Journal of Advanced Applied Scientific Research (JOAASR)
Not a member yet
259 research outputs found
Sort by
Decolorization of textile dye direct yellow 12 using bacteria isolated from soil contaminated with textile industry effluents
Get PDFThis investigation was taken up to study the decolorization of the textile dye, Direct Yellow 12 by making use of free and immobilized bacterial cells isolated from soil contaminated with textile industry effluents. A total of 12 isolates capable of decolorizing Direct yellow 12 were obtained. With screening, 2 isolates namely DY9 and DY 10 were selected for further decolorization studies of the dye. Biochemical characterization of both the isolates was carried and both were tentatively identified as Bacillus species. Optimization of decolorization the dye with respect to various parameters was carried out with one factor at a time approach. The optimum pH for both cultures was found to be 9. A temperature of 37ºC, a Shaking speed of 150 rpm and Bushnell Haas medium supplemented with 100 mg/L Starch and a Dye concentration of 2% were optimum for both cultures. Optimum decolorization with DY9 was obtained with 100 mg/L KNO3 and that with DY10 was with 100 mg/L Yeast extract. A comparative study on the decolorization of Direct Yellow 12 under unoptimized and optimized conditions using both isolates was carried out. The results showed a marked increase in decolorization with both isolates under optimized conditions. The two cultures, individually and as a consortium were immobilized in Calcium alginate. Batch decolorization of the dye using free and immobilized cultures of DY9 and DY10 was carried out. The immobilized cultures showed an increase in decolorization compared to free cells. At a lower dye concentration, the immobilized consortium showed a higher decolorization. However, with increase in concentration of the dye, individual immobilized cultures proved better for decolorization. Repeated batch decolorization was carried out to check the stability of the calcium alginate beads. The current investigation showed that free and immobilized cells of both the isolates could be used in the water and soil bioremediation
Application of derivative maps to Homotopy
Get PDFThe perspective of unification of mathematical concepts of Group Actions and Homotopy have been the bottom line of our study. We exploit this to a higher degree by investigating the derivatives associated with these. Heading in this direction, this paper is about linking the derivative of Homotopy and the derivative of Group Action. Firstly, we verify if the derivative of a Group Action is itself a Group action and whether the derivative of a Homotopy is a Homotopy. For this purpose, we take only special Group Actions and Homotopies restricted to the Euclidean space. We then discuss when the derivative of Group Action is a Homotopy and vice-versa. Thus our aim here is to find if the derivative of a Homotopy can lead to the existence of a related Group Action and the relevant criteria that must be satisfied for such a relation.
This paper also investigates when the derivative of Homotopy between two functions is a Homotopy in addition to being a Group Action as well. The derivative of Group Action and Homotopy are dealt with in an attempt to find if the derivative of Group Action is also a Homotopy. Since the derivative of a special action is also an action, we verify if this action is a Homotopy. Thus we interlink the derivative of the concepts of our study as theorems/propositions. In particular, we obtain conditions for the derivative of a Homotopy to be a Group Action.Summarizing, this paper is about finding the derivative of Group Action and Homotopy if the presence of one leads to the existence of the other and if so when
Effect of xenobiotic compounds on steroidogenesis in humans
Get PDFGonadal steroids are crucial hormones responsible for the proper functioning and growth of the body. The sex hormones are produced in the adrenal glands and gonads by a process called steroidogenesis. Steroidogenesis is an enzymatic reaction where cholesterol gets converted to active steroid hormones in the respective gonads and play a dominant role in determining the primary and secondary characteristics of organisms. Studies has revealed that highly divergent groups of xenobiotic compounds are known to obstruct with steroidogenesis and cause endocrine-disrupting effects. Environmental contaminants such as DDT and PCBs are known to affect steroidogenesis. Chemicals such as azole fungicides and antifungal drugs is known to function as powerful inhibitors of steroidogenic enzymes, resulting in endocrine disruption. With the increasing various hormonal disorders and decreased fertility rate due to stress and improper lifestyle, understanding the role and environmental impact of sex hormones on humans helps to manage and lead a healthy life. This review highlights the biosynthesis, functional mechanism of estrogen, progesterone and testosterone hormones including the effects of its varying levels and the influence of endocrine disrupting compounds (EDCs) on the steroidogenesis process
A COMPARATIVE ANALYSIS OF MACHINE LEARNING ALGORITHMS FOR IPO UNDERPERFORMANCE PREDICTION
Get PDFInitial Public Offerings (IPOs) are a popular way for companies to raise capital and enter the public markets. However, many IPOs underperform and fail to meet the expectations of investors. In this research paper, we explore the use of different machine learning models, namely AdaBoost, Random Forest, Logistic Regression, ANN and SVM, for predicting IPO underperformance. We collect and pre-process a dataset of IPOs from the past few years, and use it to train and evaluate the performance of each model. Our results show that Artificial Neural Network model is better suited for predicting IPO underperformance. Additionally, our analysis provides insights into the factors that contribute to underperformance and highlights the importance of certain features in predicting IPO performance. Our research provides valuable information for investors and financial analysts interested in predicting the performance of IPOs and mitigating the risks associated with IPO investments. We have tested machine learning models, namely AdaBoost, Random Forest, Logistic Regression, ANN and SVM. After Comparing the accuracy of all the models, we arrived at the conclusion that ANN model performed the best with an accuracy of 68.11%
Diabetes Prediction using Decision Tree, Random Forest, Support Vector Machine, K-Nearest Neighbors, Logistic Regression Classifiers
Get PDFOne of the world's deadliest diseases is diabetes. It is an additional creator of different assortments of problems. Ex: Coronary disappointment, Visual impairment, Urinary organ illnesses, and so forth. In such cases, the patients are expected to visit a hospital to get a consultation with doctors and their reports. They must contribute their time and cash every time they visit the hospital. Yet, with the development of AI techniques, we have the adaptability to search out a response to the present problem. We have progressed an advanced framework for handling data that can figure regardless of whether the patient has polygenic sickness. In addition, being able to foresee the onset of the disease is crucial for patients. Data withdrawal has the adaptability to eliminate concealed information from an enormous amount of diabetes-related data. The most important outcomes of this research are the establishment of a theoretical framework that can reliably predict a patient's level of risk for developing diabetes. We have utilized the existing categorization methods such as DT (Decision Tree), RF (Random Forest), SVM (Support vector Machine), LR (Logistic Regression) as well as K-NN (K-Nearest Neighbors) for predicting the severity of Type-II Diabetes patients. We got an accuracy of 99% for the Random Forest, 98.40% for the Decision Tree, 78.54% for Logistic Regression, 77.94% for SVM (Using RBF Kernal SVM), and 77.64% for KNN
Attention deficit and hyperactivity disorder (ADHD): Overview of Gender differences, Genetic, Epigenetic, and Non-genetic aspects
Get PDFAttention deficit and hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Around 2.8% of the adult population is affected by ADHD. There are various factors that contribute to the development of ADHD which can be differentiated based on its mode of transmission. Some factors are manifested through inheritance and some are categorized as epigenetic. However, it is quite challenging to determine a well-described cause that contributes to the development of ADHD. Furthermore, there are significant differences between affected men and women. One of the most noticeable differences being that cognitive flexibility and verbal fluency are the qualities that are more evident in male counterparts, whereas for the female counterparts, working memory and inhibition are the qualities that are prominent. This review focuses on the manifestation of ADHD as well as the epigenetic, genetic, and non-genetic factors influencing it. The review also aims to draw attention to the variations between ADHD-diagnosed men and women. The knowledge of the myriad of factors that influence ADHD could be vital in designing efficient and effective therapeutics against this condition. In addition, the differences between men and women could also be exploited to understand the development of ADHD for improved and personalized remedies
Structural and elastic properties of Strontium doped Phosphate bioactive glasses
Get PDFBioactive glasses are a class of biomaterials which have the potential of becoming suitable candidates for osteogenesis. The glasses made with phosphate as the former have exceptional properties. The functional characteristics are due to the lower values of viscosity and dispersion and higher values of refractive indices. These glasses show high transparency in the range of UV spectrum. Inclusion of oxides first group and second group elements i.e., alkali and alkaline earth metal oxides respectively into the glass network modify the properties and increase the chemical resistance of phosphate glasses. Different compositions of strontium doped phosphate glasses were prepared using melt quench technique. X – Ray Diffraction (XRD) studies were performed in order to confirm the amorphous nature . The effect of adding modifier into the glass matrix was evaluated using FTIR characterization. The elastic parameters like moduli and Poisson’s ratio were calculated using Makishima and Mackenzie model. It was validated that modifiers have a significant impact on glass structure and bioactivity. These glasses are found to be capable in reducing burden on metallic biomaterials for osteogenesis and hence contribute for sustainable environment
Improvement in Electrochemical Performance of Lithium Rich Li2RuO3 Cathode With Co-doping Strategy
Get PDFLithium-rich layered oxides based on Ru are interesting as cathode materials because they have high energy density and reversible capacity. However, due to the problems of weak structural stability and voltage decay, their commercial utility is limited. To address this, we use a DFT+U quantum mechanics to investigate the co-doping strategy on Li2RuO3 (LRO) for improved battery performance. In particular, the effect of two co-dopants Ti and Co has been studied. The co-doping strategy has been found to significantly improve the structural and thermal stability of LRO. By slowing the oxygen removal reaction, Ti and Co improve structural stability. Co-doping with Ti and Co increases the maximum open circuit voltage at least by 5.5% and decreases the voltage reduction by a minimum of 44%. Bandgap is also increased by a minimum of 6% with co-doping. In particular, Li2Ru0.5Ti0.375Co0.125O3 provides the highest maximum voltage of 4.4V with 61% decrease in the voltage reduction and 40% lower bandgap (0.45eV)
Optimization of Heat Treatment parameters to facilitate machining of SAE4340 steel without compromise on Mechanical properties
No full textSAE 4340 is a medium carbon low alloy steel used in many automobile and aircraft applications because of its high strength and toughness. But its machinability is very low and hence this poses difficulty in manufacturing the parts needed for such applications. Machinability of this material can be improved by adopting suitable tool material like CBN or ceramics. But these tool materials are costly and usually need high speed machines like CNC which are suitable mainly for mass production. Moreover, these inserts are brittle and chip off fast especially when intermittent cuts are involved especially in the rough machining of castings in large numbers. For this reason, it is proposed to improve machinability by adopting suitable heat treatment to the steel without considering the type of tool material being used. This will change the basic property and microstructure of the steel to facilitate machining. The inter-critical heat treatment process is suggested wherein the material is heated between the upper and lower critical temperatures followed by water quenching and suitable tempering. To begin with, the material was normalized to 850°C in order to carry out specimen preparation. The specimens were then subjected to quenching at two different temperatures of 770 and 790°C in the inter-critical range after which tempering was carried out at 580°C. Tensile strength of around 1100 N/mm2, impact strength of around 120J and hardness in the range of 35 to 40 HRC were obtained. Machinability tests were carried out on a centre lathe with lathe tool dynamometer set up using a brazed tip tool at low and high speeds giving a depth of cut of 1mm. The cutting forces were in the range of 60 to 70 kg force indicating good machinability. Thus without compromise in mechanical properties, good machinability was attained
Effect of Silver Nanoparticles on the Synthesis of Algal Lipids
Get PDFIn light of the increasing depletion of fossil fuel reserves throughout the world, excessive pollution from greenhouse gases, and a gradual increase in carbon dioxide (CO2) content in the atmosphere as a result of many anthropogenic interventions that have significantly altered the global carbon cycle, renewable energy sources have major future potential. Due to the ability to alter their lipid processes in response to environmental changes, microalgae can be utilized as a replacement since they are versatile enough to thrive in a range of environments and serve as a source of bioenergy. It is also an appealing medium for absorbing the extra CO2 existing in the atmosphere. Water samples with visible algal colonies were collected from different sources in India and isolated on BG11 medium. To boost the lipid yield of the strains, silver nanoparticles prepared from ginger (Zingiber officinale) extracts were added after the specific strains of microalgae had their biomass production assessed. According to morphological analyses, all the isolates were spherical, green in colour, unicellular in structure, and had a range of cell sizes. The highest lipid concentration was identified in the microalgal isolate JUMAC-7 whereas the lowest was found in JUMAC-4 according to research on how silver nanoparticles triggered lipid synthesis. Therefore, the inclusion of silver nanoparticles opens a new paradigm for efficient lipid production and consequent quality biodiesel production