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Deciphering the Nature and Dynamics of Gig-Platform Jobs: Workers Hidden Precarity
The technology-driven gig-platform sector has emerged as a new source of employment generation both globally as well domestically. This recent transformation in the labour market is reshaping the nature of labour practices, labour relations, workers rights, and contracts. The sector has huge potential to generate millions of job opportunities by leveraging the use of digital technology. As this sector continues to generate more jobs, such jobs are portrayed as fostering economic growth, while creating meaningful jobs, which are mutually beneficial to workers and employers in terms of providing flexibility and freedom, better earning opportunity, and promoting social inclusion, by which it implies that women are increasingly equipped to find better jobs. This article critically examines the developmental roles of platform jobs which are being particularly highlighted within the policy circle, in academic literature, and tech companies through workers lens. It delves deeper into the discussion on those very aspects of platform jobs just listed, including the flexibility and freedom debate, workers income, and the gender aspect of jobs. In doing so, it carefully examines these aspects with respect to their implications on workers in terms of working conditions and regulatory aspects. The article brings out the workers precarity hidden within those developmental aspects of gig-platform jobs. 2024 CSD. -
Deciphering the impact of COVID-19 pandemic on food security, agriculture, and livelihoods: A review of the evidence from developing countries
With COVID-19 now spreading in developing countries, massive consequences on health and livelihoods are feared. Food security is the most important and crucial aspect of sustainable development. The agricultural sector forms the backbone of the economy and provides livelihood to a large section in developing countries. Therefore, the disruption in food security and the agricultural sector will have far-reaching impacts on these countries. Owing to the importance of these sectors, this paper performs a comprehensive assessment of the effect of COVID-19 on food security and agriculture. The research suggests coping and mitigation mechanisms that can be adopted to sustain livelihoods. 2020 The Author(s) -
Deciphering the global research trends and significance of moral intelligence via bibliometric analysis
Introduction: Moral Intelligence (MI) as a concept has gained importance in recent years due to its wide applicability in individual, organizational, and clinical settings or even policy making. The present study employed Bibliometric analysis to understand the emerging topics associated with MI and its global research trend. This papers primary aim was (i) to explore the temporal and geographic growth trends of the research publication on MI. (ii) to identify the most prolific countries, institutions, and authors, working on MI, (iii) to identify the most frequent terminologies, (iv) to explore research topics and to provide insight into potential collaborations and future directions, and (v) to explore the significance of the concept of moral intelligence. Method: Bibliometric analysis was used to understand the emerging topics associated with MI and its global research trend using the SCOPUS database. VOS viewer and R were employed to analyze the result. Through the analysis conducted, the development of the construct over time was analyzed. Results: Results have shown that Iran and the United States and these two combined account for 53.16% of the total country-wise publications. Switzerland has the highest number of Multi-county publications. Authors from Iran and Switzerland have the most number of publications. Emerging topics like decision-making, machine ethics, moral agents, artificial ethics, co-evolution of human and artificial moral agents, green purchase intention etc were identified. Discussion: The application of MI in organisational decision-making, education policy, artificial intelligence and measurement of moral intelligence are important areas of application as per the results. Research interest in MI is projected to increase according to the results delineated in this article. Copyright 2024 Bagchi, Srivastava and Tushir. -
Decentralized financial assets: An attraction beyond stock market investments
The Chapter revolves around the attraction that the blockchain-backed decentralized financial products have created in the investment market. These new-gen decentralized finances would be Defi, Metaverse coins, Stablecoins, Cryptocurrency, smart contracts, and privacy coins. The influence of social media and high internet penetration levels have made the retail and partial investors very well aware of many alternate financial investment products. Though there is an increase seen in the Stock Market investments as well a drastic increase in the alternate market is seen. In recent times major stock markets have created indexes separately. It is the icing on the cake with the highest attention of the globe. The regulations have put the Defi Assets under unpredictable volatility but the attraction towards cryptocurrency and other digital asset gain still exists. The study aims to identify the relationship between the increase in investment in the stock market and the alternative. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Decentralized Data Integrity: Integrating MySQL with Blockchain for Resilient Healthcare Systems
A transformational solution to the problems created by healthcare data management is presented by the integration of MySQL and blockchain technology, centered around security, scalability, and efficiency. This paper presents MBHA MySQL-Blockchain Healthcare Architecture combining thestructured data storage, querying capabilities of MySQL with the decentralized, tamper-proof framework of blockchain. The system shows impressive performance metrics with an average API response time of 1.54 seconds for user registration and 841 milliseconds for login. The database queries and data retrieval or insertion took less than 1 millisecond, and JWT tokens were generated for authentication in less than 50 milliseconds. Conclusion Results indicate an efficient real-time system to accomplish tasks with integrity in terms of data but also with safety in operations. This architectural model, discussed above, is issues regarding data security and access with a need to provide care-collaboration needs. Scalability would then be optimized while keeping down computational overhead; in fact, work toward readiness for adoption is mainly towards being more regulatory compliant. 2025 River Publishers -
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Decent Work Deficit: A Challenge on the Women Empowerment in Indian Agricultural Sector
Women play a crucial role in Indian agriculture, but they also confront several obstacles that reduce their productivity and prevent them from fully engaging in the sectors development. The majority of women in India are employed in agriculture, which is one of the sectors that contributes most to the GDP and is essential to the economic development of the nation. Although women continue to have a significant and recognized role in agriculture, their function is frequently overlooked. Women make up about 75% of the full-time labor force on Indian farms. The nation wont develop unless its women farmers are empowered. Only through decent work labour the agriculture sector will be developed which will help in the empowermentof women agricultural Labourers in India. So the government should take all steps to implement the decent work concept of ILO in the Indian agricultural sector. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Debrahmanization
This chapter explores the concept of Brahmanism and its pervasive influence on the caste system in India, emphasizing the need for debrahmanization as a means to dismantle caste-based oppression. Historically rooted in the priestly castes dominance, Brahmanism has shaped societal structures by perpetuating inequality, while debrahmanization seeks to challenge this hierarchical order. This chapter examines the theoretical underpinnings of Brahmanism, including its socio-political ideology, and contrasts it with alternative movements, such as Buddhism, which aim to disrupt Brahmanical supremacy. The process of debrahmanization is positioned as a critical act to create an egalitarian society, advocating for political and intellectual engagement with anti-caste movements. Scholars like Ambedkar, Phule, and contemporary thinkers have advanced this discourse, emphasizing the need to address caste discrimination in all areas of life, including education, literature, and politics. Ultimately, this chapter argues that debrahmanization is a necessary step towards achieving social justice and creating a more inclusive and democratic India. 2026 selection and editorial matter, Mahitosh Mandal and Sanjiv Kondekar; individual chapters, the contributors. -
Death-worlds, Necropolitics and Decoloniality Colonial Negotiations in Mah
The boundaries of sovereignty are mostly relegated to modern and late modern political thoughts that focus on biopolitical and democratic theories. This paper marks a shift of sovereign subjectivity to the interstitial spaces of life and death of the colonial subjects. Through the study of the necropolitics of colonial control in the erstwhile French colony of Mah as narrated in the novel On the Banks of the Mayyazhi, this paper argues that colonial subjectivity and the idea of sovereignty have decentred itself from the traditional notions of political control and violence to newer avenues of life and death. The perusal of the decolonial approach to necropolitics will examine how colonial logic has shaped the idea of sovereignty. 2024 Economic and Political Weekly. All rights reserved. -
Death Rituals and Change Among Hindu Nadars in a South Indian Village
This article examines changes in the death rituals performed among Hindu Nadars in a South Indian village. It emphasises the importance of understanding ritual changes within their specific micro-level local contextual framework, including changing social structures at household and village level. This empirical evidence showcases how changing rituals connected to death reflect various adaptations through imitation, substitution and alteration of specific ritual elements and performants. It also identifies emerging class distinctions among Nadars and their connection with changes in rituals associated with death. This analysis of the changes depicts how Nadars use ritual actions in pragmatic ways, symbolically expressing and realising their aspirations for status enhancement through such ritual performances. 2021 SAGE Publications. -
Death of Vernaculars and Language Hegemony: An ethnography of the higher education sector in 21st century India
The paper examines how new age pedagogies and neoliberal policies consciously work towards naturalizing English languages hegemony in institutions of Higher Education (IHE) in India. An ethnographic study the paper foregrounds the precarious positioning of non-English Indian languages vis-vis the pervading discourses of internationalization and education as job/skill oriented. Hegemony of English in the present is coupled with a restructuring of language departments as well as fleeting market demands for human capital. The paper also brings into question the role of the Internet and related technologies in reorganizing the linguistic dynamics of HE. Instead of democratizing, the Internet produces new monopolies in knowledge production, controls knowledge traffic from global North to South and further legitimizes the language hegemony. The paper argues that, in the last two decades, the neoliberal rupture has been leading HE institutions to a death of vernaculars within their physical, cultural and academic spaces. 2024, Hiroshima University,Research Institute for Higher Education,. All rights reserved. -
Dealing with missing values in a relation dataset using the DROPNA function in python
Python provides a rich data structure library called PANDAS, which provides fast and efficient data transformation and analysis. The word PANDAS is an abbreviation of Python Data Analysis Library. PANDAS facilitate optimized and dynamic data structure designs work with "relational" or "labeled" data. Python's approach is meant to provide a high-level, high-performance building block that can be used to do real-world analysis of data. PANDAS Library is allowing users to import data from different file formats, such as CSV, SQL, Microsoft Excel etc. [1]. It helps in data preparation, as well as in data modeling, for those projects, which aims data analysis for the extraction of information. Python's future will be built on this layer for statistical computing. In addition to discussing future areas of work and growth opportunities for statistics and data analytics applications built on Python, the study provides details about the language's design and features [2]. In this research paper, we intend to solve the problem of missing values in a dataset using the DROPNA function in Python using PANDAS library. 2023 Scrivener Publishing LLC. -
Dead Names, Living Futures Reflections from a Dera in Bhopal
Lance Larsens poem captures a particular kind of parental dissonance: the desire to honour ones child as they are now, while occasionally startled by a past that appears in mundane momentscontrasting the experiences of transpeople in a collective home in Bhopal. 2026, Economic and Political Weekly. All rights reserved. -
De novo synthesis of 2,2-bis(dimethylamino)-3-alkyl or benzyl 2,3-dihydroquinazolin-4(1H)-one compounds
A new versatile and efficient strategy for the synthesis of 2,2-bis(dimethylamino)-3-alkyl or benzyl 2,3-dihydroquinazoline-4(1H)-one compounds has been developed by one-pot multicomponent reaction with isatoic anhydride, amines followed by in situ-generated Vilsmeier reagent. The reaction has also been studied with different amines and solvents. 2017 Taylor & Francis. -
DDoS Intrusions Detection in Low Power SD-IoT Devices Leveraging Effective Machine Learning
Security and privacy are significant concerns in software-defined networking (SDN)-applied Internet of Things (IoT) environments, due to the proliferation of connected devices and the potential for cyberattacks. Hence, robust security mechanisms need to be developed, including authentication, encryption, and distributed denial of service (DDoS) attack detection, tailored to the constraints of low-power IoT devices. Selecting a suitable tiny machine learning (TinyML) algorithm for low-power IoT devices for DDoS attack detection involves considering various factors such as computational complexity, robustness in dealing with heterogeneous data, accuracy, and the specific constraints of the target IoT device. In this paper, we present a two-fold approach for the optimal TinyML algorithm selection leveraging the hybrid analytical network process (HANP). First, we make a comparative analysis (qualitative) of the machine learning algorithm in the context of suitability for TinyML in the domain of SD-IoT devices and generate the weights of suitability for TinyML applications in SD-IoT. Then we evaluate the performance of the machine learning algorithms and validate the results of the model to demonstrate the effectiveness of the proposed method. Finally, we see the effect of dimensionality reduction with respect to features and how it affects the precision, recall, accuracy, and F1 score. The results demonstrate the effectiveness of the scheme. 1975-2011 IEEE. -
DDoS Intrusions Detection in Low Power SD-IoT Devices Leveraging Effective Machine Learning
Security and privacy are significant concerns in software-defined networking (SDN)-applied Internet of Things (IoT) environments, due to the proliferation of connected devices and the potential for cyberattacks. Hence, robust security mechanisms need to be developed, including authentication, encryption, and distributed denial of service (DDoS) attack detection, tailored to the constraints of low-power IoT devices. Selecting a suitable tiny machine learning (TinyML) algorithm for low-power IoT devices for DDoS attack detection involves considering various factors such as computational complexity, robustness in dealing with heterogeneous data, accuracy, and the specific constraints of the target IoT device. In this paper, we present a two-fold approach for the optimal TinyML algorithm selection leveraging the hybrid analytical network process (HANP). First, we make a comparative analysis (qualitative) of the machine learning algorithm in the context of suitability for TinyML in the domain of SD-IoT devices and generate the weights of suitability for TinyML applications in SD-IoT. Then we evaluate the performance of the machine learning algorithms and validate the results of the model to demonstrate the effectiveness of the proposed method. Finally, we see the effect of dimensionality reduction with respect to features and how it affects the precision, recall, accuracy, and F1 score. The results demonstrate the effectiveness of the scheme. 1975-2011 IEEE. -
DC-DC and DC-AC Converters with Bi-Directional Capabilities for EV Applications
Abstract: This paper presents the design and implementation of a compact bidirectional DC-DC converter coupled with a DC-AC inverter for electric vehicle (EV) motor-drive applications. Both propulsion and regenerative braking modes are made possible by the suggested architecture, which facilitates smooth power transfer between a 48 V battery and a series- wound AC motor. Additionally, the inverter provides controlled AC stimulation for a dependable motor operation, while a high- efficiency bidirectional DC-DC converter controls battery power flow during acceleration and recovers energy during braking. In order to maintain dynamic stability under changing load circumstances, an Arduino Nano microcontroller uses a proportional-integral (PI) control method to regulate motor speed and current. Cross-conduction losses are decreased and MOSFET switching safety is improved by customized PWM pulse generation with dead-time insertion. 2026 IEEE. -
DAWM: Cost-Aware Asset Claim Analysis Approach on Big Data Analytic Computation Model for Cloud Data Centre
The heterogeneous resource-required application tasks increase the cloud service provider (CSP) energy cost and revenue by providing demand resources. Enhancing CSP profit and preserving energy cost is a challenging task. Most of the existing approaches consider task deadline violation rate rather than performance cost and server size ratio during profit estimation, which impacts CSP revenue and causes high service cost. To address this issue, we develop two algorithms for profit maximization and adequate service reliability. First, a belief propagation-influenced cost-aware asset scheduling approach is derived based on the data analytic weight measurement (DAWM) model for effective performance and server size optimization. Second, the multiobjective heuristic user service demand (MHUSD) approach is formulated based on the CPS profit estimation model and the user service demand (USD) model with dynamic acyclic graph (DAG) phenomena for adequate service reliability. The DAWM model classifies prominent servers to preserve the server resource usage and cost during an effective resource slicing process by considering each machine execution factor (remaining energy, energy and service cost, workload execution rate, service deadline violation rate, cloud server configuration (CSC), service requirement rate, and service level agreement violation (SLAV) penalty rate). The MHUSD algorithm measures the user demand service rate and cost based on the USD and CSP profit estimation models by considering service demand weight, tenant cost, and energy cost. The simulation results show that the proposed system has accomplished the average revenue gain of 35%, cost of 51%, and profit of 39% than the state-of-the-art approaches. 2021 M. S. Mekala et al. -
DATING APPS, FORMS OF ABUSE AND PERSONALITY TYPE
[No abstract available] -
Date Palm: Genomic Designing for Improved Nutritional Quality
Date palm (Phoenix dactylifera L.) is one of the oldest fruit trees known where a significant amount of breeding has been carried out to improve various agronomic and nutritional characteristics. Numerous studies have been done to improve the nutritional composition and quality of the fruit due to its significant biological properties. Various strategies have been formulated for improving the agronomic characters through biofortification as well as preserving through postharvesting techniques. Modern breeding practices using molecular markers have significantly helped to identify the phenotypic, as well as genotypic, diversity for the selection of superior date palm cultivars, advanced agronomic characters like nutritional quality, disease resistance, and yield. Availability of the whole genome sequence, organellar sequence, and genetic map of date palm has helped breeders in modification and improvement of the characteristics. With the availability of bioinformatic tools and gene editing knowledge, the nutritional composition of date palm can be effectively manipulated to develop better crops along with good agronomic characters and resistance to diseases. The authors have compiled the nutritional composition of date palm fruits and detail the strategies to edit the genome and improve nutritional quality. Springer Nature Singapore Pte Ltd. 2023.