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Defiance in the Shadows: Flames of Resilience in the Selected North Korean Memoirs
The resilient autobiography focuses on the interpersonal dynamics of life narratives, including the relationships that have exacerbated the hardships described and the ones that have provided the support and strength necessary to overcome them. The selected text for this paper is A Thousand Miles to Freedom: My Escape from North Korea by Eunsun Kim and Sebastien Falletti and In Order to Live: A North Korean Girls Journey to Freedom by Yeonmi Park and Maryanne Vollers. These two texts talk about their catastrophic journey from North Korea because of poverty caused by famine and their migration to China, where they were trafficked and subjected to humiliation and their final escape to South Korea. The memoirs depict the individual?s embodiment of resilience as they narrate their own struggles and victories in overcoming hardship. Resistance to adversity and suffering, as well as the ability to bounce back from painful experiences in one?s own life and in the lives of others, are the hallmarks of resilience. Trauma becomes ingrained in attempts for survival in both memoirs, which illustrate the catastrophic impacts of famine, relocation, and personal loss. One effective approach to enhance resilience is reorganizing and reestablishing control over one's life after a traumatic event. Interpretations and writings of the personal narrative are offered from both the subject?s and an outsider?s points of view. Thus, the life story is formed in a dual sense: autobiographically and biographically. 2024 Sciedu Press. All rights reserved. -
Defluoridation of Drinking WaterFluoride Wars
Fluorine is also known as two-edged sword. At lower doses, it influences tooth by inhibiting tooth caries, while in high doses, it causes dental and skeletal fluorosis. It is known that some quantity of fluoride is important for the formation of tooth enamel and mineralization in tissues. The present work aims at providing safe and potable water to rural areas where this element has created a menace. This work also suggests the use of few adsorbents such as paddy husk and coir pith which are affordable and removes fluorine to greater extent. The study concludes that materials which are used as adsorbents and can be safely inculcated as fluorine removal adsorbents which help people to have safe potable water. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Deforestation, Climate Change and the Sustainability of Agriculture: A Review
This study aims to survey the literature and factual evidence on the nexus between deforestation and agriculture through an assessment of the potential impacts of climate change in the context of the world, India, and the Western Ghats. The Western Ghats region was chosen for this study because of its deep ecological significance. A few underlying themes were created and findings were documented under each theme that ranged from the causes of deforestation, the transformation of forest land for agriculture, the nexus between agriculture, deforestation and climate change, climate-driven agricultural vulnerability and the reconciliation of forest protection with agriculture. These findings suggest that shifting agriculture has been a dominant source of deforestation. The primary climatic impacts on agriculture are seen through crop yield falls. Indias arid and semiarid tropical regions have witnessed high climate-driven agricultural sensitivity. This could be on account of the fact that Indias tropical forests have witnessed high deforestation. The presence of higher tree densities in areas under Joint Forest Planning and Management in the Western Ghats create the potential for sparing remaining land areas for non-forest uses such as agriculture. 2024, Editorial office of Journal of Resources and Ecology. All rights reserved. -
Deformation Diagnostic Methods for Transformer Winding through System Identification
Transformers play a critical role in the power system. Dynamics of the power system changes if the transformers are out of service for scheduled and unscheduled maintenance work under contingency situations. Faults, overloading, and mechanical abnormalities causes the incipient and critical damages to the transformer. The isolation of transformers leads to the voltage profile change, load curtailments, high compensation, economic loss, and many more problems. It is very important to know the problems occurred in the transformer parts to repair and restore it into the system to attain better stability, reliability, and economics. The transformer health monitoring system consisting of prediction, identification, and diagnostics in online as well as offline mode that will provide sufficient content to the managerial utility to take actions against the problem anticipated or occurred. The heuristic survey inks, the probability of damage in the transformer winding is more compared to the other parts. A novel method using system identification is proposed for the diagnosis of transformer winding. The location and extent of mechanical deformations can be ascertained along with specifically detecting radial and axial deformations in the transformer windings. A system identification approach in frequency and time domain were employed in the diagnostic algorithms for the sweep frequency response dataset. For both transfer function and state space model, a reference table called deformation information tableau has been synthesized for lumped parameter transformer model by varying series and shunt circuit elements systematically. The details of deformation are extracted from the tableau for actual frequency response data for a specified frequency range and winding type. The crosscorrelation of two-dimensional frequency response arrays, one being a signature array and other being deformation array, is used to represent relativity as a singleton. A toolbox is developed for the generation of heuristic deformation information tableau and to diagnose using the diagnostics algorithm developed. The proposed algorithms were verified and simulated for continuous disk type winding. 2019 IEEE. -
Degradation of azodyes in wastewater by using hydrodynamic cavitation technique
The organic waste water discharged from various industries consists of large amounts of dyes & cyanides & other toxic carcinogenic pollutants which are harmful to human health & ecosystem. Release of carcinogenic dyes is hazardous & has a detrimental effect on the well being of an individual. The present work is focussed at finding the viability of hydrodynamic cavitations process in the degradation of dyes. To study the degradation, influence of various parameters on degradation rate has been studied. BEIESP. -
Degree of Children Influence on Parents Buying Decision Process
European Journal of Business Management Vol. 4, No. 14, pp 49-57, ISSN No. 2222-2839 -
Delay Minimization Technique to improve the efficiency of Parameter Optimized Hysteretic Current Controlled Parallel Hybrid ETPA in Mobile Communication
This paper proposes a delay minimization technique to improve the efficiency of a parameter-optimized hysteretic current-controlled parallel hybrid envelope tracking power amplifier (etpa). In a hysteretic current-controlled hybrid topology, a linear amplifier operates parallel with a hysteretic current-controlled switching converter. Block level simulation of etpa is performed using the simulink tool. The traditional parameter optimization technique is first implemented, and its limitation is analysed. The proposed delay minimization technique helps to overcome the limitation of the traditional approach and has been proven to be valid for any input frequency. The proposed technique offers an efficiency improvement of 14.9% compared to the traditional technique for an input frequency of 20mhz and provides an average efficiency improvement of 6.26% for an input frequency range of 2mhz to 60mhz. 2024 IEEE. -
Delayed in sensorimotor reflex ontogeny, slow physical growth, and impairments in behaviour as well as dopaminergic neuronal death in mice offspring following prenatally rotenone administration
The environment is varying day by day with the introduction of chemicals such as pesticides, most of which have not been effectively studied for their influence on a susceptible group of population involving infants and pregnant females. Rotenone is an organic pesticide used to prepare Parkinson's disease models. A lot of literature is available on the toxicity of rotenone on the adult brain, but to the best of our knowledge, effect of rotenone on prenatally exposed mice has never been investigated yet. Therefore, the recent work aims to evaluate the toxic effect of rotenone on mice, exposed prenatally. We exposed female mice to rotenone at the dose of 5mg/Kg b.w. throughout the gestational period with oral gavage. We then investigated the effects of rotenone on neonate's central nervous systems as well as on postnatal day (PD) 35 offspring. In the rotenone group, we observed slow physical growth, delays in physical milestones and sensorimotor reflex in neonates and induction of anxiety and impairment in cognitive performances of offspring at PD-35. Additionally, immunohistochemical analysis revealed a marked reduction in TH-positive neurons in substantia nigra. Histological examination of the cerebellum revealed a decrease in Purkinje neurons in the rotenone exposed group as compared to the control. The data from the study showed that prenatally exposure to rotenone affects growth, physical milestones, neuronal population and behaviour of mice when indirectly exposed to the offspring through their mother. This study could provide a great contribution to researchers to find out the molecular mechanism and participating signalling pathway behind these outcomes. 2023 International Society for Developmental Neuroscience. -
DELHI: A NOVEL by Khushwant Singh
[No abstract available] -
Delving into the Bubble Detection of Specific NSE Sector Indices
This study meticulously examines market bubbles within specific sectors of the National Stock Exchange (NSE) over the period from January 2017 to December 2023, employing robust methodologies like RADF, SADF, and GSADF tests. The analysis, centered on 11 sectoral indices, integrates GSADF values with RADF and SADF, offering nuanced perspectives that underscore the sector-specific nature of bubbles. Notably, the study highlights bubble occurrences during the 2020 global crisis due to pandemic, emphasizing their dynamic and diverse manifestations amid the pandemic. Exclusive identification of bubbles in NSE IT, NSE Metal, and NSE Pharma enriches the strategic insights available to investors, facilitating informed decision-making and risk management. The sector-wise approach contributes to a holistic understanding of market dynamics, providing investors with valuable tools to navigate the intricacies of the financial landscape. Future research avenues may delve into regulatory impacts on sector-specific bubbles and explore the interplay between macroeconomic indicators and sectoral bubbles, offering deeper insights into market dynamics. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Delving into the Exchange-Traded Funds (ETFs) Market: Understanding Market Efficiency
Exchange-traded funds (ETFs) are the most popular products in the financial sector today. There is extensive literature on the multifractal analysis of some stock markets, but not about the multifractal behaviour of the ETF market. This study examines the efficiency of stock index ETFs worldwide from an Efficient Market Hypothesis (EMH) perspective, using the ETFs: Ishares Msci World ETF (URTH), Ishares Russell 1000 ETF (IWB), SPDR S&P 500 ETF TRUST (SPY), Ishares Global Clean En. ETF (ICLN), Ishares USD Green Bond ETF (BGRN), from 1 January 2021 to 24 May 2024. It analyses a pre-conflict and a geopolitical conflict to uncover distinct patterns of behaviour reflecting significant changes in market conditions. Before the conflict, the Ishares MSCI World, Ishares Russell 1000, SPDR S&P 500 and Ishares USD Green Bond ETFs showed signs of anti-persistence in returns, indicating a lack of strong relationship or predictability between short-term price movements. The Ishares Global Clean Energy ETF did not reject the random walk hypothesis, suggesting that returns follow a pattern closer to random, where market prices already efficiently reflect all available information. During the conflict, there was a transition in the ETFs' behaviour patterns, as evidenced by the increases in slope values for Ishares MSCI World, Ishares Russell 1000, SPDR S&P 500, Ishares Global Clean Energy and Ishares USD Green Bond. Thus, the possible transition from anti-persistence to long-term memories in ETF returns during the conflict. For portfolio managers, these findings highlight the need to continually adapt investment strategies to manage risks better and take advantage of opportunities in a dynamic and complex investment environment. 2024, Creative Publishing House. All rights reserved. -
Demand and Supply Forecasts for Supply Chain and Retail
Demand and supply forecasts serve as the backbone of strategic decision-making in todays rapidly changing business environment, assisting organizations in optimizing inventory levels, production planning, and pricing strategies. The ability to forecast demand and supply accurately is critical for effective supply chain and retail management. This chapter provides a comprehensive overview of supply chain and retail demand and supply forecasts. It discusses various forecasting methods and techniques, as well as related concepts. In addition, the chapter emphasizes the significance of accurate forecasting in optimizing supply chain and retail operations, as well as emerging trends and future directions in demand and supply forecasting. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Demand Forecasting Methods: Using Machine Learning to Predict Future Sales
To thrive in the market today, businesses must increase the effectiveness, dependability, and accessibility of their services. Sales estimation and operative demand scheduling definitely impact the end result of the organizations, influencing their procurement process, production, delivery, supply chain, marketing communications, etc. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Demand response for residential loads using artificial bee colony algorithm to minimize energy cost
Power performance expectations are increasing, impacting designs and requiring advanced technology to improve system reliability. Demand Response (DR) is a highly flexible customer driven program in which customer voluntarily changes his energy usage patterns during the peak demand to maintain the system stability and reliability and thereby improves the performance of the gird. This paper proposes a novel algorithm for optimization of the DR schedule of the residential loads for various hours of the day using Artificial Bee Colony (ABC) algorithm. Here, the objective function is subjected to the constraints like cost constraints, time constraints and load demand. The results show that the proposed approach enhances potential in solving problems with good reliability compared with existing approaches. 2015 IEEE. -
Demineralization of sub-bituminous coal by fungal leaching: A structural characterization by X-ray and FTIR analysis
The filamentous fungi, A. niger, A. flavus and Penicillium spp were studied for their ability to demineralise the low rank Indian coals. The FTIR spectra of coals showed the presence of stretching vibrations of -OH bond, aliphatic -CH, -CH2 and - CH3 absorptions, C=C and -CH of aromatic structure and mineral groups. X-ray analyses revealed that coal consists of crystalline carbon of turbostratic structure. The average lateral sizes (La), stacking height (Lc) and the interlayer spacing (d002) of the crystallite structure were calculated which ranged from 343.64 to 1.5, 223.20 to 22.54 and 3.35 to 3.60respectively. The structure of coal was modified to a product similar to that of pure graphite after leaching with Penicillium spp. Scanning electron microscopy (SEM) analysis of coal revealed a layer like structure on the surface. -
Democratising Intelligent Farming Solutions to Develop Sustainable Agricultural Practices
In this chapter, the transformative potential of democratising intelligent farming solutions is discussed, primarily in the context of the sustainable farming. Technologies including the Internet of Things (IoT), global positioning systems (GPS), Unmanned Aerial Vehicles (UAVs), computer vision, and artificial intelligence (AI) have redefined farming activities. Such advances have allowed decision-making and optimised resource utilisation to be driven by real-time data. The democratisation of AI tools are meant to make AI-driven agriculture accessible to all. As such, this chapter discusses the interplay of bottom-up and top-down approaches, highlighting their roles in promoting the accessibility of AI tools and their benefits to farmers. The integration of such AI tools would transform contemporary agriculture into agriculture 4.0. This revolution would be characterised by real-time data, predictive analytics, and precision farming techniques. Further, the integration of technology such as wireless networks and the global navigation satellite system (GNSS) increases precision and the ability to monitor farming activities. The idea of democratising intelligent farming solutions is meant to herald agriculture 4.0, which would improve crop quality, climate resilience of crops, and the income of farmers. It would also improve broader macroeconomic aspects by promoting education and information and communication technology (ICT) skills and potentially reducing income inequality gap while promoting socio-economic well-being. 2025 selection and editorial matter, Sirisha Potluri, Suneeta Satpathy, Santi Swarup Basa, and Antonio Zuorro; individual chapters, the contributors. All rights reserved. -
Demographic characteristics influencing financial wellbeing: amultigroup analysis
Purpose: The study attempts to understand the factors impacting the financial wellbeing of IT employees in India using confirmatory factor analysis (CFA). It utilizes well-established survey instruments to assess the impact of financial literacy, financial behaviour and financial stress on financial wellbeing. The study also attempts to understand the role of demographic factors (age, gender, monthly income, job category and work experience) in determining financial wellbeing through multigroup analysis. Design/methodology/approach: Structured equation modelling (SEM) is used to study the link between the determinants. The study also attempts to understand the role of demographic factors (age, gender, monthly income, job category and work experience) in determining financial wellbeing through multigroup analysis. Data used for the analysis covers 237 employees working in the IT sector. Findings: While financial literacy and financial behaviour have a significant positive impact on financial wellbeing, financial stress has a significant negative impact. Financial behaviour and financial stress were found to have a mediating role in the relationship between financial literacy and financial wellbeing. The demographic variables significantly moderate the relationship between the factors leading to financial wellbeing. Originality/value: The results show the need for financial wellbeing programs to focus on enhancing financial knowledge and improving financial planning. Further, it suggests offering customized financial wellbeing programs based on the employee's demographic characteristics rather than following a one program, fits all approach. 2021, Emerald Publishing Limited. -
Demographic constructs and savings behavior of adult people /
Journal of Emerging Technologies And Innovative Research, Vol.6, Issue 3, pp.409-412, ISSN No: 2349-5162. -
Demography-Based Hybrid Recommender System for Movie Recommendations
Recommender systems have been explored with different research techniques including content-based filtering and collaborative filtering. The main issue is with the cold start problem of how recommendations have to be suggested to a new user in the platform. There is a need for a system which has the ability to recommend items similar to the users demographic category by considering the collaborative interactions of similar categories of users. The proposed hybrid model solves the cold start problem using collaborative, demography, and content-based approaches. The base algorithm for the hybrid model SVDpp produced a root mean squared error (RMSE) of 0.92 on the test data. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Demystifying artificial intelligence and customer engagement: A bibliometric review using TCCM framework
Artificial intelligence (AI) has grabbed the attention of the extent of literature and customer engagement of many business organizations in the past decade, especially with the advancement of machine learning and deep learning. However, despite the great potential of AI to solve customer problems and engage customers, there are still many issues related to practical uses and lack of knowledge to create value through customer engagement. In this context, the present study aims to full fill the gap by providing a critical literature review based on 53 A* and A categories of Australian Business Deans Council (ABDC) journals (2011-2023) by highlighting the benefits, challenges, framework, and future research directions in theory, context, characteristic and methodology (TCCM) areas. These findings contribute to both theoretical and managerial perspectives for developing a future novel theory and new forms of management practices. 2024, IGI Global. All rights reserved.