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Abstract Alcohol-based fuels have shown high compatibility with spark-ignition (SI) engines, which require improvements in fuel efficiency and emissions reduction to meet modern environmental standards. While extensive research has been conducted on ethanol and other lower-order alcohols, there has been comparatively limited investigation into higher-order alcohols like butanol and pentanol as fuel alternatives. Previous studies on pentanol-gasoline blends in SI engines have demonstrated improved engine performance and reduced emissions. Building on this, the present study focuses on analyzing the flame characteristics—specifically speed and distribution—of pentanol-gasoline blends within the engine. In this study, pentanol was blended with gasoline by the volume of 10%, 20%, and 30%, namely 1-PNL10, 1-PNL20, and 1-PNL30, and tested in a twin-cylinder gasoline engine with an MPFI system at various load conditions. The study has focused on investigating the flame propagation of gasoline-pentanol blends by examining the in-cylinder flame image. The in-cylinder combustion evolution was visualized and captured by using an AVL Visio scope camera. Flame characteristics such as spatial flame distribution and flame speed were evaluated from the captured flame images for pentanol–gasoline blends and compared with sole gasoline. The flame study indicates that the addition of pentanol favored to increase in the flame speed, which in turn improved the combustion rate. The flame intensity and distribution area increased with the addition of pentanol in gasoline, demonstrating improved in-cylinder combustion with increased peak in-cylinder pressure and heat release rate. The insights on the flame characteristics of pentanol–gasoline blends were used to rationalize the discussion on engine performance and emissions. The performance of the engine was enhanced while increasing the proportion of Pentanol in the gasoline. The 30% Pentanol gasoline blend showed 5.71% higher BTE than gasoline at full load condition. Emissions like CO and HC also decreased at the same time, and NO emission increased. From the test results, it can be concluded that Pentanol can be blended with gasoline up to 30% without any engine modifications.

Special functions and special polynomials have been used and studied widely in the context of Geometric function theory of Complex Analysis by the many authors. Here, in our present investigations, making use of the convolution, we first introduce a new subclass of Bazilevivč bi-univalent functions involving the Bernoulli Polynomials. We then find the first two Taylor-Maclaurin coefficient [Formula: see text] and [Formula: see text] for our defined functions class. We then calculate the bounds for the Fekete Szegö inequality for the defined function class. Also some known consequences of our main results are highlighted in the form of Corollaries.

Abstract This study explored the recovery of oil from lemon peel biomass and then tested it in a spark ignition as a substitute for gasoline. The study adopted the micro-arc oxidation coating technique, intending to improve the engine performance of the lemon peel oil-gasoline blends. The oil was recovered from discarded lemon peel biomass using steam distillation and then tested in the engine as a fuel by blending it with gasoline at volume ratios of 10, 20, and 30%. An endoscopic visualization approach was employed in this research work to assess the combustion initiation and flame characteristics of gasoline and lemon peel oil blends under different test conditions. Compared to gasoline and blends comprising 20 and 30% lemon peel oil, the 10% lemon peel oil mix produced higher thermal efficiency and lower emissions. The optical analysis demonstrated that premixed combustion with the 10% blend was found to be the highest, resulting in improved combustion and subsequently increased cylinder pressure. To improve the engine performance of the lemon peel oil blends with higher substitution (20 and 30%), the piston was coated with a ceramic coating. A novel technique, namely the micro-arc oxidation technique, was utilized for the coating. The coated piston engine fueled with a 20% lemon peel oil blend showed a 3% and 4.69% increase in thermal efficiency compared to the uncoated piston fueled with a 20% blend and sole gasoline, respectively. The hydrocarbon and carbon monoxide emissions of the engine with a coated piston fueled by the 20% lemon peel oil blend were reduced by 12.7% and 12%, respectively, as compared to gasoline operation in the engine with an uncoated piston.

Background and aim: Phytoformulation therapy is a pioneering strategy for the treatment of metabolic disorders and related diseases. The aim of the present study was to investigate the protective effect of a phytoformulation consisting of hydroxycitric acid and capsaicin against obesity-related cardiomyopathy. Experimental procedure: Sprague-Dawley rats were fed HFD for 21 weeks, and phytoformulation (100 mg/kg body weight) was administered orally for 45 days starting at week 16. Results and conclusion: We found that HFD supplementation resulted in significant hyperglycemia and caused an increase in cardiac lipid deposition, inflammation and apoptosis in the heart. Phytoformulation therapy not only significantly decreased blood levels of glucose, cholesterol, triglycerides, free fatty acids, and inflammatory cytokines in obese rats, but also protected cardiac tissue, as shown by histological analysis. Conversely, phytoformulation therapy decreased mRNA levels for sterol regulatory element-binding factor 1, fatty acid synthase, acetyl-CoA carboxylase, and fatty acid binding protein 1 genes involved in fatty acid synthesis and absorption in obese rats. It increased the levels of lysosomal acid lipase, hormone-sensitive lipase, and lipoprotein lipase genes involved in fatty acid degradation in the heart. In addition, the phytoformulation improved cardiac inflammation and apoptosis by downregulating the genes nuclear factor kappa-light-chain enhancer of activated B cells (NF-kB), tumour necrosis factor α, interleukin-6, toll-like receptor-4 (TLR-4), BCL2-associated X and caspase-3. In conclusion, our results show that the phytoformulation improved insulin sensitivity and attenuated myocardial lipid accumulation, inflammation, and apoptosis in the heart of HFD-induced obese rats by regulating fatty acid metabolism genes and downregulating NF-kB/TLR-4/caspase-3.

This paper introduces a novel subclass, denoted as Tσq,s(μ1;ν1,κ,x), of Te-univalent functions utilizing Bernoulli polynomials. The study investigates this subclass, establishing initial coefficient bounds for |a2|, |a3|, and the Fekete-Szegö inequality, namely |a3−ζa22|, are derived for this class. Additionally, several corollaries are provided to further elucidate the implications of the findings.

The power system is mainly affected by transient situations caused by switching heavy loads. The system may become unstable when transient situations occur. The power system should be able to perform continuous operation to maintain its voltage within acceptable limits. To achieve more stability and increase its speed of response, an Automatic Voltage Regulator (AVR) system requires the inclusion of a controller. The AVR system in the generating station uses the PID controller to adjust the abnormal voltage caused by transient conditions. To maintain the nominal voltage level under all the load conditions in the system, a bio-inspired meta-heuristic algorithm called Artificial Rabbit Optimization (ARO) algorithm is proposed to tune the PID controller gain parameters and obtain the optimal gain, thereby the AVR system adjusts the generator terminal voltage to nominal levels. The ARO algorithm inspires natural survival techniques to improve the AVR performance by reducing errors. To maintain a stable voltage profile in a power system, this research mathematically models survival techniques using the Internet of Things (IoT) to obtain an optimal solution. As a result, all devices connected to the power network receive a stable voltage that ensures their voltage reliability. The effectiveness of the proposed algorithm for the AVR system is verified with the MATLAB R2022a model, and the statistics functions are implemented in the module of Pandas, Scipy and mathematical investigations done in Numpy. The proposed ARO algorithm achieves a better voltage profile with less than 12.63% maximum peak overshoot during the system's transient response. The proposed algorithm provides the fastest response and highest stability comparable to other optimisation algorithms.

Many problems are associated with dynamic changes in the power system, mainly because the number of switching loads has increased. These loads induce ineffective system behaviour, reduce the system voltage profile, and lead to improper voltage regulation. The proposed Automatic Voltage Regulator (AVR) system is intended to eliminate the above problem and preserve the system voltage at the generator terminal within the allowable range. In this work, Proportional-Integral-Derivative (PID) controllers are applied to enhance the dynamic behaviour of the AVR system. The Zebra Optimization Algorithm (ZOA) and Osprey Optimization Algorithm (OOA) algorithms are implemented to optimize the system's transient response by modifying the gain of PID controller parameters, which include proportional, integral, and derivative parameters, to preserve a stable voltage profile. To achieve an optimal solution, the mathematical model of the proposed system is realized in the Internet of Things (IoT). The connected loads in the system can operate at the nominal voltage level through PID controller tuning using ZOA and OOA. The proposed system's performance is evaluated and verified with MATLAB R2023a. ZOA showed an improvement of 18.5 % with a peak overshoot of 0.01 % during the system-transient condition. Compared to conventional optimization algorithms implemented in AVR systems, ZOA provides faster responsiveness and enhanced system stability.

Abstract Cloud Computing, the efficiency of task scheduling is proportional to the effectiveness of users. The improved scheduling efficiency algorithm (also known as the improved Wild Horse Optimization, or IWHO) is proposed to address the problems of lengthy scheduling time, high-cost consumption, and high virtual machine load in cloud computing task scheduling. First, a cloud computing task scheduling and distribution model is built, with time, cost, and virtual machines as the primary factors. Second, a feasible plan for each whale individual corresponding to cloud computing task scheduling is to find the best whale individual, which is the best feasible plan; to better find the optimal individual, we use the inertial weight strategy for the Improved whale optimization algorithm to improve the local search ability and effectively prevent the algorithm from reaching premature convergence. To deliver services and access to shared resources, Cloud Computing (CC) employs a cloud service provider (CSP). In a CC context, task scheduling has a significant impact on resource utilization and overall system performance. It is a Nondeterministic Polynomial (NP)-hard problem that is solved using metaheuristic optimization techniques to improve the effectiveness of job scheduling in a CC environment. This incentive is used in this study to provide the Improved Wild Horse Optimization with Levy Flight Algorithm for Task Scheduling in cloud computing (IWHOLF-TSC) approach, which is an improved wild horse optimization with levy flight algorithm for cloud task scheduling. Task scheduling can be addressed in the cloud computing environment by utilizing some form of symmetry, which can achieve better resource optimization, such as load balancing and energy efficiency. The proposed IWHOLF-TSC technique constructs a multi-objective fitness function by reducing Makespan and maximizing resource utilization in the CC platform. The IWHOLF-TSC technique proposed combines the wild horse optimization (WHO) algorithm and the Levy flight theory (LF). The WHO algorithm is inspired by the social behaviours of wild horses. The IWHOLF-TSC approach's performance can be validated, and the results evaluated using a variety of methods. The simulation results revealed that the IWHOLF-TSC technique outperformed others in a variety of situations.

Objective: To determine how biochanin-A (BCA) affects high-fat diet and streptozotocin-induced pathological changes in lipid metabolism and antioxidant status in diabetic rats. Methods: Diabetic rats were orally administered BCA (10 mg/kg body weight) for 30 days to investigate its effects on lipid profiles and oxidative stress markers in the liver and kidney. In addition, the mRNA expression of antioxidant and lipid metabolism enzymes in the liver was examined. Results: BCA attenuated hyperlipidemia by regulating mRNA expressions of HMG-CoA reductase, fatty acid synthase, carnitine palmitoyl transferase, and acetyl-CoA carboxylase. Additionally, BCA reduced high-fat diet and streptozotocin-induced oxidative stress by suppressing lipid peroxidation, improving superoxide dismutase, catalase, and glutathione peroxidase levels, and upregulating mRNA expressions of these enzymes. Conclusions: BCA may be a promising nutraceutical for the treatment of dyslipidemia and oxidative stress associated with diabetes.

The application of electrode heating is proposed in electrochemical micromachining (EMM). In the EMM process, the temperature of the electrode, voltage, duty cycle, and electrolyte concentration are considered process parameters. Taguchi L18 mixed-level orthogonal array (OA) design was adopted for designing the experiments and this study highlights the effect of temperature on responses such as radial overcut (ROC), material removal rate (MRR), and conicity factor (CF). In addition, multicriterion design making (MCDM) with VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje, i.e., multi-criteria optimization and compromise solution) technique is used for finding the best alternatives based on the distinct weight assessing methods such as equal weights method (EWM), analytic hierarchy process (AHP), and entropy-based weights method (EBWM). Furthermore, a confirmation test is also conducted to find the best optimal parameters and their levels among the EWM-VIKOR, AHP-VIKOR, and EBWM-VIKOR. The results revealed that AHP-VIKOR provides a maximum improvement of 0.945 among the three methods.

Integration technique is becoming effective due to the world’s largest power requirement, which has imposed a considerable need for various techniques by which electricity can be generated or integrated, as well as the assumption that integrating solar energy into nonrenewable source materials is essential to minimize the relative to nonresource consumption and thus reduces fossil fuel consumption. Photovoltaic (PV) systems are at the forefront of this transformation, harnessing the sun’s renewable electricity and converting this from DC to AC. Controlling the power grid utilizes power system photovoltaic energy production and the many ramifications of grid-scale PV energy module integration into energy systems. To completely integrate photovoltaic (PV) processes into a network, cost-effective and efficient technologies of energy storage must be used in conjunction with smart energy management systems. Electrical energy storage system (EESS) could have been used to improve a system’s stability and the performance, to recent technology improvements and quick efficiency improvements. This research provides an understanding of EESS for the photovoltaic system as well as a complete evaluation of the developing penetration level of PV. As the worldwide photovoltaic solar market is expanding, growing onsite use of PV-generated energy would become increasingly critical to ensure the stability of the grid. This research study was the first one to provide such a comprehensive overview of all forms of energy storage devices which can be used in conjunction with PV, including both thermal and electrical energy storage systems. Finally, a simulation of optimization planning is executed. The result reveals that lowering peak loads and lowering electricity usage lowers the price of electricity.

AA6262 and AA5456 alloys are welded through friction stir weld (FSW) with process parameters of tool speed of 1200 rpm, welding speed of 25 mm/min, and tool angle of 3 degree. A cylindrical shape HSS-13 tool is used to perform the welding process To improve mechanical properties of tensile strength (TS), yield strength (YS), elongation%, hardness, and wear behavior, postweld heat treatment was conducted on the FSW sample at different temperatures from 300°C to 500°C. The influence of heat treatment (HT) changes the material characteristics. It is observed that the maximum TS (209 MPa) and YS (178 MPa) are identified when maintaining temperature 350°C on the FSW sample. The reduction in elongation of as-welded joints is entirely improved by HT, and the elongation percentage is almost increased to 5% when increasing temperature on the heat treatment process, and hardness test results exhibited that the increased hardness value (120Hv) is found at HT-300°C nugget zone distance of 0 to 5 mm range.

Outlier detection in multivariate dataset is not quite trivial when compared to univariate. The tediousness in multivariate outlier is due to presence of swamping and masking effect which portrays an ideal sample point as outlier instead of true one. To overcome all this problems, robust techniques can be applied instead of classical outlier detection methods because the latter fails to find out the correct outlier. This paper enumerates various techniques like Mahalanobis, Cook’s, Leverage points, DFFITS, minimum volume ellipsoid (MVE) and minimum covariance determinant (MCD) for detection of outliers or anomalies in multivariate space and best will be identified. Researchers can use that technique to identify outliers before going for analysis, as this will assist in significant results.

Electrochemical machining is a nonconventional machining process in which the metal removal is achieved by the electricity and chemical solution known as an electrolyte. It is the reverse electrolysis process where the application of electricity facilitates the current travel in between anode and cathode. The mechanism of the ion movement is similar to the electrolysis process. Electrochemical machining (ECM) is a type of advanced machining process which employs electricity to perform the machining process on the workpiece. It is also known as a reverse electroplating process where metal removal is achieved instead of metal deposition on the metal surface. There are various parameters that affect the metal removal process in the ECM process, such as electrolyte, power supply, workpiece material, and tool material. The electrolyte is one of the key factors impacting the machining rate, surface finish, and reliability of the produced parts. In this project, a brief study is carried out regarding the electrochemical process and the electrolytes where the properties, functions, merits, and demerits are evaluated. The impact of the various electrolytes and their suitability for machining of various metals is also discussed. The findings of the effect produced by using the mixture of the electrolyte in the electrochemical machining process are discussed in this project. The effects of the complexing agents on the electrolyte and the electrochemical process as a whole are also reviewed.

The regulations of legislative bodies regarding the recycling and reusage of automotive materials has caused a great deal of obligation among automotive manufacturers to use natural fibres or green composites. Green composites or more commonly known as bio-composites are made up of natural fibres. Natural fibres are used by humankind since prehistoric times. The natural fibre is obtained from plants as well as animals. Since the natural fibre is obtained from natural as well as biological resources, it is biodegradable and recyclable. This paper presents the study and analysis conducted to address the suitability of natural fibre in the automotive industry. This paper discusses the finite element analysis of four different natural fibre composites used for making car door panel, i.e., flax, jute, sisal, and leather are taken for the material study. This paper helps to find the effectiveness of each of the four natural fibre composites that have already been used in the automotive sector. This paper includes the analysis of four different natural fibres with and without the addition of the aluminium as the reinforcement material. This project revolves around the design of the composite fibre sheet and analysis of the mechanical parameters such as equivalent stress, shear stress, strain, deformation, and so on. The studies and observations of the analysis showed that the natural fibre with the aluminium reinforcement proved to be much stronger than that without the reinforcement. The results of finite element analysis showcased lowest total deformation and equivalent strain in the flax as 1.026 m and 0.017 mm/mm, respectively. However, sisal showed the lowest equivalent stress and shear stress which were 68.09 and 38.178 MPa, respectively. Additionally, leather showed the highest amount of stress, strain, and deformation, and hence leather was deemed to have undesirable properties regarding the usage in car door panels. All the materials except leather were found to be safe under the loading conditions. Hence, the flax fibre is recommended by the project to have superior properties compared to the other materials.

The aim of the present study is to recycle and reuse the WEO as an alternative fuel for compression ignition (CI) engine. For this purpose the WEO was cracked in the catalytic fuel reformer by using the catalyst zeolite 4A. The output of the catalytic fuel reformer is in the gaseous form which is condensed using water cooled condenser. The oil obtained after condensing the reformulated gas is named as WEOZ. To know the suitability of using the WEOZ as alternate fuel for IC engines, the different properties of WEOZ were determined. The different properties include specific gravity, kinematic viscosity, flash and fire point, gross calorific value, pour point, density. The properties of WEOZ were compared to that of diesel fuel. All the fuel properties are closer to that of the neat diesel fuel. The FTIR analysis was also be conducted for diesel and WEOZ. The result of FTIR analysis was compared to that of diesel fuel. The FTIR result revealed that the major transmittance spectrums peak for diesel and WEOZ were alkanes and the presence of the hydrocarbon was clearly seen in the WEOZ. Based on this investigation, it was suggested that WEOZ has a potential to be used as alternate fuel for diesel engine. Hence an environmentally unfriendly WEO can be recycled into a useful resource and serves as an alternative source of fuel for diesel engine.

This paper reports the results of experimental investigations on the influence of the addition of cerium oxide in nanoparticle form on the major physiochemical properties and the performance of diesel. The fuel is modified by dispersing the catalytic nanoparticle by ultrasonic agitation. The physiochemical properties of sole diesel fuel and modified fuel are tested with ASTM standard procedures. The effects of the additive nanoparticles on the individual fuel properties, the engine performance, and emissions are studied, and the dosing level of the additive is optimized. Cerium oxide acts as an oxygen-donating catalyst and provides oxygen for the oxidation of CO during combustion. The active energy of cerium oxide acts to burn off carbon deposits within the engine cylinder at the wall temperature and prevents the deposition of non-polar compounds on the cylinder wall which results in reduction in HC emission by 56.5%. Furthermore, a low-cost metal oxide coated SCR (selective catalyst reduction), using urea as a reducing agent, along with different types of CC (catalytic converter), has been implemented in the exhaust pipe to reduce NOx. It was observed that a reduction in NOx emission is 50–60%. The tests revealed that cerium oxide nanoparticles can be used as an additive in diesel to improve complete combustion of the fuel and reduce the exhaust emissions significantly.