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Investor's behaviour to COVID-19 vaccination campaign; An event study and panel data analysis in the southeast asian region
This study examines how the COVID-19 immunization campaign has influenced the stock market responses in the WHO Southeast Asian Region. The effects of the immunization campaign on the WHO Southeast Asian countries were different, and the study used event study techniques and panel-data regression models to investigate the impact of the WHO South-East Asian capital market. Some countries like India, Sri Lanka, and South Korea had positive markets that responded to the news, while others did not. The findings of this study suggest that investors make fair assessments and respond to events and announcements, but they tend to have a more visible reaction to negative incidents than to positive news/events. However, after 51 days, the WHO South East region as a whole had internalized the encouraging news. The study has a few limitations, such as a small dataset and period, only a few variables and models, and so on. Future studies could include a few additional countries and periods to produce more significant results. Originality/value- This study contributes to the existing knowledge about the impact of drugs and vaccinations on stock markets. It is the first study to investigate how the WHO Southeast Asian Region's COVID-19 immunization program affects the stock market reaction. The study used keywords such as Immunization campaign, abnormal returns, Cumulative average abnormal returns, Event Study, and WHO Southeast Asian Region. 2025 Universidad Nacional Autonoma de Mexico. All rights reserved. -
Investor's behaviour to COVID-19 vaccination campaign; An event study and panel data analysis in the southeast asian region
This study examines how the COVID-19 immunization campaign has influenced the stock market responses in the WHO Southeast Asian Region. The effects of the immunization campaign on the WHO Southeast Asian countries were different, and the study used event study techniques and panel-data regression models to investigate the impact of the WHO South-East Asian capital market. Some countries like India, Sri Lanka, and South Korea had positive markets that responded to the news, while others did not. The findings of this study suggest that investors make fair assessments and respond to events and announcements, but they tend to have a more visible reaction to negative incidents than to positive news/events. However, after 51 days, the WHO South East region as a whole had internalized the encouraging news. The study has a few limitations, such as a small dataset and period, only a few variables and models, and so on. Future studies could include a few additional countries and periods to produce more significant results. Originality/value- This study contributes to the existing knowledge about the impact of drugs and vaccinations on stock markets. It is the first study to investigate how the WHO Southeast Asian Region's COVID-19 immunization program affects the stock market reaction. The study used keywords such as Immunization campaign, abnormal returns, Cumulative average abnormal returns, Event Study, and WHO Southeast Asian Region. 2025 Universidad Nacional Autonoma de Mexico. All rights reserved. -
Involvement and implementation of corporate social responsibility (CSR): A case of COVID-19 evidence from various countries
Industry performance is a pivotal indicator for assessing the robustness of economic growth of a country. Any fluctuations in this indicator wield considerable influence over economic growth. Previous research has established that the industry performance is not a static phenomenon but rather exhibits variations across different time periods. Amongst the multitude of crises, the COVID-19 pandemic reverberated across every nation, spreading to all strata of society. It had an adverse impact on both public and private sector impacting the lives of millions. Industries were struggling with dwindling profits, thus trying vehemently to cut costs in diverse realms. This challenging financial predicament made it difficult for companies to uphold their corporate social responsibilities. Hence, only a few companies initiated CSR activities due to the paucity of funds. Having this in the backdrop, this case study analysis aims to examine corporate involvement and implementation of CSR activities during the COVID-19 pandemic and assesses the extent to which these activities have helped improve people's lives. 2024, IGI Global. All rights reserved. -
Involvement of chalcones and coumarins in environmental stress tolerance
Plants are invariably subjected to various environmental stresses that hinder their normal growth and development, which leads to decreased plant productivity and yield. To combat the detrimental effects of such abiotic and biotic stresses, plants have developed diverse mechanisms and one of the prominent ones includes the production of secondary metabolites like phenolic, alkaloids, terpenes, etc. Secondary metabolites serve as major components of the plant stress responses. Chalcones (1,3-diaryl-2-propen-1-one) and coumarins (1,2-benzopyrone) are precursors of flavonoids, a common secondary metabolite of plants that provide a beneficial role during oxidative and biotic stress. Apart from protection, coumarins have certain roles in promoting or inhibiting plant growth, affecting cell division and differentiation and auxin metabolism. These compounds are also known to possess therapeutic properties such as anti-inflammatory, anti-microbial, anti-cancer, and cytotoxic effects when isolated from plants. Besides, chalcones and coumarins have allelopathic effects and protect plants against herbivory. Owing to excellent ROS scavenging properties, chalcones, coumarins, and their derivatives are extensively employed as agents to alleviate adversities associated with abiotic stresses like osmotic, heat, and cold stress, and in defense against pathogen invasion. The application of these secondary metabolites to mitigate atrocities of environmental stress in plants is an interesting and concurrent area of investigation. This chapter highlights the structural and functional details of chalcones and coumarins and their implications in ameliorating environmental stress in plants. 2024 Apple Academic Press, Inc. All rights reserved. -
Involvement of Social Enterprises in Promoting Sustainable Agricultural Practices: The Case of Uravu and Buffalo Back
Social enterprises are not-for-profit or for-profit organizations that work for the development of the community in different ways and are sustainable through their products or services. One such initiative of social enterprises is supporting and promoting agriculture and agricultural products. This chapter focuses on two social enterprises, Uravu and Buffalo Back, which work with farm products and their role in promoting sustainable agriculture practices. The primary data are collected through personal interviews with top-level managers, and secondary data are collected from websites and other published documents. This study looks at the concept of sustainability in terms of finitude, fragility and fairness. These two case studies explain how social enterprises promote the development of agriculture. The former organization ensures the communitys livelihood through farming support, upgrading local knowledge, technologies, skill development and marketing their commodities. The latter focuses on promoting farmers to focus on sustainable organic farming techniques and selling their products to customers. This study can help future entrepreneurs understand different models they can use to develop the agricultural sector through their social actions. 2024 by World Scientific Publishing Co. Pte. Ltd. -
Iodine Mediated Oxidative Cross-Coupling of Benzo[d]Imidazo[2,1-b]Thiazoles with Ethylbenzene: An Unprecedented Approach of C3-Dicarbonylation
A versatile approach of iodine mediated C3-dicarbonylation of benzo[d]imidazo[2,1-b]thiazoles (IBTs) with ethylbenzene has been reported. The reaction conditions were optimized by screening in various solvents, catalysts, and oxidants. The reaction is compatible with various substrates and was successfully demonstrated to offer moderate to good yields. 2022 Taylor & Francis Group, LLC. -
Iodine promoted synthesis of pyrido[2?,1?:2,3]imidazo[4,5-c]quinoline derivatives via oxidative decarboxylation of phenylacetic acid
An unprecedented and efficient molecular iodine promoted domino protocol for the synthesis of N polycyclic pyrido[2?,1?:2,3]imidazo[4,5-c]quinolines were reported from phenylacetic acid and 2-(imidazoheteroaryl)anilines. This methodology was also extended for the preparation of benzo[4?,5?]thiazolo [2?,3?:2,3]imidazo[4,5-c]isoquinolines in good yields. However, this protocol proceeds via a sequential decarboxylation of phenylacetic acid with I2/DMSO system followed by Pictet-Spengler cyclization in good yields. 2022 Taylor & Francis Group, LLC. -
Ion-imprinted carbon dots: rationally designed fluorescent probes for the detection of selected metal ions from aqueous solutions
Photoluminescence properties of Carbon Dots (CDs) have been leveraged for their use as sensors for a variety of analytes, including inorganic ions, organic molecules, and biomolecules. The selective fluorescence response of CDs to specific analytes is generally not pre-designed. Rationally designed synthesis of CDs with pre-defined selectivity to specific analytes is a less explored avenue. This study presents a novel method for the customized synthesis of CD fluorescent probes and an ion-imprinting-based selective detection of metal ions using these CDs. Poly(sodium 4-styrenesulfonate) [PSS] treated with Cd(ii) ions was used as the precursor for preparing Cd-imprinted CDs, and a modified form of these CDs was used for the sensing of Cd(ii) in aqueous solutions. As synthesized CDs have Cd(ii) ions on their surface, which were subsequently removed through appropriate chemical treatment. This removal results in binding sites of Cd(ii) ions on the CDs. Formation of such binding sites results in alterations of the fluorescence of CDs. Exposure of these particles to analytes containing Cd(ii) ions leads to the re-occupation of the binding sites by the metal ions, resulting in a distinct fluorescence response, which serves as the sensing readout. Effectiveness of this ion-imprinting approach is demonstrated by the selective and sensitive fluorescence response of the CDs towards Cd(ii) ions, with a limit of detection (LOD) of 3.62 nM. This strategy of Cd(ii) detection using ion-imprinted CDs represents a novel effort in CD-based sensors, and this can be extended to the sensing of other cations also. This journal is The Royal Society of Chemistry, 2025 -
Ion-imprinted chitosan-stabilized biogenic silver nanoparticles for the electrochemical detection of arsenic (iii) in water samples
Arsenic is one of the most harmful heavy metals, and needs constant monitoring and control. A susceptible and selective sensor for arsenic (iii) detection in polluted water samples has been developed by using chitosan-stabilized silver nanoparticles (AgNPs). A glassy carbon electrode (GCE) is modified with chitosan-stabilized silver nanoparticles, which provides sufficient sites for interaction with the analyte. The synthesized silver nanoparticles are characterized using different characterization techniques, such as UV-Visible spectroscopy, transmission electron spectroscopy (TEM) and particle size distribution. The particle size and polydispersity index (PDI) value of the chitosan stabilized silver nanoparticles are found to be 6 nm and 0.3, respectively, which enhances the electroactive surface area and hence the sensor sensitivity. The ion imprinting technique is used to improve the selectivity of the sensor. The arsenic sensor is found to be very selective in the presence of other possible interferents like Pb2+, Zn2+, Cu2+, Ag+ and Fe2+. The detection of As(iii) was performed using differential pulse anodic stripping voltammetry (DPASV) and the detection limit was found to be 11.39 pM. The developed sensor is successfully tested for the picomolar level detection of arsenic (iii) in different water samples. 2023 The Royal Society of Chemistry. -
Ionic strength and phase systems influence nanotubular material functionality
We synthesized novel thiacyanine chromonic liquid crystals (CLCs) and structurally characterized using NMR and mass spectrometry. The impact of distinct substitution at the para position of aromatic counter anions, aliphatic counter ion chain length, and varied spacer parity of thiacyanine dyes on CLC formation is investigated. Liquid crystal properties of the synthesized dyes are characterized by polarizing optical microscopy (POM) and X-ray diffraction (XRD) studies. Dyes exhibit nematic (N), lamellar (L?), columnar rectangular (Colr), and columnar oblique (Colob) CLCs at different concentrations in the water. Electronic absorption spectra reveal Scheibe aggregation in all the dyes. Cylicvoltametry studies confirm redox behaviour in TC-1a and TC-5e dyes. Chromonic LCs hybrid nano-materials are synthesized using solgel method. Scanning electron microscopy employed to confirm nano tubular fiber structure of the hybrid nanomaterilals. 2024 Elsevier B.V. -
IoT and AI for Real-Time Customer Behavior Analysis in Digital Banking
Digital transformation has revolutionized the banking industry, ushering in an era of enhanced customer experiences and operational efficiency. The convergence of Internet of Things (IoT) and Artificial Intelligence (AI) technologies has further propelled this evolution by providing real-time insights into customer behavior. This research explores the integration of IoT and AI for real-time customer behavior analysis in the context of digital banking. The proliferation of connected devices, ranging from smart phones to wearables, has generated an unprecedented volume of data. IoT facilitates the collection of diverse data points, such as transaction history, location information, and device interactions, creating a comprehensive digital footprint for each customer. Simultaneously, AI algorithms leverage this wealth of data to analyze, predict, and respond to customer behavior dynamically. In the realm of digital banking, understanding and adapting to customer behavior in real-time is crucial for providing personalized services, preventing fraud, and optimizing operational processes. This research delves into the mechanisms by which IoT sensors and devices, coupled with AI algorithms, enable banks to gain deeper insights into customer behavior patterns. Key components of the proposed system include data acquisition through IoT devices, secure data transmission protocols, and AI-driven analytics engines. In conclusion, this research advocates for the symbiotic relationship between IoT and AI in digital banking to enable real-time customer behavior analysis. 2024 IEEE. -
IoT and Eye Tracking based system for Cerebral Palsy Diagnosis and Assistive Technology
Children with Dyskinetic Cerebral Palsy often suffer significant challenges in interacting with digital devices due to their impaired motor control which hinder the use of traditional input methods such as keyboard and touch screens. The limitations can be overcome by developing assistive technology such as the IOT based system that the paper proposes. The paper proposes an eye-tracking system that uses web-cameras along with computer vision algorithms to detect gaze direction and blink patterns paired with a handheld IOT console that bridges the interaction between the user and the digital interface. The study also proposes ways to assess and evaluate a patient's motor and cognitive functions. The proposed solution keeps in mind the motor limitations of a DCP patient and aims to enhance the accessibility of digital interfaces, providing children with severe motor impairments a more intuitive and inclusive means of interacting with technology. 2025 IEEE. -
IoT and Supply Chain Management: Enhancing Efficiency and Security through Smart Technologies
By offering real-time visibility, increased efficiency, and better security, the Internet of Things (IoT) is revolutionizing supply chain management, this paper investigates. IoT devices enable seamless connectivity between products, warehouses, and logistics networks, allowing businesses to manage inventory, forecast demand, and prevent theft or fraud. Examining case studies of IoT implementations in supply chains, the article explores how data-driven insights maximize logistics, lower running costs, and lower risk-profile. It also suggests ways to improve IoT security in supply chains and tackles the security issues raised by IoT like data leaks and illegal access. IoT-based Supply Chain Management (SCM) solutions notably increase operational efficiency, cost reduction, security, inventory correctness, responsiveness, data processing time, downtime, energy consumption, scalability, and customer happiness, according the comparison table. IoT solutions save costs by 30% and have 95% efficacy-a 26.67% improvement over conventional systems. With only one documented security event year instead of five in conventional systems, security is also enhanced. Response time to disturbances drops and inventory accuracy rises as well. IoT solutions additionally provide 400% scalability increase. 2025 IEEE. -
IoT and Sustainability Energy Systems: Risk and Opportunity
As IoT (Internet of Things) and smart technologies have developed rapidly, many technological advancements have been made possible. The IoTs main objective is to assist in simplifying processes in a number of different felds, to improve the effciency of technologies and protocols, and ultimately to improve quality of life. Although IoT technologies can beneft the population in numerous ways, their development must be evaluated from an environmental viewpoint to ensure that global resources are used effciently and to prevent negative effects. As previously described, considerable research effort is needed to explore the advantages and disadvantages of IoT technologies. Engineering professionals, industrial experts, and academic researchers successfully interacted at the conference. Several key tracks made up the conference, including smart city, energy and environment, e-health, and engineering modeling. Specifcally, the editorial covered a number of topics including (i) IoT in sustainable energy and environmental management, (ii) smart cities enabled by IoT, (iii) ambient assisted living, and (iv) IoT technologies for transportation and low-carbon products. An important outcome of our introductory analysis has been a greater understanding of both the scientifc developments in IoT applications and the potential ecological consequences associated with increasing IoT applications. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
IOT and UAV Integrated System for Proactive Crop Disease Prediction
The productivity of agriculture is often affected by the crop diseases incurring economic loss and reduced food production. Detecting these crop diseases in the early stages is the need of the hour to mitigate the spread of the disease and manage the crop yield effectively. This paper presents a proactive crop disease prediction system by employing the technologies such as Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoT) to detect and mitigate the crop disease at early stages. The employed UAVs have a high resolution camera to capture the aerial images of crops and leaves. The images captured via UAVs are transferred to a computing environment dynamically for analysis purposes. The analysis is performed on the images to predict the disease of the leaf along with its intensity. After analyzing and predicting the leaf disease and its intensity, the pesticide information is passed to the IoT sensors which are fixed in the fields to spray the recommended pesticide. The system analyzes the captured images by leveraging the machine learning algorithms in the realtime to identify different diseases and predict the spread of the disease. The proposed proactive approach helps the farmers to take preventive actions to identify the crop disease at the early stage and mitigate them in a timely manner to produce a better crop yield. Moreover, the proposed method provides a cost-effective solution for disease prediction and is easily accessible to farmers to enhance crop productivity. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
IoT and wearables for detection of COVID-19 diagnosis using fusion-based feature extraction with multikernel extreme learning machine
Presently, wearables act as a vital part of healthcare sector and they are able to offer exclusive perceptions about the person's health conditions. In contrast to traditional diagnosis in a hospital environment, wearables can give unrestricted access to real-time physiological data. COVID-19 epidemic is increasing at a faster rate with limited test kits. Hence, it becomes essential to develop a novel COVID-19 diagnostic model. Numerous studies were based on the utilization of artificial intelligence techniques on radiological images to precisely identify the disease. This chapter presents an efficient fusion-based feature extraction with multikernel extreme learning machine (FFE-MKELM) for COVID-19 diagnosis using internet of things (IoT) and wearables. Primarily, the wearables and IoT are used to capture the radiological images of the patient. The presented FFE-MKELM model incorporates Gaussian filtering based preprocessing for removing the noise that exists in the radiological image. Besides, directional local extreme patterns with deep features based on Inception v4 model are applied for the FFE process. In addition, MKELM model is utilized as a classification model to determine the appropriate class label of the input radiological images. Moreover, monarch butterfly optimization algorithm is applied to fine tune the parameters involved in the MKELM model. Experimental validation of the FFE-MKELM model is performed against benchmark dataset and the outcomes are inspected under different measures. The resultant simulation outcome ensured the betterment of the FFE-MKELM method by demonstrating an increased sensitivity of 97.34%, specificity of 97.26%, accuracy of 97.14%, and F-measure of 97.01%. 2022 Elsevier Inc. All rights reserved. -
IOT based application for monitoring electricity power consumption in home appliances
Internet of Things is one of the emerging techniques that help in bridging the gap between the physical and cyber world. In the Internet of Things, the different smart objects connected, communicate with each other, data is gathered from the smart objects and based on the need of the users, and the data gathered are queried and sent back to the user. IoT helps in monitoring electrical and physical parameters. Electricity consumption from electronic devices is one among such parameters that need to be monitored. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper proposes a Wi-Fi enabled simple low cost electricity monitoring device that can monitor the electricity consumption on home appliances which helps to analyses the consumption of electricity on a daily and weekly basis. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
IOT based application to detect fall with a measured force
Fall of patients and aged individuals may end up deadly if unnoticed in time. A fall detection framework has been developed which sends caution notification to the concerned individuals or to the specialist, at the time of occurrence. To limit the consequences of associated wounds/damage caused by the fall, such a device has been developed. The model in this study, detects the fall and measures the force of the fall without using the force sensor and the direction of the fall. In this study, the body posture is obtained from change of increasing speed in three axes, which is measured with a triaxial accelerometer (ADXL335). The sensor is set on the lumbar area to interpret the tilt point. The value obtained from the sensor is compared with the threshold given to diminish the false cautions and furthermore provides the force by which the individual has fallen and the direction in which the person has fallen. The threshold value is computed by the execution of various trials on subjects in different directions of fall. The sensor data is collected on the fall is computed and analyzed in the Audrino microcontroller. The location of fall is detected by GPS beneficiary, which is customized to trace the subject persistently. On detecting the fall, the gadget sends an instant message through GSM module to the emergency contact. The developed model is tested on 7 volunteers who replicated falls in different direction with varying forces. Out of 28 trials, 80% of exactness is accomplished with zero false cautions for dayto-day activities like sitting, lying down on bed and grabbing objects. IAEME Publication. -
IoT Based Bus Identification and Distance Notifier for the Visually Impaired
Public transport is a major obstacle for the visually impaired, and it tends to limit their independence and mobility. To overcome this problem, the current project presents an IoT-based bus identification and distance notification system that is meant to offer real-time support and improve the traveling experience of the visually impaired commuters. The system uses a Raspberry Pi controller in combination with an RFID reader and several RFID cards, each one of which is designated for a particular bus, to detect oncoming vehicles. A GPS unit monitors the position of the bus at all times, so it is possible to calculate exact distances to any of the stops. For additional convenience, the system includes three push-button switches programmed to three predetermined bus stops. Users may pick their destination stop, and the system will offer auditory feedback in terms of distance to the selected destination. Feedback is offered by an earphone, providing hands-free use and receiving instructions without visual interaction. The integration of RFID-based bus identification, GPS location, and voice guidance provides smooth real-time information, less reliant on outside help. The system increases mobility confidence through accurate, timely, and convenient information, enabling blind travelers to make use of public transport independently. Through the combination of IoT technology and assistive technologies, the project enables enhanced accessibility and inclusion in urban mobility systems. 2025 IEEE.