Volume 12 | Issue 4

 Abstract

In addition to being a science, medicine is also an art. It deals with the fundamental processes of life, which must be comprehended before they can be guided; it does not consist of manufacturing pills and plasters.The number of products based on novel drug delivery systems has grown dramatically in recent years, and it is anticipated that this trend will continue. When it comes to dose forms, tablets are more relevant and convenient than other types. Higher selectivity products for drugs used in medical treatments are made possible by innovations in tablet dosage forms. Tablets are the most widely used dosage form today, making up about 70% of all ethical pharmaceutical preparations produced. They can be made directly from powders, granules, pellets, or film-coated multiple units. Tablets are defined as solid pharmaceutical dosage forms containing drug substances with or without suitable diluents and prepared by either compression or moulding methods. Therefore, tablets can be broadly classified as compressed tablets and moulded tablets. Compressed tablets can be further classified as directly compressible tablets, chewable tablets and tablet triturates etc

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Tablets , Types of tablet, manufacturing methods

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Diabetes is a common chronic disease in mostly all countries worldwide. The most commonly used method to measure glucose level in blood is an invasive method which is painful, expensive and danger in spreading infectious diseases. Over a long term, the invasive method results in damage of finger tissues. As an alternative, the Non-invasive method can be used which facilitates frequent testing, relieves pain and discomfort caused by frequent finger pricks. A Non-invasive method of glucose level measurement is proposed. The variation in the intensity of NIR light received from the photo detector after passing through the finger is used to determine the glucose level of blood. The measured glucose level is displayed in LCD display and also transmitted to the android application which is created in the mobile phone to display and store data via Bluetooth.

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 Keywords

HC-05 Bluetooth Module, Arduino UNO, NIR module

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The main objective of this project is to design a secure ATM system using multi-factor authentication system. The use of ATM machines is increasing day by day but fraud is also increasing rapidly. ATMs play an important role in bank transactions, but with increasing fraud, people are scared to use ATM systems. This innovative system eliminates the need for physical cards and enhances security through face recognition technology. The user initiates the transaction by entering the account number, activating the camera for facial recognition and the face will be captured and stored in database. If the individual is authorized using convolutional neural network, the transaction proceeds seamlessly. For elderly users, relationships such as daughters or sons can be registered, and their facial images are stored in a secure database. When nominee attempts a transaction, the system recognizes the database for successful facial recognition, facilitates the limited withdrawal amount. This not only adds a layer of personalized security but also accommodates the needs of older individuals who may find traditional ATM transactions challenging. Furthermore, the system leverages geolocation technology to enhance security. Transaction, including the amount withdrawn and the ATM location, are communicated to the user's registered device. This ensures that users receive real-time alerts about transactions, providing the security and transparency.

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 Keywords

Multi-factor Authentication, Cardless Transactions, Facial Recognition, Deep Convolutional Neural Network

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An initial public offering (IPO) has become one of the preferred investments for investors. In recent years, many companies have come up with IPOs to raise funds to meet their requirements. Investing in an IPO is considered a risky investment because the market behavior is not known, especially in a volatile share market. The performance of the IPO varies in accordance with the market, i.e., from bullish to bearish. The interests of the investors are influenced by the market trend and, thus, the performance of the IPO. IPOs can be a risky investment. For the individual investor, it is tough to predict the performance of a stock or share on its initial day of trading. In this study, the performance of IPOs from offer price to closing price on the trading day in India during 2022, listed on the Indian Stock Exchange, is examined. Researchers found that there is, on average, a significantly positive return. This paper analyses the performance IPOs for the companies listed in NSE and BSE.

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Initial public offering, Indian Market, IPO performance, Listing Gains, Linear regression, paired T-tests

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Paytm and Google Pay. The analysis focuses on several key aspects including user base, market share, transaction volume, security features, user experience, and future prospects. The study utilizes a combination of quantitative data from industry reports, financial statements, and user surveys to provide a comprehensive overview of both platforms. Additionally, qualitative factors such as brand reputation, innovation, and strategic partnerships are also considered. The findings suggest that both Paytm and Google Pay have experienced significant growth in their user bases and transaction volumes over the years. However, Google Pay has shown a stronger presence in terms of market share and technological advancements. On the other hand, Paytm has excelled in diversifying its services and establishing a strong brand presence in various sectors beyond payments

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Paytm Googlepay Financial Statements Digital Payment

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Now a days people want to complete their work within minimum amount of time. So, use of automated systems is trending. This paper describes the home automation system designed and developed using Arduino with Bluetooth module. This home automation system will be a simple and reliable technology with Android application. Home application such as Fans, Bulbs, Air Conditioners, and automatic door lock will be controlled by home automation system. When people will be out of home, they can monitor and control the application of smart home using Android Application. This will be secure, user friendly, and low cost, solution for smart home.

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Automated System, Arduino, Home Automation, IOT

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. As per the measurements given by Strategy Analytics (SA), an IT statistical surveying institution, the number of the mixed media advanced cell clients at present surpasses 1 billion. However, since the sight and sound PDAs are taken wherever by clients generally due to its helpful elements are liable to be lost or taken. Subsequently, most mixed media PDAs are currently furnished with different underlying locking features. These incorporate an individual distinguishing proof number (PIN), which utilizes a straightforward number mix; a secret phrase, which uses numbers and characters; design lock by means of hauling in the favored course; face acknowledgment of the client; face and voice recognition of the client; and drag to conceal the screen. Among these, design lock, PINs, and passwords are the most generally used locking highlights, however they are profoundly helpless against shoulder surfing and smear assaults, and accordingly another sort of locking system is required.

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security

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Secure personal data sharing in the cloud is a crucial issue since it raises a number of security and data confidentiality challenges while using cloud services. Many obstacles still stand in the way of attaining practical fine-grained access control in the Personal Information Sharing system, including data privacy protection, flexible data sharing, effective authority delegation, and computing performance optimization. Before outsourcing to the cloud, personal records must be encrypted to safeguard privacy. Here, offer an effective data sharing system for healthcare data sharing that simultaneously protects data privacy, implements fine-grained access control, and delegated authority. It is suggested that a duplicate generation mechanism along with a two-server computing environment be used to secure patient MHRs in the healthcare cloud. The replica server acts as a second gallery for duplicate MHR, which gives the attacker the impression that it is the original data uploaded by data owner. A duplicate file will be kept on another server when a user uploads a file to the original server. The duplicate files are obtained from the beginning in our proposed methodology to ensure improved security. In this way, the decoy files are called when an intruder is identified accessing the system. The Elliptic Curve Cryptography (ECC) algorithm is being used in the suggested strategy to encrypt the medical records.

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Public Key Generator (PKG), Elliptic Curve Cryptography (ECC), Architecture description languages (ADLs),linear secret sharing scheme (LSSS)

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The Desktop Voice Assistant marks a significant evolution in human-computer interaction, incorporating advanced natural language processing and voice recognition technologies into desktop computing environments. This transformative software allows users to control their computers effortlessly through spoken commands, promoting a hands-free and intuitive computing experience. This abstract delves into the key features, benefits, and potential applications of the Desktop Voice Assistant, underlining its contribution to improved accessibility, productivity, and overall user satisfaction within the desktop computing domain.

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Desktop Voice Assistant, Python, Natural Language Processing, Voice Recognition, Human-Computer Interaction, Automation, User Experience.

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BACKGROUND Hand hygiene is crucial in healthcare settings for infection control and patient safety. It is a global health issue and the most cost-effective way to reduce infections and antimicrobial resistance. Hand hygiene is the act of cleaning one's hands with soap or handwash and water to remove viruses/bacteria/microorganisms, dirt, grease, or other harmful and unwanted substances stuck to the hands. Improving hand hygiene practices among healthcare workers can significantly reduce the incidence of HAIs. The WHO estimates that proper hand hygiene practices could prevent up to 50% of healthcare-associated infections. Guidelines for hand hygiene practice have been issued by World Health Organization (WHO) and Center for disease control and prevention (CDC, Atlanta) but lack of awareness among HCW result in poor compliance which could have serious aftereffects on a healthcare system. OBJECTIVES i. To assess the level of pretest-posttest knowledge regarding hand hygiene in prevention of infection among healthcare workers in selected hospitals of Guwahati, Assam. ii. To assess the level of pretest-posttest practice regarding hand hygiene in prevention of infection among healthcare workers in selected hospitals of Guwahati, Assam. iii. To determine the effectiveness of video assisted program regarding hand hygiene in prevention of infection by comparing pretest-posttest level of knowledge and practice among healthcare workers in selected hospitals of Guwahati, Assam. iv. To correlate the knowledge and practice regarding hand hygiene in prevention of infection among healthcare workers in selected hospitals of Guwahati, Assam. v. To find the association between knowledge and practice before video assisted program regarding hand hygiene in prevention of infection among healthcare workers with selected demographic variables. METHODS AND MATERIALS: Pre experimental one group pre-test post-test design was used in this study. Non probability convenience sampling technique was used for obtaining the adequate sample for the study. Study was undertaken on 100 healthcare workers working in selected hospitals of Guwahati, Assam. Healthcare workers were selected on the basis of inclusion criteria. Pre-test knowledge was checked using standardized knowledge questionnaire and practice was assessed using observational checklist. The post-test was conducted on the seventh day after the administration of video assisted programme in the same manner. RESULTS: Result showed that out of 100 health care worker, majority 44(47%) were in the age group of >40 years,59(59%) was male, 78 (78%) of the respondents were under metrics, 35(35%) were working in ICU, 64(64%) had worked for more than 2 years, 95(95%) had attended the training on hand hygiene, 100(100%) have alcohol based handrub practice. In pre-test knowledge, majority 61(61%) had inadequate knowledge with a mean knowledge score of 9.5 and SD 2.90. whereas in post-test knowledge, majority 77(77%) had adequate knowledge with a mean knowledge score of 22.26 and SD 3.70. In pre-test practice, majority 62(62%) had moderately adequate practice with a mean practice score of 10.46 and SD 2.74. whereas in pre-test practice, majority 51(51%) had moderately adequate practice with a mean practice score of 20.03 and SD 3.36. The calculated value of 'T' (4.71) was more than the tabulated value (1.98) at 0.05 level of significance for knowledge and the calculated value of 'T' (3.18) was more than the tabulated value (1.98) at 0.05 level of significance for practice which signifies that video assisted programme was effective in increasing the knowledge and practice for healthcare workers. The analysis depicted that there was significant association between pre-test knowledge regarding hand hygiene and education, settings and work experience, there was significant association between pre- test practice regarding hand hygiene. CONCLUSION: Based on the analysis of the findings of the study, the following inferences were drawn. There was evident increase in the knowledge and practice in all areas included in the study after the administration of video assisted program on hand hygiene. Thus, it was proved that the video assisted program was an effective teaching method for creating awareness on the importance of hand hygiene.

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hand hygiene, healthcare workers, alcohol based handrub, prevention of infection

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A novel multimodal stress prediction system combines psychological questioning to assess emotional states and facial recognition technology to analyze facial expressions. By integrating these approaches, the system accurately determines stress levels in users. Through a series of tailored psychological questions and real-time facial emotion recognition, the system provides a comprehensive assessment of the user's stress levels using machine learning techniques. The culmination of this process yields a precise percentage indicating the individual's stress level, enabling timely interventions and personalized stress management strategies. This innovative project aims to revolutionize stress monitoring by leveraging both psychological profiling and facial recognition technologies.

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psychological profiling, facial recognition, machine learning, stress levels

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Title: Intelligent Autonomous Delivery Robots - Little Indian: The Last Mile Abstract: The last mile delivery problem has long been a bottleneck in supply chain logistics, posing challenges for efficiency, cost-effectiveness, and environmental sustainability. In response, the emergence of autonomous delivery robots promises transformative solutions. This paper introduces LITTLE INDIAN, an Intelligent Autonomous Delivery Robot designed to revolutionize last mile delivery operations. LITTLE INDIAN is equipped with state-of-the-art technologies, including artificial intelligence, computer vision, and advanced robotics. These enable it to navigate complex urban environments, interact safely with pedestrians and vehicles, and autonomously deliver packages to designated locations. Through its intelligent decision-making capabilities, LITTLE INDIAN optimizes route planning, adapts to dynamic environmental conditions, and ensures timely and secure deliveries. Key features of LITTLE INDIAN include its compact size, modular design, and energy-efficient propulsion system, which enhance maneuverability and minimize environmental impact. Moreover, its integration with cloud-based management platforms enables real-time monitoring, fleet coordination, and seamless integration with existing logistics infrastructure. This paper outlines the technical specifications, operational capabilities, and potential benefits of LITTLE INDIAN in enhancing last mile delivery efficiency, reducing costs, and mitigating carbon emissions. Additionally, it discusses ongoing research, regulatory considerations, and future prospects for the widespread adoption of autonomous delivery robots in transforming the last mile logistics landscape.

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Autonomous Delivery Robots Last Mile Delivery Little Indian Artificial Intelligence Route Optimization Energy Efficiency Cloud-Based Platform Regulatory Compliance Sustainability Logistics Ecosystem

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In this paper, I have presented views in contrary to the concept of privatisation of prisons, with respect to India and why it would not be enforceable and effective in India. Privatisation essentially means delegating or transferring operation and management of a facility or system to a private company that provides services like medical facilities, goods and services, shelter and housing, vocational training and so on, in exchange for a fee from the State. Evidently, the purpose or objective, with which the prison was established, is to deter crimes by punishing the offender or to rehabilitate and reform the offender in order to ensure their eligibility to maintain their livelihood outside the prison. This paper further brings into focus the theories presented by Marx with reference to Foucault's theory of Discipline and Punishment, shedding light on how the prison system works and how the privatisation of prisons is a political agenda perpetuated in order to economically benefit a country rather than reforming the prisoners. This paper also analyses this concept in respect of relevant case studies such as the Standford Prison Experiment, the PPP agreement of Tihar Jail and privatisation of prisons in the United States of America and how it affected the rights of the prisoners.

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Prison System, Privatization of Prisons, PPP Agreement, Indian Constitution, Marxist Theory.

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Smart irrigation systems are considered to be the next level in agriculture, where they use artificial intelligence (AI) for their design. The system makes decisions using sensors that monitor humidity, temperature, and environment to gather data at the appropriate times. With the use of artificial intelligence algorithms like machine learning models, this information can be interpreted, and an effective irrigation plan can be put in place depending on crop type and climate conditions. Water resources in any region are valuable because they are required for life. In underground water well, where This paper is implemented, controlling the auto water supply will ensure that different areas of the place get their own share of water. Using the system's advanced features and remote control capability; farmers can monitor and manage soil moisture levels, reduce water waste, enhance crop productivity, minimize damage from diseases and insects, and save up to 50% in operational costs. The advantage of this approach is that it will support local knowledge combined with technology application to enhance agricultural production and environmental protection. The project's hardware includes the Arduino Uno controller as its core, the DHT11 sensor which measures temperature and humidity, as well as the soil humidity sensor; two solenoid valves control the water flow. Once the artificial intelligence component is integrated, the systems will initiate and the Blynk (Android) app, using the Internet of Things (IoT), will continuously monitor the sensor data.

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AI technology, Water management, Irrigation optimization, Crop yield prediction, Sensor network, Machine learning, Automated valve control, Sustainability, Farm efficiency.

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 Abstract

Self-damage is a main international hassle that influences people and economies alike. It is becoming extra not unusual as cities grow and era advances, especially in growing countries. In positive regions, traditional forecasting techniques that rely on historical data might not be sufficient, making it greater difficult to quick recognize and are expecting styles in self-damage. The FAST assignment uses social media facts and numerous system learning algorithms, consisting of Decision Tree, ARIMA, Bayesian Ridge, SVR, XGBoost, Random Forest, CatBoost, and Voting Regressor, to close this gap. By using those cutting-edge techniques, FAST enhances traditional forecasting methods by using presenting actual-time insights into new self-harm traits. To further improve prediction accuracy, the examine combines the advantages of separate models into an evaluation this is greater robust with the aid of utilizing ensemble processes.This novel approach affords a greater comprehension of the difficult interactions between social affects and behavior that lead to self-damage, equipping stakeholders and policymakers with practical know-how to perform preventative interventions globally.

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Self-harm, nowcasting, forecasting, online social networks, cross-lingual text classification

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This research paper presents the development and evaluation of an artificial intelligence model specifically adapted for the diagnosis of early chronic kidney disease (CKD).Emphasis on explainability ensures transparent and understandable predictions, which are key to the adoption of AI in healthcare. CKD is a major global health problem that requires early diagnosis to stop kidney damage and reduce healthcare costs. The project aims to contribute to proactive solutions recognizing the borderline implications of CKD. Using an optimization framework balances classification accuracy and increases overall efficiency. This ML (Machine Learning) algorithm uses three key features for the diagnosis of CKD: Hb (hemoglobin), specific gravity, hypertension and required indicators for early detection of CKD. This model offers solutions and challenges, especially in developing countries, by emphasizing cost reduction and increasing the availability and affordability of health care. We also used methods to combine predictions from multiple models, including techniques such as a stacking classifier, yielding an impressive 100% accuracy.

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Estimated glomerular filtration rate (eGFR),Hypertension,ExtraTree Classifier, Random Forest, AdaBoost Classifier, XGBoost,Extension Stacking Classifier,

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The performance of flexible pavement is determined by the functions of the component layers, particularly the subgrade. Subgrade is the compacted layer of soil provide the lateral support to the pavement. Our approach is to improve the properties of soil is with addition of admixtures like lime and stone dust with soil. Soil stabilization is one of the most suitable alternatives which are widely used in pavement construction. Soil stabilization and soil treatment gives an innovative solution to improve the engineering properties of soil by improving the bearing capacity, durability of weak soil and other characteristics as per requirement. In this study lime and stone powder has been selected as a stabilizer. The soil is tested in the laboratory by reinforcing it with different percentages of lime and stone dust, namely 5%, 10%, 15%, 20%, 25%, 30%. Atterberg limit and compaction test were carried out on both unmodified and modified soil. California bearing ratio (CBR) test was performed to determine the strength properties of the soil, lime, stone powder mixtures.

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Flexible Pavement, Subgrade Soil, Stabilization, Lime, Stone dust, CBR, Bearing Strength.

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Lotus extraction, Carrot juice , Moisturising

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Within the fast-changing field of digital marketing, Tesla is one of the leading innovators in the automotive sector. This abstract presents a thorough plan for improving Tesla's digital marketing tactics by utilizing the company's distinctive brand identification and state-of-the- art technologies. The tactics that have been suggested cover a range of digital platforms, such as influencer alliances, social media, content marketing, and search engine optimization (SEO). Tesla can connect with its audience more deeply and increase brand advocacy by utilizing social media sites like Instagram, Twitter, and LinkedIn. In addition, a focus on content marketing with blogs, films, and interactive experiences may inform customers about technical breakthroughs, environmental programs, and Tesla goods. In addition to boosting organic traffic, this strategy establishes Tesla as an expert in the electric vehicle In addition, maximizing Tesla's online exposure in search engine results using SEO strategies attracts potential buyers at different phases of the buying process. Tesla can draw in quality leads and increase conversion rates by continuously producing insightful content and optimizing keywords associated with electric cars and environmentally friendly transportation. And various means of networks. Furthermore, collaborations with celebrities and industry experts may help Tesla expand its brand messaging and reach new audiences. Collaborating with environmental activists, tech enthusiasts, and automotive influencers may help Tesla build brand credibility and generate conversation about its offerings and goals. Which can help brand to achieve its objectives. The recommended digital marketing techniques provide a road map for Tesla to improve its market visibility, establish meaningful connections with customers, and promote long-term success in the digital era. Tesla can continue to lead the way to a greener, more connected future by combining creative techniques with a dedication to quality. With uniqueness in their branding techniques In conclusion, Tesla can drive brand growth, improve consumer connections, and preserve its position as an automobile industry innovator by incorporating these unique digital marketing methods into its overall marketing framework. This summary captures the core of the recommended tactics, offering practical insights for Tesla's digital marketing efforts in the rapidly changing digital marketplace.

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Digital marketing, social media , online marketing, strategies

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This paper investigates the impact of in-store promotion in triggering impulse buying behaviour. Researchers and Practitioners have been interested in the field of impulse buying for the past sixty years (Rook, 1987; Peck and Childers, 2006; Chang et.al, 2011). In this research data was collected through structured questionnaire from 1050 respondents from four non-metro cities of Maharashtra viz. Pune, Nagpur, Nasik and Aurangabad. The number of respondents was equally distributed as 525 males and 525 females. A structure questionnaire containing 17 items were answered by respondents on Likert Scale from 1-5.Chronbach's alpha value was then calculated to check the reliability of collected data. For Hypothesis testing T-Test and ANOVA were used. Number of respondents from each city was selected in proportion to the population of the city. For data analysis Arithmetic mean, standard deviation, t-test, Analysis of Variance (ANOVA), and F - Test were used in the appropriate places. The data obtain was analyzed in SPSS 16.00 software. Respondents were posed with statements based on monetary and non-monetary deals, impact of promotion signs on buying behaviour, placement of products in the store and role of cards in making impulse purchases. It was concluded that same factor have different impact on male and female shoppers of non-metro cities of state. These findings are expected to be used by decision-makers in retail businesses to formulate in-store promotional activities and create customer value following the target market to increase consumers' willingness to buy private label products.

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 Keywords

Consumer Behaviour, In-store promotions, non-monetary deals, Impulse buying behaviour, monetary deals

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