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ON 3-DIMENSIONAL QUASI-PARA-SASAKIAN MANIFOLDS AND RICCI SOLITONS
The purpose of this paper is to study 3-dimensional quasi-para-Sasakian manifolds and Ricci solitons. First, we prove that a 3-dimensional non-paracosymplectic quasi-para-Sasakian manifold is an ?-Einstein manifold if and only if the structure function ? is constant. Further, it is shown that a Ricci soliton on a 3-dimensional quasi-para-Sasakian manifold with ?=constant is expanding. Moreover, we show that if a 3-dimensional quasi-para-Sasakian manifold admits a Ricci soliton, then the flow vector field V is Killing, and the quasi-para-Sasakian structure can be obtained by a homothetic deformation of a para-Sasakian structure. Besides, we study gradient Ricci solitons and prove that if a 3-dimensional non-paracosymplectic quasi-para-Sasakian manifold with ?=constant admits a gradient Ricci soliton, then the manifold is an Einstein one. Also, a suitable example of a 3-dimensional quasi-para-Sasakian manifold is constructed to verify our results. 2022 A. Razmadze Mathematical Institute of Iv. Javakhishvili Tbilisi State University. All rights reserved. -
A Novel Approach for Fractional (1 + 1 ) -Dimensional BiswasMilovic Equation
In this paper, we find the solution for (1 + 1 ) -dimensional fractional Biswas-Milovic (FBM) equation using the q-homotopy analysis transform method (q-HATM). The Biswas-Milovic equation is a generalization of the nonlinear Schringer (NLS) equation. The future scheme is the elegant mixture of q-homotopy analysis scheme with Laplace transform technique and fractional derivative considered in Caputo sense. To validate and illustrate the competence of the method, we examine the projected model in terms of arbitrary order. Moreover, the nature of the attained results have been presented in 3D plots and contour plots for different value of the order. The gained consequences show that, the hired algorithm is highly accurate, easy to implement, and very operative to investigate the nature of complex nonlinear models ascended in science and engineering. 2021, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Invariant Submanifolds of (?)-Sasakian Manifolds
In this paper, we consider invariant submanifolds of an (?)-Sasakian manifolds. We show that if the second fundamental form of an invariant submanifold of a (?)-Sasakian manifold is recurrent then the submanifold is totally geodesic. We also prove that, invariant submanifolds of an Einstein (?)-Sasakian manifolds satisfying the conditions (Formula presented) (X, Y) ? = 0 and (Formula presented)(X, Y) (Formula presented)? = 0 with ?r ? n(n 1) are also totally geodesic. 2020. All Rights Reserved. -
h-almost Ricci Solitons on Generalized Sasakian-space-forms
The aim of this article is to study the h-almost Ricci solitons and h-almost gradient Ricci solitons on generalized Sasakian-space-forms. First, we consider h-almost Ricci soliton with the potential vector field V as a contact vector field on generalized Sasakian-space-form of dimension greater than three. Next, we study h-almost gradient Ricci solitons on a three-dimensional quasi-Sasakian generalized Sasakian-space-form. In both the cases, several interesting results are obtained Kyungpook Mathematical Journal -
On (?)-Lorentzian para-Sasakian Manifolds
The object of this paper is to study (?)-Lorentzian para-Sasakian manifolds. Some typical identities for the curvature tensor and the Ricci tensor of (?)-Lorentzian para-Sasakian manifold are investi-gated. Further, we study globally ?-Ricci symmetric and weakly ?-Ricci symmetric (?)-Lorentzian para-Sasakian manifolds and obtain interesting results. 2022 Academic Center for Education, Culture and Research TMU. -
The zamkovoy canonical paracontact connection on a para-kenmotsu manifold
The object of the paper is to study a type of canonical linear connection, called the Zamkovoy canonical paracontact connection on a para-Kenmotsu manifold. 2021 D. G. Prakasha et al. -
Static perfect fluid space-Time and paracontact metric geometry
The main purpose of this paper is to study and explore some characteristics of static perfect fluid space-Time on paracontact metric manifolds. First, we show that if a K-paracontact manifold M2n+1 is the spatial factor of a static perfect fluid space-Time, then M2n+1 is of constant scalar curvature-2n(2n + 1) and squared norm of the Ricci operator is given by 4n2(2n + 1). Next, we prove that if a (?,?)-paracontact metric manifold M2n+1 with ? >-1 is a spatial factor of static perfect space-Time, then for n = 1, M2n+1 is flat, and for n > 1, M2n+1 is locally isometric to the product of a flat (n + 1)-dimensional manifold and an n-dimensional manifold of constant negative curvature-4. Further, we prove that if a paracontact metric 3-manifold M3 with Q? = ?Q is a spatial factor of static perfect space-Time, then M3 is an Einstein manifold. Finally, a suitable example has been constructed to show the existence of static perfect fluid space-Time on paracontact metric manifold. 2022 World Scientific Publishing Company. -
A Critical analysis of the law relationg to elementary education in india Viz-A-Viz Minimum level of learning
The demand for free and compulsory education started in the British period. newlineThe framers directed that the object of Article 45 must be achieved within ten years newlineof the commencement of the constitution. After several judicial strictures the newlineConstitutional (Eighty Sixth) Amendment Act 2002 (Amendment Act, 2002) declared education as a fundamental right. To execute this mandate the Children Right to Free and Compulsory Education Act 2009 (RTE Act, 2009) was passed. However, the government has failed to fulfil the mandate of giving quality education in terms of minimum level of learning under the RTE Act. One of the newlineparameters of the Quality Monitoring Tool under Sarva Shiksha Abhiyan (SSA) is newlineto give quality education in terms of minimum level of learning. But, when it was newlinerealized that the children from Government schools are completing their primary newlineeducation without minimum level of learning, three amendments had been made to the RTE Act 2009, i.e., during 2012, 2015 and 2019. Yet, the latest Annual Survey on Education Report shows that there is poor minimum level of learning among children who have completed their primary education in government primary newlineschools. Thus, the purpose of this research is to critically analyse the RTE Act 2009 newlineand the subsequent amendments to the Act of 2009 and to study various policies and schemes under SSA, to explore the reasons for low level of learning in government primary school and to make suggestion to improve the minimum level of learning. -
A critical analysis of the law relating to elementary education in India viz-a-viz minimum level of learning /
The “demand for free and compulsory education” started in the British period. The framers directed that the object of Article 45 must be achieved within ten years of the commencement of the constitution. After several judicial strictures the Constitutional (Eighty Sixth) Amendment Act 2002 (Amendment Act, 2002) declared ‘education’ as a fundamental right. -
Nutraceuticals to prevent and manage cardiovascular diseases
Unhealthy lifestyle and diet are the key risk factors to cardiovascular diseases. A healthy cardiac and vascular system can prevent cardiovascular-related diseases like hypertension, atherosclerosis, and heart stroke. Identifying pharmacologically important metabolites had paved the way to contemporary medicine. People are more attracted to them as they are majorly plant-based metabolites such as polysaccharides, polyphenols, polysterols, and vitamins as cardio-protectors. Preclinical, clinical, and animal studies provide substantial data confirming nutraceuticals as a promising therapeutic agent in curing cardiovascular diseases. This chapter summarizes on major bioactive molecules as nutraceuticals with preclinical and clinical studies, emphasising their cardiovascular protective roles. 2023 Elsevier Inc. All rights reserved. -
Detection and Classification of Thoracic Diseases in Medical Images using Artificial Intelligence Techniques: A Systematic Review
Artificial Intelligence is at the leading edge of innovation and is developing very fast. In recent studies, it has played a progressive and vital role in Computer-Aided Diagnosis. The chest is one of the large body parts of human anatomy and contains several vital organs inside the thoracic cavity. Furthermore, chest radiographs are the most commonly ordered and globally used by physicians for diagnosis. An automated, fast, and reliable detection of diseases based on chest radiography can be a critical step in radiology workflow. This study presents the conduction and results of a systematic review investigating Artificial Intelligence Techniques to identify Thoracic Diseases in Medical Images. The systematic review was performed according to PRISMA guidelines. The research articles published in English were filtered based on defined inclusion and exclusion criteria. The Electrochemical Society -
Comparison of Augmentation and Preprocessing Techniques for Improved Generalization Performance in Deep Learning based Chest X-Ray Classification
Convolutional Neural Network (CNN) models are well known for image classification; however, the downside of CNN is the ineffectiveness to generalize and inclination towards over-fitting in case of a small train dataset. A balanced and sufficient data is thus essential to effectively train a CNN model, but this is not always possible, especially in the case of medical imaging data, as often patients with the same disease are not always available. Image augmentation addresses the given issue by creating new data points artificially with slight modifications. This study, investigates ten different methods with various parameters and probability and their combined effect on the test dataset's generalization performance and F1 Score. For the study, three pre-Trained CNN models, namely ResNetl8, ResNet34, and ResNet50, are fine tuned on a small training dataset of 500 Pneumonia and 160 Non-Pneumonia(Normal) Images for each augmentation setting. The test accuracy, F1 Score, and generalization performance were calculated for a test dataset consisting of 50 Pneumonia and 16 Non-Pneumonia(Normal) Images. 2022 IEEE. -
DEVELOPMENT AND EVALUATION OF PNEUMFC NET: A NOVEL AUTOMATED LIGHTWEIGHT FULLY CONVOLUTIONAL NEURAL NETWORK MODEL FOR PNEUMONIA DETECTION
The aim of this study is to address the challenges of pneumonia diagnosis under constraint resources and the need for quick decision making. We present the PneumFC Net, a novel architectural solution where our approach focuses on minimizing the number of trainable parameters by incorporating transition blocks that efficiently manage channel dimensions and reduce number of channels. In contrast to using fully connected layers, which disregard the spatial structure of feature maps and substantially increase parameter counts, we exclusively employ only convolutional layer approach. In the study, X-ray image dataset is used to train and evaluate the proposed Convolutional Neural Network model. By carefully designing the architecture, the model achieves a balance between parameters and accuracy while maintaining comparable performance to pre-trained models. The results demonstrate the model's effectiveness in detecting pneumonia images reliably. In addition, the study examines the decision-making process of the model using Grad-CAM, which helps to identify important aspects of radiographic images that contribute to the positive pneumonia prediction. Furthermore, the study shows that the proposed model, Pneum FC Net not only has the highest accuracy of 98%, but the total trainable model parameters is only 0.02% of the next best model VGG-16, thus establishing the potential of this new robust Deep Learning model. This research primarily addresses concerns related to mitigating significant computational requirements, with a specific focus on implementing lightweight networks. The contribution of this work involves the development of resource-efficient and scalable solution for pneumonia detection. 2024 Little Lion Scientific. All rights reserved. -
Gray Level Co-occurrence Matrix based Fully Convolutional Neural Network Model for Pneumonia Detection
This study presents a new method to improve the detection ability of a convolutional neural network (CNN) in pneumonia detection using chest X-ray images. Using Gray-Level Co-occurrence Matrix (GLCM) analysis, additional channels are added to the original image data provided by Guangzhou Children's Hospital in Guangzhou, China. The main goal is to design a lightweight, fully convolution network and increase its available information using GLCM. Performance analysis is performed on the new CNN model and GLCM-enhanced CNN model, and results are compared with Transfer Learning approaches. Various evaluation metrics, including accuracy, precision, recall, F1 score, and AUC-ROC, are used to evaluate the improved analysis performance of CNN. The results showed a significant increase in the ability of the model to detect pneumonia, with an accuracy of 99.57%. In addition, the study evaluates the descriptive properties of the CNN model by analyzing its decision process using Grad-CAM. 2024, J.J. Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology. All rights reserved. -
Social media strategies of royal challenges Bangalore team and perception of its fans /
Indian Premier League (IPL) buzz is primarily driven by marketing actions of the broadcaster, Here the researcher brings out the key aspects for the success of Royal Challengers Bangalore (RCB) franchise through social media part of sports communication to connect with their fans to build a brand identity, manage reputations, and engage fans through various clubs. -
An efficient deep learning based stress monitoring model through wearable devices for health care applications
Due to the mental stress of the human, the negative effects are known to be recent decades. Early detections of high level stresses are necessary to stop harmful consequences. Studies have proposed on wearable technologies which detect human stress. This study proposes stress detection systems which use physiological signals of people collected by wearable technologies and attached to human bodies. They can carry it during their daily routine. This works proposed system includes removal of artifacts in bio signals and feature extractions from these cleaned signals. Since, DL (deep learning) based models are proven to be the best for these analyses, this article uses a random differential GWO (Grey wolf optimization) algorithm for feature extraction and a ML (machine learning) algorithm called RF (random forest) has been used for classification of the human body parameters like activities of the heart, conductance in skins and corresponding accelerometer signals. The proposed stress detection system is implemented with the real time data gathered from 21 participants. This approach can detect the stress of a human and prevent it from early stages with necessary lectures to avoid the negative effects. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Market Reaction to Dividend Announcements During Pandemic: An Event Study
This study analyses the difference in stock market reactions to dividend announcement during the pandemic. The thirty constituent stocks of Sensex, the index of Bombay Stock Exchange (BSE), is used for analysis. This allows cross-industry comparison of the market reaction. The study examines stock market reactions covering 44 days around the dividend announcement dates. The primary objective of this study is to understand whether the price adjustment linked to the dividend announcement news during the pandemic was different from the earlier years. This empirical study employs the conventional event study methodology using abnormal returns (ARs) to examine the stock market reaction to dividend announcement. The market reaction to dividend announcement was increasingly positive during the pandemic, compared to previous years. The statistical pooled t-tests showed there was a significant relationship between the pandemic and ARs. The findings also indicate that the difference in the market reaction to dividend announcement was more prominent in services stocks than that in manufacturing. Further, the results also verify the weak-form of efficiency of Indian stock exchange. 2021 Management Development Institute. -
Green Bonds Driving Sustainable Transition in Asian Economies: The Case of India
On September 25, 2015, 193 countries of the United Nations (UN) General Assembly, signed the 2030 Agenda to work towards attaining 17 Sustainable Development Goals (SDGs) and its associated 169 targets and 232 indicators. With one of the largest renewable energy programs, India is well-poised to be a role model for low-carbon transformation to other Asian countries. However, bridging the financing gap is critical to ensure that the country meets its SDG targets. Though the SDGs identified by the UN are broad-based and interdependent, for ease of analysis we have grouped them into five themes people, planet, prosperity, peace, and partnership based on existing UN models. This paper investigates the financing gap for green' projects linked to planet-related SDG targets in India. It builds an argument for utilizing green bonds as an instrument to bridge the gap. After establishing the potential of green bonds in raising the finance to meet India's planet-related SDG targets, we look at the current policy landscape and suggest recommendations for successful execution. The paper concludes that deepening of the corporate fixed income securities market and firming up guidelines in line with India's climate action plans are inevitable before green bonds can be considered a viable financing option. 2021. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. All rights reserved. -
A review of innovative bond instruments for sustainable development in Asia
Purpose: Advancing the economies in Asia toward meeting sustainable development goals (SDGs) needs an unprecedented investment in people, processes and the planet. The participation of the private sector is necessary to bridge the financing gap to attain this objective. Engaging the private sector can contribute significantly to attaining the 2030 agenda for SD. However, the financial markets in Asian economies are yet to realize this potential. In this context, this paper aims to discuss the state of finance for SD in Asia and identifies innovative financial instruments for attracting private investments for SDs in these economies. Design/methodology/approach: This study relies on published articles, reports and policy documents on financing mechanisms for SD. The literature review covered journal data sources, reports from global institutions such as the UN, World Bank, International Monetary Fund and think-tanks operating in the field of climate change policies. Though the topic was specific to financial market instruments, a broader search was conducted to understand the different sources of sustainable finance available, particularly in Asia. Findings: The investments that are required for meeting the SDGs remain underfunded. Though interest in sustainability is growing in the Asian economies, the financial markets are yet to transition to tap the growing interest in sustainable investing among global investors. This paper concludes that to raise capital from private investors the Asian economies should ensure information availability, reduce distortions and unblock regulatory obstacles. It would also need designing policies and introducing blended financing instruments combining private and public funds. Research limitations/implications: Though the study has grouped Asian economies, the financing strategy for SDGs should be developed at the country-level considering the domestic financial markets, local developmental stage, fiscal capacity and nationally determined contributions. Further research can focus on developing country-specific strategies for using innovative financial instruments. Originality/value: Mobilizing funds for implementing the 2030 Agenda for SD is a major challenge for Asian economies. The paper is addressed to national policymakers in Asian economies for developing strategies to raise capital for SD through private participation. It provides opportunities for revisiting national approaches to sustainable finance in these economies. 2021, Emerald Publishing Limited. -
2,2,6,6-Tetramethylpiperidinyloxyl (TEMPO) Radical Mediated Electro-Oxidation Reactions: A Review
Over the last few decades, the interest in green and sustainable chemistry has led to the development of different synthetic methodologies which utilize clean reagents. In that direction, the electro-oxidation reactions are considered as one of the most interesting and promising methods. This is predominantly due to their environmentally benign nature, as oxidation can be achieved without the need for commonly used oxidizing agents. 2,2,6,6-Tetramethylpiperidinyloxyl radical commonly known as TEMPO is a stable aminoxyl radical utilized for the oxidation of various classes of alcohols to carbonyl compounds by using cyclic voltammetry. The present review focuses on the various electrochemical reactions utilizing TEMPO as a mediator such as the oxidative conversion of alcohols, carbohydrates, amines, sulphur-containing compounds, and alkenes in both laboratory as well as industrial scales and covers literature from 1950 till present date. The properties, reactivity, and yield percentages of these reactions would provide a basis for better electrocatalyst design in future studies involving TEMPO and its derivatives as mediators. 2021 Wiley-VCH GmbH