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A Cross-sectional Study for Examining Catastrophic Healthcare Expenditure Across Socio-demographic Variables among Employees in a Sedentary Occupation
Health expenditure above a certain threshold level can result in a financial catastrophe by reducing the expenses on necessities. Certain socio-demographic variables have been observed to play a role in influencing catastrophic healthcare expenditure, guiding the present study to examine this scenario for employees in sedentary occupations. A cross-sectional study has been conducted among 370 employees recruited through a random sampling technique. Multinomial logistic regression was used to test the main objective of the study. The factors associated with a higher probability of catastrophic healthcare expenditure were males with increasing age. Years of work experience tend to be associated with a lower likelihood of catastrophic healthcare expenditure. No conclusive evidence could be drawn for BMI, income, marital status and education. 2024 Indian Journal of Community Medicine. -
Social Media Sentiment Analysis of Stock Market on Tweets
Sentiment categorization is utilized in today's world to analyze social media data about the stock market and estimate its future stock movement. We investigated the possible influence of 'public sentiment' on 'market trends' using sentiment analysis and machine learning concepts. Due to the enormous number of components involved, such as economic situations, political events, and other environmental factors that may affect the stock price, stock price prediction is an exceedingly complicated and challenging process. Because of these considerations, evaluating a single factor's influence on future pricing and trends is challenging. As more individuals spend time online, the popularity and impact of numerous social media platforms has skyrocketed in recent years. Twitter is one such social media tool that has exploded in popularity. Twitter is a terrific place to stay up to speed on current societal trends and perspectives. The 'Twittersphere' is a melting pot that supports diverse viewpoints, emotions, and trends, and it has the potential to be a crucial influencer in influencing and shaping perceptions. 2022 IEEE. -
Predictive Modelling of Heart Disease: Exploring Machine Learning Classification Algorithms
In addressing the critical challenge of early and accurate heart failure diagnosis, this study explores the application of five machine learning models, including XGBoost, Decision Tree, Random Forest, Logistic Regression, and Gaussian Naive Bayes. Employing cross-validation and grid search techniques to enhance generalization, the comparative analysis reveals XGBoost as the standout performer, achieving a remarkable accuracy of 85%. The findings emphasize the significant potential of XGBoost in advancing heart failure diagnosis, paving the way for earlier intervention, and potentially improving patient prognosis. The study suggests that integrating XGBoost into diagnostic processes could represent a valuable and impactful advancement in the realm of heart failure prediction, offering promising avenues for improved healthcare outcomes. 2024 IEEE. -
The digital transformation: Crafting customer engagement strategies for success
In the business world, the digital transformation has ushered in an era of unprecedented change. The explosive growth of digital technology over the past three decades has profoundly changed how businesses operate, compete, and engage with their customers. Businesses across industries have been forced to navigate this constantly changing environment due to the adoption of cloud computing, data analytics, the growth of e-commerce, and the rise of artificial intelligence. Organizations are forced to reconsider their strategies, operations, and consumer engagement models as a result of this significant instability. This chapter discusses the role of artificial intelligence in aiding customised and personalized marketing strategies, acknowledging the diverse preferences and behaviour of consumers. It shares insights on branding and customer management in an AI-driven environment. It also emphasises on online and technology-mediated customer engagement. 2024, IGI Global. All rights reserved. -
Potential health, environmental implication of microplastics: A review on its detection
Microplastic contamination of terrestrial and aquatic environment has gained immense research attention due to their potential ecotoxicity and biomagnification property when enterer into food chain. Heterogenous nature of microplastics coupled with their ability to combine with other emerging pollutants have increased the severity of this crisis. Existing detection methods often fails to accurately quantify the amount of microplastic components present in environmental and biological samples. Thus, a great deal of research gap always exists in our current understanding about microplastics including the limitations in screening, detection and mitigation. This review work presents a comprehensive out look on the impact of microplastics on both terrestrial and aquatic environment. Furthermore, an in-depth discussion on various microplastic detection techniques recently used for microplastic quantification along with their significance and limitations is summarised in this review. The review also elaborates various physical, chemical and biological methods used for the mitigation of microplastics from environmental samples. 2024 Elsevier B.V. -
A generalized software reliability prediction model for module based software incorporating testing effort with cost model
As software innovation has advanced, it has been noted that the testing effort function (TEF) is one of the key factors influencing the improvement of software reliability. This paper presents a simplified model which incorporates the testing effort for the reliability growth of a software. A closed form solution has been derived for the reliability of the software. This study examines the impact of testing efforts on a software reliability model based on NHPP. The sensitivity analysis has been made available to investigate how the created model's system parameters affect the cost function, mean value function, and softwares reliability. The parameters of the model have been estimated using the non-linear least square estimation (MLE) method in MATLAB software. Additionally, a warranty cost model is constructed to assess the optimal release policy for the software. The general form of the reliability expression involves elliptic integrals, which can be computed easily through a software like Mathematica. We have derived analytical solutions for reliability pertaining to several particular cases. Optimal release time for the software product has been calculated for some particular cost-sets. Goodness of fit curves have been plotted to compare the proposed model with some well-known existing SRGMs. Numerical illustrations are provided to bolster the analytical outcomes. The Author(s), under exclusive licence to Society for Reliability and Safety (SRESA) 2024. -
Predictors of Hypertension among Indian Women of Reproductive Age Group: An Analysis from NFHS-5 Data
Introduction: Hypertension among women not only augments the risk of cardiovascular diseases but also leads to antenatal and intra-natal complications. Materials and Methods: A subset of data collected during National Family Health Survey-5, comprising of 7,24,115 women, 1549 years of age was analysed to identify key predictors of hypertension, using Probit Regression Model (PRM) which was run separately for rural and urban women. Results: Overall prevalence of hypertension among women of reproductive age group was 11% (10.4% and 12% in rural and urban areas respectively). 5% and 13.41% of women were obese and 1.2% and 2.6% were diabetic in rural and urban areas respectively. Obese, uneducated, rich women and those on medications showed higher prevalence, while women consuming milk, eggs, chicken, fruits, and vegetables daily showed lower prevalence. On using PRM, significant predictors of hypertension were increasing age, rural residence, pregnancy, increasing weight, diabetes, illiteracy, access to medical insurance, and indulgence in alcohol and smoking. Conclusion: Findings from the study contribute to the body of evidence favouring multifactorial causation. Hypertension awareness should be promoted especially among rural residents, older women, with emphasis on intake of balanced diet with less consumption of sodium and increased intake of fruits and vegetables. 2023 National Journal of Community Medicine. -
Unraveling the synergy between oxygen doping and embedding Fe nanoparticles in gC3N4 towards enhanced photocatalytic rates
With graphitic carbon nitride (gC3N4) showing considerable potential for photocatalytic applications, the four significant limitations: surface area, light-harvesting capability, photogenerated charge separation, and charge transfer at the interface, need to be comprehensively addressed. The present work aims to exfoliate the gC3N4 stacking layers and fragment the layers horizontally to form ultra-thin nanosheets (NS) by a facile mixed-acid treatment. The surface area of gC3N4 increased by one order of magnitude (120 m2/g), due to the formation of nanosheets with planar size below ?50 nm. Moreover, incorporating non-metal (oxygen) anion dopants and metal (iron) nanoparticles enhances the overall reactivity of gC3N4 NS under light irradiation. Co-integration of these strategies led to ?17 times improvement in the photocatalytic pollutants degradation rate compared to pristine gC3N4. First-principles calculations and experimental evidence suggest the formation of an intermediate band within the bandgap of gC3N4, caused by the hybridization of N-Fe-O, which assists in harvesting a larger number of photons. Nanosheet morphology provides a shorter distance to photogenerated charges towards the surface, while the incorporation of Fe and O together offers the lowest charge transfer resistance at the interface to efficiently degrade the adsorbed pollutant molecules on the surface. With all these promoting features along with cost-effective and stable elements, Fe-O-gC3N4 NS provides an ideal solution for tuning the intrinsic morphological and electronic structure of gC3N4 for its effective application in various photocatalytic reactions. 2022 -
Biodegradable blend film derived from polycaprolactone an guar gum blend for packaging application /
Patent Number: 202141012114, Applicant: Sudhakar Y N. -
Automatic fertilizer dispenser robot /
Patent Number: 354319-001, Applicant: Ravikumar R. -
Properties of high strength concrete with reduced amount of Portland cement a case study
In the last 15years Bangalore city has systematically modernized its concrete production process with the help of ready-mix concrete (RMC) facility. However, one of the present requirements of these facilities is to lower its carbon footprint by reducing consumption of Portland cement in the concrete production process. Further, the demand for high-strength concrete (HSC) has increased due to construction of high-rise buildings and other major infrastructure projects in the urban areas of the city. Therefore, this study presents the experimental test results of HSC mixes proportioned with reduced consumption of Portland cement. Four types of concrete mixes with 50% of Portland cement replaced by ground granulated blast furnace slag (GGBS) were considered. Additionally, two control mixes without GGBS replacement were also tested. Fresh, hardened, and durability properties of all the mixes were experimental determined and presented. The results showed that concrete mixes proportioned with 50% GGBS obtained a maximum 28-day compressive strength of 77 MPa. Further, all the mixes with GGBS exhibited superior durability properties when compared to control mixes. Thus, concrete mixes with 50% GGBS replaced for Portland cement are favourable for producing HSC at RMC facilities at Bangalore city. 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Insight into the effects of waste vegetable oil on self-healing behavior of bitumen binder
The application of waste vegetable oil (WVO) in bitumen has been the subject of research for years, however, the self-healing behavior of WVO modified bitumen (WMB) has not been adequately reported. In this research, molecular dynamics (MD) simulations and laboratory experiments were performed to reveal the effects of WVO on the self-healing behavior of bitumen. Models of base bitumen and WMB were constructed. Further, dynamic calculations were carried out for the self-healing models of base bitumen and WMB both with 10 microcracks. The energy properties, conformation and density of bitumen during the self-healing process were analyzed. Meanwhile, the effects of WVO on the fractional free volume (FFV) of bitumen, the distribution of bitumen components and the mobility of bitumen molecules were investigated. Finally, the modified fatigue-healing-fatigue (FHF) test was conducted to verify the effects of WVO on the self-healing efficiency of bitumen. Results show that Van der Waals forces drive the mobility of bitumen molecules. Along with the disappearance of the central microcrack, the density of the self-healing system gradually increases and finally reaches that of the bulk bitumen. WVO with superior mobility capacity increases the FFV of bitumen and converts asphaltene large aggregated structure into small aggregated structure, which facilitates the mobility of the bitumen during the self-healing process. Thus, the addition of WVO contributes to the self-healing efficiency of the bitumen. The modified FHF test also verified that the self-healing efficiency of bitumen is improved with the presence of WVO. These findings provide further insight into the self-healing behaviors of WMB. 2022 -
The flow analysis of Williamson nanofluid considering the Thompson and Troian slip conditions at the boundary
In this article, the impact of Joule heating on the thermal performance of Williamson nanofluid is analyzed under the influence of viscous dissipation along with the Joule heating. Also, the flow is subjected to Thompson and Troian slip conditions that directly influence the velocity of the flow at the boundary. Meanwhile, to achieve the even distribution of nanoparticles in the nanofluid, gyrotactic microorganisms are dispersed whose motion is due to the virtue of density gradient. The heat conduction at the surface is governed by the convective condition which allows the interpretation of the Biot number. The mathematical model is constructed employing these presumptions using partial differential equations, which are then subsequently reduced using similarity transformations to get the ordinary differential equations (ODEs). The RKF-45 numerical approach is used to solve the nonlinear ODE system thus acquired, and the findings are validated by comparing them to the previously published works. The results of this study showed that the higher values of thermophoresis and Brownian motion parameters cause more heat conduction. Also, the rise in the Eckert number that relates to the internal friction enhances the temperature conducted by the nanofluid. Meanwhile, the Lorentz force helps in controlling the flow velocity. 2023 Taylor & Francis Group, LLC. -
Heat transfer simulation of reline flowing in an elliptic shaped duct: A deep eutectic solvent
Deep Eutectic solvents have emerged as promising alternatives to conventional solvents due to their unique properties and applications. The flow of deep eutectic solvents in various industrial processes has garnered significant attention due to their versatile applications in fields ranging from chemical engineering to energy storage. This study presents a comprehensive mathematical model aimed at elucidating the intricate behavior of eutectic solvent flow within an elliptic duct, a geometric configuration relevant to many real-world systems. In this article, the deep eutectic solvent is composed of choline chlorideurea and is also called Reline. The proposed mathematical model accounts for the complex interplay of fluid dynamics, thermodynamics, and elliptic duct geometry. Key components of the model include the Navier-Stokes equations, which describe the fluid flow, coupled with heat transfer equations to account for temperature variations within the system. The model also considers the phase change behavior of the eutectic solvent, which may exhibit solidification or crystallization phenomena under certain conditions. Numerical simulations and analytical solutions are employed to investigate various aspects of eutectic solvent flow within elliptic ducts, such as velocity profiles, pressure distributions, temperature gradients, and phase transition phenomena. The study explores the influence of key parameters, including the Reynolds number, the aspect ratio of the duct, and the thermophysical properties of the eutectic solvent, on the systems behavior. From the results, it was clearly observed that the velocity at the narrow region decreased as the pressure raised and the Reynolds number profile indicated the presence of turbulent flow behavior. 2024 Taylor & Francis Group, LLC. -
Pandemic, War and Geo-Political Risk: The Outlook for Global Economy
This Chapter analyses the world economic outlook in the backdrop of the Pandemic, the Russia-Ukraine war, geo-political tensions, and social unrest emerging around the world. The COVID-19 Pandemic an unwanted gift from the nature spreading across the nations in multiple waves and mutation has devastated the global economy. The governments and central banks responded with huge bailouts to beat the potential recession that led to excess liquidity and demand-pull inflation. The global GDP declined due to multiple lockdowns to contain the spread of the virus. Due to scarcity of inputs, labour and supply chain disruptions the cost of production surged and augmented cost-push inflation. Further, the Russian invasion of Ukraine aggravated the supply-side shocks from sanctions and energy and food inflation surgeda 38-year highto 6.7 percent in advanced economies and 8.7 percent in emerging markets and developing economies creating misery among people particularly in the low-income countries. The running magnitude of inflation complicated the policy efforts, and the central banks and governments reversed the trade-off for inflation from safeguarding the growth. Besides, the social unrest in developed countries (Canada, New Zealand, the US, Austria, the Netherland) and developing countries (Chile, Algeria, Iran, Iraq, Lebanon, Brazil, Belarus, Sri Lanka, Ethiopia, Burkina Faso, Tajikistan, and Sudan) have added the geo-political tensions (China and Taiwan) worsening the world economic outlook. The first section of this chapter narrates the COVID-19 pandemic impact (loss of lives and livelihood), leading to declining trends in global GDP, income, employment and international trade, and increasing trends in poverty, unemployment, inequality and inflation. The second section analyses the impact of the Russian invasion of Ukraine and social unrest gathering around the world leading to geo-political tensions, supply-side shocks and inflation trending to a level not seen in the last four decades. The policy efforts reversed to monetary tightening and increasing the interest rates causing capital outflows, currency depreciation and foreign exchange reserve meltdown. Developing countries with limited fiscal space to counteract are prone to prolonged stagflation (inflation plus unemployment) and skewflation risk (product prices rising but asset prices falling). In the near-term, the global economy is facing an extremely challenging outlook due to sharply rising food, fertilizer and energy prices, and rising interest rates, capital outflows, currency depreciation and unsustainable levels of external debt. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
A weighted-Weibull distribution: Properties and applications
The paper describes a two parameter model and its relationship to the widely used Weibull model. Mathematical properties of the distribution like survival and hazard functions, moments, harmonic and geometric means, Shannon entropy and mean residual life are derived. Different methods of estimation are discussed and a simulation study is performed to verify the efficiency of estimation methods. Applications of our distribution in different scenarios observed in real life areillustrated. 2023 John Wiley & Sons Ltd. -
Post-Operative Brain MRI Resection Cavity Segmentation Model and Follow-Up Treatment Assistance
Post-operative brain magnetic resonance imaging (MRI) segmentation is inherently challenging due to the diverse patterns in brain tissue, which makes it difficult to accurately identify resected areas. Therefore, there is a crucial need for a precise segmentation model. Due to the scarcity of post-operative brain MRI scans, it is not feasible to use complex models that require a large amount of training data. This paper introduces an innovative approach for accurately segmenting and quantifying post-operative brain resection cavities in MRI scans. The proposed model, named Attention-Enhanced VGG-U-Net, integrates VGG16 initial weights in the encoder section and incorporates a self-attention module in the decoder, offering improved accuracy for postoperative brain MRI segmentation. The attention mechanism enhances its accuracy by concentrating on a specific area of interest. The VGG16 model is comparatively lightweight, has pre-trained weights, and allows the model to extract incredibly detailed information from the input. The model is trained on publicly available post-operative brain MRI data and achieved a Dice coefficient value of 0.893. The model is then assessed using a clinical dataset of postoperative brain MRIs. The model facilitates the quantification of the resected regions and enables comparisons with each brain region based on pre-operative images. The capabilities of the model assist radiologists in evaluating surgical success and directing follow-up procedures. 2024 by the authors of this article. -
Pre and Post Operative Brain Tumor Segmentation and Classification for Prolonged Survival
The aim of this research was to provide a detailed overview of the techniques in detecting and segmenting meningioma brain tumor in pre- and post-operative MRI images and classify for presence of meningioma thereby giving an early diagnosis to decrease the death rate. This study examines trending techniques for brain tumour segmentation and classification in Magnetic Resonance (MR) images of pre and post-surgery. For the segmentation and anomalies in the brain categorization, several approaches such as regular machine learning techniques (K-mean bunching, Fuzzy C mean grouping etc.), Deep Learning-based approaches (CNN, ResNET, Dense Net, VGG etc.), classical algorithms (Snake contour, watershed method etc.), and hybridization approaches were applied, according to the analysis. Information base, for example, BRATS, Fig-Share, EPISURG or TCIA can be taken to gather clinical pictures which principally contains of 2 classifications, pre and post pictures of Brain tumor. The multiple processes of brain tumour segmentation methodologies, such as preprocessing, feature extraction, segmentation, and classification, are also explained in this work. The task of segmenting residual and recurrent tumors differs greatly from that of segmenting tumors on baseline scans before surgery. This study shows that each approach has its own set of pros and limitations, as well as notable findings in terms of precision, sensitivity, and specificity, according to the comparison research. The use of segmentation approaches to determine success and reliability has been discovered. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Effect of treated and untreated domestic sewage water irrigation on tomato plants
Background and Objectives: Agricultural cultivations in the world are suffering from water shortages. Water scarcity poses challenges in the economy and health of people all over the world. The present study aimed the cultivation of tomato plants using groundwater, treated and untreated domestic sewage water and tried to make a comparative study on the heavy metals present in the leaves and fruits of the tomato plants. Materials and Methods: The water samples were analyzed for various physicochemical parameters such as; pH, total hardness, chloride, total alkalinity, dissolved oxygen and heavy metal. Stomatal conductance was measured using porometer. The heavy metal analysis was conducted using Atomic Absorption Spectrometer. Results: All physicochemical parameters were found to be below the permissible level of standard values in the groundwater and treated domestic sewage water, but above the permissible level in untreated domestic sewage water. Stomatal conductance was found to be very low in the plants treated with untreated domestic waste water (296.33/428 in the ventral surface during the morning and noon, respectively) when compared to the leaves of the plants treated with other water samples. Untreated domestic sewage water showed a very high level of lead, i.e., 7.5354 ppm, whereas the treated sewage water contained 0.5650 ppm slightly above the permissible level. Conclusion: The present study has revealed that the treated domestic sewage water would be used for the irrigation of agricultural cultivation. 2020 Jobi Xavier and Akhil K. Varghese. -
Antioxidant activities of leaves and fruits of piper nigrum and piper longum
Background and Objectives: Herbs and spices have been used to enhance flavors of food, as well as for their medicinal purposes. Herbs usually contain antioxidant properties. The present study was focused on the importance of the antioxidants present in Piper nigrum and Piper longum widely used by the people of India in their food. Materials and Methods: The methanolic extracts of the leaves and fruits of both Piper nigrum and Piper longum were prepared using soxhlet extraction method. The total phenolic content (TPC) of the plant samples were determined by the Folin-Ciocalteu method. The total flavonoid content (TFC) of the plant was determined. The inhibitory effect of the plant against oxidation by peroxides was evaluated by ferric thiocyanate assay. Results: The highest concentration of phenol was obtained from Piper nigrum leaves. The highest flavonoid content was observed in the Piper nigrum leaves (0.15 mg). The higher reducing potency of the antioxidants was present in the leaves and fruit of Piper nigrum and Piper longum exhibiting their antioxidant properties. The ability of the plant extracts of Piper nigrum and Piper longum against lipid peroxidation was revealed through the efficiency of inhibiting the radicals at a percentage of 58.33, 77.77, 66.66 and 22.22, respectively. Conclusion: From the study it was concluded that leaves and fruits of Piper nigrum and Piper longum have shown high antioxidant properties. So, they are considered to be rich sources of natural antioxidants for food, cosmetic and pharmaceutical industries. 2020 Jobi Xavier and Seju Thomas.