Overview of Indexes Used in NOSQL Databases of MongoDB Architecture

The present day transactions result into petabytes of data collected and the credit almost goes to the booming ICT industry. The data received is able to detect the hidden patterns for the enterprises and research industry and help them to improve their traditional methods. However the data is unstructured and requires new innovative technologies to be implemented in the architecture handling big data. In the present paper, we have tried to explore the NOSQL database handling techniques and specifically the indexes that help to reduce the time complexity to handle the unstructured data. This paper is divided into four sections where the first section compares the DBMS and DSMS followed by the literature review on this technique and introduction to the MongoDB architecture and overview of NOSQL databases. The fourth section handles the types of the databases, it’s index types. Fifth section describes the performance comparison of the various MongoDB with RDBMS

Data Classifier for Encryption in Cloud

The aim of this project is to provide the cloud security infrastructure with a security policy such that the data encryption takes place as per need of data and provide suitable security to data based on the security needs of data with resource optimization in mind, as most of the data stored in cloud database would not be a classier document. Some of, or a high percentage of, data must be no encryption required-data. A model is needed which would not only classify the data but also handle the security concerns of data according to class which could be based on any security parameter, security criteria, or a set of conditions which are to be decided in accordance with the cloud service provider .On the basis of these predefined security criteria classes are formed and eventually various types of policies can be applied to the classes for which the cloud service provider agrees and is capable of. The data have different values and characteristics that must be identified before sending to cloud severs. As per the literature review so far the model present is a combination of K-Nearest Neighbor (K-NN) classifier and the Rivest, Shamir and Adelman (RSA) algorithm ,where data is classi?ed into sensitive and non sensitive data ,only the sensitive data is encrypted using RSA algorithm. In a cloud server, the data are stored in two ways. First encrypt the received data and store on cloud servers. Second store data on the cloud servers without encryption. As the literature states, after implementing this model it is found that the confidentiality level of data is increased and this model is proved to be more cost and memory friendly for the users as well as for the cloud services providers. This classi?cation technique uses binary number of class. The sensitivity of data can vary from more than just two levels. The data can grow two large to handle by K-NN and better technique exists to handle large data sets. For encryption any outsource algorithm would do more appropriate for cloud environment. This project proposes a model with more number of target classes which can handle the sensitivity of data more precisely and satisfy the need of security architecture. The model uses decision tree induction algorithm for classifier and the encryption algorithm can be used in varieties with a single class with no encryption. The classified data is then loaded into the servers into different data centres. The model aims at classi?cation of data on basis of various security parameter or cloud policies

NLO QCD Corrections to BcB_c-to-Charmonium Form Factors

The $B_c(^1S_0)$ meson to S-wave Charmonia transition form factors are calculated in next-to-leading order(NLO) accuracy of Quantum Chromodynamics(QCD). Our results indicate that the higher order corrections to these form factors are remarkable, and hence are important to the phenomenological study of the corresponding processes. For the convenience of comparison and use, the relevant expressions in asymptotic form at the limit of $m_c\rightarrow0$ for the radiative corrections are presented

Adherence to self-administered tuberculosis treatment in a high HIV-prevalence setting: a cross-sectional survey in Homa Bay, Kenya.

Good adherence to treatment is crucial to control tuberculosis (TB). Efficiency and feasibility of directly observed therapy (DOT) under routine program conditions have been questioned. As an alternative, Médecins sans Frontières introduced self-administered therapy (SAT) in several TB programs. We aimed to measure adherence to TB treatment among patients receiving TB chemotherapy with fixed dose combination (FDC) under SAT at the Homa Bay district hospital (Kenya). A second objective was to compare the adherence agreement between different assessment tools

A Wearable Glove for Measuring Fingers Flexion to Identify Specific Hand Gestures Using Flex Sensors

This paper presents a special method of communication for the speech impaired people and other patients using their hand gestures. A microcontroller based system has been developed for measuring fingers flexion to identify specific hand gestures using flex sensors. The system is made wearable and has been deployed on a glove. To measure the fingers flexion for a specific hand gesture five flex sensors are tailored for each finger on the glove. These flex sensors produce signals corresponding to different hand gestures and finger movements. Flex sensors simply change their resistance values according to the degree of bend angle made. They convert the change in bend to electrical resistance-the more the bend, the more is the resistance value. The system has been built around a widely used eight bit microcontroller ATMega328P that has a built-in 10-bit multiplexed channel Analog-to-Digital Converter for the signal conditioning purpose. The important factors while designing a glove is the calibration, the finger size, height and thickness varies from patient to patient and these inaccurate measurements of parameter leads to overlapping of the sign

Altmetric Analysis of Highly Cited Publications on Digital Library in Brazil and India: A Comparative Study

In Library and Information Science, Altmetrics is one of the emerging metrics to capture the online attention of scholarly literature. The present paper is an attempt to do a correlation study of an altmetric score and citations received by the highly cited publications of Digital library in Brazil and India country during 1989-2017. The study reveals that India is the county which received altmetric attention as compared to Brazil. While doing Altmetric analysis, it was found that discipline wise, Librarians followed by PhD scholar are the maximum readers whereas subject-wise, Computer science professionals contribute the maximum readership followed by social science disciplines in India in the field of a digital library. So, it is the need of time to explore the area more so that altmetric would become one of the standard indicators to measure the research impact in a professional

Scroll-Time and Echo-Chambers: Effect of Mass Media on Ingroup Bias and Polarization

Information disseminated through mass-media has been known to significantly influence behaviors such as voting (Iyengar & Kinder, 1987), brand preferences (Tversky & Kahneman, 1981), and public opinion (McCombs & Shaw, 1972). More specifically, the way information is framed and presented in mass media (for instance through "breaking news" and "sensational headlines") can reinforce existing beliefs and contribute to political and ideological polarization, with partisan media creating "echo chambers" that deepen biases (Hobolt et al., 2024). The current study leverages these insights to investigate the effects of the echo-chambered media and the time available for information consumption in an intergroup context across three experiments. Going by the minimal group paradigm, Experiment 1 employed a randomized, untimed presentation (non-echo-chamber) of news about an ingroup and an outgroup, while Experiment 2 used a blocked, untimed design (echo-chamber), and Experiment 3 a blocked, timed design (echo-chamber, doomscroll). All experiments involved two news sources with varying reliability (low and high) disseminating valanced (positive/negative) intergroup news headlines, and the participants were asked about the degree to which they believed the specific news items. Results showed that the manner of news presentation and timing moderated ingroup favoritism, with higher propensity to believe positive ingroup than positive outgroup news and vice-versa for the negative news, with the most significant bias emerging in Experiment 2 and negative news bias in Experiment 3. These findings shed light on how patterns of media consumption may influence intergroup perceptions and lead to polarization in society

Trade Potential Of India With Mercosur Countries Using Revealed Comparitive Index Method

Founded in 1991, by signing a treaty of Asuncion among four founder member countries comprising of Argentina, Brazil, Uruguay and Paraguay is an intergovernmental association and was a beginner step to create free trade area. It’s been three decades from the establishment, the demise of southern cone common market has been announced several times; may it be Brazilian Devaluation(1999), Argentina Economic Crisis(2001- 02), Global Economic Crisis(2008) but still MERCOSUR has survived, deliver democratic stability, increased trade flows and international exposure to its member countries. In this research paper we will analyse the India’s trade potential with Mercosur countries for different product lines. This article will firstly review the historical evolution of MERCOSUR, then will discuss the trade potential of Mercosur nations and India and finally explores the challenges that are being faced

Enhancing Patient Outcomes in Intra-Aortic Balloon Pump Therapy: The Critical Role of Nurse-Led Interventions

Intra-aortic balloon pump (IABP) therapy is a vital intervention for patients with severe cardiac conditions, offering haemodynamic support in life-threatening situations. However, the success of this therapy depends significantly on the knowledge, skills, and care provided by nursing professionals. This comprehensive review explores the essential role of nurses in optimising IABP therapy, focusing on their key responsibilities, patient monitoring, and the delivery of compassionate, patient-centred care.The review outlines the evolution of IABP technology, its mechanism of action, and the common complications associated with its use, including limb ischaemia, infection, and bleeding. A key focus is the impact of nurse-led interventions in minimising these risks, ultimately improving patient recovery, reducing hospital stays, and enhancing survival rates. Evidence suggests that proactive nursing care, including vigilant monitoring and early detection of complications, plays a critical role in improving patient outcomes.Despite technological advancements, challenges persist in the effective use of IABP therapy, such as gaps in training, variations in nursing practice, and limited resources. To address these issues, the review emphasises the need for evidence-based guidelines, continuous professional education, and multidisciplinary collaboration. Integrating these elements ensures that nurses can provide high-quality care, enhancing the safety and effectiveness of IABP therapy.Additionally, this article highlights areas for further research into innovative technologies and nurse-led solutions that could enhance IABP management. It also underscores the need for policy reforms to support the implementation of best practices in healthcare systems, ultimately improving patient outcomes. Core Insight: Nurses are at the heart of optimising intra-aortic balloon pump (IABP) therapy, bridging technology with compassionate care. Their expertise in monitoring, early intervention, and patient-centred support significantly improves outcomes. Strengthening nurse-led interventions through evidence-based training and collaboration is essential to maximising IABP’s potential and transforming cardiac care

Investigation on the Involvement of Phytoconstituents in Endocrine Disorder: A Review

The endocrine system consists of various glands responsible for secreting hormones that regulate metabolism, growth, reproduction, and other physiological processes. Disruptions in this system, termed endocrine disorders, are linked to numerous health issues, such as obesity, diabetes, cardiovascular diseases, and metabolic syndromes. Moreover, the significance of factors such as life stage, gender and dietary habits in influencing health risks associated with endocrine disruption cannot be overstated. Synthetic medications for these conditions often have adverse side effects like hypoglycemia and heart complications, highlighting the need for alternative treatments. Herbal and natural remedies have shown promise in managing these disorders due to their lower toxicity and minimal side effects. Phytochemicals and poly-herbal therapies are emerging as effective strategies for addressing endocrine and metabolic disorders, influencing molecular targets like AMP-Activated Protein Kinase (AMPK) and nuclear factor erythroid-2- related factor (Nrf2). Specific disorders such as diabetes, Addison’s disease and hyperthyroidism are characterized by hormone imbalances, with molecular mechanisms involving insulin resistance, cortisol dysregulation, and thyroid dysfunction. Additionally, the role of factors such as life stage, gender, and dietary habits in modulating endocrine disruption-associated health risks is crucial. Natural products, including flavonoids, catechins, resveratrol, and terpenes, are being explored for their therapeutic potential in regulating hormone levels and improving metabolic health. Keywords: AMPK, Cardiovascular diseases, Diabetes, Endocrine system, Metabolic disorders