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Marangoni convective MHD flow of SWCNT and MWCNT nanoliquids due to a disk with solar radiation and irregular heat source /
Physica E : Low-Dimensional Systems And Nanostructures, Vol.94, pp.25-30, ISSN: 1386-9477. -
Marine brown algae (Sargassum wightii) derived 9-hydroxyhexadecanoic acid: A promising inhibitor of ?-amylase and ?-glucosidase with mechanistic insights from molecular docking and its non-target toxicity analysis
Jeopardized glucose hemostasis leads to cronic metaboic disorder like Diabetes mellitus and it is predicted to occur in ?700 million people in the coming 20 years. Our study aims to isolate Palmitic acid (C16H32O3), 9-Hydroxyhexadecanoic acid metabolite from Sargassum wightii to inhibit alpha-amylase and alpha-glucosidase to reduce postprandial hyperglycemia and decline the risk of diabetes. High docking score of palmitic acid with both ?-amylase and ?-glucosidase is observed in in-silico molecular docking analysis, in comparison to commercially available drug acarbose. The three hydrogen bond in palmitic acid interacts with the important amino acids like Arg195, Lys200 and Asp300 in Glide XP docking mode for alpha-amylase. For ?-glucosidase, quantum-polarized ligand docking (QPLD) was used with similar three hydrogen bond interactions. Both docking studies showed significant binding interaction of palmitic acid with ?-amylase (?5.66 and ?5.14 (Kcal/mol)) and with ?-glucosidase (?4.52 and ?3.51(Kcal/mol)) with respect to the standard, acarbose docking score. The bioactive palmitic acid isolated from the brown alga, Sargassum wightii is already seen to inhibit digestive enzyme with non-target property in Artemia nauplii and zebra fish embryos. Further studies are required to investigate its role in in vivo antidiabetic effects due to its non-toxic and digestive enzyme inhibitory properties. It can be recommended in additional pharmaceutical studies to develop novel therapeutics to manage diabetes mellitus. 2023 SAAB -
Marine macrolides as an efficient source of FMS-like tyrosine kinase 3 inhibitors: A comprehensive approach of in silico virtual screening
Marine organisms are a definitive source of antibiotics and kinase inhibitors which provide cues for discovering novel drug leads. Marine macrolides are getting much attraction due to their enzyme inhibitory potential. The present study comprehensively dealt with the virtual screening and structure-based prediction of macrolide compounds against FMS-like tyrosine kinase 3 receptors (FLT3). The FLT3 was chosen as a biological target against the 990 marine macrolides. Before the virtual screening of macrolide compounds, validation of molecular docking was carried out by re-docking of co-crystallized Gilteritinib within the FLT3. Among the selected 990 candidates of marine macrolides, 311 were failed due to the generation of insufficient conformers. Amongst the successful compounds, 22 compounds were also failed to dock within the receptor, while the remaining 657 marine macrolide entities elicited successful docking. The HYBRID Chemguass4 Score ranged from -10.17 to -0.02. This vast difference in the HYBRID ChemGuass4 score is attributed to the difference in binding potential with the receptor's binding pocket. The top ten compounds were selected based on the HYBRID ChemGuass4 Score lower than -8.0 against FLT3. The pharmacokinetics and ADME properties revealed the drug likeliness of the macrolides. 2022 SAAB -
Marital Stress and Domestic Violence during the COVID- 19 Pandemic
Marital stress and domestic violence is prevalent in every society around the world. It has become a major concern during the Covid-19 pandemic. Governments have resorted to lockdown measures in order to contain the pandemic. The pandemic has made the weaker and more vulnerable people in a household more exposed to abusive partners. Social isolation and home confinement have detrimental effects on ones mental and physical well-being. Women have been shown to be at a very high risk from violence during The Covid19 pandemic. The research paper aims to understand the factors which compel women to stay in abusive and stressful marriages and the ways in which they can be empowered to lead their life with dignity and self-respect. The cultural contexts of most societies force women to stay in abusive marriages as the woman is often portrayed as the symbol of unity in families. Understanding the cultural bindings of women trapped in abusive households during the COVID-19 pandemic is a very crucial aspect as this can help in understanding the fear and apprehensions of women trapped in destructive marriages. This can be a key factor which can make it easier for support groups while providing counselling and other kinds of support to women trapped in abusive marriages. The paper also discusses the impact of abusive relationships on children and how it negatively shapes their personality and their emotional well- being. 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Market Openness and Price Volatility: Evidence from Major Cash Crops of India
JIM Quest: Journal of Management and Technology, Vol-8 (2), pp. 01-10. ISSN-0975-6280 -
Market Reaction to Dividend Announcements During Pandemic: An Event Study
This study analyses the difference in stock market reactions to dividend announcement during the pandemic. The thirty constituent stocks of Sensex, the index of Bombay Stock Exchange (BSE), is used for analysis. This allows cross-industry comparison of the market reaction. The study examines stock market reactions covering 44 days around the dividend announcement dates. The primary objective of this study is to understand whether the price adjustment linked to the dividend announcement news during the pandemic was different from the earlier years. This empirical study employs the conventional event study methodology using abnormal returns (ARs) to examine the stock market reaction to dividend announcement. The market reaction to dividend announcement was increasingly positive during the pandemic, compared to previous years. The statistical pooled t-tests showed there was a significant relationship between the pandemic and ARs. The findings also indicate that the difference in the market reaction to dividend announcement was more prominent in services stocks than that in manufacturing. Further, the results also verify the weak-form of efficiency of Indian stock exchange. 2021 Management Development Institute. -
Marketing odyssey for a digitally native brand: a case study of Sunbird Straws
Research methodology: The case study incorporated a combination of primary and secondary data collection approach. The authors interviewed Dr Varghese, the co-founder of Sunbird Straws and the protagonist in this case study. In addition, secondary data was obtained from various sources such as newspaper articles, journal publications and company reports. Case overview/synopsis: On a rosy and vibrant morning in 2017, Dr Saji Varghese, a professor at Christ University in Bangalore, stumbled upon a curved coconut leaf on the campus resembling a straw. This sparked his motivation to transform coconut leaves into a natural straw, prompting him to initiate experiments with coconut leaves in his kitchen. The process of boiling and straining leaves became his method for crafting an eco-friendly straw. After numerous attempts, he successfully produced straws from coconut leaves, introducing a distinctive and creative concept incubated at IIM Bangalore. These unique straws, crafted by Varghese, prioritised environmental friendliness and were also crafted entirely from biodegradable materials, free from harmful chemicals. These straws demonstrated durability in hot and cold beverages for up to 3 h, maintaining their integrity without becoming soggy or leaking. As the business flourished, it reached a critical juncture. The primary challenge centred around product marketing, mainly due to consumer unfamiliarity with such sustainable straws. This was a product that also fell under the category of low involvement for consumers. Raising awareness about the product and persuading consumers to purchase presented a significant hurdle. In response, Varghese assigned his team to develop cost-effective marketing strategies. Given the start-up nature of the business, advertising budgets were constrained, and the objective was to achieve a positive return on advertising spend for every investment in advertising the product. In addition, the focus was on increasing the likelihood of selling the straws on both business-to-business and business-to-consumer levels. In this case study, Vargheses role and predicament exemplify the delicate equilibrium that entrepreneurs frequently grapple with, striking a balance between marketing strategy and return on ad spent to steer the trajectory of their businesses. It offered a valuable examination of the nuanced decisions marketers encounter as they strive for both profitability and customer-centric products. Complexity academic level: The case study is relevant to the marketing discipline. All undergraduate and postgraduate-level marketing courses in higher education institutions can use this case study. It can also be used in integrated marketing communication or digital marketing classes. It can be used further in the hospitality and management fields. Also, online courses in marketing can include this case study. 2024, Emerald Publishing Limited. -
Markov based genetic algorithm (M-GA): To mine frequent sub components from molecular structures
Processing the molecular compounds to identify the internal chemical structure is a challenging task in bio-chemical research. Popular approaches, mine the frequent subcomponents from the molecules with chemical and biological properties represented in the form of feature vector histogram. Though this helps to identify the absence or presence of mined feature, calculating the frequency of every frequent substructure involves sub graph isomorphism test which is an NP-Complete process. To overcome the above mentioned bottleneck we proposed Markov based Genetic algorithm (M-GA) in which the chemical descriptors were considered from two-dimensional representations of molecules that classify chemical compounds using mining significant substructure and generates the binary vector that generate pure active classes, singleton reactors, descriptor sets. This method scales down the process of mining substructures that are statistically significant from huge chemical databases. The results shows that the performance of proposed algorithm is improved compared to the existing algorithms. 2020, Research Trend. All rights reserved. -
Mass layoffs at BYJUS founders dilemma
Learning outcomes: This case study provides students/managers an opportunity to learn about the following: to infer the challenges involved in the downsizing of employees; to asses and evaluate BYJUS organizational culture; and to determine the impact of workplace toxicity. Case overview/synopsis: The focus of this case is the controversy faced by BYJUS due to its mass layoffs and toxic work culture. This case discusses the CEOs dilemma in resolving the controversy. Two rounds of mass layoffs at BYJUS are discussed in detail. The industrial dispute filed by Employees Union against BYJUS accusing it of denying due compensation to laid-off employees is also discussed. This case consists of a section explaining the toxic work culture at BYJUS, which is supported by employee complaints. The CEOs justification and apology have been illustrated in this case. The case ends with a closing dilemma and challenges faced by the CEO. Complexity academic level: The case is best suited for undergraduate students studying Human Resources Management subjects in Commerce and Business Management streams. The authors suggest that the instructor inform students to read the case before attending the 90-min session. It can be executed in the classroom after discussing the theoretical concepts. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 6: Human Resource Management. 2024, Emerald Publishing Limited. -
Masstige scale: An alternative to measure brand equity
Masstige marketing is a strategic word for market penetration for premium but reachable products based on brand equity, trying to develop brand awareness, likability, affection and attachment. Hence, masstige scale may allow firms to measure brand equity to derive insights into the popularity of their brands. However, there is no empirical evidence available to test whether these scales are related measures of brand equity and, at the same time, independent measures, respectively. This study investigates whether the masstige scale and multidimensional consumer-based brand equity scale measure the same constructs. A total of 493 participants evaluated four different athletic shoe brands. The multi-trait, multimethod and confirmatory factor analyses suggested that the masstige scale may be a viable alternative to consumer-based brand equity and masstige value. We discuss the implications and provide directions for future research derived from our findings. 2022 John Wiley & Sons Ltd. -
Mathematical analysis of histogram equalization techniques for medical image enhancement: a tutorial from the perspective of data loss
This tutorial demonstrates a novel mathematical analysis of histogram equalization techniques and its application in medical image enhancement. In this paper, conventional Global Histogram Equalization (GHE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Histogram Specification (HS) and Brightness Preserving Dynamic Histogram Equalization (BPDHE) are re-investigated by a novel mathematical analysis. All these HE methods are widely employed by researchers in image processing and medical image diagnosis domain, however, this has been observed that these HE methods have significant limitation of data loss. In this paper, a mathematical proof is given that any kind of Histogram Equalization method is inevitable of data loss, because any HE method is a non-linear method. All these Histogram Equalization methods are implemented on two different datasets, they are, brain tumor MRI image dataset and colorectal cancer H and E-stained histopathology image dataset. Pearson Correlation Coefficient (PCC) and Structural Similarity Index Matrix (SSIM) both are found in the range of 0.6-0.95 for overall all HE methods. Moreover, those results are compared with Reinhard method which is a linear contrast enhancement method. The experimental results suggest that Reinhard method outperformed any HE methods for medical image enhancement. Furthermore, a popular CNN model VGG-16 is implemented, on the MRI dataset in order to prove that there is a direct correlation between less accuracy and data loss. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Mathematical approach for impact of media awareness on measles disease
During the recent pandemic caused by COVID-19, media awareness played a crucial role in educating people about social distancing, wearing masks, quarantine, vaccination, and medication. Media awareness brought individual behavioral changes among the people, which in turn helped reduce the infection rate. Motivated by this, we have formulated a mathematical model introducing a media compartment to mitigate measles disease transmission. In this paper, the SEIR model is used to study measles disease in three cases: one with a delay in vaccination, the second with regular vaccination, and the third with the impact of media awareness on the spreading of measles disease. Further, the dynamical behavior of the models is studied in terms of positivity, boundedness, equilibrium, and basic reproduction number (BRN). The sensitivity analysis of the models is conducted, which verifies the importance of the BRN ((Formula presented.)) to be less than one for disease eradication. The numerical study confirms the impact of media awareness on exposed and infected populations. 2023 John Wiley & Sons Ltd. -
Mathematical foundations based statistical modeling of software source code for software system evolution
Source code is the heart of the software systems; it holds a wealth of knowledge that can be tapped for intelligent software systems and leverage the possibilities of reuse of the software. In this work, exploration revolves around making use of the pattern hidden in various software development processes and artifacts. This module is part of the smart requirements management system that is intended to be built. This system will have multiple modules to make the software requirements management phase more secure from vulnerabilities. Some of the critical challenges bothering the software development community are discussed. The background of Machine Learning approaches and their application in software development practices are explored. Some of the work done around modeling the source code and approaches used for vulnerabilities understanding in software systems are reviewed. Program representation is explored to understand some of the principles that would help in understanding the subject well. Further deeper dive into source code modeling possibilities are explored. Machine learning best practices are explored inline with the software source code modeling. 2022 the Author(s), licensee AIMS Press. -
Mathematical model for effective CO2 emission control with forest biomass using fractional operator
The emission of CO2 is the foremost culprit for global warming and is also considered a significant greenhouse gas. Due to the human populations tremendous growth and activities, the rate of CO2 in the atmosphere has increased. To mitigate the emission of CO2 there are artificial ways. But, naturally have a natural resource called "Forest Biomass," one of the significant sinks to absorb CO2 during photosynthesis. Considering all these factors, the main objective of the current investigation is to understand and illustrate the importance of forest biomass in the emission of CO2. The proposed nonlinear model consists of four variables: atmospheric CO2, human population, energy sectors, and forest biomass. We have studied the model both qualitatively and quantitatively, which will help us make future predictions. To study the model in depth, we have formed a fractional-order model to study the systems behavior at different ranges of fractional orders. The model is termed with the Caputo fractional operator. Boundness and Lyapunov stability for non-linear and fractional order models are studied, and equilibrium points, existence and uniqueness, and numerical simulation are examined. The Adams-Bashforth-Moulton method illustrates the essence of the systems numerical method. The numerical approach reveals that the altered models stability is unchanged. Also, we have examined the model by changing the parameter values to different fractional orders to understand the systems behavior, and the changes are captured as figures. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
MATHEMATICAL MODEL OF NICKEL-GRAPHENE COMPOSITE INKS FOR JETTING PROPERTIES IN INKJET PRINTING
The droplet formation process in inkjet printing is studied numerically and verified through a simulation model. The droplet formation process decides the printing quality of the coating, and a mathematical model is developed to understand the complete process from droplet formation to detachment. The Navier-Stokes equation is used to mathematically derive the droplet radius (rnumerical). COMSOL multiphysics is used for simulation and the radius (rsimulation) is calculated from the droplet mass. The rnumerical and rsimulation are compared for inks containing nickel, graphene, and nickel-graphene composite ink it is observed that the composite ink radiuses have the lowest difference (rsimulation - rnumerical = 0.085 m). A droplet is formed at 1.47 mm from the nozzle inlet, for nickel-graphene ink, and after 1.5mm for other pristine inks. The results are verified through Z number, velocity profile, and droplet mass. The droplet formation observed from the velocity profile is earliest at 120 s. It is seen that a stable droplet is generated at 100s for nickel-graphene ink and at 200 s for individual inks. 2024 Faculty of Science, Universiti Malaya. All rights reserved. -
Mathematical Modeling for Evaluating the Mechanical Properties of High Strength Concrete with Natural Zeolite and Additives
The cement manufacturing industry is a major contributor to atmospheric pollution, primarily due to carbon dioxide emissions. Consequently, there is a pressing need to develop eco-friendly concrete capable of mitigating air pollution by sequestering atmospheric carbon dioxide. In this context, the incorporation of Natural Zeolite in concrete has been investigated, as it can absorb environmental carbon dioxide. This study explored the effects of partial cement replacement with Natural Zeolite (5%) and varying percentages of Silica Fume, Metakaolin, and Fly Ash (5%, 10%, and 15%) on the mechanical properties and carbon sequestration potential of High Strength Concrete (HSC). Comprehensive testing was conducted to evaluate the split tensile, compressive, and flexural strengths of the modified HSC. Experimental results indicated that the addition of Natural Zeolite and Metakaolin enhanced the strength of HSC, with Mix 3 displaying a higher 90-day compressive strength compared to the reference mix. The findings suggest that incorporating Natural Zeolite and other supplementary cementitious materials in concrete has the potential to alleviate environmental pollution. The dataset, comprising 900 samples, exhibited no autocorrelation or multicollinearity issues, making it suitable for multiple regression analysis. The statistically significant regression models developed in this study can effectively predict concrete strength. (2023). All Rights Reserved. -
Mathematical Modeling of Concrete Fracture Energy of Notched Specimens Using Experimental Evidence
The tensile stiffness of concrete is an important parameter for crack initiation. The microcrack initiation and propagation regulate the stressstrain behavior and the failure mode of concrete. Therefore, fundamental awareness of the fracture mechanism in terms of fracture energy is a requisite to comprehend concrete behavior. There is research consensus that fracture energy alone does not suffice to characterize the ductility/brittleness and also the size dependency of concrete. Therefore, it is necessary to evaluate the fracture energy and the characteristic length for a realistic assessment of the fracture behavior of concrete. Towards this objective, this study examined the fracture energy of concrete by experimentation, and the fracture energy proposed by various models in the literature. Further, the characteristic length proposed by Hillerborg which depicted both the material influence and the size effect, has been computed. Based on the RILEM50 FM recommendations, 18 specimens with varying grades of concrete and notch depths have been tested and the fracture energy parameters have been evaluated. Also, two regression models with key fracture parameters as variables for two-notch ratios, have been formulated for the concrete fracture energy. The arguments have been supported by experimental evidence. The Author(s), under exclusive licence to Shiraz University 2024. -
Mathematical modeling to investigate the influence of vaccination and booster doses on the spread of Omicron
The emergence of new variants, such as Omicron, has raised concerns regarding the transmission dynamics of COVID-19 and the effectiveness of vaccination strategies. This paper proposes a mathematical model to investigate the impact of vaccination and booster doses on Omicron transmission dynamics, considering various infection compartments. The model incorporates multiple compartments representing different stages of infection, including susceptible individuals, vaccinated individuals, boosted individuals, and those infected with Omicron. The infection dynamics are captured by parameters such as vaccine efficacy, vaccination with booster received efficacy, and infection rate. Using mathematical analysis and numerical simulations, we explore how different vaccination and booster strategies affect the spread of Omicron. The normalized sensitivity analysis method of R0 is investigated to understand the importance of parameters in disease transmission. Furthermore, we assess the influence of infection compartments, such as asymptomatic and symptomatic cases, on overall transmission dynamics. 2023 Elsevier B.V. -
Mathematics as an agent of dialogue in the society
Though Mathematics is mostly considered as a subject of the intelligent, it is used by everybody for daily activities. It acts as an efficient agent of dialogue in the society. Its role in transferring abstract knowledge to concrete experience, in interpreting the unknown and as a tool for problem-solving are discussed in this paper. Mathematics also helps human beings to transcend from concrete experience to abstract knowledge. This paper showcases various elements of Mathematics over a wide spectrum, from those useful in everyday life of human beings to the discussions on potential and actual infinity. Mathematics is an integral part of human life and an essential tool in knowing the universe. We do not deliberately side with any of the schools in Mathematics or that of Philosophy. 2017 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore). -
Mathematics Self-Efficacy, Utility Value and Well-Being Among School Students in India: Mediating Role of Student Engagement
Teaching and learning mathematics has many challenges, including student engagement, attitudes and beliefs toward mathematics. Students experience stress and anxiety while learning mathematics. Mathematics is perceived as a complex subject. Student self-efficacy and a sense of utility value of mathematics topics can impact student learning and well-being. The current study aims to examine the mediating role of student engagement on the relationship between mathematics self-efficacy, utility value and well-being among students. A cross-sectional survey of 774 eighth-grade students (491 male and 283 female) from India was carried out using standardized scales to measure the study variables. The mediation analysis tested two conceptual models. The findings indicate that student engagement mediates the relationship between self-efficacy and student well-being (model 1), and student engagement mediates the relationship between utility value and student well-being (model 2). The structural equation model results indicate an acceptable fit of the tested conceptual models. The study findings call for focusing on socio-emotional aspects of mathematics learning to improve the well-being of students. 2023 Research Council on Mathematics Learning.