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STABILITY IN CHAOS: IMPACT OF MONETARY, FISCAL, AND FIRM CHARACTERISTICS ON INVESTOR SENTIMENT IN ASIAN EMERGING MARKETS
This study investigates the impact of firm characteristics, monetary policies, and fiscal policies on investor sentiment, specifically focusing on market volatility and trading volume in six Asian emerging markets during the pre-pandemic and pandemic periods. Using panel data regression on a sample of 5,619 firms between 2015 and 2023, this study analyses the distinct roles of firm-specific factors and macroeconomic policies in shaping market behaviour during periods of economic instability. The findings reveal that firm characteristics such as capital structure and payout policies consistently drive both volatility and trading volume. Monetary policies, particularly interest rates and money supply, showed heightened significance during the pandemic, while fiscal policies, though largely insignificant pre-pandemic, became more relevant during the crisis. The study's results provide critical insights for policymakers and investors on the dynamic interplay between firm-level and macroeconomic factors during crisis periods, emphasising the need for coordinated policy responses. 2024, Universiti Malaysia Sarawak. All rights reserved. -
INVESTIGATING THE ROLE OF UTAUT2 IN THE USER SATISFACTION AND CONTINUED USAGE OF MOBILE FITNESS APPS: EVIDENCES FROM INDIA
This study examines mobile fitness app (MFA) adoption and use using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). CB-SEM analysis of 445 respondents through IBM-AMOS was conducted. UTAUT2 constructs were examined including, consumer satisfaction, e-loyalty, and mobile fitness app reuse. Also, the roles of socio-demographic factors as control variables were examined. The results indicated that UTAUT2 significantly influenced user perception of MFAs. UTAUT2 constructs increased user satisfaction. User satisfaction positively and significantly influenced e-loyalty and app reuse. The study also suggests future research on UTAUT2's role on MFAs. The study highlights UTAUT2 by revealing the constructs that influence MFA adoption, and selected consequences. (2024), (Amity University). All rights reserved. -
Efficient Brain Tumor Identification Based on Optimal Support Scaling Vector Feature Selection (OSSCV) Using Stochastic Spin-Glass Model Classification
Brain tumor detection is a developing defect finding task in medical imaging, as premature and early identification is a critical once for recommending early treatment. The tumor are identified by the laboratory through MRI images by finding the tumor regions. The Artificial intelligence play a vital role for finding, analyzing, the image data to attain the target results in medical image using various learning methodologies. Most of the existing system failed to find the find the feature dimension leads poor accuracy for identifying tumor regions due to low precision, recall rate, lower intensity in image coverage region. To resolve this problem, to propose an Optimal Support Scaling Vector Based Feature Selection (OSSCV) brain tumor identification using Stochastic Spin-Glass Model Classification (SSGM). Initially the preprocessing is done by bilateral filter and segmentation is applied by suing Active Region Slice Window Segmentation (ARSWS). To separate the tumor entity feature projection using Histogram color quantization and the features process are carried by Optimal Support Scaling Vector Based Feature Selection (OSSCV). The selected features get trained using Stochastic Spin-Glass Model Classification (SSGM) to find the tumor region. The proposed system outperforms traditional machine learning methods in brain tumor detection. Finally proposed system of Stochastic Spin-Glass Model (SSGM) performance of recall is 95.5%, the performance of F1-score is 96.1% and the performance of the 96.5%. The proposed approach has the potential to assist radiologists in diagnosing brain tumors more accurately and efficiently, leading to improved patient outcomes. 2024, Ismail Saritas. All rights reserved. -
Dual ion specific electrochemical sensor using aminothiazole-engineered carbon quantum dots
A novel electrochemical sensor capable of concurrently detecting Pb2+ and Hg2+ ions has been innovatively engineered. This sensor utilizes the anodic stripping voltammetry technique (ASV) with a composite consisting of carbon quantum dots and aminothiazole (CQD-AT). In this composite, both the carbon quantum dots and aminothiazole contribute significantly to the electroactive surface area, boasting an abundance of functional groups that include oxygen and nitrogen atoms. These functional groups serve as active sites that enhance sensor sensitivity by facilitating the electrostatic interaction-based adsorption of heavy metal ions. Aminothiazole surface is evenly covered with CQDs, which are essential for metal gets reoxidized into metal ions for stripping analysis. Due to this unique modification, the Pb2+ and Hg2+ electrochemical sensor using the CQD-AT composite coated on carbon fiber paper electrode (CQD-AT/CFP) exhibits superior analysis performance such as wide linear range (0.6 1011160 106 M) for Pb2+ and Hg2+ with a limit of detection (LOD) of 3.0 pM and 6.2 pM for Pb2+ and Hg2+. CQD-AT/CFP modified electrode can be considered as a potential material for electrochemical simultaneous determination of Pb2+ and Hg2+ in different water samples. 2023 Elsevier B.V. -
Mathematical approach for impact of media awareness on measles disease
During the recent pandemic caused by COVID-19, media awareness played a crucial role in educating people about social distancing, wearing masks, quarantine, vaccination, and medication. Media awareness brought individual behavioral changes among the people, which in turn helped reduce the infection rate. Motivated by this, we have formulated a mathematical model introducing a media compartment to mitigate measles disease transmission. In this paper, the SEIR model is used to study measles disease in three cases: one with a delay in vaccination, the second with regular vaccination, and the third with the impact of media awareness on the spreading of measles disease. Further, the dynamical behavior of the models is studied in terms of positivity, boundedness, equilibrium, and basic reproduction number (BRN). The sensitivity analysis of the models is conducted, which verifies the importance of the BRN ((Formula presented.)) to be less than one for disease eradication. The numerical study confirms the impact of media awareness on exposed and infected populations. 2023 John Wiley & Sons Ltd. -
Single-monomer dual templated MIP based electrochemical sensor for tartrazine and brilliant blue FCF
In this study, a dual-templated molecularly imprinted polymer-based electrochemical sensor was developed for the simultaneous analysis of two food additive dyes, brilliant blue FCF and tartrazine. Using a 3-aminophenyl boronic acid (3-APBA) monomer and the dual templates of brilliant blue FCF (BB) and tartrazine (TZ), the molecularly imprinted polymer (MIP) layer was electropolymerized on the carbon fibre paper (CFP) electrode. By using BB and TZ as template molecules along the electro-polymerization of 3-APBA, then removing both template molecules, the MIP film was generated on the surface of the CFP electrode. Due to the high surface area provided by modification, several complementary binding sites for template molecules are formed on the surface of the MIP sensor during this process of sensor fabrication. On the MIP/CFP electrode, the electrochemical behavior of BB and TZ was assessed. The monomer/template ratio, pH values, and influencing parameters like the electro-polymerization scanning cycles were all optimized. This sensor was applied to detect brilliant blue FCF and tartrazine in beverage and food samples using MIPAPBA/CFP electrode. 2023 -
Pseudocapacitive electrode performance of zinc oxide decorated reduced graphene oxide/poly(1,8-diaminonaphthalene) composite
Development of Reduced graphene oxide/Zinc oxide/poly(1,8-diaminonaphthalene) (rGO/ZnO/PDAN) composite and its supercapacitor performance has been evaluated. Functional, crystal and morphological structures along with the thermal stability of the polymer-impregnated composite were studied using analyses such as FTIR, powder XRD, Raman, SEM and TGA techniques. The SEM images showcased the random decoration of irregularly shaped ZnO in between the wrinkled rGO sheets and the PDAN. The defective structure of the hybrid composite contributes capacitive features through electron transfer kinetics. The specific capacitance value for the rGO/ZnO/PDAN composite modified NF electrode in 3 M KOH was found to be 239 F/g at the current density of 0.5 A/g. The capacitance retained is 92 % after 5000 cycles at 5 A/g current density. A solid-state symmetrical supercapacitor device based on a novel rGO/ZnO/PDAN composite was successfully developed, which exhibits the specific capacity (40 at 0.6 A/g), energy density (12.66 Wh/kg) and power density (993 W/kg). The synergistic combination of surface-active nitrogen heteroatoms, extended conjugation and ZnO particles decorated over rGO sheets of rGO/ZnO/PDAN ternary hybrid composite displayed significant structural stability and electrochemical pseudocapacitive performances. 2023 Elsevier Ltd -
Implementing Innovative Weed Detection Techniques for Environmental Sustainability
Agriculture, supporting over half of India's population, grapples with the challenge of weed control. Current methods applied in plantation crops lack efficiency and pose environmental and health risks. This paper advocates a paradigm shift, emphasizing the critical need for effective weed detection using cluttered unmanned aerial vehicle (UAV) images. The research methodology integrates image processing, Mask R-Convolutional Neural Networks (R-CNN), and Internet of Things (IoT). A dataset of 200 UAV images was subjected to a thorough preprocessing. In the initial phase, weeds and crops were identified with precision employing an UAV-tailored Mask R-CNN with instance segmentation. This was found to surpass traditional methods in terms of communication between the model and the agricultural environment. For timely decision-making, real-time data were collected using IoT. Average Precision (AP) values reveal high accuracy, notably 89.1% for weeds, 88.9% for crops, and an overall precision of 89.4%. The Mask R-CNN network segments and classifies images, marking weed zones communicated to farmers via Raspberry Pi with a GSM module, enabling real-time alerts and informed decision-making for efficient weed control. This holistic approach, providing object classifications, detailed bounding boxes, and masks, addresses weed control challenges, highlighting the transformative potential of advanced technologies in agriculture. 2024, Institute for Environmental Nanotechnology. All rights reserved. -
Solid-State Organic Fluorophore for Latent Fingerprint Detection and Anti-Counterfeiting Applications
A highly fluorescent material exhibiting solid-state fluorescence is particularly important in detecting latent fingerprints (LFPs) and anti-counterfeiting applications. Herein, we have synthesized a coumarin-benzothiazole moiety 3-(benzo[d]thiazol-2-yl)-2H-chromen-2-one (3-BTC) to inspect its capability to visualize LFPs and work as an anti-counterfeiting ink. The compound showed yellow-greenish emission under UV excitation and good covertness under visible light conditions. With the help of the powder dusting method, the latent fingerprints were coated with 3-BTC powder and images of the LFPs developed over various substrates including plastic, steel, aluminium plate, rubber, etc. under UV 365 nm light displayed good resolution be able to discern the patterns of all the levels 13. Apart from fresh fingerprints (taken within 10 seconds), aged (over 60 days) and incomplete eccrine LFPs were successfully visualized using 3-BTC powder. Anti-counterfeiting ink prepared using 3-BTC also proved to be a promising candidate as an anti-counterfeiting ink. Various types of paper materials, including tissue paper, printing paper, newspaper, etc. were used for evaluating 3-BTC as a satisfactory anti-counterfeiting ink. 2024 Wiley-VCH GmbH. -
ENHANCING FAKE NEWS DETECTION ON SOCIAL MEDIA THROUGH ADVANCED MACHINE LEARNING AND USER PROFILE ANALYSIS
Social media news consumption is growing in popularity. Users find social media appealing because it's inexpensive, easy to use, and information spreads quickly. Social media does, however, also contribute to the spread of false information. The detection of fake news has gained more attention due to the negative effects it has on society. However, since fake news is created to seem like real news, the detection performance when relying solely on news contents is typically unsatisfactory. Therefore, a thorough understanding of the connection between fake news and social media user profiles is required. In order to detect fake news, this research paper investigates the use of machine learning techniques, covering important topics like feature integration, user profiles, and dataset analysis. To generate extensive feature sets, the study integrates User Profile Features (UPF), Linguistic Inquiry and Word Count (LIWC) features, and Rhetorical Structure Theory (RST) features. Principal Component Analysis (PCA) is used to reduce dimensionality and lessen the difficulties presented by high-dimensional datasets. The study entails a comprehensive assessment of multiple machine learning models using datasets from "Politifact" and "Gossipofact," which cover a range of data processing methods. The evaluation of the XGBoost classification model is further enhanced by the analysis of Receiver Operating Characteristic (ROC) curves. The results demonstrate the effectiveness of particular combinations of features and models, with XGBoost outperforming other models on the suggested unified feature set (ALL). 2023 Little Lion Scientific. -
REVIEW OF CENSORING SCHEMES: CONCEPTS, DIFFERENT TYPES, MODEL DESCRIPTION, APPLICATIONS AND FUTURE SCOPE
Survival analysis is one of the key techniques utilized in the domains of reliability engineering, statistics, and medical domains. It focuses on the period between the initialization of an experiment and a subsequent incident. Censoring is one of the key aspects of survival analysis, and the techniques created in this domain are designed to manage various censoring schemes with ease, ensuring accurate and insightful time-to-event data analysis. The statistical efficiency of parameter estimates is improved by accurately incorporating censoring information by making use of the available data. This paper reviews the concepts, model descriptions, and applications of conventional and hybrid censoring schemes. The introduction of new censoring schemes from conventional censoring schemes has evolved by rectifying the drawbacks of the previous schemes, which are explained in detail in this study. The evolution of hybrid censoring schemes through the combination of various conventional censoring schemes, the data structures, concepts, methodology, and existing literature works of hybrid censoring schemes are reviewed in this work. 2024, Gnedenko Forum. All rights reserved. -
Improved reptile search algorithm with sequential assignment routing based false packet forwarding scheme for source location privacy protection on wireless sensor networks
Source Location Privacy (SLP) in Wireless Sensor Networks (WSNs) refers to a set of techniques and strategies used to safeguard the anonymity and confidentiality of the locations of sensor nodes (SNs) that are the source of transmitted data within the network. This protection is important in different WSN application areas like environmental monitoring, surveillance, and healthcare systems, where the revelation of the accurate location of SNs can pose security and privacy risks. Therefore, this study presents metaheuristics with sequential assignment routing based false packet forwarding scheme (MSAR-FPFS) for source location privacy protection (SLPP) on WSN. The contributions of the MSAR-FPFS method revolve around enhancing SLP protection in WSNs through the introduction of dual-routing, SAR technique with phantom nodes (PNs), and an optimization algorithm. In the presented MSAR-FPFS method, PNs are used for the rotation of dummy packets using the SAR technique, which helps to prevent the adversary from original data transmission. Next, the MSAR-FPFS technique uses an improved reptile search algorithm (IRSA) for the optimal selection of routes for real packet transmission. Moreover, the IRSA technique computes a fitness function (FF) comprising three parameters namely residual energy (RE), distance to BS (DBS), and node degree (ND). The experimental evaluation of the MSAR-FPFS system was investigated under different factors and the outputs show the promising achievement of the MSAR-FPFS system compared to other existing models. 2024-IOS Press. All rights reserved. -
Effect of functionalization on the energy storage performance of super capacitors derived from wood charcoal
The electrochemical performance of wood charcoal is investigated with respect to the disorders in the system after subjecting to oxidation and exfoliation conditions. The Cyclic voltammetry and galvanostatic charge discharge curves indicate an improvement in the electrochemical behavior, resulting in a marginal increase in the specific capacitance values at higher exfoliation temperatures. The improvement is predominantly due to the change in the structural disorder in the system accompanied by the incorporation of oxygen functional groups which act as electrochemical active species. The exfoliation of wood charcoal at 160 and 200C yield a specific capacitance of 6.23 and 12.24 F/g at a current density of 0.01 A/g. The ESR values representing the overall resistance of the system are observed to be 6.07 ? for 200C as opposed to 10.41 ? of the bare material, making the material more conducting. The drastic change in the structural morphology along with the optimal amount of oxygen functional groups can be the reason for this behavior. The acquired results offer useful information for investigating the possibilities of fabricating supercapacitors with wood charcoal by tuning the defects of the system. 2024 American Institute of Chemical Engineers. -
Exploring the effectiveness of mindfulness-based intervention among college students in India
This study investigated the effectiveness of an eight-week mindfulness-based intervention program on the trait mindfulness, psychological well-being and emotion regulation of college-going students. The experimental group participants were college-going students (N = 40) who enrolled for the intervention, and the participants in the control group (N = 40) were interested in the intervention and considered as a wait-list control group. The experimental group underwent mindfulness-based interventions, which included 1112 sessions, including brief exercises and meditations related to their trait mindfulness, emotion regulation, and psychological well-being. They received 23h of training per week for eight weeks. Repeated Measures of ANOVA together with an independent sample t-test were used to evaluate the effectiveness of this intervention programme. Further, Cohens d was used to calculate the effect size to explain the variance caused by the intervention program in trait mindfulness, emotion regulation, and psychological well-being. The results indicated that students significantly improved in their trait mindfulness, emotion regulation, and psychological well-being after receiving mindfulness training. In conclusion, the application of this eight-week mindfulness-based intervention sheds light on the common psychological issues confronted by college students in India, presenting itself as an advantageous tool for the professionals working in this field and offering positive effects on the overall well-being of college students. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Multivariate statistical optimization of phenolics and antioxidants from nutmeg seeds (Myristica fragrans Houtt)
The present study aimed to optimize the phenolic and antioxidant-rich extract from the nutmeg (Myristica fragrans Houtt) by using a two-factor 26-run central composite design-based response surface methodology tool. The selected parameters were extraction period (2 to 5days), solvent-to-water ratio (v/v) (50100%), and type of solvent (acetone or ethanol). The optimized extract at conditions of 3.14days incubation and 68% (v/v) acetone showed total phenolic content (TPC), total flavonoid content (TFC), and DPPH antioxidant assay as 376.38mg GAE/g DW, 34.40mg QUE/g DW and 842.46mg AAE/g DW, respectively. Among the nineteen (19) compounds identified by the LCMS, myristicin (37.74%) was found to be the highest. Nine (9) alkane-fatty acyl compounds were determined by the GCMS analysis, as well. Additionally, SEM and XRD revealed sheet-like anatomy with the presence of Carbon (C), Oxygen (O) and Potassium (K). The study presented a unique approach to optimizing phenolic-rich antioxidant extracts from nutmeg using response surface methodology, offering valuable insights for more efficient extraction of bioactive compounds with minimal resource waste and potentially enhancing the utilization of nutmeg's nutraceutical properties. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Role of Globalization and Innovation Pattern in Growth of Bank Credit: Evidence From Emerging and Advanced Asia
This study examines the role of globalization and innovation pattern (i.e., innovation by the residents and non-residents) in the growth of domestic bank credit across emerging and advanced Asian economies spanning from 1996 to 2022. The bank credit growth model includes economic growth and real interest rate as important control variables. This study employs Cross Sectional-Autoregressive Distributed Lag (CS-ARDL) as an appropriate baseline method because of the cointegration, endogeneity, and cross-sectional dependency present in the data. The long-run results for emerging Asian economies indicate that globalization exhibits a negative impact on banking credit, contrasting with the positive influence observed in advanced Asian economies due to heightened economic growth and increased credit demand. Residential innovation consistently bolsters banking credit in both sets of economies, albeit with mixed effects stemming from non-resident innovation. The long-run results further indicate the positive (negative) impact of economic growth (real interest rate) on bank credit in emerging and advanced Asian economies. These findings are reliable due to the similar results obtained from using Driscoll-Kraay Robust Standard Errors (DKSEs) as robust method. For policymakers in emerging economies, the imperative policy lies in striking a delicate balance between economic openness and bank credit, while counterparts in advanced economies are poised to bolster bank credit accessibility through foreign innovation while upholding stringent regulatory oversight. 2024 John Wiley & Sons Ltd. -
Rise of Populism in Northeast India: A Case of Assam
A blend of historical and contemporary forces has shaped populism in India. The Congress governments shortcomings (20042014), marked by dynastic politics and corruption, paved the way for the rise of populism, particularly under the Bharatiya Janata Party (BJP), which capitalized on anti?elite sentiment. Narendra Modis leadership, characterized by Hindu nationalism and a development agenda, has significantly altered Indias political landscape. This study focuses on the rise of populism in Northeast India, specifically in Assam, where populist movements and leaders have increasingly influenced the socio?political environment. It explores the socio?economic conditions and identity politics that have driven the growth of populist ideologies, often leading to the marginalization of ethnic minorities. By analyzing key political events, movements, and policies, the research seeks to uncover the root causes of populism in Assam and its impact on democracy, social cohesion, and regional stability. Employing a qualitative methodology that includes political speeches, media analysis, and empirical evidence, the study examines how political leaders in Assam have mobilized regional and ethnic sentiments for electoral gains, further exacerbating ethnic marginalization. The article aims to understand the catalysts and consequences of populist governance in Assam, offering insights into the broader trend of populism in Northeast India and its future trajectory. 2024 by the author(s). -
Role of corporate innovation and uncertainty in determining corporate investment of the firm: does financial constraint, executive risk preference and firm risk-taking ability play any role
Purpose: This paper aims to investigate the relationship between corporate innovation and the firms corporate investment. Further, the authors begin with the assertion that the relationship between corporate innovation and corporate investment is impacted by significantly a) uncertain periods, b) financial constraint, c) executives risk preference and d) firm risk-taking ability. Design/methodology/approach: This study has considered non-financial listed companies (774 firms) for the period spanning from 20102022. The authors use a fixed effect regression model within a panel data framework to examine the relationship between corporate innovation and investment. For robustness, the authors use system generalised methods of moments to investigate the relationship between corporate investment and corporate innovation across all the samples. Findings: This study finds a positive relationship between corporate innovation and corporate investment, which means when the firm tries to make some innovation, it will increase its expenditure on fixed assets. However, the positive relationship between corporate innovation and corporate investment reduces with uncertainty. Additionally, financial constraint plays a significant role in determining this relationship. Executives and firms with high risk-taking ability tend to be more inclined to make investments. Originality/value: The study is unique because it determines the impact of corporate innovation on corporate investment. The current literature is focused on corporate innovation and uncertainties. However, no light has been shed on the relationship between corporate innovation and investment. At the same time, the authors have introduced three more variables which play a significant role in determining the corporate innovation-investment relationship. , Emerald Publishing Limited. -
Exploring evolution, development, and contribution of International Journal of Industrial and Systems Engineering (20052022): a bibliometric study
International Journal of Industrial and Systems Engineering (IJISE) reached its 18th year of publishing in 2023. A comprehensive assessment of 1,096 publications using the bibliometric data analysis technique is performed to understand growth of the journal for the past 18 years. Different indicators like co-occurrence of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOS Viewer software. The findings of the study emphasise contribution of IJISE to knowledge domain. Copyright 2024 Inderscience Enterprises Ltd. -
WORKFORCE DIVERSITY: A SPOTLIGHT ON EMPLOYEE SUSTAINABILITY EXCELLENCE IN INDIA
This research paper explores a crucial yet often underestimated nexus: the relationship between workforce diversity and employee sustainability in the vibrant television media industry. Through an in-depth examination of diverse dimensions such as age, gender, culture, and socio-behavioral factors, it illuminates how these elements intricately influence the long-term viability of employees within this rapidly evolving sector. The paper's standout feature lies in its rigorous statistical analyses, which uncover the nuanced connections between workforce diversity and employee sustainability. By grounding its findings in empirical evidence, the paper transcends mere conjecture, offering a robust framework for comprehending and tackling this pressing issue. Moreover, the spotlight on the Indian media industry brings a unique perspective, given its extraordinary growth trajectory and substantial economic impact. Readers stand to gain invaluable insights into the dynamics of diversity within this context, potentially yielding transferable lessons and strategies for other industries and regions. In its culmination, the paper presents a synthesis of actionable recommendations and conclusive insights, serving as a practical guide for organizations seeking to harness diversity as a catalyst for long-term employee sustainability. With its blend of academic rigor and real-world relevance, this paper is indispensable reading for industry practitioners, policymakers, and scholars alike. 2024 Sciendo. All rights reserved.