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This study delves into the pivotal role of chassis design within Unmanned Ground Vehicles (UGVs), a cornerstone housing various components critical to the UGV's operational functionality. The context of this investigation pertains to the UGV's deployment in environments necessitating resilience against external stresses, while proficiently navigating uneven terrains with low traction. This segment meticulously documents and examines the design process to create a chassis that aligns with the project's requisites. [ABSTRACT FROM AUTHOR]

The presented study focuses on the development of a dumping platform utilizing hydraulic and servo arm mechanisms. The platform serves as a site for dumping collected oil palm fruits by an Unmanned Ground Vehicle (UGV) within an oil plant estate. The investigation is guided by existing research and design principles from various sources, highlighting the mechanics of hydraulic scissor lifts and servo motor control. The prototype employs recycled plywood, surgical syringes, and servo motors to demonstrate its functionality, though acknowledging limitations of plywood in terms of strength and durability. The results showcase the successful lifting of the UGV and tilting of the dumping bucket. The study offers valuable insights into the design considerations and mechanics involved in creating an efficient and environmentally friendly dumping platform. [ABSTRACT FROM AUTHOR]

The oil palm plantation industry heavily relies on foreign labour for harvesting, particularly for collecting loose fruits (LF) alongside fresh fruit bunches (FFB). Manual LF collection, involving bending and repetitive movements, not only diminishes productivity but also poses health risks to workers. This study proposes an automated LF collector to mitigate these challenges. The developed system integrates an LF picker with a robot arm, an LF detector using image processing and a camera, a GPS-based human-follower vehicle, a back-to-home navigation system based on weight detection, and an obstacle avoidance system. The automated LF collector aims to operate autonomously, reducing workforce reliance and enhancing productivity in oil palm plantations. The study discusses the motivation, challenges, and objectives of developing such a system, emphasizing its potential economic and societal benefits. Additionally, the implementation of a novel image processing technique, Faster Objects More Objects (FOMO), using a neural network, is detailed for efficient LF detection. The proposed automated LF collector addresses labour shortages, enhances economic productivity, and reduces the risk of worker injuries in the oil palm industry. [ABSTRACT FROM AUTHOR]

This research delves into the intricate realm of electrical and power management for a prototype Unmanned Ground Vehicle (UGV), encompassing the configuration of circuitry, wire connections, and power dissipation calculations. Leveraging insights from past journal articles, this study selects electronic components based on their attributes, advantages, and drawbacks. The chosen components are then seamlessly integrated into the UGV's General- Purpose Input/Output (GPIO) pin layout, forming an interconnected web of functionality. The UGV's physical arrangement is meticulously crafted to fit within the chassis confines while ensuring a protective casing encapsulates and safeguards all components and wires. [ABSTRACT FROM AUTHOR]

This project proposes the design of a GPS-based autonomous vehicle for the purpose of navigation and following operators in the collection of loose fruits in oil palm plantations. The aim is to reduce the burden on operators who traditionally must manually collect the loose fruits while following behind a truck. The proposed autonomous vehicle utilizes a GPS module to track its real-time location and follows the operator based on their smartphone's GPS coordinates. The vehicle's navigation is controlled by calculating displacement, bearing, and heading angles using GPS coordinates and a digital compass. The vehicle's movement is determined by the heading-to-bearing ratio, allowing it to move forward, turn left or right, or stop depending on the ratio value. The proposed design includes the selection of appropriate components such as GPS module, digital compass, Bluetooth module, motor driver module, and Arduino Mega 2560 microcontroller. The circuit diagram and prototype of the vehicle are presented. The working principle of the vehicle involves point-to- point navigation, calculation of displacement and bearing angles, and utilization of a digital compass for heading determination. The system has been tested and the results show successful navigation and movement of the vehicle based on the operator's location. However, improvements are needed for real-life deployment and extended operation duration. Overall, the GPS-based autonomous vehicle presents a promising solution for efficient and automated loose fruit collection in oil palm plantations. [ABSTRACT FROM AUTHOR]

The palm oil industry in Malaysia has undergone a significant transformation with the adoption of mechanized equipment to streamline the process of fresh fruit bunch (FFB) collection. Traditionally, manual labour-intensive techniques were employed, requiring workers to climb trees for bunch cutting and transportation. The introduction of mechanical buffaloes or harvesters equipped with hydraulic arms has revolutionized the FFB collection process. This paper explores the evolution of hydraulic arms, focusing on innovations such as articulated arms and computer-controlled robotic arms that enhance efficiency, precision, and safety. The replication of this technology through a robotic arm emphasizes data utilization, assembly, and functionality. Additionally, the study delves into the broader implications of mechanization in the palm oil industry, addressing challenges and opportunities for increased productivity and reduced labour costs. The adoption of automated harvesting techniques holds the potential to improve palm oil production, but careful consideration of specific farm needs, along with the advantages and challenges of mechanization, is essential in making informed decisions. [ABSTRACT FROM AUTHOR]

The efficiency of automated palm oil harvest collecting machines is a critical factor in the agricultural industry. This project delves into the essential process of calculating the arm capacity in these machines, which directly impacts their fruit collection capabilities. Through a combination of measurements and calculations, including factors like arm dimensions, fruit weight, and volume, this report equips industry professionals with valuable insights for selecting the most suitable equipment. It also explores the broader context of automated fruit harvesting technologies, highlighting their potential to revolutionize the agriculture sector. With a focus on precise calculations and an understanding of engineering principles, this project lays the foundation for improved operational efficiency and informed decision-making in the world of automated palm oil harvest collection. [ABSTRACT FROM AUTHOR]

This project delves into the groundbreaking technology of the automated harvest collecting machine, meticulously designed to enhance palm oil fruit collection and storage. It stands out for its precision in real-time fruit detection and optimized performance, reducing waste and maximizing agricultural profitability. The integrated detection system, featuring advanced camera detection and finely tuned algorithms, ensures accurate fruit counting and predictive storage capacity. The machine's algorithms process sensor data with exceptional accuracy, considering variables such as fruit size, shape, condition, and colour. The project highlights the continuous prediction process, with the machine adapting its strategies as it detects and counts more fruits. This innovation promises to reshape palm oil collection and processing, providing farmers with a powerful tool to enhance productivity and profitability. [ABSTRACT FROM AUTHOR]

The project focuses on creating an automatic palm harvest collecting machine, where one of the critical components is the basic mobility system required for the machine to move from one location to another. This aspect is fundamental as it underpins the entire operation. The primary goal of this project phase is to design and implement the basic manoeuvring feature of the machine, encompassing its movement and obstacle avoidance. The key concept is to enable the machine to navigate along predefined paths while avoiding obstacles. Achieving this objective necessitates the use of sensors and a microcontroller for processing sensor data and delivering required machine responses. The microcontroller will be customized to align with the specific machine requirements. Subsequent chapters in this report will delve into the research, material selection, methodology, concept design, and implementation process for this mobility feature. [ABSTRACT FROM AUTHOR]

In this project, five essential sections were developed, spanning from the investigative phase to implementation. Each segment, including data collection and transmission, cloud connectivity, AGV Wi-Fi vehicle, fertilizing mechanism, and data analytics, was meticulously crafted based on selected tools and methodologies. NodeMCU ESP8266 was chosen as the microcontroller for data collection and transmission, successfully executing tasks of receiving and transmitting data to the cloud server. Google Sheet was employed as the cloud service provider due to its suitability for the project, with advantages over other platforms discussed. The workflow of the Wi-Fi controlled vehicle and cloud connectivity was elucidated through block diagrams, and the decision tree function was detailed using flowcharts. The successful system implementation and results were showcased. For data analytics, Microsoft Power BI software was selected for its user- friendly interface. The connection between Google Sheet and Power BI was outlined in a block diagram, and step-by-step instructions for observing data analytics results were provided through flowcharts. The Power BI results and dashboards were presented in the system implementation section, emphasizing the comprehensive approach taken in this project. [ABSTRACT FROM AUTHOR]

The presented study focuses on the development and integration of a smart fertilizing system, comprising data collection, cloud connectivity, AGV Wi-Fi vehicle, fertilizer mechanism, and data analytics. This chapter provides a detailed explanation of the integrated system, featuring prototype designs and circuit diagrams for enhanced comprehension. The circuit diagram delineates two key sections: plantation monitoring devices and smart fertilizing vehicles, elucidating activity sequences through block diagrams and flowcharts. Comprehensive testing results are presented to demonstrate the system's functionality, aiding in the identification of optimal fertilizing routes for the AGV Wi-Fi vehicle within the plantation. Furthermore, the integrated system is bolstered with cloud connectivity, enabling precise fertilizer dispensing based on nutrient levels in specific areas. This modification ensures comprehensive coverage of nutrient-deficient regions, enhancing the system's efficiency and feasibility in fertilizing all oil palm trees effectively. [ABSTRACT FROM AUTHOR]

This paper aims to develop a smart solution for powering operations in palm oil plantations without traditional power sources. Batteries step in due to the absence of electrical outlets, managed by an Arduino Uno. Various sensors and devices draw power from these batteries. To tackle battery life concerns, a battery management approach is explored, investigating different battery types and power-saving methods like sleep down modes. Research involves into power bank compatibility with Arduino and strategies to minimize sensor power usage. Rechargeable batteries like power banks and 9V options are favored over solar. Sleep mode integration, triggered by motion sensors, aids energy efficiency, enhancing battery life. [ABSTRACT FROM AUTHOR]

This research focuses on palm fruit harvesting using data from Internet of Things (IoT) technologies. Alternatives to relying on error, one can might consider using sensors for tracking. However, advanced sensors can be expensive. Therefore, we are considering cheaper options with simplified sensors. One form detects movement, while the other detects pressure. These choices could simplify fruit counting without spending much. Our research involves past studies, understanding parts, and how they connect. [ABSTRACT FROM AUTHOR]

The effective use of modern technology is proving useful when compared to contemporary agricultural practices observed in areas such as Southeast Asia and the Middle East. This study investigates the palm oil business in Malaysia, an important contributor to the nation's economy, which must deal with a challenge faced by the Red Palm Weevil (RPW). The timely detection of Red Palm Weevil (RPW) infections has a major effect, and this study investigates a device that utilizes an accelerometer to detect vibrations induced by RPW. The results indicate that the above-mentioned strategy is effective in detecting RPW difficulties at an early stage, therefore delivering a lot of help to the farming industry and other related fields. [ABSTRACT FROM AUTHOR]

The purpose of these investigations is to help palm oil farms in determining when their produce is ready for harvest. For large farms, this is a major issue because it is laborious to manually separate ripe from unripe fruit. During its training phase, the sophisticated system they used (called YOLOv5n) performed excellently. Testing carried out in real time demonstrated its ability to distinguish between ripe and unripe palm oil fruits from a reasonable distance. The study also investigates other approaches people are taking using technology like micro controllers and cameras with advanced features to reach this objective. This system functions as a helpful tool, allowing farms to save both time and money. Comparable to an innovative fruit picker. [ABSTRACT FROM AUTHOR]

This research proposes an automated sensory system that uses the Blynk IoT platform to monitor the production of palm tree oil. The system incorporates temperature, humidity, and soil moisture sensors to gather vital environmental data. The Blynk platform receives this data wirelessly, allowing for real-time analysis and visualization. Using this approach gives palm tree growers the ability to maximize fertilizer and irrigation, improving the quantity and quality of their oil. This technology is beneficial for effective plantation management because of the Blynk platform's user-friendly interface and the expanding role of IoT in agriculture. [ABSTRACT FROM AUTHOR]

This research introduces a user-friendly AI system designed to improve palm oil plantations. The system monitors the plantation's environment using sensors and provides helpful recommendations for irrigation schedules, pest control, and tree health. By analysing historical data and weather conditions, the AI system can predict future trends and guide decision-making. The main purpose is to increase efficiency, productivity, and cost-effectiveness for a thriving and sustainable palm oil plantation. [ABSTRACT FROM AUTHOR]

The integration of Internet of Things (IoT) technology into a palm fruit ripeness detection system is the focus of this part of the paper. IoT's remote control and monitoring capabilities are pivotal for sensor-driven setups. In the palm oil industry, where conventional fruit ripeness assessment methods are inefficient, IoT emerges as a solution. Notably, platforms like Blynk and technologies like LoRaWAN are instrumental. Blynk facilitates streamlined device connectivity and management, while LoRaWAN's extensive coverage suits large agricultural areas. A practical prototype integrating Arduino and Node MCU ESP8266 showcases IoT's potential in optimizing agricultural practices. [ABSTRACT FROM AUTHOR]

This study focuses on using a special sensor to figure out if palm fruits are ready to be picked. Usually, people look at the color of the fruits or count how many have come loose from the tree to know if they're ripe. But because there aren't enough workers, sometimes the fruits become too ripe before they're picked. So, this study suggests using a color sensor to check the fruit's color and decide if it's ready. Other research like "Segregation of oil palm fruit ripeness using color sensor" (2022) used a color sensor and a small computer to sort ripe and not ripe palm fruits. Similarly, "Application of Colour Sensor in the Determination of Tomato Fruit Ripeness" (2019) made a tool to sort ripe and not ripe tomatoes using a color sensor and a small motor. "Information System Prototyping of Strawberry Maturity Stages" (2020) used a color sensor and a small computer to find out if strawberries are ripe and showed results on a webpage. This research could help palm oil farms work better by using color sensors to decide if fruits are ripe. [ABSTRACT FROM AUTHOR]

This paper investigates the global use of palm oil, particularly in Malaysia and Indonesia. The palm oil industry faces losses due to a lack of workers causing delays in harvesting fresh fruit bunches (FFBs). To address this, a device is developed using falling fruits to gauge their ripeness. The literature review explores factors contributing to oil losses and how FFB ripeness impacts oil quality. It also examines mechanical fruit harvesting. The process of selecting materials and components for the prototype is explained. The prototype's implementation involves fixing it to palm trees to catch falling fruits. In conclusion, this research offers a solution to the problem of labour shortage-related losses in the palm oil industry by utilizing falling fruits to determine ripeness, potentially benefiting the industry's productivity and financial stability. [ABSTRACT FROM AUTHOR]

The research described in this paper outlines the comprehensive development process of a system spanning five key sections: data collection and transmission, cloud connectivity, AGV Wi-Fi vehicle, fertilizing mechanism, and data analytics. The investigation involved the careful selection of tools and techniques for each section, with a focus on NodeMCU ESP8266 as the microcontroller for data collection and transmission, utilizing various sensors. Google Sheet was chosen as the cloud service provider due to its suitability for the project, and a detailed comparison of platform advantages was provided. The workflow of the WIFI controlled vehicle and cloud connectivity was elucidated through block diagrams and flowcharts. The system implementation successfully integrated Google Sheet with Microsoft Power BI for data analytics, leveraging its user-friendly interface. The connection setup between Google Sheet and Power BI was illustrated, and a step-by-step guide for interpreting data analytics results was presented. The paper concludes by showcasing the implemented system and displaying the Power BI dashboard, demonstrating the practical application of the developed solution. [ABSTRACT FROM AUTHOR]

The farming industry has an important part in Malaysia's economy, making a substantial contribution to its gross domestic product (GDP) and contributing as a major source of employment for a significant section of the general population. However, the life expectancy of oil palm trees, which are necessary for the cultivation and extraction of palm oil, could be reduced due to insufficient soil conditions. A real-time smart agriculture system was developed with the aim of helping farmers. The system utilizes sensors and Wi-Fi connectivity to gather and transmit data regarding soil conditions to a cloud-based platform which can be accessed through an application for smartphones. This technology provides farmers with accurate data at all times, therefore enhancing their decision-making capabilities and expanding oil palm profitability. The research being investigated shows the possibility of larger implementation in the field of the agriculture industry. [ABSTRACT FROM AUTHOR]

The primary purpose of this study is to examine the impacts of different chemical characteristics and substance quality of water collected from Karani Mitta Lake (ground water) to innovative drinking standards water. The samples were collected at Karani Mitta Lake. The samples were analysed using chemical criteria for drinking and irrigation water quality standards samples 18 (Group 1= 18), and the computation was done using G-power 0.8 with alpha and beta values of 0.05, 0.2 with a 95% confidence range. The significant p-value is less than 0.05, i.e. p=0.048. There is no obvious difference. The Novel Standards drinking water analysis uses a high number of samples (N=18) to determine the quality of water. The quality of water of Stream water of pH, BOD, COD, Hardness, Alkalinity, Acidity, Dissolved Oxygen, Turbidity are 7.80, 1.81, 138.71, 87.07, 19.6, 7.11, 7.741, 21.52 and the novel standard drinking water of pH, BOD, COD, Hardness, Alkalinity, Acidity, Dissolved Oxygen, Turbidity are 7.5, 1.25, 100, 55, 8.5, 7.5, 7.2, 25. The novel Irrigation water Standards are 7.5, 2.2, 220, 65, 45, 7.2, 8, 25. G-power 0.05 is used in the calculation, with alpha and beta values of 0.05 and 0.02 respectively. The SPSS carried out has a significance of 0.048 (p<0.05). This shows that there is a statistically significant difference between the two groups considered in this study. Karani Mitta drinking water standards contribute to continuous growth by making this water suitable for agriculture, however treatment is necessary for drinking. Karani Mitta Lake (ground water) for drinking and water system regulations, polluted water must be treated using a number of methods, including organic and chemical treatment. [ABSTRACT FROM AUTHOR]

Clays are weak and have little capacity and they are often stabilized by adding stabilizing substances called additives. Using pond ash to stabilize soil has recently reduced environmental pollution and provided financial gains. The purpose of this work is to use compaction tests to conduct a comparative analysis of the effects of innovative stabilizers derived from industrial wastes, such as class C pond ashes and lime kiln dust, on the geotechnical properties of high-plasticity clay. Two teams of soil samples undergo compaction testing to examine the changes in their compaction characteristics (Cluster 1: soil without pond ash cluster N=16; Cluster 2: soil with pond ash cluster N=16). G power value accuracy of 95%. The study analysed two distinct categories of soil samples: Group 1, comprising no pond ash, and Group 2, containing 5% pond ash. Soil group 2 was prepared by incorporating five percent pond debris by dry weight into the soil. The mean value (1.414, 1.211), standard deviation (0.157, 0.12956), and mean standard error (0.03925, 0.03939) were obtained using group statistics using SPSS version 26. The results indicate that the maximum dry density (MDD) decreased, and the optimal moisture content (OMC) rose with increasing pond ash concentration. Furthermore, optimum moisture content (OMC) increased and maximum dry density (MDD) decreased when pond ash–up to 25%–was added. As compared to compaction characteristics, the geotechnical properties of the soil samples with class C pond ash were shown to be more effective. [ABSTRACT FROM AUTHOR]

The goal of this research study was to fill in the information gaps about the specifically bauxite mineral, in lateritic mineral pockets, which are particularly where laterites, bauxites, and associated clays are generated, as well as there are many sorts of articles that affect laterites and bauxites. In this study, the laterite and bauxite deposits in the Kolhapur and Raigad district of Maharashtra are investigated. The Sentinel 2A satellite from ESA Copernicus produced the data that was utilised in this investigation, which was then altered in the specified locations using SNAP 9.0. Western Maharashtra's laterites and bauxites are found as a crown over through the metasediments of the Deccan fold, which occupy a large area. Shahuwadi Taluk's laterites and bauxites are examples of high-level deposits that are found at altitudes higher than 1000m. At this instance, the spectral properties of lateritic bauxite were used to investigate the spectral signatures of specimens of lateritic bauxite using GIS software (Sentinel 2A). The spectral signature of Sentinel 2A and core resolution were adopted for this analysis, and it used the VNIR-SWIR (visible-near-infrared and short-wave infrared) domain to detect vegetative spectral signatures. After implementing the formulae in SNAP 9.0, pixel values of the images were employed based on these variances. The image was further processed after being uploaded to SNAP 9.0, and then output in the form of band ratio of band 11 and band 12 images was produced. Extensive subaerial weathering of rocks produces lateral bauxite. Gibbsite, Boehmite, and Diaspore are specific aluminium-hydroxide minerals that are particularly enriched in this rock. Bauxite is classed as lateritic, karstic, or tikhvin type according to its geological discoveries, and lateritic bauxite reserves constitute around 86% of the world's reserves. Bauxite deposits are mapped along the studied region using the SNAP 9.0 methodology, and the distribution of bauxite deposits were superimposed over the spectral band of various spectrums in the research region. The magnitude of the bauxite mineral resources is indicated by the pictorial illustration of the existence of bauxite. Both the minerals presented were 95% accurate in terms of minerals, with no significant difference of 0.076. To execute quantitative forecasting information and to contrast the lateritic conception data and Modified/ Novel lateritic formulae facts of pixel values, the Statistical Package for the Social Sciences (SPSS) version 26 was used. The generated result shows that the SPSS value calculated is more than that of p mentioned as per the criterion i.e. 0.076 and thus claims that Sentinel 2A has no significant difference with the data calculated using lateritic index formulae after compared with novel lateritic index. [ABSTRACT FROM AUTHOR]

The main goal of this investigation is to enhance the precision of crop forecasting by transitioning from the Adaboost method to Naive Bayes analysis. The current inadequacy in food production and forecasting is attributed to anthropogenic climate change, resulting in low supply. This has significant adverse effects on farmers' economic conditions due to poor yield and the challenges associated with predicting future crops. This research initiative aims to assist novice farmers by leveraging machine learning to recommend suitable crops. The approach involves aggregating information on crop seeds along with specific requirements for optimal growth, encompassing nitrogen and phosphorus levels, temperature, humidity, pH, and rainfall. Statistical analysis, employing a t-test for independent samples with a significance level of 0.001 (p<0.05), G-power of 0.8, mean, and standard deviation, was conducted on data collected from diverse sources. In this experiment, a total of 20 samples were gathered and divided into two groups of 10 each. Group 1 utilized the Innovative Naive Bayes technique, while Group 2 employed the Adaboost methodology. The data analysis revealed that the Naïve Bayes Algorithm exhibited high accuracy (99.39%) compared to the Adaboost algorithm (79.45%) with a significance level of the independent sample t-test at 0.001 (p<0.05). This suggests that the Gaussian Naive Bayes algorithm is more accurate in predicting crop outcomes than the Adaboost algorithm. Key terms associated with this study include Crop Prediction, Crops, Adaboost Algorithm, Innovative Naive Bayes Algorithm, Machine Learning, Crop Yield Forecasting, and Maize. [ABSTRACT FROM AUTHOR]

The study's objective is to discover innovative antiviral medications that prevent phosphoprotein when SwissDock software is used to analyze viral infections with the greatest fatality rates, such as Rabies. The clincalc.com was used to calculate sample sizes G power was set at 80%. In this investigation, 10 various drugs (N=10) in total, along with a reference drug, were chosen to determine each drug's ability to bind to and inhibit the viral protein. A reference drug was used to compare results. Three-dimensional structures of ten antiviral drugs were found in the Protein Data Bank (PDB) chemical database, along with the three-dimensional structure of phosphoprotein. SwissDock was used to perform molecular docking of antiviral drugs with phosphoprotein. The software algorithm generates outputs by leveraging the similar shapes of biomolecules. SwissDock analysis indicates that 10 novel antiviral drugs bind with the phosphoprotein. Among these drugs, the novel antiviral drug Zanamivir exhibited a p-value of p=0.001 (p<0.05) in an independent sample t-test. This suggests that the full fitness data demonstrated a statistically significant difference between Zanamivir and the reference drug. It was found that the tested medicine Zanamivir interacted more strongly with the viral phosphoprotein; as a result, it was determined that this medication may effectively reduce the phosphoprotein and be used to treat rabies virus infections. [ABSTRACT FROM AUTHOR]

The primary objective of research work is to compare power consumption of a single-edge trigger FF and a double-edge trigger FF in a CMOS technology model with twenty transistors. There are two groups involved in the research: Two groups were formed, one using a double-edge trigger FF design and the other using a novel single-edge trigger FF design ten participants were drawn from each group. A G power of 80% is used to calculate the expected sample size. The built-in FF is used for a range of length values. Using the GDI approach, the length's value ranges from 30 to 90 nm. A novel FF with a single-edge trigger uses 0.5350 watts of power, while a double-edge trigger FF uses 4.7980 watts. The results indicate a statistically significant difference (p=0.000; t-test for independent samples, p<0.05) between the Double Edge Triggering FF(DETFF) and the innovative Single Edge Triggering FF(SETFF). In terms of power consumption, innovative SETFF performs noticeably better than the DETFF. [ABSTRACT FROM AUTHOR]

This study utilizes molecular docking techniques to identify optimal ligands for stabilizing the FTO protein mutant using the Autodock Vina algorithm. The mutant R316Q 3D structure of human FTO was obtained from RCSB PDB and UniProt. Missense mutations with predicted the impact of FTO in deleterious structural effects were sourced from the SNP database and respective mutagenesis of these mutations was conducted by SPDBV server. Ligand structures were retrieved from PubChem, and molecular docking was performed using Pyrx with Autodock Vina. The R316Q mutant was found to exhibit significant effects associated with poly malformation syndrome. The study identified promising ligands that bind to the protein's active sites and deleterious mutations in FTO. Future directions include molecular simulations and in vivo studies to potentially develop a drug for poly malformation syndrome. [ABSTRACT FROM AUTHOR]

The purpose of this study is to create highly functional silicon-substituted hydroxyapatite and characterization using Fourier transform infrared spectroscopy (FTIR). It was synthesized by wet chemical precipitation method. Chemicals including calcium nitrate tetrahydrate (Ca(NO3)2·4H2O), silicon nitride (Si₃N₄), diammonium hydrogen phosphate ((NH4)2HPO4), and ammonium hydroxide (NH4OH) solution were used in this study. The data were analyzed for silicon-substituted samples (N=4). FTIR was used to characterize the resulting Si-HAp nanoparticles, and the SPSS software was employed to implement the FTIR method. The results revealed minor chemical variations in peak values for 1%, 5%, and 10% silicon incorporation in hydroxyapatite. The statistical analysis showed a p-value of 0.002 (p<0.05), but the weight of silicon in hydroxyapatite did not yield significance, with a p-value of 0.177 (p<0.05). The comparative analysis indicates that 10% silicon substitution in hydroxyapatite demonstrates superior properties compared to other substitution levels. The findings suggest that hydroxyapatite with 10% silicon substitution showed improved properties than other substitution levels, making it a promising candidate for bone regeneration, enhancing structural integrity, and dental implantation applications. [ABSTRACT FROM AUTHOR]

The main objective of the research is to decolorize reactive dye aqueous solution by electro fenton process and compare it with the conventional Fenton process. We used a reactor and two electrodes to analyse the many elements involved in the electro-Fenton method of removing reactive brown dye. For the method, both the conventional fenton process, which uses H2O2 and ferrous sulphate as catalyst, and the Novel Electro Fenton Process with electrodes were used. Two groups were used for this review, totaling 32 samples, each comprising a total of 16 samples. Pretest power is determined using 80%, an alpha value of 0.05, and respective 95% confidence intervals. The independent sample T-test was performed using SPSS software, version 22. Electro fenton procedure with reactive brown dye in aqueous solution has a mean colour removal rate of 68.80%, whereas traditional fenton process with receive brown dye in aqueous solution has a mean colour removal rate of 44.50%. The SPSS carried out has a statistical significance of 0.000 (p<0.05). This demonstrates that the two approaches taken into account in this analysis have a statistically significant difference. The standard deviation values are 1.36551 and 1.43479 then, standard error is 0.34138 and 0.35870 respectively. Novel electro fenton process has the most colour removal than Conventional fenton process within the constraints of this study. [ABSTRACT FROM AUTHOR]

The scope of the research is to compare conventional concrete and the 10% Novel E-waste replaced concrete material of M30 grade concrete. The composition of various items present in concrete mix are segregated with Novel E-waste 20mm, superplasticizer, cement (53 grade PPC), fine aggregate (sieve size 4.75mm), coarse aggregate (sieve size 20mm), and water. In this research the main set of events are grouped in two categories. Group-1 (control group/conventional concrete) and group-2 (experimental group/Novel E-waste concrete). In this project first group has 18 samples and the Second group has 18 samples, Total samples of N=36 The analysis was performed with a G-power of 0.8, alpha and beta values set at 0.05 and 0.2 respectively, and a 95% confidence interval. The independent sample T-Test yielded a value of (p>0.05), specifically (p=0.256). The One-way ANOVA conducted using SPSS confirmed differences in the mechanical properties between conventional concrete and Novel E-waste Concrete. The average compressive strength for conventional concrete was found to be (31.12 N/mm2), while for Novel E-waste concrete it was (34.15 N/mm2). A significant difference was noted with a significance value of (p<0.05), precisely (p=0.000), and standard deviations of 0.65 and 0.79, respectively. It was determined that Novel E-waste concrete, when mixed with a superplasticizer, exhibited a lower compressive strength percentage compared to conventional concrete. [ABSTRACT FROM AUTHOR]

This research is to compare traditional concrete with lightweight concrete, which involves blending M30 Grade of Concrete and substituting some coarse aggregate with pumice aggregate. This involved replacing 50% of cement, fine aggregate, and coarse aggregate with silica fume and 10% with metakaolin by weight. Fine aggregate was replaced with M-Sand, while pumice served as the coarse aggregate. An independent t-test was conducted using 80% G-power, comparing two groups: conventional and lightweight concrete. Thirty-six cubes were cast, with 18 each for conventional and lightweight concrete, sized at 150 mm x 150 mm x 150 mm. After 28 days of curing, compressive strength was measured using testing equipment. The study found a statistically significant difference in compressive strength between the two groups, with a P-value<0.000. The group statistics for the sample with 50% silica fume and 10% metakaolin, along with novel pumice stone as coarse aggregate, showed mean values of 34.3311 and 43.8550, standard deviations of 1.65492 and 0.78011, and standard errors of 0.39007 and 0.18387, respectively. The mean compressive strength of controlled concrete is 34.33 N/mm², while for the modified concrete, it was 37.65 N/mm², representing an increase of 8.81% over conventional concrete. This indicates that the concrete incorporating pumice stone, silica fume, and metakaolin performs better and has greater impact than conventional concrete. [ABSTRACT FROM AUTHOR]

The scope of this research is about the removal of turbidity by comparing the Novel Oleifera moringa Seed and Strychnos Potatorum seed as a natural coagulant for cheyur lake water.: The novel Oleifera moringa Seed and Strychnos Potatorum seed are used as coagulants to remove turbidity of lake water. Two groups are considered. Group 1 seed is novel Oleifera moringa and group 2 seed is Strychnos Potatorum. Each group has 16 samples. Total sample of N=32. The pretest g power is determined with 80% and with alpha value of 0.05 and confidence intervals are 95% respectively. The lake water having turbidity level is 33.8 NTU before coagulation-flocculation process was done. When the process is done, turbidity removal percentage of novel Oleifera moringa seed is 81.83% and Strychnos Potatorum seed is 75.05% respectively. The SPSS carried out has a significance of p=0.000 (p<0.05). This shows that there is a statistical significant difference between the two methods considered in this study. The standard deviation values are 2.71105and 2.30924 then, standard error is 0.67776 and 0.57731 respectively. The novel Oleifera moringa seed would perform better turbidity removal than Strychnos Potatorum seed. [ABSTRACT FROM AUTHOR]

Aim: The purpose of this study is to remove turbidity from wastewater by using novel Carica papaya and Hibiscus rosa coagulants. Materials and Methods: Carica papaya and Hibiscus rosa coagulants were used to treat dye wastewater using a coagulation process. The two groups, control (Hibiscus rosa) and experimental (Carica papaya) have 15 samples for each group respectively, and a total of 30 samples. The paired t-test is performed by utilizing G-power of 80%. Turbidity removal is used as a quality index in this study. Results: Carica papaya showed the maximum removal of 67% compared to Hibiscus rosa (59%) coagulant in wastewater treatment. The paired sample t-test on two groups showed that there was a statistically significant difference with p value as 0.001 (p<0.05). Conclusion: From this study, the maximum turbidity removal was achieved by using Carica papaya compared with Hibiscus rosa. [ABSTRACT FROM AUTHOR]

This study aims to compare the thermal efficiency of two types of solar still which use renewable energy for the production of pure water from domestic kitchen wastewater. A Novel Frustum of Square Pyramid Solar Still performance was compared with a standard single slope solar still. The experimental setup or this study included Novel Frustum of Square Pyramid Solar Still as group 1 and standard single slope solar stills as group 2. The stills used were made of GI and acrylic sheets. The active area of both the stills were kept the same. The sample size is calculated as 20 samples per group and a total of 40 samples with 80% of total G power. The results show that the still with frustum of pyramid shape had higher thermal efficiency compared to the still with single slope. The average efficiency of the still with frustum of the pyramid was 22.84% and the average efficiency of the still with single slope was 15.98%. Thus, the still with frustum of the pyramid had an 7.16% higher efficiency. The statistical analysis shows that there exists a statistically significant difference between novel frustum of square pyramid and standard single slope solar still on thermal efficiency with p value p=0.000 (p<0.05). The study concluded that the still with novel frustum of square pyramid shape was more efficient than the still with single slope. The still with frustum of the pyramid had a 7.16% higher efficiency. The higher efficiency of the still can be attributed to the increased surface area exposed to the renewable energy sunlight, which allowed for better absorption of radiation and more efficient evaporation of water. [ABSTRACT FROM AUTHOR]

To assess water quality standards using a Novel Spatial Analysis approach at the catchment basin level and analyze water pollution while identifying the key pollutant parameters, in order to highlight areas of high pollution risk within the catchment basin. The data were analysed using GIS software while taking into account various chemical factors such as Chemical Oxygen Demand (COD), Total Nitrogen (TN), Total Phosphorus (TP), Nitrate nitrogen (NO3-N), and Nitrite nitrogen (NO2-N). To better understand this, 36 water samples from 16 zones were collected from Karani Mitta Lake Andhra Pradesh, India. To assess the level of water quality, single factor pollution index and comprehensive pollution index approaches have been used, together with the Geographic information system (GIS). A comparison of drinking and irrigation standards was conducted using SPSS software on the mentioned parameters. This illustrates the typical water quality in watersheds that are impacted by different parameters, highlighting the presence of pollutants such as COD, total phosphorus, total nitrogen, and nitrite nitrogen, which exceed standard class III levels at 17, 5.65, 0.140, 0.460, and 0.030, respectively, in mg/L. Drinking water standards are set at lower levels of 10, 1, 0.05, 0.5, 1, and 10 mg/L, while wastewater standards are higher at 20, 2, 0.5, 1, 45, and 20 mg/L. The analysis was conducted with a G-force of 80% and a 95% confidence interval. The SPSS test resulted in a significance value of 0.000 (p<0.05), indicating a significant difference between the two groups compared in this study. The contamination levels within the catchment basin are correlated with a novel spatial analysis technique, which provides valuable information for effective control and treatment strategies to manage contamination in the catchment basin. [ABSTRACT FROM AUTHOR]

Improving the material machining by improving various input conditions promotes the functional stability of the component with high reliability and claims goodwill to the concern. The primary objective of this research is to experimentally examine how much materials can be removed with the help of a CNC turning center with respect to unit time from the material of Aluminum alloy Al-Si12CU by selecting of suitable tool or tool coating. Silicon Insert is conventionally employed (Control group) and WCC-coating on it is proposed (experimental group). A cylindrical bar of Al-Si12CU alloy, with dimensions 50mm in diameter and 20mm long the workpiece. The Control group workpieces (the predicted number of sample machining on workpieces with 80% G power setting was 20 for each group) were machined under the same working conditions with uncoated Silicon nitride inserts whereas the experimental group samples were machined with WCC-coated silicon nitride inserts. The material removal rate (MRR) calculated for machining the Al-Si12CU alloy was according to ASTM standards. The observations of MRR were statistically tested, the average performance by the coated tool was 1.801 mm3/min whereas it was for the uncoated tool 1.624 mm3/min. The probability of error was 0.3% and it was less than 5%. The observations are acceptable, and the proposed tool has significantly high performance in terms of MRR. This suggests that the WCC-coated silicon nitride inserts outperform the uncoated ones in terms of MRR. The findings affirm the effectiveness of the experimental design and highlight the substantial variance between the two groups. In summary, this investigation demonstrates that using WCC-coated silicon nitride inserts leads to a higher MRR when turning Al-Si12CU alloy compared to uncoated silicon nitride inserts. [ABSTRACT FROM AUTHOR]

The present research aims to analyze the combustion characteristics of an diesel engine when fed with a mixture of hydrogen and biodiesel. The primary objective is to ascertain if this fuel mixture may provide a greater heat release rate and identify the ideal combination of pressure for combustion. The fuel composition consists of hydrogen (20%), biodiesel (30%), and diesel (50%). In the experiments, diesel fuel served as the benchmark for comparison. A stationary Kirloskar single cylinder diesel engine, featuring a bore diameter of 87.50 mm and a stroke length of 110mm, was utilized. This engine was connected to an eddy current dynamometer, set to standard parameters for the research. The sample size of 40 was calculated using the G power calculator to achieve an 80% confidence level. Based on the conducted experimental trials, the study focused on the performance of a four-stroke compression engine. Specifically, the trials examined the output of the engine when using a mix blend known as D50H20BD30, which consists of plain diesel fuel. The mean value obtained for this blend was 68.8556. In comparison, the mean value for plain diesel fuel alone was 71.6689. The pressure measurements for plain diesel fuel averaged at 39.9922, whereas for the D50H20BD30 blend, the mean pressure value was 33.7822. Achieving this outcome is expected to lead to a decrease in engine emissions and encourage cleaner fuel combustion. The independent samples t-test revealed a statistically significant p-value of 0.021 (p<0.05), indicating a notable difference between the two groups. This result was obtained with a 95% confidence interval. Statistical significance is seen between the two groups. In comparison to pure diesel, the fuel mix D50H20BD30 of HRR exhibited a modest rise of 2.83%, while the produced fuel blends D50H20BD30 of pressure shown a notable decrease of 6.21%. These findings suggest that these fuel blends have the potential to enhance engine efficiency. A comprehensive understanding of the combustion properties of these fuel mixes is necessary in order to assess their potential significance for climate change mitigation and the reduction of fossil fuel use. [ABSTRACT FROM AUTHOR]

This study examined the performance of a recycled AA6061 alloy that was reinforced with nano MgO ceramic reinforcing particles using the stir casting method and compared it with recycled aluminium alloys. To attain a consistent distribution of reinforcement inside matrix materials, the casting process was employed utilizing a stir casting technique, with a melt temperature of 720°C and a stirring speed of 500 rpm. The samples have been separated into two independent categories, namely the group conducting the experiment and the group acting as a control. The statistical significance between these two groups is assessed through their use of T-test analysis. The observation shows that significance p=0.000 was obtained, which is less than 0.05, indicating that there is statistically significant difference between the two groups. In the context of this investigation, it was observed that the flexural strength of newly developed composites, consisting of recycled AA6061 alloy reinforced with nano-Magnesium oxide, exhibited a notable increase of 28%. This enhancement can be attributed to the amplified surface areas resulting from the interaction between the composite constituents. [ABSTRACT FROM AUTHOR]

To enhance the mechanical characteristics for engineering applications, this work aims to produce a unique bio composite that incorporates natural fiber. At 0, 10, 20, and 30% weight fractions, kenaf fiber (KF) is used to strengthen biopolymer poly-butylene succinate (PBS). An injection molding machine was used to create the polymer composite by adding chopped KFs to the molten PBS. A comparison is made between the prepared composite and plain PBS in terms of their machining characteristics, namely drilling. A control group consisting of unreinforced PBS and an experimental group consisting of PBS with KFs added. There were four groups given consideration. Using the G-Power calculator, three samples were analyzed for each group, each with a probability of 0.05 and a 95% confidence interval. Along with increasing their stiffness and hardness, chopped KFs added to PBS also increase their mechanical strength. Measurements are made of the amount of fiber delamination when a solid carbide tool is drilled in a vertical machining centre. A substantial difference between the groups under consideration is found in the analysis, with a significance level of 0.000 (p<0.05). This indicates that the degree of delamination rises when more KFs are included. Though its mechanical strength is greater, adding KFs to the PBS matrix, under the parameters of this investigation, results in increased delamination because the fibers pull out of the matrix during drilling. [ABSTRACT FROM AUTHOR]

In this study of this research is to improve in accuracy for blast disease in rice crops using K-Nearest Neighbour Algorithm and compared with Random Forest Algorithm. To predict the Rice Blast illness, K-Nearest Neighbour Algorithm and Random Forest in both used, with different training and testing splits. In this case, 169 samples were employed in each of the two groups for an analysis that involved 10 iterations in total. The ClinCalc programme is used as a tool to calculate the setup's correctness for supervised learning. This test's average Gpower is about 80% using G power setting values of 0.05 and 0.80. Novel Supporting Vector Machine and K-Nearest Neighbour's performance at identifying Blast Disease in rice crops will depend on the quality of chosen dataset. The K-Closest Neighbour approach outperforms Random Forest (88.5950%) in terms of both Accuracy and loss, with an Independent Sample T-test of p=0.001 which is considered to be statistically significant. The K-Nearest Neighbour method (88.595%) is more accurate than Random Forest (78.100%) Algorithm. K-Nearest Neighbour can be more effective than Random Forest when dealing with high-dimensional data and when there is a complex relationship between the features and the label for the selected dataset. [ABSTRACT FROM AUTHOR]

This study aimed at finding the influence of MWCNT nanoparticles particles fillers on the quasi-static puncture force of Kevlar/Glass/Kevlar fiber composite, which is weakened by impact force. The investigation involved quasi-static puncture tests on two groups of samples: 20 KGK base composites, without any filler, remaining as control and 20 MWCNT filler samples included, hence forming MWCNT experimental group. The study had Power of 80% and significance level (alpha) of 0.05, from which at least 40 samples were estimated to conduct the investigation. Epoxy resin LY556 in combination with hardener HY951 has been implemented, resulting in the introduction of innovative MWCNT nanoparticles acting as filler that represents a novel experimental set. It was shown in experimental data that the hold-time for composites with and without filler varied conspicuously; the filler was demonstrated by the p-value of 0.000 (significance at p<0.05). The most important figure of all is the 2% of the MWCNT filling in the NGK laminate that appears to be of utmost importance as the addition of MWCNT nanoparticles is believed to increase the punch power of the NGK fibre laminate composites. [ABSTRACT FROM AUTHOR]

This project aims to find the compressive strength of the recycled AA5051 alloy with and without reinforcing novel SiO2 using the stir casting method. Materials and Methods: The reinforcing particles used were novel silicon dioxide with a particle size of less than 50 nm, and the matrix materials used were recycled AA5051 alloys. To achieve consistent reinforcement distribution in matrix materials, it was casted using a stir cast method at a melting temperature of 720°C and a stirring speed of 500 rpm. Two types of samples were prepared using recycled AA5051 alloy (Control Group 1), Silicon dioxide reinforced AA5051 alloy nanocomposite (Experiment Group). Each group had a sample size of 20, with a pre-test power of 80%, a beta of 0.05 %, and a CL of 95%. The compressive strength of the novel silicon dioxide reinforced recycled AA5051 alloy was analyzed and compared with the control group material by using SPSS-V26 software. It was noted and observed that the significance of synthesized nanocomposites p=0.000 (2-tailed) was attained, which is lower than (p<0.05). This indicates that there is a statistical significance obtained between the control and experimental groups. Within the limitations of present study, it was found that there was an upgrade in the compressive strength of novel silicon dioxide reinforced recycled AA5051 alloy composites improved by 69.9% within the study's limitations. [ABSTRACT FROM AUTHOR]

In order to improve microhardness qualities, the article compares the traditional friction welding approach with the innovative hash pattern friction welding of EN 10083 steel. In total, two groups commercial and hash pattern friction welding were used in the study. There are sixteen pieces of work in each category. The dimension of the material is 30 mm in diameter and 60 mm in length. It is then welded by a CNC machine with care, and the micro-Vickers hardness tester is used to specify the microhardness of it. This process has a G power of 80%, and the sample size is calculated using α = 0.05 per set and the total sample size calculated is 32. Time, temperature, frictional force, and spindle speed are taken into consideration for results that have Z-pattern friction welding or commercial friction welding with increased microhardness. Between two groups, there were statistically significant differences since the significant value of p=0.000 (2-tailed), which is less than (P<0.05). The hash pattern friction welding has a 5.6% higher microhardness than standard friction welding (571>539) HV. Because of the increased frictional temperature caused by the pattern in the workpiece, the metallurgical bonding was strong enough to have greater Microhardness. The results of this experiment indicate that, although commercial friction welding has a Vickers hardness of 539 HV at 1400 rpm, 5.5ton, 4mm depth of penetration, and 25 seconds, hash pattern friction welding's hardness of 571 HV. [ABSTRACT FROM AUTHOR]

This work is to evaluate performance of buck-boost converter with a PV array fed innovative Boost converter that is controlled by PI controller in order to increase efficiency. By increasing the voltage gain in sustainable power electronics devices, two distinct converters were examined analytically and through simulation in this study. New boost converters are covered first, followed by a review of conventional buck-boost converter techniques. A total of fourteen efficiency samples were obtained using different duty cycles. There are two sets of these samples, each with seven samples. Group 2 is regarded as a buck-boost converter, while Group 1 is thought to be a new boost converter. G power is assumed to be 0.8. The results show that the buck-boost converter has a mean efficiency of 97.63%, while the novel boost converter has a higher overall mean efficiency of 98.07%. Significant results were observed for the independent sample t test, with a value of 0.029 (p<0.05). The results show that, for the chosen data samples, the novel boost converter that has been proposed has a greater efficiency than the buck-boost converter. This indicates that innovative boost converters outperform boost converters by a significant margin. [ABSTRACT FROM AUTHOR]

The research work is comparative investigation of two elaborate algorithms entitled a novel Evolutionary based Bat Algorithm (EBA) plus a Bat Algorithm (BA) aimed at reducing the power losses in the radial structure through optimal allocation OA in DSTATCOM. Novel Evolutionary gives insight on the Bat Algorithm its utilization for optimal location with the reduced sizing of DSTATCOM under the radial dissemination scheme. The sample predetermined size stands as Gpower software value defining both groups each of 7 sample with total of 14 samples. The G power is estimation for power value of 0.8. Achieved power restoring value of EBA yields regulation power comparative too BA technique. The independent sample t test value 0.003 (p<0.05) stands significant. EBA-based optimization restored power loss reduction (real power loss: 151.9855 KW; reactive power loss: 70.8874 KVAR) than BA-based technique (real power loss: 152.7152 KW; reactive power loss: 71.1048 KVAR). [ABSTRACT FROM AUTHOR]

This study's goal is to manage the voltage gain in the Buck converter by changing the input voltage using a traditional FL controller and a turned fuzzy logic (TFL) controller. TFL control and Fuzzy Logic control are implemented to identify the changes in voltage gain under varying input voltage conditions. In this study, 14 samples were used, and the sample size was determined using the Gpower software for two groups. G power is assumed to be 0.8. According to the results, The Buck Converter in Novel Turned Fuzzy Logic control has a greater gain in the output voltage of 1.5614 V for the selected data than classical analysis, but a lower output voltage gains of 1.4114 V. The uncorrelated population value of 0.0012 (p<0.05) is significant. The simulation results show that utilizing TFL instead of the FL controller implies greater authority over output power across a board range. The MATLAB-Simulink application drives these procedures. [ABSTRACT FROM AUTHOR]

The goal of this work is improvement of output power of three phase rectifier using the novel space vector PWM technique compared with conventional PWM technique by reducing the harmonics. In total 14 samples of output power were taken which are collected from varying voltage. To assess the output power enhancement of the three-phase rectifier with unique space vector PWM approach and standard PWM technique, these samples are sorted into two groups, each having seven samples. G power is assumed to be 0.8. This paper shows that the standard PWM technique has harmonics of 52.59% whereas the unique space vector PWM technique has harmonics of 27.47%. The statistically significant result obtained is 0.000 (p<0.05), which is significant. According to this research, the unique space vector PWM technique greatly outperformed the traditional PWM technique in improving the output power of the three-phase rectifier by lowering harmonics in sustainable power electronics. [ABSTRACT FROM AUTHOR]

The pupose of this paper is to analyze and maximize energy yield of the novel Rooftop Photovoltaic system compared with the Ground-mounted Photovoltaic system by limiting the ohmic wiring loss by using the PVsyst software. For the innovative Rooftop PV system, 12 samples—that is, 12 months of a year—were acquired by running simulations in the programme. The final outcome is the total amount of energy generated annually. To collect 12 more samples for a ground-mounted photovoltaic system, the same procedures are performed. Gpower is taken as 0.8. A new rooftop photovoltaic system generates 3832.0 kWh of electricity, while a ground-mounted photovoltaic system generates 3551.4 kWh. A statistically significant value of 0.026 (p<0.05) has been observed. It has been shown that when compared to ground-mounted PV, the novel rooftop PV technology offers a higher energy output, which improves efficiency. [ABSTRACT FROM AUTHOR]