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Prevalence of Cardiovascular Diseases in South Asians: Scrutinizing Traditional Risk Factors and Newly Recognized Risk Factors Sarcopenia and Osteopenia/Osteoporosis
One of the primary reasons for complications and death worldwide are cardiovascular diseases (CVDs), with a death toll of approximately 18 million per year. CVDs include cardiomyopathy, hypertension, ischemic heart disease, coronary heart disease, myocardial infarction, heart attack, hearth failure, etc. Over 80% of the CVD mortality is recorded from lower and middle-income countries. Records from the past decade have highlighted the increase of CVDs among the South Asian populations, and the prime purpose of the review is to jot down the reasons for the steep spike in CVDs. Studies analyzing the causative factors for the increase of CVDs in South Asians are still to be verified. Apart from known predisposing and lifestyle factors, other emerging risk factors associated with CVDs, namely the musculoskeletal diseases sarcopenia and osteopenia, should be tracked to tackle research gaps in upcoming analyses. This requires loads of scientific efforts. With proper monitoring, the raising alarm that the CVD burden generates can be reduced. This review discusses the already established signs and recognizes important clues to the emerging etiology of CVDs in the Asian population and prevention measures to keep it at bay. 2023 Elsevier Inc. -
Prevalence of hypertension and determination of its risk factors in korangrapady, udupi district, coastal Karnataka, India
Objective: Hypertension is a global public health problem that estimates about 4.5% of overall disease burden. It is a general health challenge in economically developing and developed countries. High blood pressure prevalence is increased from 11.2% to 28% (p<0.001) and 2342.2% in rural and urban area according to the study done in Delhi for about 20 years. It is one of the important risk factors of cardiovascular disease, which is associated with morbidity and mortality. The aim was to identify the significant correlates of hypertension in a rural village in south India. Methods: Data were collected through a door-to-door survey among the residents of the village. Data collected was related to demographics and anthropometric measures. Blood pressure was measured with the help of the medical supervisor. Data were analyzed using Chi-square test for comparison between attributes. The potential hazard factor of hypertension was found by performing binary logistic regression model. Result: Of 299 participants considered for the study, 50 were hypertensive contributing to the overall prevalence of 16.72% with 95% confidence interval of 0.12920.2137, in which females have the prevalence rate of 17.8% and males with the prevalence rate of 15.5%. The study outcome identified education level, occupation, and family history of hypertension is the predicted risk factors. Conclusion: The high blood pressure prevalence is low and comparable with the studies conducted in other rural regions of India. More studies are, however, required to decide the appropriation and determinants of hypertension in different parts of this region. 2018 The Authors. -
Preventing Data Leakage and Traffic Optimization in Software-Defined Programmable Networks
The first widely used communication infrastructure was the telephone network, often known as a connection-oriented or circuit-switched network. While making a phone call, these networks will first set up a connection, and then tear it down after the call has ended. The connection made during the call would not be used again. Thus, connectionless or packet-switched networks have been introduced, with an aim to send voice signals as data packets. When compared to conventional network architecture, SDN's separation of the data plane and control plane of networking devices makes the management of these devices directly programmable via a centralised controller. It uses a MAS-based distributed architecture to categorise network flows, and it's called the Traffic Classification Module. Each host or server's high-priority application traffic is isolated via Deep Packet Inspection (DPI). The time consumed for a packet to travel from one endpoint to another is referred to as the average packet delay, whereas the controller's reaction time is twice the average packet delay. Few works existed that utilised routing strategies to decrease the typical packet delay in SDN. To reduce the controller's response time, Software-Defined Networks (SDNs) need a routing algorithm that reduces the average packet delay. Each of the proposed modules and the whole combined SDN-MASTE framework were put through their paces in a series of experiments and emulation-based tests to see how well they performed. 2023 IEEE. -
Prevention and Mitigation of Intrusion Using an Efficient Ensemble Classification in Fog Computing
Cloud services in fog network is a platform that inherits software services to a network to handle cloud-specific problems. A significant component of the security paradigm that supports service quality is represented by intrusion detection systems (IDSs). This work develops an optimization environment to mitigate intrusion using RSLO classifier on a cloud-based fog networks. Here, a three-layer approach namely the cloud, end point, and fog layers is used as a trio to carry out all of the processing. In the cloud layer, three layers of processing are required for handling the dataset metrics which are data transformation metrics, feature selection metrics, and classification processes. With log transformation, data is transformed using KS correlation-based filter which is used to choose a feature. The classification using an ensemble methodology of RideNN classifiers which is a Rider Sea Lion Optimization (RSLO), a created classifier, is used to tune the ensemble classifier. Physical work is carried out at another layer called an end point layer. A trained ensemble classifier is used for intrusion detection in the fog layer. A greater precision, recall, and F-measure were obtained with an accuracy approximately 95%, with all benefits of the suggested RSLO-based ensemble strategy. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Prevention of Child Sexual Abuse : A Protection Motivation Theory-Based Intervention for Mothers of Preadolescents
Child sexual abuse (CSA) is a growing concern in the world. Prevention of CSA in India is challenging due to deep rooted traditional values and beliefs. Sex and related matters newlineare difficult topics for parents to discuss. Lack of parental awareness leads to increased newlinerisk for CSA. Maternal care is the most influential aspect of child rearing and they need information and skills to educate children on sexual abuse. The literature review was based on Bloom s taxonomy for academic writing. The need for systematic and evidencebased approach in primary prevention was identified. The aim of this study was to test the efficacy of Protection Motivation Theory (PMT)-based psycho education program in enhancing mothers knowledge, attitude and sense of parental competence among mothers. An interactive mixed-method design embedding quantitative and qualitative methods selected 72 mothers as participants from Kannur, Kerala. Mothers aged between 30-40 years who had preadolescent children (8-12 years) were assigned to control and experimental group. A facilitator s psycho education manual was developed embedding PMT constructs for the intervention. The quantitative results indicated significant differences between the groups for CSA knowledge and attitude. The impact of the intervention was moderate to high. The qualitative results indicated the benefits of intervention. Mothers have overcome communication blocks, misconceptions regarding CSA education are cleared, are aware of risks and warning signs and are confident to deal with CSA disclosure. The involvement of mothers in the prevention program was found to be effective in this study. The findings of this study have important implications for developing theory- based interventions for CSA prevention. The application of systematic evidence-based interventions promotes active engagement of participants for applying the learnt skills effectively. The culturally sensitive issues like CSA needs more contextual understanding of the problems to find effective solutions. -
Prevention of Data Breach by Machine Learning Techniques
In today's data communication environment, network and system security is vital. Hackers and intruders can gain unauthorized access to networks and online services, resulting in some successful attempts to knock down networks and web services. With the progress of security systems, new threats and countermeasures to these assaults emerge. Intrusion Detection Systems are one of these choices (IDS). An Intrusion Detection System's primary goal is to protect resources from attacks. It analyses and anticipates user behavior before determining if it is an assault or a common occurrence. We use Rough Set Theory (RST) and Gradient Boosting to identify network breaches (using the boost library). When packets are intercepted from the network, RST is used to pre-process the data and reduce the dimensions. A gradient boosting model will be used to learn and evaluate the features chosen by RST. RST-Gradient boost model provides the greatest results and accuracy when compared to other scale-down strategies like regular scaler. 2022 IEEE. -
Price Discovery and Asymmetric Volatility Spillovers in Indian Spot-Futures Gold Markets
International Journal of Economic Sciences and Applied Research, Vol-5 (3), pp. 65-80. ISSN-1791-5120 -
Price Discovery of Currency Futures at NSE
The current study aimed to examine the causal relationship between the NSE currency future rates and currency spot rates in order to identify the price discovery mechanism at NSE market and its integration with foreign exchange market (spot market). To study the causal relationship between the said markets, we have considered daily closing rates for NSE currency futures and currency spot rates for selected pairs of currencies, i.e. USD/INR, GBP/INR, JPY/INR and EURO/INR. The data was obtained from www.nseindia.com and www.investing.com for the period from Jan-2010 to Sep-2017, which makes approximately 1750 observations for each currency pair in each market. It is found that the spot rate for JPY/INR leads the future rate. It is also identified that the spot rate for USD/INR does not cause the changes in futures. It indicates that the market integration between spot and futures at NSE for currency pair USD/INR is strong compared to other selected currency pairs. From the variance decomposition test we found that there is almost no impact of variance in USD/INR spot rate on future rate variance forecast errors. It implies that the causal relationship between for USD/INR spot and future rates is strong and mature compared to the measured causal relationships for the remaining currency pairs. This study concludes that the price discovery process for currency pair USD/INR is better at NSE currency futures among the selected currency pairs. Copyright 2022 by authors, all rights reserved. Authors agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License -
PRICE DISCOVERY, CAUSALITY, CONDITIONAL VOLATILITY & FORECASTING IN INDIAN FUTURES MARKET: EVIDENCE FROM 2001 - 2011
This work investigates the price discovery, causality, conditional volatility and forecasting in S&P CNX Nifty spot Market returns and S&P CNX Nifty Future Market Returns. The overall data study is classified into In-sample and Out-sample observations and the research work has been carried out by using the daily data from 1st January 2001 to Dec 31st 2011. The Out-sample analysis is carried on from 1st Jan 2011 to 31st Dec 2011. The dataset for the above analysis was retrieved from www.nseindia.com. The research also refines down with long term and short term dynamics of prices between spot and futures market by using various forecasting models such as Root Mean Square Error, Mean Absolute Error, Theil??s Inequality U test etc for Out- sample observation. Apart from this, the In-sample analysis has been carried out by Market Model, Johansen Cointegration test, Granger Causality test, Vector Error Correlation Model and GARCH Model. The results of the above tests indicate futures become the base for building up the spot, the causality tests and response analysis function indicate that future prices tend to discover new information more rapidly than spot, and the hence this will indicate more accurate forecasts of spot prices but not the spot to future and this price discovery function of futures prices has strengthened of homogenous structure of Index over recent years and it is disseminated in price discovery and risk management functions Keywords: Price Discovery, NSE, Volatility, GARCH, Cointegration, VECM JEL Classification: C22, C32, F47, G11 -
Price Minds: AI-Driven Insights, Recommendations and Dynamic Pricing
This research aims to enhance e-commerce systems by leveraging customer behavior analysis, dynamic pricing, and personalized recommendations. With the increasing demand for tailored shopping experiences and competitive pricing, businesses require adaptive solutions. The study integrates synthetic and real-time customer data to identify purchasing patterns and segment customers effectively. Dynamic pricing strategies are applied to optimize revenue while maintaining customer satisfaction. A unified framework combines clustering techniques, real-time data streams, and decision-making models to deliver actionable insights for business operations. The proposed system dynamically adjusts pricing and recommends products based on individual customer preferences and behavior. The approach addresses the growing need for intelligent systems that adapt to market trends and consumer demands. Results demonstrate improved operational efficiency, better customer engagement, and enhanced profitability. This work highlights the importance of real-time analytics and intelligent pricing mechanisms in advancing e-commerce and creating competitive advantages in rapidly evolving markets. 2025 IEEE. -
Pricing and content Netflixs dilemma in India
Learning outcomes: The learning outcomes of this study are as follows:1. Analyze the pricing strategy followed by Netflix in India;2. Examine the challenges faced by media companies, including over-the-top (OTT) service providers, in developing content for target consumers in emerging markets; and3. Evaluate the dynamics of the Indian OTT industry and understand the effect of external and internal factors on the growth of Netflix in India. Case overview/synopsis: This case discusses the dilemma faced by Netflix in India regarding pricing and content. Netflix was accused of hurting the religious and political sentiments of Indians by broadcasting bold shows such as Sacred Games and A Suitable Boy. Netflix is caught in a dilemma between its pursuit to achieve its target of achieving 100 million subscribers from India versus continuing its profitable high pricing strategy. Another key dilemma is regarding the streaming of attractive bold content which may occasionally hurt the religious/political sentiments of some Indians or stream only safe content which may be deemed as boring by its young target audience. Complexity academic level: Undergraduate and postgraduate students studying Marketing courses in Commerce and Business Management streams can use this case. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 8: Marketing. 2022, Emerald Publishing Limited. -
Pricing of liquidity risk in the indian stock market
Empirical literature from developed stock markets identifies liquidity risk to have impacts on the price of a stock. Given this, using one-minute trade and quote data of fifty stocks constituting the NIFTY 50 Index, this study examines the pricing of liquidity risk in the Indian stock market. The study uses thirteen liquidity measures identified from literature that cover the cost, quantity, time and multidimensional aspects of liquidity. The innovations in the liquidity measures are considered as the proxy for liquidity risk. Employing Generalized Methods of Moments estimation, the study proves that Indian investors expect to have a premium for holding securities that are illiquid when the whole market is illiquid. It proves liquidity risk as a priced factor and thus validates the liquidity-adjusted capital asset pricing model in the Indian stock market. It cautions the investors that the liquidity shocks can have significant inferences on portfolio diversification strategies to be adopted. 2020 GEA College – Faculty of Entrepreneurship. All rights reserved. -
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Primary mirror active control system simulation of Prototype Segmented Mirror Telescope
The upcoming large astronomical telescopes are trending towards the Segmented Mirror Telescope (SMT) technology, initially developed at the W M Keck Observatory in Hawaii, where two largest SMTs in the world are in use. SMT uses large number of smaller hexagonal mirror segments aligned and positioned by the use of three position/force actuators and six intersegment edge sensors. This positioning needs to be done within nanometer range to make them act like a monolithic primary mirror in the presence of different disturbances like wind, vibration & thermal effects. The primary mirror active control system of SMT does this important task at two levels. First at a global scale, by measuring edge sensor information continuously and commanding actuators to correct for any departure from the reference surface. And second at local actuator level, where all the actuators maintain their position to the reference control inputs. The paper describes our novel approach of primary mirror active control simulation of Prototype Segmented Mirror Telescope (PSMT) under design and development at Indian Institute of Astrophysics (IIA), Bangalore. The PSMT is a 1.5m segmented mirror telescope with seven hexagonal segments, 24 inductive edge sensors, and 21 soft actuators. The state space model of the soft actuator with Multiple-Input Multiple-Output (MIMO) capability is developed to incorporate dynamic wind disturbances. Further, a segment model was developed using three such actuators which accept actuator position commands from the global controller and telescope control system and yields tip-tilt-piston (TTP) of a single segment. A dynamic wind disturbance model is developed and used to disturb the mirror in a more realistic way. A feed forward PID controller is implemented, and gains are appropriately tuned to get the good wind rejection. In the last phase, a global controller is implemented based on SVD algorithm to command all the actuators of seven segments combined to act as a single monolithic mirror telescope. In this paper, we present the progress of PSMT active control system simulation along with the simulation results. 2017 IEEE. -
Prime Influential Factors Determining Prime Influential Factors Determining Employability of Engineering Graduates in Bangalore
The question of employability has risen as a problem worldwide. India produces around 400000 engineers every year. But, according to a study done by Nasscom, only one in four engineering graduates is employable. The remaining lagged in technical skills and know-how, ability to converse in English, make oral presentations or work in teams. According to a recent survey jointly carried out by the Federation of Indian Chambers of Commerce and Industry (FICCI) and the World Bank, 64 percent of surveyed employers are ??somewhat, ??not really or ??not at all satisfied with the quality of the engineering graduates skills. Graduates are found lacking in important skills like entrepreneurship, communication in English and use of modern tools and technologies. It has been argued that if colleges want to improve the employability of their graduates, they have to focus on reducing these important skill gaps through improvements in curriculum and teaching methods. The primary objective of the paper is to identify a set of factors that may have a bearing on the employability of engineering graduates in Bangalore and then find out how they are being rated by the institutions engaged in training these graduates on one hand and their prospective employers on the other and then find out the prime factors or dimensions influencing the kind of response received from each side, i.e. the institution and the industry. Lastly, if differences are found between the decisive factors or principal components of the industry and the institution, the study also intends to propose qualitative suggestions that can help to bridge the gaps thereby accelerating chances of employability of engineering graduates. -
Primordial Planets with an Admixture of Dark Matter Particles and Baryonic Matter
It has been suggested that primordial planets could have formed in the early universe and the missing baryons in the universe could be explained by primordial free-floating planets of solid hydrogen. Many such planets were recently discovered around the old and metal-poor stars, and such planets could have formed in early epochs. Another possibility for missing baryons in the universe could be that these baryons are admixed with DM particles inside the primordial planets. Here, we discuss the possibility of the admixture of baryons in the DM primordial planets discussed earlier. We consider gravitationally bound DM objects with the DM particles constituting them varying in mass from 20 to100 GeV. Different fractions of DM particles mixed with baryonic matter in forming the primordial planets are discussed. For the different mass range of DM particles forming DM planets, we have estimated the radius and density of these planets with different fractions of DM and baryonic particles. It is found that for heavier-mass DM particles with the admixture of certain fractions of baryonic particles, the mass of the planet increases and can reach or even substantially exceed Jupiter mass. The energy released during the process of merger of such primordial planets is discussed. The energy required for the tidal breakup of such an object in the vicinity of a black hole is also discussed. 2023 by the authors. -
Principles and clinical interventions in social cognition
There are a plethora of questions experts are asking surrounding the intersection of clinical intervention practices with social cognition. How do neuro-cognitive processes shape social understanding? What experimental methods illuminate social cognitive complexities? How can social cognition be applied practically in clinical contexts and psycho-social rehabilitation? How does social cognition influence decision-making and cross-cultural perspectives? To find the answers to these concerns, researchers can now look to Principles and Clinical Interventions in Social Cognition, a research book which delves into recent advances, practical applications, and future trajectories within the intricate relationship between social processes and cognitive mechanisms. It adopts a unique structure, each chapter offering a concise introduction to a specific aspect of social cognition. From foundational principles to applications in clinical interventions and individual well-being, it covers neuro-cognitive processes, experiments, and social cognition in various clinical and health conditions. This book stands out for its emphasis on the practical applications of social cognition in interventions and rehabilitation for clinical populations. By addressing the intersection of social psychology and cognition, it provides actionable insights and potential solutions to the complex challenges in the field. The content spans a broad spectrum, including attention and perception, affect, motivation, behavior, learning, memory, language, decision-making, attitudes, prejudice, stereotyping, theory of mind, self, and others. The interdisciplinary nature of this book makes it an authoritative resource for professionals, researchers, and students in psychology, neuropsychology, cognitive psychology, cognitive neuroscience, social work, sociology, management, allied health sciences, and other areas of social science. By offering a blend of historical context, cognitive processes, social behavior, and real-world applications, this book bridges gaps and offers a holistic understanding of social cognition. 2024 by IGI Global. All rights reserved. -
Prior Cardiovascular Disease Detection using Machine Learning Algorithms in Fog Computing
The term latent disease refers to an infection that does not show symptoms but remains forever. In this paper, proposed a novel methodology for addressing latent diseases in machine learning by integrating fog computing techniques. Here there is a link between HIV to heart disease, that is when a person progresses to the next stage of HIV, a plague infection develops, causing cholesterol deposits to form. Plaque development causes the inside of the arteries to constrict over time, which may stimulate the release of numerous heat shock proteins and immune complexes into the bloodstream, potentially leading to heart disease. Heart disease has long been considered as a significant life-threatening illness in humans. Heart disease is driven by a range of factors including unhealthy eating, lack of physical exercise, gaining overweight, tobacco, as well as other hazardous lifestyle choices. Five different classifiers are used to perform the precision; they are Support vector machine, K-nearest neighbor, decision tree, and random forest, after we have used the classifier, the recommended ideal will split disease into groups which is created based on their threat issues. This will be beneficial to doctors assisting doctors in analyzing the risk factors associated with their patients. 2023 IEEE. -
Prioritisation of Challenges in OTT Video Platforms: A Multi-criteria Decision-Making Approach
Over-the-top (OTT) video platforms have emerged as the preferred choice for on-demand entertainment. In this ever-changing landscape, OTT video platforms face many challenges to being relevant in the market. Identifying and prioritizing challenges is pivotal for the sustainable growth of OTT platforms. This paper aims to comprehensively examine and prioritize the challenges of the OTT video platform. The challenges are identified through an extensive literature review and unstructured interviews with six OTT industrial experts. The importance of each challenge is measured based on the analytical hierarchy process (AHP) to develop a hierarchy of those challenges. The AHP analysis results indicated customer retention as the most significant challenge, followed by content, customer experience, infrastructure, and bandwidth. The study is subjective to the experts opinions and available literature regarding the OTT platforms. The insights gleaned from this research are poised to offer substantial value to digital platform operators, media professionals, and managers. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Prioritisation of Challenges in OTT Video Platforms: A Multi-criteria Decision-Making Approach
Over-the-top (OTT) video platforms have emerged as the preferred choice for on-demand entertainment. In this ever-changing landscape, OTT video platforms face many challenges to being relevant in the market. Identifying and prioritizing challenges is pivotal for the sustainable growth of OTT platforms. This paper aims to comprehensively examine and prioritize the challenges of the OTT video platform. The challenges are identified through an extensive literature review and unstructured interviews with six OTT industrial experts. The importance of each challenge is measured based on the analytical hierarchy process (AHP) to develop a hierarchy of those challenges. The AHP analysis results indicated customer retention as the most significant challenge, followed by content, customer experience, infrastructure, and bandwidth. The study is subjective to the experts opinions and available literature regarding the OTT platforms. The insights gleaned from this research are poised to offer substantial value to digital platform operators, media professionals, and managers. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.