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Psychological experiences and travel Adversities: A Mixed-Method study of the regular commuters in traffic congestion
This study investigated the psychological experiences and consequences of travel adversities during traffic congestion using a three-phase sequential exploratory mixed-methods design. Phase 1 explored the travel adversities, psychological experiences, and consequences of a sample of ten (four women and six men) regular commuters of Bangalore's congested roads using semi-structured interviews. In phase 2, a checklist was developed listing the fundamental themes from phase 1 with Likert-type responses ranging from 0 (never) to 5 (always). Phase 3 gathered data in the checklist and tested the statistical validity of the thematic model in a sample of 190 (81 women and 103 men) regular commuters. Attride-Stirling model thematic network was established with 57 fundamental themes categorized and assigned under the organizing themes of travel adversities (n = 6), negative affect (n = 28), fight (n = 7), flight (n = 6), and negative road occurrences (n = 10), in the global theme, psychological experiences and consequences. Structural equation modeling indicated that (1) negative affect significantly predicted fight and flight, (2) fight is a significant predictor of negative road occurrences, and (3) psychological experiences and consequences create a self-perpetuating cycle, with travel adversity triggering negative emotions, which results in fight responses leading to negative road occurrences, further intensifying travel adversity. A mathematical model is established based on this statistical validation, which holds potential applications in real-time traffic algorithms. 2024 -
An adaptive inertia weight teachinglearning-based optimization for optimal energy balance in microgrid considering islanded conditions
The energy balance in islanded microgrids is a complex task due to various operational constraints. This paper proposes a new approach to multi-objective optimization for achieving energy balance in aMicrogrid(MG) in both islanded and normal modes. Optimal load control (OLC)is achallenge, due to a lack of capacity to generate the global optimum after each run. The latest variant of Teaching Learning Based Optimization (TLBO), known as Adaptive-TLBO, includes both modifications during exploitation and exploration stages (ATLBO). The results achievedwith the proposed method are exceptional on a modified IEEE 33-bus system. In addition to the improvement of the voltage profile and the decrease of the distribution losses, the energy balance improves with the method. The proposed ATLBO algorithm overrides any proposed other algorithm, as shown by comparison with PSO, base TLBO, Backtrackingsearch algorithm (BSA) and cuckoo search algorithms, etc. (CSA). The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. -
Sibling influence on musical identity in emerging adults
A key characteristic and an important task of emerging adulthood is identity development. Music provides an important context for identity development, especially in emerging adults, and siblings in turn play an important role in the process of identity development. Using a qualitative narrative approach, this study aims to understand the role of siblings in the musical identity development of emerging adults. Five emerging adults between the age range of 1825years were recruited and interviewed individually. Thematic narrative analysis of the transcripts gave rise to 3 themes: Sibling Relationships, Early Identity and Discrepancy, and The Growth Journey. Overall, it was evident that siblings played a crucial role and had a large impact on the identity development process of the participants. This study provided support for Arnett's theory of emerging adulthood, with identity exploration being a defining feature of this developmental period. Further, the study also supported the notion of important others impacting the identity verification process according to identity control theory. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
An efficient deep learning based stress monitoring model through wearable devices for health care applications
Due to the mental stress of the human, the negative effects are known to be recent decades. Early detections of high level stresses are necessary to stop harmful consequences. Studies have proposed on wearable technologies which detect human stress. This study proposes stress detection systems which use physiological signals of people collected by wearable technologies and attached to human bodies. They can carry it during their daily routine. This works proposed system includes removal of artifacts in bio signals and feature extractions from these cleaned signals. Since, DL (deep learning) based models are proven to be the best for these analyses, this article uses a random differential GWO (Grey wolf optimization) algorithm for feature extraction and a ML (machine learning) algorithm called RF (random forest) has been used for classification of the human body parameters like activities of the heart, conductance in skins and corresponding accelerometer signals. The proposed stress detection system is implemented with the real time data gathered from 21 participants. This approach can detect the stress of a human and prevent it from early stages with necessary lectures to avoid the negative effects. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Fluorescent imidazole derived sensor for selective in vitro and in vivo Fe2+ detection and bioimaging in zebrafish with DFT studies
Herein, we have developed imidazole derivatized fluorescent probes IM-1 and IM-2 for extremely selective detection of Fe2+ with rapid response (LOD: 3.245 ?M for IM-1 and 0.297 ?M for IM-2) and excellent binding constants (0.214 105 M?1 and 1.004 105 M?1). Aqueous ethanol system was employed to assess the sensing potency of the probes both in vitro and in vivo in zebrafish is the main highlight of this work. The synthesized fluorophores possess admirable quantum yields of 0.61 and 0.78. The 1:1 binding mechanism of ligands with Fe2+ ions is supported by Job's plot and ESI-Mass spectrum. The synthesized probes demonstrated limited cytotoxicity both in vitro (MDA-MB-231 cells) and in vivo (zebrafish, Danio Rerio) studies. These results prompted us to employ the probes IM-1 and IM-2 to trace out intra cellular Fe2+ ions in zebrafish embryos. 2024 Elsevier B.V. -
Are expensive decisions impulsive? Young adults impulsive housing and real estate buying behavior in India
Purpose: The purpose of the study is to determine website quality, materialism, psychological factors, hedonic value and social media as factors that influence the young adults impulsive housing and real estate buying behavior in India. In addition, this study also measures the mediating effects of social media influence between psychological factors and hedonic value and young adults impulsive housing and real estate buying behavior. Design/methodology/approach: Related literature, quantifiable variables with a five-point Likert Scale, hypothesis testing and mediators are used to study the model. A systematic questionnaire that was divided into six sections was used. A total of 385 valid responses were collected and analyzed through a structural equation model. Findings: The results suggest that materialism, psychological factors and social media have a considerable impact on young adults impulsive housing and real estate buying behavior. The findings also ascertained that website quality and hedonic value do not have a considerable impact on young adults impulsive housing and real estate buying behavior. Research limitations/implications: This study is limited to the responses of young consumers from a limited number of brokers and regions in India. Future studies could be more widespread across the globe. Originality/value: As per the review of existing literature, this research is the first, to the best of the authors knowledge, to determine the factors affecting the impulse buying decision mainly in the housing and real estate sector with the target consumers being young. 2022, Emerald Publishing Limited. -
Multifunctional characteristics of biosynthesized CoFe2O4@Ag nanocomposite by photocatalytic, antibacterial and cytotoxic applications
Carissa carandas, a traditional medicinal herb with a high concentration of antioxidant phytochemicals, has been used for thousands of years in the Ayurveda, Unani, and homoeopathic schools of medicine. By employing Carissa carandas bark extract as a reducing and capping agent in green biosynthesis, we extend this conventional application to produce CoFe2O4 and CoFe2O4@Ag nanocomposite. A variety of techniques have been used to characterize the synthesised nanocomposite, including UVVis, FTIR, XRD, FESEM, EDX, and BET. The CoFe2O4 and CoFe2O4@Ag nanocomposite demonstrated promising antibacterial action against human bacterial pathogens like B. subtilis and S. aureus as gram positive and P. aeruginosa and E. coli as gram negative with inhibition zones of 24.3 0.57, 17.4 0.75 and 20.5 0.5, 19.8 1.6 mm respectively, and the obtained results were superior to the nanocomposite without silver. Moreover, in-vitro cytotoxicity effects of biosynthesized CoFe2O4 and CoFe2O4@Ag were performed on the human breast cancer cell MCF-7. It was found that the MCF-7 cells' 50% inhibitory concentration (IC50) was 60 ?g/mL. Additionally, biosynthesized CoFe2O4 and CoFe2O4@Ag nanocomposite was used to demonstrate the photocatalytic eradication of Rhodamine Blue (RhB). Due to the addition of Ag, which increases surface area, conductivity, and increased charge carrier separation, the CoFe2O4@Ag nanocomposite exhibits a high percentage of photocatalytic degradation of ? 98% within 35 min under UV light irradiation. The photocatalytic performance of as-synthesised nanocomposite was evaluated using dye degradation-adsorption in both natural light and dark condition. Under dark conditions, it was found that 2 mg mL?1 CoFe2O4@Ag in RhB aqueous solution (5 ppm) causes dye adsorption in 30 min with an effectiveness of 72%. Consequently, it is anticipated that the CoFe2O4@Ag nanocomposite will be a promising photocatalyst and possibly a noble material for environmental remediation applications. 2023 Elsevier Ltd -
The Evaluation of Security and Privacy Components in the Context of Peer-To-Peer Power Trading Methodologies using Network Intelligence
The widespread implementation of renewable energy sources, along with a more proactive approach to managing electricity use, is causing a shift in the way power systems operate and electricity is traded in the market. The P2P economy in particular is benefiting from this change. To efficiently handle the fast changes in renewable power generation at the distribution network level, a local market mechanism that can adapt is required. The efficient and safe operation of the distribution network is also bound to be affected by the extensive adoption of P2P energy trading. This study presents a new paradigm for P2P power trading that accounts for constraints imposed by distribution network security. Specifically, the design makes use of the generalised quick dual ascent method. The article lays out the groundwork for an event-based local peer-to-peer market, which would facilitate rapid and efficient energy swaps inside a certain region. The next step in making sure the distribution system is secure is to evaluate the impact of peer-to-peer transactions on the network using the nodal voltage and network loss in relation to nodal power injections. This allows for an internal determination of how to distribute the costs of P2P energy trading and the incorporation of the external operating constraints. Distributed market-clearing is also applied efficiently by means of a universal quick dual ascent technique. The numerical results show that the proposed model can implement P2P energy trading securely into the distribution system. Furthermore, the method for solving the problem shows remarkable efficiency in achieving convergence. 2024, Auricle Global Society of Education and Research. All rights reserved. -
Task-based Autoethnographic Pedagogical Approach: a phenomenological inquiry into online learning of Critical Food Studies courses
The disengaging experiences reported in the online mode of learning have resulted in considerable deliberations highlighting the need for pedagogical innovations. Therefore, it is crucial to rethink these ideas and develop pedagogical approaches that accommodate a dynamic understanding of learning spaces and meet the demands of the teachinglearning environment of the contemporary period. This study discusses the various steps through which the task-based autoethnographic pedagogical approach (TAPA) was implemented in an undergraduate-level Critical Food Studies course and proposes it as an effective approach to administering certain courses by enabling active learning in the online mode. The study captures learners perceptions of meaningful online learning experiences by using an interpretative phenomenological approach, mapping the aspects that contribute to a sense of rekindled interest and involvement in the course. Some of the dominant patterns that emerge from this phenomenological study are (1) appreciation towards praxis-based online learning, (2) recognition of lived space as a ripe site for inquiry and learning, (3) a heightened sense of engagement with lived contexts, and identity discourses, (4) learners negotiations with TAPA, and (5) learner as an active agent and curator of knowledge. Thus, while situating TAPA as an effective pedagogical approach for online learning and Critical Food Studies curriculum, it is also posited as an approach that initiates negotiation with the epistemic hierarchies within academia. Education Research Institute, Seoul National University 2022. -
On the Hermite and Mathieu Special Characterizations to the Logarithmic ZakharovKuznetsov Equations
In this paper, we find the new travelling wave solutions for several aspects of logarithmic ZakharovKuznetsov (ZK) equations using an efficient technique called the special function method which is composed of Hermite and Mathieu differential equations being novel and special functions. In order to illustrate the efficiency of the projected scheme, we considered four different examples with different cases, namely, logarithmic ZK (log-ZK) equation, logarithmic modified ZK (log-mZK) equation, and logarithmic ZK modified equal width (log-ZK-mEW) equation and logarithmic ZKBenjaminBonaMahony (log-ZKBBM) equation. The behaviour of the obtained results and corresponding consequences are illustrated and captured. Finally, the obtained results confirm that the considered solution procedure can be widely employed to find the solution and also capture some interesting and stimulating consequences. 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Combined weighted feature extraction and deep learning approach for chronic obstructive pulmonary disease classification using electromyography
The COVID-19 outbreak has led to a rise in respiratory disease-related deaths, including Chronic Obstructive Pulmonary Disease (COPD). Early diagnosis of COPD is crucial, but it can be challenging to distinguish between different chronic pulmonary diseases due to their similar symptoms, leading to misdiagnosis and time-consuming manual inspections. To address this issue, this paper explores the use of a deep learning model to differentiate COPD from other lung diseases using lung sound captured during Electromyography (EMG). The model includes steps such as noise removal, data augmentation, combined weighted feature extraction, and learning. The model's efficacy was evaluated using various metrics, including accuracy, precision, recall, F1-score, kappa coefficient, and Matthews correlation coefficient (MCC), with and without augmentation. The results show that the model achieved 93% accuracy and outperformed other existing state-of-the-art deep learning models, increasing the robustness of clinical decision-making. The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2023. -
Factors influencing career decision of undergraduate and postgraduate students: an Indian context
Purpose: The objective of the study was to explore the factors influencing the career decisions of students doing the students' undergraduate (UG) and postgraduate (PG) programmes from urban private universities/colleges in the Indian context. Design/methodology/approach: Career decision-making is determined by different factors and is contextual. The present study explores and identifies the prominent factors influencing career decision-making. A pool of 33 questions was developed, and these questions were initially administered to a sample of 233 students. Principal component analysis with Varimax Rotation identified salient factors. In the second study, confirmatory analysis was performed based on the opinion of 304 students. Findings: The study shows that the student's career deciding factors include (1) career clarity, (2) career exploration, (3) career reward and recognition and (4) career initiative for professional and personal growth. Originality/value: The study focussed on career-deciding factors for UG and PG students from urban universities/colleges in the Indian context and the findings can be used for planning career counselling interventions. 2023, Emerald Publishing Limited. -
Gammaless gamma-ray bursts?
One of the possible resolutions of the compactness problem in gamma-ray bursts (GRBs) is by invoking the Lorentz factors associated with the relativistic bulk motion. This model applies to GRBs where sufficient energy is converted to accelerate the ejected matter to relativistic speeds. In some situations, this may not be a possible mechanism, and as a result, the gamma rays are trapped in the region. In this work, we look at such possible scenarios and where the neutrino pair production process can dominate. As a result, the neutrinos can escape freely. This could give rise to a scenario where the release of neutrinos precedes the gamma-ray emission that is much attenuated. This model can thus possibly explain why fewer GRBs are observed than what is expected. 2023, Indian Association for the Cultivation of Science. -
Solution of a dengue fever model via fractional natural decomposition and modified predictor-corrector methods
In this paper, we solved a model of a well-known infectious disease called dengue fever via fractional natural decomposition and modified Predictor-Corrector (PC) methods. A study of the dengue epidemic in the Cape Verde Islands off the coast of West Africa in 2009 has been resumed here for a better understanding of the results. The results are obtained using Liouville-Caputo and new generalized Caputo-type fractional derivatives. The numerical simulations are presented for various orders of given derivatives. Existence and uniqueness analysis of the given problem are also performed in the new generalized Caputo sense. The explored results are verified using figures. The main target of this paper is to explore the different dynamics of the given dengue fever model via two types of fractional numerical algorithms. 2024 World Scientific Publishing Company. -
Income Inequality in Globalization Context: Evidence from Global Data
This paper empirically investigates the relative effectiveness of economic globalization, trade openness, and financial openness on income inequality in low-, middle-, and high-income countries for the panel data over the period from 1991 to 2020 by endogenizing economic growth, urbanization, agriculture, industry, and service sectors value-added as % of GDP as control variables in income inequality function. The results emanating from the panel pooled mean group-autoregressive distributed lag (PMG-ARDL) test provide evidence of a significant long-run relationship among the variables. Interestingly, economic globalization reduces income inequality for high- and middle-income countries and increases it in low-income countries. On the other hand, trade openness reduces income inequality in high- and middle-income countries but increases it for low-income countries. In contrast, financial openness lessens income inequality in low-income countries but increases it for middle- and high-income countries. We find that urbanization increases income inequality in low-, middle- and high-income countries. We also find that economic growth decreases (increases) income inequality in high (middle and low)-income countries. Moreover, it is found that industrial and service sectors output decrease (increases) income inequality in high (middle and low)-income countries, whereas agricultural output improves (deteriorates) income distribution in middle- and low- (high) income countries. In light of these findings, we suggest that the governments of low-income countries need to focus more on improving the level of globalization and trade openness to improve their economic conditions in long run. Both high- and middle-income countries should also improve their financial openness so that effective utilization of overseas finance will flourish their overall economy. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
Mathematical analysis of histogram equalization techniques for medical image enhancement: a tutorial from the perspective of data loss
This tutorial demonstrates a novel mathematical analysis of histogram equalization techniques and its application in medical image enhancement. In this paper, conventional Global Histogram Equalization (GHE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Histogram Specification (HS) and Brightness Preserving Dynamic Histogram Equalization (BPDHE) are re-investigated by a novel mathematical analysis. All these HE methods are widely employed by researchers in image processing and medical image diagnosis domain, however, this has been observed that these HE methods have significant limitation of data loss. In this paper, a mathematical proof is given that any kind of Histogram Equalization method is inevitable of data loss, because any HE method is a non-linear method. All these Histogram Equalization methods are implemented on two different datasets, they are, brain tumor MRI image dataset and colorectal cancer H and E-stained histopathology image dataset. Pearson Correlation Coefficient (PCC) and Structural Similarity Index Matrix (SSIM) both are found in the range of 0.6-0.95 for overall all HE methods. Moreover, those results are compared with Reinhard method which is a linear contrast enhancement method. The experimental results suggest that Reinhard method outperformed any HE methods for medical image enhancement. Furthermore, a popular CNN model VGG-16 is implemented, on the MRI dataset in order to prove that there is a direct correlation between less accuracy and data loss. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Influence of Synthesis Temperature on the Structural, Morphological and Optical Properties of MoO3 Nanorods
Molybdenum trioxide nanomaterials have attained notable attention in the recent past and are used in various optoelectronic and biomedical applications. Here blue and purple blue light emitting MoO3 nanophosphors were synthesized using the simple hydrothermal method at three different temperatures 100C, 150C, and 200C. Structural characterization using XRD along with Raman spectroscopy confirms the formation of a highly stable orthorhombic phase. Micro strain effects have been analyzed by employing the Williamson-Hall method using a uniform deformation model. Nanorod like morphology was obtained from FESEM. Optical analysis, using Tauc plot shows a decreasing trend in bandgap value with increasing temperature. Emission peaks in the photoluminescence spectrum are associated with the transition between the sub-bands of the Mo5+ defect state. From CIE coordinates it is confirmed that the characteristic light from the samples is blue and purple-blue. Being an excellent blue and purple blue light emitting phosphor, MoO3 is a suitable material for future LED and fluorescence imaging applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
Catalyzing the Affordability of Perovskite Solar Cells with Aluminum-Modified Cubic Titania
As a key component of perovskite solar cells (PSCs), the electron transport layer (ETL) extracts charges efficiently. While TiO2 is widely recognized as a superior electron transport material (ETM) for its numerous advantages, the morphological limitations of spherical TiO2 nanoparticles (NPs) lead to significant electron losses. Therefore, as an alternative to nanospheres, TiO2 nanocubes are synthesized through a solvothermal route and employed as ETM in the low-cost carbon electrode-based perovskite solar cells (CPSCs). The structural, morphological, and optical properties of the TiO2 nanocubes (NCs) are studied and compared with TiO2 nanospheres (NSs) in detail. The device possessing cubic TiO2 achieved a power conversion efficiency (PCE) of 10.6% with a current density (Jsc) of 21.79 mA/cm2. Recognizing that the oxygen vacancies in cubic TiO2 are lower than in spherical TiO2, it is inferred that further reduction of oxygen vacancies in cubic TiO2 could enhance the current collection. Hence, to get rid of the oxygen vacancy (which acts as an electron trap) in the cubical TiO2, aluminum (Al3+) is incorporated into its matrix. A comprehensive analysis of its impact on structural and optical behavior follows. In addition to its cost-effectiveness and conductive nature, it has been observed that the stable form of Al3+ replaces the unstable Ti3+ (which acts as a trap state), thereby reducing the recombination rate. With the highest current collection of 22.85 mA/cm2, a PCE of 11.3% has been recorded for the solar cell that possessed 1% Al-doped TNC. Furthermore, the ambient stability of the respective device shows ?85% of its initial PCE. The effect of the TiO2 nanostructure and Al3+ doping in TiO2 nanocubes is discussed elaborately in this work. 2024 American Chemical Society -
An efficient adaptive reconfigurable routing protocol for optimized data packet distribution in network on chips
The deadlock-free and live lock-free routing at the same time is minimized in the network on chip (NoC) using the proposed adoptive reconfigurable routing protocol (ARRP). Congestion condition emergencies are avoided using the proposed algorithm. The input packet distribution process is improved among all its shortest paths of output points. The performance analysis has been initiated by considering different configuration (N*N) mesh networks, by sending various ranges of data packets to the network on chip. The average and maximum power dissipation of XY, odd-even, Dy-XY algorithm, and proposed algorithm are determined. In this paper, an analysis of gate utilization during data packet transfer in various mesh configurations is carried out. The number of cycles required for each message injection in different mesh configurations is analyzed. The proposed routing algorithm is implemented and compared with conventional algorithms. The simulation has been carried out using reconfigurable two-dimensional mesh for the NoC. The proposed algorithm has been implemented considering array size, the routing operating frequency, link width length, value of probability, and traffic types. The proposed ARRP algorithm reduces the average latency, avoids routing congestion, and is more feasible for NoC compared to conventional methods. 2024 Institute of Advanced Engineering and Science. All rights reserved. -
Fossil fuel derived GQD as a photosensitizer in dye-sensitized solar cells
Solar energy is an abundantly available renewable source, and several generations of photovoltaic cells have been developed for harnessing it. Dye-sensitized solar cells (DSSC) are viable and potent solar energy harvesters. Sensitizer, a vital part of DSSC, has been researched for years. Alternatively, fossil fuel-Lignite is one of the world's least explored energy sources. Unfortunately, it has been used as a fuel for power generation and tagged as a pollutant. Therefore, in this study, we use lignite-derived graphene quantum dots (GQD) as a DSSC sensitizer and attempt to add value. GQDs with varied bandgaps were obtained and used as sensitizers, and a maximum PCE of 2.87 % was obtained. Additionally, GQD sensitizers were exposed to UV light for 48 h, and the fabricated device exhibited 2.90 % efficiency, showing the photostability of GQDs. Furthermore, the device showed a higher Rrec of 166.57 ?, substantiating the better performance of DSSC. Thus, sensitizers derived from lignite showed a novel use for feedstock previously used for combustion. 2023 Elsevier B.V.