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A study on partial domination in graphs
The theory of domination is one of the most studied fields in graph theory. Many new domination parameters have been defined and studied so far. One such parameter that was introduced in 2017 is partial domination number. For a graph G = (V,E) and for a p ∈ (0,1], a subset S of V(G) is said to partially dominate or p-dominate G if |N[S]| ≥ p|V(G)|. The cardinality of a smallest p-dominating set is called the p-domination number and it is denoted by γp(G). In scenarios wherein domination concepts are applied, partial domination concepts can also be applied with the added advantage of being able to dominate the underlying graph partially, when the need arises. This advantage makes this parameter appear unique amongst most other domination parameters. We present some basic properties of partial dominating sets, some properties related to particular values of p, some properties related to the eccentricity of a p-dominating set, some results in the line of classical domination and characterization of minimal and minimum p-dominating sets. Then we study partial domination in the context of prisms of graphs. We give some bounds for partial domination numbers of prisms of graphs G in terms of partial domination numbers of G for particular values of p. We define universal γp-fixers and universal γp-doublers and we characterize paths, cycles and complete bipartite graphs which are universal γ 1 2 - fixers and universal γ 1 2 - doublers. Then we concentrate on establishing a domination chain in the context of partial
domination, which we call as ‘partial domination chain’. -
Purchase intention of deconstructed end-of-lifecycle fashion products in an online and offline retail environment
Obsolete or slow-moving inventory is one of the major influencers for the bottom line of any business today. Surplus stock- be it from overbuys, returns, defects or simply merchandise hitting the end of their lifecycle- need to be accounted, accommodated and dealt with in a manner that can least affect the planned margins. For the fashion newlinebusiness, such merchandise poses greater challenges. The business is ground by seasonal preferences, fast-changing trends, short lead-times and shorter shelf-lives. With rising costs of traditional retail businesses, the associated costs of carrying such inventory are something that the newlineretailer can easily do without. At the retailers end, such merchandise is newlineoften subjected to traditional liquidation methods such as Markdowns, carry forwards, or selling at lowered prices to discount stores or factory outlets. From a manufacturer s perspective, overruns from production newlineare either sold at discounted costs to the retailer or are diverted to other sources of sales. In either case, such decisions do affect the margins of the business, and retailers often account for these necessary evils while planning their pricing strategy. Liquidation methods for such obsolete merchandise also need to meet the additional challenge of maintaining the perceived value of the products, and to not adversely newlineaffect planned margins due to lowered price points. This study seeks to explore fashion consumers acceptance of Deconstructed or up-cycled fashion for such obsolete or EOLC (End-of-lifecycle) merchandise that newlineremain unsold. It also maps the Perceived value of such merchandise and explores the other factors that may affect the Purchase Intention of the merchandise, like the Internal reference price, Perceived monetary newlinesacrifice and Perceived quality. Through an experimental study, a comparative analysis is built across consumers in an E-commerce vs newlineOffline store purchase scenario, to derive if the method of presentation of such products affects the Purchase intention. -
IOT based prediction of rainfall forecast in coastal regions using deep reinforcement model
This research proposes an IoT based technique for predicting rainfall forecast in coastal regions using a deep reinforcement learning model. The proposed technique utilizes Long Short-Term Memory (LSTM) networks to capture the temporal dependencies between the rainfall data collected from the coastal regions and the prediction model parameters. The proposed technique is evaluated on a dataset of rainfall data collected from the coastal regions of India and compared to traditional methods of rainfall forecasting. The accuracy and reliability of these models are evaluated by comparing them to prior models. Precipitation in coastal locations may be predicted with an average accuracy of 89% using the suggested model, as shown by the results. The suggested framework is computationally efficient and can be trained with little input. The results of this research give strong evidence that the proposed model is an effective tool for coastal precipitation forecasting. 2023 The Authors -
A Lightweight LCDECG Model for Cardiovascular Diagnostics Using ECG Features
Cardiovascular disease (CVD) is among the leading causes of death around the world, requiring accurate and reliable diagnostics, and early detection. This project aims at the development of an efficient and accurate, lightweight model to classify heart rhythms based on an ECG.. In this paper, we propose the LCDECG (Lightweight Cardiac Diagnostic ECG) model, which integrates deep morphological feature extraction from ECG with clinically relevant handcrafted features. With MobileNetV2 used as a feature extractor and statistical descriptors of ECG signals, both the pathways are combined at the feature level for multi-class classification of cardiac conditions. Experiments conducted on the Dataset demonstrate better classification performance with 97.8% accuracy, 96.4% precision, 97.1% recall, and 96.7% F1-score over traditional neural networks alone or only statistical methods. The model is able to achieve the desired results as it only utilizes 2.43M parameters in its architecture, and therefore is amenable to real-time deployment in resource-scarce environments. Its use is advantageous for facilitating timely and early detection, which is necessary to improve patient survival and reduce healthcare costs through preventative treatment. Current ECG readings are based on manual assessment by trained cardiologists, which can be time-consuming and potentially subjective, depending on several professionals in the medical field evaluating the tracing. Due to the increased incidence of cardiovascular disease globally, and the limited number of professionals, particularly in developing countries, there is even greater need for automated convenient and trustworthy ECG tracing for diagnostic support. 2025 IEEE. -
Advancing precision medicine: Uncovering biomarkers and strategies to mitigate immune-related adverse events in immune checkpoint inhibitors therapy
Immune-related adverse events (irAEs) can have a major influence on patient outcomes, but their usage is frequently confounded by immune checkpoint inhibitors (ICIs), which have revolutionized cancer treatment by increasing anti-tumor immunity. With a focus on immunological dysregulation and the resulting tissue-specific toxicities, this review clarifies the fundamental processes of irAEs. We look at contemporary clinical treatment techniques to lessen the impact of these adverse events, such as the application of immunosuppressants and patient monitoring procedures. Additionally, it is emphasized how future research is necessary to find predictive biomarkers that can forecast the development of irAEs, allowing for early intervention and individualized therapy methods. In order to improve the therapeutic index of ICIs, we also examine the crucial balance between optimizing anti-tumor activity and reducing immunotoxicity. This study aims to further the existing discussion on enhancing the safety and effectiveness of ICI medicines, which will eventually improve cancer patient care, by pointing out possible research avenues. 2025 The Authors -
Dalit Activism
In the post-Ambedkar era, Dalit activism has expanded beyond traditional modes and methods of protest by adopting diverse strategies. This includes social media campaigns like #DalitLivesMatter, which align with global movements such as #BlackLivesMatter. It signals a shift towards more globalised and intersectional forms of protest. There is a notable transition from an exclusive focus on domestic advocacy to transnational alliances for greater impact. Caste-based oppression has been framed as a violation of fundamental human rights, which demands accountability from both national and international agencies. Many scholars find the gap between international advocacy for Dalit rights and grassroots-level Dalit activism quite concerning. Some scholars believe that Dalit activism has lost much of its transformative potential and revolutionary vigour, and the movement has been reduced to a mere pressure group. These political pitfalls allow us to understand the challenges and complexities of Dalit activism and the factors that shaped its course. This chapter aims to trace the trajectory of Dalit activism and provide a detailed background to facilitate a critical engagement with the concept of activism. It explores its historical progression, strategic shifts, and ongoing struggles to offer a comprehensive view of how Dalit activism has evolved into its current form. 2026 selection and editorial matter, Mahitosh Mandal and Sanjiv Kondekar; individual chapters, the contributors. -
Dalit Studies
Dalit Studies emerged as a pivotal academic discipline in South Asia in the 1990s with a unique set of research agendas that offer new frameworks for understanding caste, gender and marginalised identities. The field stands out for integrating theoretical frameworks into the lived experiences of caste-oppressed communities. It was shaped by the confluence of material, ideological and intellectual shifts, including the critique of caste-Hindu dominance in academia. By prioritising the experiences of Dalits, it bridges the gap between theory and practice and engages with critical debates on representation, particularly insider vs. outsider perspectives in articulating Dalit experiences. It equips the learners not only with intellectual tools but also with the skills to attain self-reliance and dignity in their socio-political lives. As a critical tool, it calls for a rethinking of knowledge production, methodology and representation. Its growing global relevance is evident in universities across the United States, the United Kingdom, and South Africa, where programs and courses explore the intersections of caste, race, and gender within broader contexts of subjugation and resistance. This chapter traces the evolution of Dalit Studies, examining its theoretical foundations, key concepts and debates, and its growing visibility in academic institutions worldwide 2026 selection and editorial matter, Mahitosh Mandal and Sanjiv Kondekar; individual chapters, the contributors. -
Secure Data Processing System Using Decision Tree Architecture
[No abstract available] -
Consuming Appetites, Disappearing Meals: Things Becoming Food in Chana Porters The Thick and the Lean
This paper aims to highlight the complex entanglements between the material and metaphorical meanings of food in literature through a close reading of Chana Porters The Thick and the Lean (2023). The novel follows the appetites and aspirations of three women in an alternative world where good food is taboo and culinary pleasures are forbidden; instead, abstinence from eating is hailed as the ultimate form of devotion. Drawing on Emma Roes conceptualization of things becoming food, this paper examines the mechanism through which foodstuff gainsor fails to gainmeaning in Porters food-averse universe. It argues that the novel challenges conventional perceptions of female appetites by reconfiguring edibility as constituted through intercorporeal as well as discursive practices. The paper approaches this process as a form of translation, contending that Porter integrates content and form to highlight the resistive potential of food and female appetites in capitalist food systems. 2025 Taylor & Francis Group, LLC. -
Experimentally optimizing a spinning disk by manipulating its mass distribution and radius
The scientific method enables the experimental study of complex phenomena by isolating key variables. This work explores the significant properties of spinning bodies. Optimizing spinning disks is the primary aim of this work. Optimization is achieved by manipulating the moment of inertia (MOI) of the disk, allowing a longer duration of spin and lowering the rate of energy dissipation. Experiments are designed and conducted to explore the relationship between the radius and mass distribution of the disk and the angular deceleration experienced by it. Effects of the same on energy retention is analyzed. Empirical data is interpreted graphically while accounting for systematic and random uncertainties. Percentage change in duration of spin as a result of percentage change in physical quantities is studied. Moving mass away from the central axis of the spinning disk increases its duration of spin from a constant initial angular velocity. Energy retention is also improved. Increasing the radius of the disk increases the duration of spin and reduces the rate of energy dissipation. The above conclusions are drawn from experiments where the mass and thickness of the disk are controlled along with other necessary factors that can influence the results. The experiments confirm the existing theory relating to the moment of inertia, angular quantities, resistive torques and kinetic energy of spinning disks. The experiments provide insights into the behavior of spinning disks in practical situations, especially in problems concerned with optimization in the field of mechanical engineering. 2026 Veeresha et al., published by Paradigm. -
Microbial biofertilizers: A sustainable agricultural approach to augment crop resilience against biotic and abiotic stresses
Increasing plant growth and yield with the aid of plant growth-promoting bacteria is a widely accepted, eco-friendly and economic approach in modern agriculture. Their use as an alternative to widely used harmful chemical fertilizers and pesticides can improve overall soil health and fertility, thereby enhancing crop yield. The positive modulation of genes related to growth and development, fruit formation, stress tolerance and phytohormone production helps plants significantly during maturation. Furthermore, the enhanced production and expression of defence-related hormones aid in survival under various stress conditions, such as drought, pH fluctuations, salinity and water stress. In addition, the application of growth-promoting bacteria, mainly from species such as Azospirillum, Bacillus, Klebsiella, Enterobacter, Pseudomonas, Azotobacter, Burkholderia, Rhizobium, Alcaligenes, Arthrobacter and Serratia supports plant growth and development by improving soil porosity, pH and salinity conditions. This review briefly outlines the role of the plant growth-promoting bacteria as microbial biofertilizers that enhance crop resilience under both biotic and abiotic stress conditions. By highlighting recent advances in understanding the mechanisms of microbe-plant interactions under these stresses, it also provides unique insights into how microbial biofertilizers can be employed for sustainable agriculture. This has direct relevance for policymakers and farmers by reducing dependence on chemical fertilizers, which have various negative impacts, thereby promoting long-term environmental sustainability and improved agricultural practices. (2025), (Science Press). All rights reserved. -
Magnetic iron oxide nanoparticles immobilized on microporous molecular sieves as efficient porous catalyst for photodegradation, transesterification and esterification reactions
Magnetic iron oxide nanoparticles were immobilized on microporous molecular sieves (13X) via a plant extract mediated green synthesis method. The prepared material was then characterized using XRD, FTIR, TGA, FESEM, and TEM techniques. The synthesized iron oxide nanoparticles-molecular sieves (Fe2O3/MS) composite showed excellent photodegradation of methylene blue (MB) at 99% efficiency. Enhanced photocatalytic properties were observed in comparison with the pure iron oxide (Fe2O3) nanoparticles synthesized. Catalytic conversion of triglycerides to fatty-acid ethyl esters (FAEE) was carried out using sunflower oil, and the reaction showed very good catalytic activity in the transesterification of sunflower oil, converting 84% of the sunflower oil to FAEE. The catalyst was also used in the esterification reaction and found to have excellent applicability. The catalyst showed excellent reusability, and easy separation from the reaction mixture using an external magnet. This enables the synthesized material to act as a promising photocatalyst in degradation and organic synthesis. Very few reports are available on the synthesis of magnetic iron oxide coated on molecular sieves and used for photodegradation, transesterification, and esterification catalysis. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Novel synthesis and dft calculations of 3-PHENYL-2-(1H-TETRAZOL-5-YL)acrylamdes under catalyst-free, one-pot cascade reaction /
Patent Number: 202141023459, Applicant: Jyothis Devasia.
The present invention offers a novel method for the synthesis of 3-phenyl-2-(1H-tetrazol-5-yl)acrylamides 4(a-g) under catalyst-free conditions. All the reactions were carried out in an one-pot cascade process starting with various aromatic/heteroaryl aldehydes, 2-cyanoacetamide and sodium azide at 110 oC using dimethylformamide (DMF) as a solvent. In addition, the reaction conditions were screened for optimization conditions towards solvent, catalyst, temperature and equivalence of sodium azide. -
Single activity recognition system: A review
Human Activity Recognition (HAR) plays an important role in smart home assisted living system which is one among the growing research area in smart computing. In this modern era, Smart home assisted living is highly recommended for elderly people to monitor and assist in taking care of themselves. HAR is applied in various ambiences to recognize single activity and group activity as well. This chapter focuses on single activity recognition system with respect to variety of sensors used in smart homes, activity recognition methods and wide range of communication systems that helps to ease the living style of elderly people in healthy environment which can be linked to the advancement of IoT technology in smart building. This chapter reviews many applications with variety of sensors, real time smart home projects, and smart home assisted living systems including activity recognition methods and communication systems. Springer Nature Switzerland AG 2020. -
The indian pulsar timing array data release 2: II. Customised single-pulsar noise analysis and noise budget
We present the results of customised single-pulsar noise analysis of 27 millisecond pulsars from the second data release of the Indian Pulsar Timing Array (InPTA-DR2). We model various stochastic noise sources present in the dataset using stationary Gaussian processes and estimate the noise budget of the InPTA-DR2 using Bayesian inference, involving model selection, Fourier harmonics selection, and parameter estimation for each pulsar. We check the efficacy of our noise characterisation by performing the Anderson-Darling test for Gaussianity on the noise-subtracted residuals. We find that all 11 pulsars with time baseline ? 2.5 yr show Gaussian residuals and do not have evidence for any red noise process in the optimal model, except for PSR J1944 + 0907, which shows presence of DM noise. PSRs J0437 - 4715, J1909 - 3744 and J1939 + 2134 show preference for the most complicated noise model, having achromatic and chromatic red noise processes. Only 4 out of 15 pulsars with time baseline ? 2.5 yr show significant non-Gaussianity in noise-subtracted residuals. We suspect that this may require more advanced methods to model noise processes properly. A comparative study of six pulsars with data removed near solar conjunctions showed deviations from the parameter estimates obtained with the original dataset, indicating potential bias in red noise processes due to unmodeled solar-wind effects. The results presented in this work remain broadly consistent with the InPTA-DR1 noise budget, with better constraints obtained on noise processes for several pulsars and support for achromatic red noise in PSR J1012 + 5307 due to the extended time baseline. 2026 The Author(s). -
Human gut microbiota and regulation of human behavior
The human body is often referred to as a microbiome, embodying a multitude of microbes. Specifically, the gut microbiome constitutes a cluster of bacteria within the gastrointestinal (GI) system. In both healthy individuals and those facing health issues, these bacteria significantly impact human physiology. They form an integral part of the unconscious system that exerts influence over human behavior. Globally, researchers are actively investigating the components of a good gut microbiome to enhance our comprehension of the role gut microorganisms play in health and disease. The gut harbors a diverse array of bacteria, encompassing both hazardous and beneficial types. Furthermore, studies on specific health-improving parasitic species are yielding biological insights that may propel the development of novel drugs. The gut microbiome directly impacts an individual's health by secreting physiologically active compounds like vitamins, essential amino acids, and lipids. Moreover, it indirectly influences the immune system and metabolic functions, thereby affecting moods and cognitive functions. Recognition of the role played by gut microbiota extends to various diseases and disorders. Evidence demonstrates significant interactions between the microbiome and certain drugs, profoundly shaping their intended effects. The interplay between the immune system, gut microbiota, and psychiatric disorders such as eating disorders, as well as conditions like cancer, autoimmune diseases, and autism spectrum disorder, is increasingly evident through ongoing research. This is unsurprising given the pivotal roles played by daily caloric intake, eating habits, and food composition in regulating various biological systems. Recent research sheds light on the intricate gut-brain axis (GBA), a two-way communication system where the gut receives signals from the brain, and vice versa. Microbes in the GI tract produce neurotransmitters that influence crucial functions like learning, memory, attention, and emotions. Even a slight change in the gut microbiome can lead to inflammatory reactions, connecting to the hypothalamic-pituitary-adrenal (HPA) axis and influencing human behavior. Under stressed conditions, changes in the gut microbiome can harm helpful bacteria, reduce the variety of bacteria in our gut, and allow harmful bacteria to grow. This makes us more likely to get sick and causes inflammation in our gut. Some studies even suggest that chemicals produced by the gut during an infection can affect our brain, making us more prone to feeling anxious or depressed. Knowing that our gut microbiome influences our behavior, it's essential to pay attention to what we eat, avoid drugs that harm our gut bacteria, and consider taking probiotic supplements in our diet. 2025 Elsevier Inc. All rights reserved. -
International Competences for Undergraduate Psychology: Relevance to the United Nations Sustainable Development Goals
The 17 global goals of the United Nations Sustainable Development Goals (SDGs) are a call to action for governments and organizations around the world to work towards a sustainable future for all people and the planet. Human behaviour is directly or indirectly tied to all of the SDGs; therefore, psychology as a discipline is critical to their achievement. In this article, wea team of 12 psychology educators from eight countries (three from the Global South) representing six continentsoutline connections between psychology and the SDGs. We argue that psychology education at the foundational undergraduate level should integrate the SDGs into curricula. We describe the framework of psychological literacy that we believe is central to a strong undergraduate education in psychology and outline its conceptual relationship to the SDGs. We then describe the International Competences for Undergraduate Psychology, which explicitly mention the SDGs, but are also closely linked to them across all seven International Competences for Undergraduate Psychology competence categories (psychological knowledge, psychological research methodologies and methods, and the five psychology-relevant areas: values and ethics; cultural responsiveness and diversity; critical thinking and problem-solving; communication and interpersonal skills; and personal and professional development). Finally, psychology educators from six countries (Aotearoa New Zealand, Australia, Brazil, Cameroon, India, and the United States) describe teaching and assessment strategies that harness both the International Competences for Undergraduate Psychology and the SDGs. These strategies offer examples to spur psychology educators to consider how they might make these connections in their own classes and curricula and in their own culture and context. 2025 Canadian Psychological Association -
The Impact of Cryptocurrency Trading on Economic Growth in GCC Countries: An Empirical Analysis
This study explores the impact of cryptocurrency trading on economic growth in Gulf Cooperation Council (GCC) countries from 2016 to 2019, with GDP as the measure of economic growth. The analysis reveals a substantial positive relationship between cryptocurrency trading volume and GDP using Ordinary Least Squares (OLS) and Generalized Linear Models (GLM) regression techniques. The analysis underscores the role of increased cryptocurrency market activity in fostering economic growth and advancing the GCC economies integration into global financial frameworks. This highlights the transformative potential of cryptocurrencies as a driver of economic progress within the region. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Effect of Coriolis force on Rayleigh-Bard convection with internal heat generation
The objective of this paper is to analyze the influence of the Coriolis force and internal heat source on Rayleigh-Bard convection in a Boussinesquian fluid of depth d. A linear theory which is oriented towards the normal mode analysis technique is used for this mono-diffusive convection in order to find the criteria for the onset of Rayleigh-Bard convection. The eigenvalue of the said problem was obtained by the use of the Galerkin method in the cases of rigid-rigid, rigid-free, and free-free velocity boundary combinations considering the isothermal and adiabatic temperature boundaries that determine the stability of the system. The effects of various parameters, Taylor number and the internal Rayleigh number are put under consideration only for stationary convection. Treating Taylor number as a critical parameter, shown that it plays a major role in stabilization of the system in case of any particular infinitesimal disturbance. The destabilization of the system has been possible with rotation by treating internal Rayleigh numbers as a critical parameter since the increase in values of the internal Rayleigh number advances the onset of convection. Oscillatory convection seems highly improbable as the scaled frequency of oscillation remains less than 0 for all combinations of Prandtl number, internal Rayleigh number, and Taylor number. 2019, Accent Social and Welfare Society. All rights reserved. -
Heat and mass transfer of triple diffusive convection in viscoelastic liquids under internal heat source modulations
The influence of sinusoidal (trigonometric cosine [TC]) and nonsinusoidal waveforms (square, sawtooth, and triangular) of internal heat source modulation on triple diffusive convection in viscoelastic liquids is investigated. An Oldroyd-B type model is taken into account for viscoelastic liquids. Nonlinear analysis is carried out using a truncated representation of the Fourier series. To analyze the heat and mass transfer over a triply diffusive liquid layer, expressions for average Nusselt and average Sherwood numbers are derived using 8-mode generalized Lorenz equations. The transient behavior of Nusselt and Sherwood numbers is analyzed on different parameters of the problem. From the results, it is found that the internal heat source enhances the heat transfer and diminishes the mass transfer while the heat sink diminishes the heat transfer and enhances the mass transfer. The results for respective waveforms are obtained for each parameter and it is found that the maximum heat and mass transfer occurs due to TC waveform. The limiting cases of viscoelastic liquids (Newtonian, Oldroyd-B, Maxwell, and RivlinEricksen) have been tabulated and corresponding results for each of the waveforms onheat and mass transfer have been shown. 2021 Wiley Periodicals LLC