Authors:Francis Omoniyi, Alabi Aderemi B. , Salawu Mufutau A. , Babalola Olayinka A. Pages: 1 - 9 Abstract: This paper studies the conductivity and chemiresistive H2S gas sensitivity of graphene(75wt%)-Cu(25wt%) composite thin film, using self-made chamber and common laboratory apparatus. The method adopted involves mixture of 2 drops of ethanol with the synthesized composite and prepared on a glass substrate by tape casting method. Two small copper metal sheets were used as electrodes for clipping of crocodile which were also connected to digital meter for resistance readings and its changes. The X-ray Diffraction (XRD) shows that annealing temperature reduced the crystallite sizes. The Fourier Transform Infrared Radiation (FTIR) spectra show the functional groups present to be transition metal carbonyls or aromatic combination bands, terminal alkyne (monosubstituted), isothiocyanate and that between 2300 and 2400 cm-1 indicates N=C=S functional group and evidence of CO2 interaction with external surface of the material or intercalating in the interlayer of the host material Also, increase in the conductivity was observed due to decrease in resistivity. The response/sensitivity peak of the sensor to hydrogen sulfide was seen to rise proportionally as temperature rose with percentage 3.97% for as grown, annealed at 200°C is at 12.98% while the annealed at 400°C is at 27.34%. Keywords:Articles
;
The Effect of a Riga Plate On Casson Hybrid Nanofluid Flow Along a
Authors:Silas Okuma, Aworinde Adekunle , Areo Adeisa Olusegun , Akande Mariam Ololade , Adegbite Peter , Akindele Akintayo Oladimeji Pages: 10 - 22 Abstract: This study investigates the effect of a Riga plate on the flow characteristics of a Casson hybrid nanofluid through a stretching cylinder embedded in a porous medium in the presence of an exponential heat source and thermal radiation. This model is used to explore the potential applications of this analysis in the fields of cancer treatment and wound healing. The governing partial differential equations are converted into a system of nonlinear ordinary differential equations using suitable similarity transformations. The governing partial differential equations (PDEs) were reduced to ordinary differential equations (ODEs) using similarity variables, and the heat transfer phenomena, fluid flow dynamics, and nanoparticle behavior in the base fluid were captured through numerical analysis. The Casson fluid model was used to capture the non-Newtonian characteristics of blood-like fluids in the circulatory system, and stretching was employed to mimic the blood vessel. The modeling involved incorporating thermal radiation (Ra) and an exponential heat source, which are encountered in cancer treatment. The Runge-Kutta order 4 with shooting technique was used to obtain numerical solutions of the governing equations, and the effects of the Casson fluid parameter, curvature parameter, nanoparticle volume fraction, Eckert number, and radiation parameter were analyzed. The results showed that the Riga plate affected the flow patterns by increasing the temperature, and the temperature distribution was improved by increasing the radiation parameter and nanoparticle concentration. The insights from this study could be used to optimize heat-based treatments for cancer and wound healing, where control of fluid dynamics and heat transfer processes is critical. Keywords:Articles
;
Development of an Orthosis to Compensate Volumetric Dysmetria of Feet
Authors:António Magalhães, Carla Peixoto Pages: 23 - 32 Abstract: The concept of symmetry applied to the two halves of the human body has been the subject of reflection by anatomists. One of the most common inequalities is dysmetry of the lower limbs (LL), especially the legs and/or feet. In the case of a height difference in the legs, if it is very pronounced, it is necessary to develop strategies capable of correcting or reducing its impact on the quality of life of people who live with it daily. A rare type of dysmetria is the volumetric difference of the feet, not accompanied by changes in the length of the legs. In these cases, filling with conventional orthopedic insoles to improve the fixation of the foot inside the shoe is completely inappropriate because it slightly increases the length of the respective lower limb, which is reflected in changes in the spine that can degenerate into severe scoliosis. To solve these problems, a volumetric compensation orthosis applicable to this type of situation was developed. Using modern three-dimensional scanning and 3D printing techniques, an orthosis was customized for placement inside the shoes of an individual with this volumetric anomaly. To ensure walking comfort, a common flexible material (TPU) was chosen, and the printing parameters were studied based on feedback given by the user. As a measure of the effectiveness of the developed product and to analyze the effect produced, tests were carried out to compare gait patterns before and after the correction was established. The results found showed an approximation to standard gait patterns, a considerable improvement in the fixation of the foot inside the shoe and an interchangeability that allows the use of the orthosis in any type of footwear, such as classic shoes, boots or sneakers. Keywords:Articles
;
A Low-Cost Monitoring System for Energy Consumption Analysis During Machining Operation
Authors:Akmal Najihah Ibrahim, S.C. Johnson Lim Pages: 33 - 44 Abstract: CNC machining is a common manufacturing process which requires significant energy consumption. The first step towards energy savings is to monitor the energy consumption of CNC machines, which are usually equipped with a three-phase electrical power supply. However, existing energy metres are costly for detailed measurements of a machine's energy consumption level. This study developed a low-cost energy measurement device based on the Arduino microcontroller-based platform to monitor energy consumption during CNC machining processes. The product development methodology includes the measurement procedure, calibration, pilot study prior to the commencement of the actual study, and results validation. A field experiment was conducted to validate the design's functionality. Preliminary energy measurements were performed on tool standby, tool changing, spindle rotation speeds, and feed rates. Results showed that the average standby power of the CNC machine is 5.15 kWh, with actual power consumption for the coolant pump motor, spindle motor, and feed motor being 0.43 kW, 0.77 kW, and 0.45 kW, respectively. Energy consumption is increased with spindle rotation speed and feed rate increments. The analysis results demonstrated the product's ability as a cost-effective solution for machining energy monitoring. Keywords:Articles
;
Ethnobotanical Survey of Medicinal Plants Used in the Treatment of Transmissible Diseases
Authors:Bawale Sani Halliru, Nuraddeen Wada, Abdulrahman Mahmoud Dogara, Aisha Abdullahi Mahmud, Isah Labaran, Hussaini Danlami Pages: 45 - 55 Abstract: Herbal medicine, as an ancient traditional medical method, predates the establishment of contemporary healthcare systems within human culture. Globally, several groups develop their own indigenous forms of medicine and corresponding methodologies for treating and enhancing overall well-being. The research presents a comprehensive ethnobotanical survey of medicinal plants used in the treatment of transmissible diseases in Katsina State. A random selection technique was employed in conjunction with an open-ended interview guide over the period spanning from October 2022 to June 2023. The demographic information of the respondents was ascertained using Excel 2016. Quantitatively, the documented plants were subjected to analysis based on their Relative Frequency of Citation (RFC). This study identified 26 medicinal plants used in the administration and treatment of various transmissible diseases in the northern Nigerian state of Katsina. Moringa oleifera (28%) is the most frequently reported plant, followed by Olea Europaea (24%) and Azadirachta indica (20%). Leaves were the most frequently used part of the plants (69%), common method of preparation is decoction (65%). As their popularity and recognition expanded throughout the world, plants with medical potential remain the sole hope for the future. According to the current study, people of Katsina citizens had a solid awareness of the medicinal plant. Even with the progress of contemporary medicine, the people in the area still depend on using traditional plants for medical purposes. Keywords:Articles
;
Botanical Vegetables Recognition on Raspberry Pi Using Single Shot Detector (SSD)
Authors:M. Iqbal Mortadza, M.N. Shah Zainudin, M.I. Idris, W.H. Mohd Saad, M.R. Kamarudin, Z.A.F.M. Napiah, Nurul Zarirah Nizam, Sufri Muhammad Pages: 56 - 64 Abstract: Advancements in computer vision technologies have fueled research interest in automating object detection, particularly in agricultural contexts. Human eyes prone to error during the sorting process when differentiating the various types of botanical vegetables such as bell pepper (capsicum), chili, tomatoes, etc. Hence, the use an object detection method is believed could categorize this botanical vegetables precisely, allowing farmers to optimize their operations and reduce labor expenses. This study explores the identification of various botanical vegetables types using a Raspberry Pi and the Single Shot Detector (SSD). The proposed approach involves curating an extensive botanical vegetables dataset with detailed annotations to optimize training process. Implementing SSD on the Raspberry Pi capitalizes on its processing power and versatility. Our research demonstrates the system's effectiveness in detecting a wide range of botanical vegetables, including chili, capsicum, tomatoes, and vegetable leaf, achieving an average precision of 89% across diverse environmental conditions. Computational efficiency analysis showcases its real-time vegetable detection capabilities, rendering it suitable for agricultural applications such as automated sorting, inventory management, and quality monitoring. Keywords:Articles
;
Assessment of Deep Learning Model System for Blood Glucose Time-Series Prediction
Authors:Ade Anggian Hakim, Farhanahani Mahmud, Marlia Morsin Pages: 65 - 75 Abstract: Diabetes has become one of the most severe and prevalent chronic diseases, leading to life-threatening, costly, and disabling consequences and reduced life expectancy. Uncontrolled blood glucose (BG) conditions become a factor in diabetes mellitus sufferers, which then causes BG levels that are too high (hyperglycemia) and too low (hypoglycemia). People with Type 1 Diabetes Mellitus (T1DM) require long-term BG management to keep BG levels. Deep learning models using Continuous Glucose Monitoring (CGM) data to monitor and regulate BG concentrations in diabetic patients with prediction values to prevent hypoglycemia and hyperglycemia is very important. Based on some of the latest research, the deep learning Temporal Fusion Transformer (TFT) model is considered an approach method with superior performance in time-series prediction. Therefore, in this study, two TFT models, the TFT and AutoTFT univariate models, were proposed for the time-series BG prediction for T1DM patients. In this study, the two proposed TFT models with two baseline models, were trained and tested on the ShanghaiT1DM dataset. The proposed and baseline models were trained using manual and auto-tuning hyperparameters with Optuna on cross-validation for prediction horizons (PHs) of 30 and 60 minutes, respectively. The performance metrics used to evaluate the models were mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean squared error (RMSE). As a result, the TFT model is superior to the baseline LSTM model, also the proposed AutoTFT models achieved the smallest MAE, MAPE, and RMSE for both 30 and 60-minute PHs, respectively of all models used. Besides, the BG prediction results with 30-minute PHs are better than those with 60-minute PHs for all the models. This shows that the AutoTFT model stands as a promising tool for the accurate prediction of adverse glycemic events. Keywords:Articles
;
Removal of Phenols from Synthetic Wastewater by Horseradish Peroxidase (HRP)
Authors:Nurul Zakiah Md Salleh, Siti Amira Othman Pages: 76 - 83 Abstract: Plant peroxidase has a solid potential to remove phenol from wastewater. However, large-scale use of these enzymes for phenol removal requires a source of cheap, abundant, and easily accessible peroxidase-containing material. In this study, the horseradish peroxidase (HRP) removes the phenolic compound from the phenolic environment. The enzymatic method was used to show a reduction of toxicity between the treated and untreated phenolic solution. The HRP, with the addition of hydrogen peroxide (H2O2), reacted with the phenolic compound and produced a treated solution containing about 20% of phenol compared to the initial acidic solution. The concentration of the treated solution was then determined using UV-Vis and FTIR spectroscopy. The effects of treating the acidic solution with HRP enzyme and H2O2 were studied. The HRP enzyme decreases the amount of phenol present in an acidic solution by 80 %. The most effective concentrations for treating the acidic solution were HRP at 1.0 M and 1.0 M of H2O2 at neutral pH. Keywords:Articles
;
Protective Effects of Aqueous Extract of Piper nigrum Whole Fruits Against Tramadol-induced Hepato-and Nephrotoxicity in Wistar Rats
Authors:Quadri Nurudeen, Sulyman Abdullahi, Mansurat Bolanle Falana, Muhammed Robiu Asinmi, Muhammad Ali Dikwa, Oghebetega ThankGod Oweh Pages: 84 - 94 Abstract: Tramadol, a widely used analgesic, is becoming more abused in most countries. Hence, this study aims to investigate the protective effects of aqueous extract of Piper nigrum whole fruits on tramadol-induced toxicity in male Wistar rats. Six groups (A-F) of male Wistar rats were exposed to a 14-day oral treatment. Specifically, the control group, induced group (tramadol at 60 mg/kg), reference drug group (Vitamin C at 250 mg/kg) and the extract groups (250, 500, and 1000 mg/kg). The levels of liver cellular markers ALT, AST and ALP as well as the kidney function parameters (urea, creatinine and uric acid) showed a significant (p<0.05) increase following the administration of 60 mg/kg of tramadol and a significant reversal was observed following the administration of extract in a dose dependent manner. However, K+ and HCO3- showed a significant (p< 0.05) decrease and were also reversed following the administration of extract in a dose dependent manner. Tramadol also showed a significant (p<0.05) increase in the concentration of WBC and LYM, and a significant (p< 0.05) decrease in the levels of RBC, HGB, HCT, RDW-SD, RDW-CV, and MPV. The reference drug and the extract showed significant (p< 0.05) reversal in the levels of these biochemical parameters. Histological examination revealed normal liver and kidney architecture in all groups, indicating no signs of inflammation or damage. These findings revealed that the aqueous extracts from whole fruits of P. nigrum at concentrations of 250 and 500 and 1000 mg/kg may potentially offer protection and general improvement in the overall health status and function of the hematopoietic system. Keywords:Articles
;
Federated Learning Based Enhanced FedBA with MobileNet Convolutional Neural Network for the Identification of Columnar Cactus
Authors:Muhammad Numan Ali Khan, Mohd. Norzali Hj. Mohd, Fawad Salam Khan, Tasiransurini Ab Rahman, Muhammd Khurram, Suhail Kazi Pages: 95 - 104 Abstract: With the advancement in artificial intelligence (AI) technology and Internet of Things (IoT) growing popularity, the use of unmanned aerial vehicles (UAVs) as IoT devices is also being studied. However, privacy issues and limited communication resources restrict the use of unmanned aerial vehicles. Federated Learning (FL) has emerged as a promising approach for training machine learning models on decentralized devices while maintaining data privacy and reducing the communication costs. To aggregate the model on the server-side FL server uses various aggregation algorithms. One such promising aggregation algorithm is FedBA for non-identically and independently distributed (non-IID) data via UAVs. However, despite its advantages, FedBA may face challenges related to convergence speed, robustness to malicious clients, and overall efficiency. To solve these challenges, this study presents a FL model aggregation technique in which clients and servers communicate parameters as opposed to data, thereby enhancing privacy, and reducing communication costs UAVs images. This research proposes enhancements to the FedBA algorithm aimed at addressing these challenges and improving its performance. The method proposes federated learning based enhanced FedBA with MobileNet Convolutional Neural Network (CNN) for the identification of columnar cactus in the Tehuacán-Cuicatlán Valley of Mexico. Using a public dataset of over 20,000 remote sensing images, the suggested model is evaluated and found to be superior to InceptionV3 and modified MobileNet CNN. The key contributions of this work include the introduction of momentum for faster convergence, adaptive learning rates for better optimization and model aggregation clipping to prevent extreme updates. The proposed FL framework mitigates the issue of slow convergence and communication cost for non-IID data from UAVs. Enhanced FedBA more effective than typical FL algorithms. The classification accuracy before aggregation is 95% and improved to 97% after aggregation. Keywords:Articles
;
Soxhlet and High-Pressure Processing (HPP) Method: Antimicrobial Study on the Chromolaena odorata and Azadirachta indica Leaves Extracts Against Six (6) Opportunistic Bacteriast Six (6) Opportunistic Bacteria
Authors:Nur Helwa Kamaruszaman, Muhammad Faiz Razali, Sity Aishah Mansur, Angzzas Sari Mohd Kassim, Aliff Hisham A. Razak, Hariz Haikal Nasuha, Noor Akhmazillah Mohd Fauzi Pages: 105 - 112 Abstract: Chromolaena odorata and Azadirachta indica are well-known for their antimicrobial properties and have long been utilized in traditional medicine for treating various skin ailments. This study aimed to compare the efficacy of two extraction methods, Soxhlet extraction and High-Pressure Processing (HPP), in extracting bioactive components from C. odorata and A. indica, and their resulting antimicrobial activity. The antimicrobial properties of the extracted samples were assessed using the Kirby-Bauer disc diffusion method and minimum inhibitory concentrations (MICs). The maximum inhibition zones against E. coli were observed for Soxhlet-extracted C. odorata (17.25 mm) and A. indica (16.67 mm). The MICs were recorded as 0.78% for C. odorata and 3.13% for A. indica, which were notably higher than those of the HPP extracts. For the HPP extracts, treatment at 600 MPa for 10 minutes showed lower MICs against E. coli, with values of 100.0% and 12.5% for C. odorata and A. indica, respectively. Overall, the antimicrobial activity of the Soxhlet-extracted samples was significantly greater than that of all HPP samples. Although Soxhlet extraction demonstrated higher antimicrobial activity, HPP offers advantages as an efficient herb extraction method due to its ability to extract essential compounds from C. odorata and A. indica in a short period and its non-thermal nature, which reduces the degradation of bioactive chemicals. Therefore, these findings hold significant promise, particularly in the cosmeceutical and health product sectors, where the potential of C. odorata and A. indica as natural antimicrobial agents and wound healers could contribute to minimizing harm to human health. Keywords:Articles
;
Open Access journal
