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Experience of Resilience in Women with Breast Cancer : Implication for Resilience-Based Intervention
Breast cancer is prevalent among Indian women and affects their physical, emotional, and social well-being. Resilience in breast cancer refers to the ability to maintain newlinepositivity and adapt to challenges. However, evidence-based studies and theoretical newlineframework interventions on resilience in the Indian context are lacking. The current newlinestudy aims to explore the subjective experience of resilience and intend to provide resilience-based intervention in Indian women with breast cancer. The study also explores sociodemographic, clinical outcomes, relation with resilience, quality of life and posttraumatic growth in the Indian context. The study uses a qualitative approach with phenomenological paradigm to understand the patterns, processes and outcomes in exploring the concept of resilience. Purposive sample of 33 participants from two hospitals in Bengaluru, India were recruited. The participants consisted of 21 breast cancer survivors on follow-up, four on anti-cancer therapy and eight family members of breast cancer survivors for triangulation. Along with sociodemographic, clinical details, and the Connor-Davidson Resilience Scale (2003) to screen for categorising the resilience levels was collected. The in-depth interview guide was validated with experts to collect data. The interviews were tape-recorded, transcribed, and subjected to member checks, triangulation, intercoder reliability, and thick description to ensure the validity of the findings. The data was analysed using reflective thematic analysis by Braun and Clarke (2019). The finding describes four themes of experience of resilience in women with breast cancer. (1) Cancer diagnosis is a life-changing experience. Breast cancer diagnosis and therapy causes existential crisis, psychological distress, and social stigma. (2) Restoring healthy perception in an adverse event. Navigating challenges and achieving a balance between internal and newlineexternal factors. (3) Types of support-the pathway to resilience. -
Investigation on multistep purified carbon nanostructures synthesized from a variety of hydrocarbon precursors
Nanotechnology has become by far the fastest growing area and the shooting star in materials science. Carbon is a fascinating element observed in a large variety of morphologies and atomic structures owing to its chemical ability to form different hybridizations. Carbon nanotechnology has gained significant attention, energized by discoveries such as fullerenes, followed by carbon nanotubes, and, of course the latest addition to the carbon family, graphene. Graphene, a two- dimensional honeycomb lattice of sp2-bonded carbon atoms, possesses a wealth of exceptional properties that has resulted in intense research activities. Although graphenes prospect for applications in wide areas is attractive, making and manipulating graphene is a daunting task. The most fruitful and cost-effective way to synthesize graphene in huge scale from bulk graphite is by reduction of Graphene oxide. Graphene oxide is nothing but a corrugated carbon sheet with over half of the carbon atoms functionalized with hydroxyl and epoxy groups, and edges partially occupied by hydroxyl, carboxyl, ketone, ester and even lactol structures. It has recently emerged as a new carbon-based nanoscale material that provides an alternative path to graphene due to its own alluring properties. In the present study, carbon nanomaterials are derived from hydrocarbon precursors- kerosene, camphor and liquid paraffin by thermal decomposition. Graphene oxide is then synthesized from these carbon nanostructures by modified Hummers technique. The as-prepared soot nanostructures and graphene oxide nanosheets are investigated by various experimental techniques viz. Raman Spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), UV- Visible Spectroscopy, Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray Spectroscopy (EDS), X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM) and X-Ray Photoelectron Spectroscopy (XPS). The effect of ultrasonication on the samples is also studied. -
How to win back the disgruntled consumer? The omni-channel way /
Journal of Business And Retail Management Research, Vol.12, Issue 4, pp.200-207, ISSN No. 2056-6271. -
From the local to the global: the journey of Suguna Foods
Learning outcomes: On completion of this case study, students will be able to understand collaboration and synergy between farmers and organisations through value creation, like fundraising, based on the comprehension of the resource-based theory; understand the overview and concept of the value chain and supply chain management in the agribusiness to reduce costs of inventories; understand the concept of segmentation and positioning to increase revenue for organisations by leveraging existing resources human and financial; and understand the branding strategy to create a sustainable competitive advantage for Suguna Foods. Case overview/synopsis: Suguna was started by two brothers, B. Soundararajan and G.B. Sundararajan, to help other farmers. Suguna, with just 200 broilers in 1984, grew to be the number 1 poultry company across India. Soundararajan was a pioneer and innovator who started contract farming in India in 1991. This model helped both the farmers and the company to became successful. The farmers always struggled to pay the cost of feed and other materials, as credit was not readily and easily available from financial institutions. Suguna helped farmers by providing feed, medicines, etc., free of cost in return for the good rearing of chickens. Because of the success of this venture, they decided to continue with it. Today, Suguna is a successful company that sells chicken, eggs and processed meat. They modernised the retail chain to supply consumers with fresh, healthy and hygienic meat. Sugunas vision was to Energize rural India by helping farmers succeed. They helped over 40,000 farmers from 15,000+ villages in 18+ Indian states. Although the growth helped both farmers and Suguna, the increased cost of raw materials for Suguna and increased input costs/power costs for farmers had to be tackled on a war footing so that both could have good income despite the increased inflation. Moreover, the retail price of live chicken was more or less stagnant in the past five years, especially after the start of the COVID-19 pandemic. Complexity academic level: This case can be used as the basis for a 90-min class discussion. This case study is suitable for use in an master of business administration course module or in an executive education program on developing an understanding of value creation in the business model in a rural market and also how the supply chain works. This case study can also be used to teach pricing, segmentation in marketing and supply chain perspectives and decision-making skills. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS8: Marketing. 2023, Emerald Publishing Limited. -
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Forecasting volatility evidence from the futures market in India
This thesis focuses on modelling and forecasting of select products in the Indian futures market using econometric time series models and artificial neural network based models. These models have been compared for their forecasting accuracy to determine the best forecasting model for a particular futures series. This study applies GARCH, EGARCH, PARCH, TARCH, and Artificial Neural Networks (ANN) to assess the best predicting model for exchange rate futures, commodity index futures and stock index futures. After testing for stationarity of data series, GARCH, EGARCH, PARCH and TARCH models are developed. In addition to in-sample forecasts, 1-day, 5-day, 10-day, 15-day and 30-day out-of-sample forecasts have been carried out. For ANN, data is scaled using the minmax scaling methodology to ensure that newlinethe data series is normalised and in the range of 0 to 1. ANN is developed using the feedforward methodology. While the basic neural network architecture has one input layer, one hidden layer and one output layer, the number of neurons in the input and hidden layers vary from 1 to 20. The optimum number of input and hidden neurons in their respective layers are then selected based on the combination which gives the least error. These network combinations are used for out-of-sample forecasting and errors are compared with the forecast output of the GARCH models. RMSE, MAE, MAPE, Theil s-U statistic and Correlation coefficient is computed for error newlinecomparison. Results indicate that for currency futures and commodity index futures, ANN provides better forecast accuracy. For stock index futures, GARCH family models work better in some cases. -
Impact of catchment, direct to consumer advertisement on consumer buying intention: Retailer and consumer aligned perspective from Indian pharmaceuticals industry /
Internaional Journal of Management Studies, Vol.6, Issue 1, Part 5, ISSN No: 2249-0302. -
Expatriate perceptions towards commitment based HR practices: impact on job retention in Indian IT industry /
International Journal Of Management And Development Studies, Vol.6, Issue 8, pp.29-45, ISSN: 2320-0685 (Online) 23211423 (Print). -
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Anomaly detection in online social media
Online Social Media (OSM) is a platform where users post opinions, discussions, product reviews, random thoughts, advertisements, comment exchanges and status updates.These platforms help in text mining applications such as prediction of election results, newlinestudying global mood trends, public perception of a national concern or an issue, mining of public health knowledge, detecting epidemics and business analytics. These newlineapplications also present some research challenges like personal data stealing, community phishing, hate speeches, spreading misconceptions, cyber bullying and terror attack planning. Some of these challenges are anomalies or outliers which don t conform with the majority ones. The anomalies focused in this research work are behavioral and content anomalies. Data preprocessing for textual data from OSM plays an important role for creation of the Vector Space Model (VSM) which is used as an input for behavioral and content anomaly models. The contents posted by the public in OSM is written using natural language and sometimes may not follow the formal communication mode. It has lexical, newlinesemantic and syntactic ambiguities and becomes a challenging task to extract accurate information and discover logical patterns during the text mining process. Some of the commonly used methods for text mining are, Bag of Words (BoW), N-grams and Term newlineFrequency-Inverse Document Frequency (TF-IDF). Few limitations of these techniques newlineare, high dimensional sparse feature vectors, missing contextual meaning, presence of newlineweak features and Part of Speech ambiguity. In this research study, an improvised Feature Engineering model is proposed which is a combination of Forward Scan Trigrams and weighted TF-IDF to address the creation of an efficient Vector Space Model (VSM). This proposed model is used with an improvised Feature Hashing technique to address the removal of weak features. -
A low cost and high actuation speed 3D printed prosthetic arm /
Patent Number: 202241047867, Applicant: Sujatha A K. -
System method for crop and fertilizer recommendation through soil nutrient monitoring using cyber physical system and machine learning /
Patent Number: 202141022914, Applicant: Dr. Ajith Danti.
The present invention relates to system and Method for crop and fertilizer recommendation through soil nutrient monitoring using cyber physical system and machine learning. The objective of the present invention is to solve the problems in the prior art technologies of crop and fertilizer recommendation based on soil nutrient, soil type and agriculture field location. -
An IOT based self phased analysis of adverse effects in covid recovered patients /
Patent Number: 2021101599, Applicant: Jasmine Selvakumari Jeya I. -
Processor implemented method for watermarking and cyber protection of deep learning models /
Patent Number: 202141013761, Applicant: Dr. C Kailasanathan.
The present invention relates to processor implemented method for watermarking and cyber protection of deep learning models. The objective of the present invention is to solve the problems in the prior art related to technologies of cyber security in communication and processing of block chain data. -
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STUDY OF EFFECT OF NON-LINEAR TEMPERATURE PROFILE AND CORIOLIS FORCE ON THE ONSET OF RAYLEIGH-B??NARD- MARANGONI MAGNETO CONVECTION
The effects of non-linear temperature gradients and rotation on the onset of Rayleigh ?? Benard ?? Marangoni magneto ?? convection in an electric conducting Newtonian fluid are studied using the Galerkin technique. In the case of Rayleigh-Benard convection, the eigenvalue is obtained for free-free, rigid-free and rigid-rigid velocity boundary combinations with isothermal and adiabatic temperature conditions on the boundaries. In the case of Marangoni and Rayleigh-Benard-Marangoni convection the eigenvalues are obtained for an upper free / adiabatic and a lower rigid / isothermal boundaries. A linear stability analysis is performed. The influence of various parameters on the onset of convection has been analyzed. The four non-linear temperature profiles are considered and their comparative influence on onset is discussed. -
Study of Nanolayered Structure of Commercially Available Carbon Materials and Soot
Developments in the modern world periodically call for the discovery or invention of new and exotic materials. In the present situation, to develop unique and novel materials, which move beyond the barriers of the physical limits of the amount of micro- miniaturization possible as well as the current technology and take advantage of the opportunities not yet imagined, is not at all a need but a necessity. The advent of Nano technology of carbon allotropes is a giant leap towards this goal. The starting of the era of carbon nanomaterials traces back to 1985 when the fullerenes with a foot ball structure were accidently discovered. From then on, the field of carbon nanotechnology was in the constant limelight on account of the amazing properties displayed by the various allotropes of carbon. These properties are dependent mainly on the type of hybridization present in the nanostructures, which categorizes them to amorphous or crystalline. Also, there exist some structures which are the combination of these two and are termed as nanocrystalline or turbostratic structures. The discovery of graphene, which has a turbostratic structure and is the thinnest material known and the strongest ever measured, with outstanding properties such as highest room temperature electrical conductivity; high mechanical robustness etc was a ground breaking one. These remarkable properties open up a wide range of potential applications ranging from clean energy to nano-electronics to bio-medical devices. Thus, it is a necessity to explore and characterize various effective sources of these nanomaterials. The present study is an attempt to investigate such efficient, easily available and cost-effective precursors. Soot, also known as black carbon, is a fine-grained solid residue that results from incomplete combustion of hydrocarbons and is a widely used precursor for the production of carbon nanomaterials. Carbon soot is a major component of smoke from the combustion of carbon-rich organic fuels and hydrocarbons and hence has a vast number of sources. In the study presented here soot obtained from the thermal decomposition of commercially available kerosene, diesel oil, paraffin wax and lubricant oil is investigated. Nanostructure of the commercially available carbon black is also studied. Various techniques such as Micro Raman spectroscopy, Fourier Transform Infrared Spectroscopy (FT-IR), X-ray diffraction (XRD), High Resolution Scanning Electron Microscopy (HR-SEM), Electron dispersive spectroscopy (EDS) and elemental analysis are employed for the structural and morphological characterization of the samples. Raman scattering is used as a probe to study the disorder in the carbon skeleton materials. The intensity ratio of the D and G modes occurring in the spectra is proportional to the number of rings at the edge of the grain and also indicates the quality of the sample. FT-IR spectroscopy is used to characterize qualitatively the functional groups of carbon materials. XRD is the most common analytical technique used for determining the structure of ordered and disordered carbons from the positions of the diffraction peaks at 2?? angle. The structural parameters like the size of the ordered grains along c and a axis (Lc and La), the average spacing of the crystallographic (002) planes (d002) can be determined through Scherrer equations. SEM micrographs give the surface morphology of the nanomaterials present and the EDS analysis gives the abundance of the microscopic constituents. Elemental composition of the samples can be derived from the elemental analysis using CHNS (Carbon Hydrogen Nitrogen Sulphur) analyser. The present study shows that all the samples investigated obeys the Tuinstra-Koening relation and posses a nanocrystalline structure. The ratio of the defect and graphite bands is found to be very low, especially in the case of diesel soot which has a value very much lower than those reported in the earlier studies, indicating high quality and a low amount of disorder in the samples. HR-SEM micrographs clearly indicate that the carbon nanostructured present in the samples are in the form of non-uniform nanospheres with diameter varying between 26-100 nm. The characteristic diffraction peak of graphene corresponding to (100) diffraction is observed in the x-ray diffraction profiles of all the samples. The interlayer spacing determined in all the samples lies very close to that of graphite. The H/C atomic ratio from the CHNS analysis is found to be very low and confirms the nanocrystalline structure of the materials. The graphite band position in the IR spectra indicates that the nanospheres formed are to be composed more of crystalline graphitic carbon. From the EDS analysis it is evident that all the samples have very high carbon content and are free from impurities and thus concludes that the materials and methods used in the present study for the synthesis of carbon nanospheres possessing a nanocrystalline structure are efficient and cost effective and are good precursors for graphene. -
ANALYSIS OF MARKETING AND ADVERTISING STRATEGIES OF DECCAN HERALD, BANGALORE
For years newspapers have sold papers through racks on the streets. With change in consumer behaviour, the sales and purchases of newspapers have also transformed. Technological advancement brought in a demand to be innovative and to suit the changing behaviour of the consumer. Newspaper like any other commodity has to fight for its survival and make an impact on the consumer??s mind. The days of ??Plan Buy?? have taken a backseat because of availability of many options for the product of the same kind. There comes a need to draw all the attention of the consumer to the devices of innovation in order to make a purchase. Newspapers therefore, have adopted different elements of the marketing communication mix of the integrated marketing communications to smartly market themselves at every level to reach and appeal to ever changing readers. The research will aim at studying the changes by the newspaper organization in order to market their newspaper through ??An Analysis of Marketing and Advertising Strategies of Deccan Herald, Bangalore.?? The research is aimed at studying the steps and procedures that are taken by the newspaper organization to position their newspaper to the target readers to get the desired market share. The research will also try and gauge the impact of the marketing and advertising strategies adopted. If there is an impact what might be the possible reasons and till what extent. The research will make a detailed analysis by interviewing people from Deccan Herald, Bangalore to get in-depth knowledge about the steps and procedures taken by the newspaper organization. Also, in addition a sample survey was conducted with a total sample size of 85 to gauge the impact.