International Journal of Advances in Scientific Research and Engineering (IJASRE), ISSN:2454-8006, DOI: 10.31695/IJASRE
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Anthocyanin as Colorectal Anticancer: A Brief Review
Get PDFColorectal Cancer (CRC) is dangerous cancer that causes many cases of death in the world. This cancer spike occurred in 2020 with 1.15 million cases and is expected to increase in 2040 by 1.92 million CRC cancer cases. Some of the most popular drugs used for CRC chemotherapy are 5-Fluorouracil, Oxaliplatin, and Irinotecan. The effects caused by chemotherapy using synthetic drugs are loss of appetite, fatigue, vomiting, numbness, hair loss, and low blood cell count. Anthocyanins are a group of flavonoid compounds and polyphenols with antioxidant, antimutagenic, and anticancer activity that can be developed as CRC anticancer. Anthocyanins do not cause side effects in CRC patients. This article is a review of anthocyanin activity to reduce the risk of colorectal cancer (CRC) in terms of molecular mechanisms, the proliferation ability of cancer cells, and promoting apoptosis of CRC cells
Analysis on Natural Fibre Sisal and Areca Polymer Based Composite Material
Get PDFPresent days natural fibers have transformed the matter of research field among various fields of study to inculcate it in the manufacture of composites instead of the production of composites using areca and sisal polymer-based composite. This is due to respective advantages related to natural fibers like eco-friendly, low cost, convenience in copiousness, and biodegradability. Stacks of work have been carried out in the production of natural fiber-reinforced polymer composites, using natural fibers like areca and sisal polymer-based composite and their mechanical properties have been studied. Here is an attempt made on the literature survey of areca and sisal fibre built polymer composites where different properties of areca and sisal fibers, its adulthood level, surface treatment effect on properties of fibers, composite formation with different matrices, its mechanical properties have been highlighted
Household Waste Recycling Knowledge and Markets, Challenges and Successes, in the Yassa, Douala, Cameroon
Get PDFThis research paper presents the results of a survey consisting of recycling knowledge and markets in Yassa a residential neighborhood in Douala 3 municipality in Cameroon from January 2018 to March 2019. Primary data was collected from field surveys and random sampling to select residents. The household survey, participant observation and participatory appraisal, focus group discussions, interviews, and questionnaires were administered to collect information from participating households regarding, gender, age, and level of education and itinerant buyers. In the Yassa, Table 1 highlights the preference of the recycled household waste fraction while in Table2, I Kg of plastic waste was bought by Itinerant waste buyers from households at 100FCFA, and later sold to middlemen at 200FCFA and middlemen to small enterprises at 400FCFA. The difference in the buying and selling prices of ferrous metal and glass illustrates their importance in the market for recyclates. Descriptive statistics were used to analyze the collected data. The results showed a predominance of females 70,4%, and 29.6% for their male counterparts with 60,2%for those with formal education and 39.8% with no educational background. The results from this study will enhance and increase the value for household waste as well as waste management recycling in Douala in particular and Cameroon in genera
Geometric Modelling and Analysis of the Amino Acid: Phenylalanine
Get PDFL-phenylalanine (Phe), an essential amino acid, is necessary for the synthesis of proteins such as catecholamine and melanin, and is also the precursor of the amino acid L-tyrosine (Tyr). In this paper, optimized structures of Phe, were calculated by using using semi-empirical models such as AM1, PM3 and MNDO; Density Functional models (DFT) at B3LYP and Hartreefock methods (HF) with 6-311++G (d,p) level. The energies and geometric parameters of Kaempferol were also determine
Goal Programming Model to Optimize the Amount of Gauze Production
Get PDFPT KHW is a company engaged in the manufacture of cotton and gauze for health and cosmetic purposes. The gauze products produced by the company sometimes exceed the number of consumer demands and sometimes there is a shortage of products. Therefore, good production planning in order to meet consumer demand with the right amount and the right time is needed so the increased profits are obtained. This study aims to determine the optimal amount of production, determine the profits obtained by the company and determine the production costs that must be incurred by the company. This study uses the goal programming method to optimize the amount of production by determining the decision variables, constraint functions and target functions. The goal functions are arranged based on the priority level desired by the company. The goal priorities considered include the goal of maximizing the amount of production, maximizing product sales profits, minimizing production costs, minimizing the use of raw materials, maximizing production time, and minimizing overtime.
 
The occurrence of Hyperglycemia among HIV positive: A Case of People Living with HIV Attending Nyeri Referral Hospital
Get PDFBackground: The hallmark of HIV infection is the progressive loss of immune cells called the CD4 cells weakening the immune system and leaving individuals vulnerable to various opportunistic infections (OIs) and other illnesses, ranging from pneumonia to cancers. Diabetes/hyperglycemia complication on set among the HIV infected has been suggested by several authors although very a minimal interest has been paid on this subject. This study looked at the correlation between hyperglycemia (a risk factor of DM) and HIV infection among HIV-infected individuals in Nyeri County Hospital-Kenya. Methods: This was a case-control study involving 193 individuals who were grouped into two groups of 97 HIV-positive HIV-Negative individuals (also referred to as study control group) based on negative HIV results and fasting blood glucose level 4.4 ± 2.2mmol/L. and 96 participants who were HIV positive. Results: A total of 193 individuals were enrolled, grouped into 97 subjects of HIV-negative individuals (control group) and 96 participants who were HIV-positive. In the study 13.54% of HIV-positive were hyperglycemic compared to 6.18% HIV- ve individuals (mean glucose level 7.6 ± 5.1 and 4.4 ± 1.1mmol/L, respectively (P>0.05) r=0.023). Conclusion: The study identified Hyperglycemic as a likely complication in HIV-infected individuals with a need to study the effect of individual diabetes mellitus risk factors in HIV-infected individuals
Malware Detection System Using Mathematics of Random Forest Classifier
Get PDFMost cyberattacks including data breaches, identity theft, fraud, and other issues, are known to be caused by malware. Some of the malware attacks are categories as adware, spyware, virus, worm, trojan, rootkit, backdoor, ransomware and command and control (C&C) bot, based on its purpose and behaviour. Malware detectors still utilise signature-based approaches to detect malicious software, which can only detect known malware. Attacks by malware pose a serious threat to people's and organizations' cybersecurity globally. These attacks are occurring more frequently and more frequently lately. Over eight billion malware attacks occurred in 2020, up 4% over the previous year, according to a Symantec report. It is crucial that computer users safeguard their computers with a malware detector like an antivirus, anti-spyware, etc. When creating a machine learning model to differentiate between malicious and benign files, it might be challenging to use domain-level expertise to extract the necessary attributes. This research aims to create a malware detector that uses a trained random forest classifier model to find malware and stop zero-day assaults. A dataset (including both harmful and benign software PE header information) was obtained from virusshare.com and used to train the random forest classifier in order to create this malware detector. The Random Forest Classifier generate greater accuracy when compared with other machine learning classifiers, such as KNN (K-Nearest Neighbors), Decision Tree, Logistic Regression etc., the random forest classifier gives a better accuracy of 99.4%. The Classifier model used here will be a better option to use in order to efficiently and effectively detect malware, it shows that the methodology can be utilized as the basis for an operational system for detecting an unknown malicious executable
Yolo Versions Architecture: Review
Get PDFDeep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years.
The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing items in images.
This article, will be focusing on comparing the main differences among the YOLO version's Architecture, and will discuss its evolution from YOLO to YOLOv8, its network architecture, new features, and applications. And starts by looking at the basic ideas and design of the first YOLO model, which laid the groundwork for the following improvements in the YOLO family. In additionally, this article will provide a step-by-step guide on how to use the YOLO version architecture, Understanding the primary drivers, feature development, constraints, and even relationships for the versions is crucial as the YOLO versions advance. Researchers interested in object detection, especially beginning researchers, would find this paper useful and enlightening
An Exploratory Analysis of Human Immunodeficiency Virus (HIV) Prevalence in Nigeria
Get PDFThis paper involved conducting a statistical analysis on the number of individuals living with HIV/AIDS. The University of Ilorin Teaching Hospital (UITH) was chosen as the case study for the years 2014 to 2019, with factors such as year, sex, and age group taken into account. During this six-year period, a total of 2604 cases were recorded at UITH. Among both sexes, females had the highest number of people living with HIV/AIDS. Additionally, the age group of 31-45 had the highest number of individuals affected by the disease. In terms of the specific year, 2016 had the highest number of people living with the disease, totalling 460 cases. A chi-square test of independence was conducted to examine the relationship between the factors, using a significance level of 0.05. The results indicated that all the considered factors were not independent of each other, meaning they were related
Climate-smart aquaculture in Tanzania: Assessment of transitional and heavy metals concentrations in a commonly used local feed ingredient for Tilapia farming
Get PDFA study conducted from January through May 2023 to assess the concentrations of heavy and transitional metals in a commonly used local feed ingredient in a farmed Nile tilapia diet (Oreochromis niloticus) in Tanzania. Eleven fish feed ingredients such as, sunflower seed cake (SFSC), wheat pollard (WP), maize bran (MB), fish meal (FM), freshwater shrimp (FWS), cattle blood meal (CBM), bone meal (BM), soya bean meal (SBM), and rice bran (RB), brewers’ spent grain (BSG) and Taro leaves (Colocasia esculenta; TL) were randomly sampled from feed manufacturers, animal feeds’ centers and other animal feeds suppliers in Arusha and Dar es Salaam region for inclusion in this study. Heavy metals and transition metals in feed ingredients were analyzed using the Energy-Dispersive X-rays Fluorescence (XRF) (Xla Pro-Spectrometer/German) at the Tanzania Atomic Energy Commission (TAEC) laboratory. The results showed that most of the fish-feed ingredients used in this study comply with the maximum allowable concentrations in Nile tilapia diets-according to the Tanzania bureau of standards and the European commission. However, the results showed that, the concentrations of reported metals (As, Pb, Cd, Hg, Co, Cu, Mo, Mn, Ni, Ag, V, Cr, Fe and Zn) varied significantly (p < 0.05 ) in most of the analyzed local feed ingredients collected in Tanzania. The study has paved the way for other researchers to further assess more feed ingredients used not only on heavy metals but other potential contaminants in feeds to ensure sustainable fish farming in Tanzania