of the mixtures of marginal materials which are natural cinder gravel, natural pozzolana and lateritic soils. Natural cinder and natural pozzolana were sourced from Ituha area in Mbeya Region and lateritic soils were sourced from Busale area in Tukuyu District Mbeya Region. In order to improve engineering properties of these marginal materials blending process of the three source materials was conducted. Characterization of source materials and four different blends which are 19La22Po59Ci, 21La20Po59Ci, 23La18Po59Ci and 25La16Po59Ci used for this study were conducted. The tests performed includes particle size distribution, Atterberg limit, compaction test and California bearing ratio.Laboratory test results indicates that all three source materials did not meet criteria to be used for construction of surfacing layer materials of LVRs in Tanzania. The results indicate that all four blends used for this study meet the specification as gravel materials for the construction of surfacing layers of LVRs in Tanzania. This is because the GC and SP values are within the recommended ranges and CBR values are above the minimum of 15%. From the results of this study, it is recommended to improve the engineering properties of marginal materials through blending techniques which could reduce the cost of construction and solve the challenge of scarce suitable materials in many areas in Tanzania.

The Evolution of China’s Wolf Warrior Diplomacy

Diana Oana Strîmbeanu — Tue, 18 Jun 2024 00:00:00 +0000

"Wolf warrior" diplomacy, a term derived from a series of popular Chinese patriotic action films, encapsulates a new assertive and confrontational style of Chinese diplomacy that emerged prominently in the late 2010s. This style has been characterized by an assertive defense of China's national interests and a proactive stance in international relations, marked by confrontational rhetoric and the strategic use of social media. The evolution of wolf warrior diplomacy can be traced through three main stages: the pre-pandemic period (2012-2019), the pandemic period (2020-2022), and the post-pandemic phase (2023-present). This paper employs critical discourse analysis to examine the speeches and public statements of Chinese officials, revealing wolf warrior diplomacy as a strategic communication effort that emphasizes China's diplomatic presence, global engagement, and assertive positions on sovereignty and regional stability. The findings highlight the complex interplay between nationalism, digital diplomacy, and China's broader geopolitical strategy under Xi Jinping's leadership

Utilize Dense Optical Flow for Small Flying Targets Detection and Tracking

Saad Alkentar, Abdulkareem Assalem — Sun, 26 May 2024 00:00:00 +0000

The detection of small targets remains a critical challenge within the field of image processing. Traditional techniques, such as image subtraction with frame-to-frame registration, suffer from high false alarm rates. Even state-of-the-art deep learning architectures, like YOLO and Masked R-CNN, exhibit limitations in this domain. In overextended distances, the inherent feature quality of small targets degrades significantly, leading to a scarcity of informative data for conventional detection algorithms. Consequently, accurate visual recognition becomes a particularly hard task.This work presents a novel detection approach that draws inspiration from the human visual attention mechanism. By leveraging dense optical flow, the model prioritizes moving objects within the scene, facilitating effective target detection. Furthermore, the proposed method employs K-Means clustering to achieve robust foreground-background separation based on color intensity characteristics. To address the limitations of dense optical flow with stationary targets, a dedicated tracking algorithm is also introduced. Our approach demonstrated a high level of accuracy (98%) when evaluated on unseen test data. Additionally, the algorithm functioned in real-time, enabling immediate processing.

Enhancing Quality Control in Medical Devices Supply Chain Using Artificial Intelligence and Machine Learning

Phani Chandra Barla — Sun, 26 May 2024 00:00:00 +0000

Due to its significance, it plays in the management of public health, the healthcare industry is among the most important sectors. The rapid spread of several diseases, most notably the COVID-19 pandemic, has put this sector of the economy in the spotlight. The healthcare supply chain (HSC) has had its weaknesses exposed by the pandemic. The healthcare supply chain is undergoing a period of revolutionary change due to new inventions such as the advent of various cutting-edge technologies such as Industry 4.0 and artificial intelligence. Within the context of a growing economy, this research aims to identify the most critical success factors for using AI in HRM. Using an approximation of SWARA, the HSC ranks CSFs of AI adoption. According to the findings, technological (TEC) factors have the greatest impact on the adoption of AI in HCI within the setting of developing nations. The following dimensions pertain to human beings, groups, and institutions: INT, HUM, and ORG.

Ameliorate Effect of Ajwa (Phoenix dactylifera) on C-Reactive Protein, Lipid Profile and Cardiac Histopathology in Rabbits

Tue, 09 Jul 2024 00:00:00 +0000

Background: High fat diet causes oxidation of accumulated fat cells which leads to Atherosclerosis. The inflammatory marker C-reactive protein has recently been identified as an independent predictor of future coronary heart disease. The inflammatory marker C-reactive protein has recently been identified as an independent predictor of future coronary heart disease. Present study evaluated the cardioprotective role of Ajwa seed paste on lipid profile and C-reactive protein (CRP) level in rabbits. Methodology: 7 months old rabbits (n=15) for 30 days were kept in animal house school under standard laboratory conditions. Rabbits were divided into three groups (n=5). Group1 served as control group fed basal diet, group 2 fed high fat diet, group 3 fed high fat diet supplemented with 6gm ajwa seed paste. Feed consumption ratio was determined in all groups on daily basis. Results: Feed consumption ratio showed significant (P>0.05) decrease in group 2and 3 fed high fat diet. In this study, lipid profile (cholesterol, triglyceride, LDL and VLDL) values were increased in group 2 compared to control group. It was found that significant (P>0.05) decrease in the level of bad cholesterol (LDL, VLDL) in group 3 (fed ajwa seed supplemented diet).HDL value showed significant (P>0.05) increase in group 3. HDL is good cholesterol and increased the level of HDL protect against the stroke and heart attack. and increase the level of good cholesterol (HDL).HDL takes the cholesterol from the body and back to liver where liver removes the bad cholesterol. The value of CRP is higher in group 2 due to the consumption of HFD and CRP level in group 3 showed significant (P>0.05) reduction. Conclusion: It is concluded from present study that ajwa seed paste is beneficial for heart health.

CNN-resNet-50 Algorithm to Detect the Novel Coronavirus (COVID-19) Using CT Images

H. Romdhane, H. Dziri, M. Ali Cherni, Fethia Abidi, Asma Zidi — Tue, 23 Jul 2024 00:00:00 +0000

The detection of the Covid-19 pandemic has been crucial in ensuring health safety and preventing the spread of the virus. In this paper, we present a novel approach by combining the CNN and ResNet-50 algorithms into a unified model. Our experimental results showcase the remarkable efficiency of the proposed method, outperforming both the individual CNN and ResNet-50 approaches. The hybrid CNN-ResNet-50 algorithm demonstrates its ability to automatically and effectively assist in the early diagnosis of COVID-19 patients. By leveraging this combined model, we aim to contribute to the improved detection and management of the pandemic.