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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. -
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. -
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. -
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 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. -
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 -
A Metal-Free KOtBu-Mediated Protocol towards the Synthesis of Quinolines, Indenoquinolines and Acridines
An expeditious strategy has been developed for the synthesis of diverse quinolines, indenoquinolines and acridines using KOtBu-mediated reaction conditions. The designed process utilizes 2-aminoaryl carbaldehydes/2-aminoaryl ketones and methyl/methylene group containing ketones as readily available feedstock. The chemical transformation was affected at room temperature within a short duration of time to obtain diverse N-heterocycles yields up to 92 %. The established process also exhibits considerable functional group tolerance with an operational simplicity. 2024 Wiley-VCH GmbH. -
Transformational leadership and organizational citizenship behavior: new mediating roles for trustworthiness and trust in team leaders
This study investigates the pivotal role of trust in bridging the effects of transformational leadership on organizational citizenship behavior (OCB). The study was conducted using a multilevel longitudinal approach with 276 employees in 71 teams from private medium-sized organizations in Kuala Lumpur, Malaysia. Transformational leadership was found to be positively related to: (1) three facets of trustworthiness (ability, benevolence, and integrity); (2) trust in the leader; and (3) OCB. All three facets of trustworthiness mediated the relationship between transformational leadership and trust in leaders. In addition, trust in the leader mediated only the relationship between the benevolence facet of trustworthiness and OCB. As OCB is inherently benevolent, these findings not only are consistent with the principle of compatibility, but they also contribute to theorizing about how trust plays an important role in the influence of transformational leadership on employees. The Author(s) 2023. -
Diverse Morphologies of Nb2O5 Nanomaterials: A Comparative Study for the Growth Optimization of Elongated Spiky Nb2O5 and Carbon Nanosphere Composite
Controlled synthesis and design of nanomaterials with intricate morphologies and active phases offer new prospects in harnessing their unique chemical and physical properties for various applications. Herein, a facile and efficient hydrothermal approach is reported for obtaining various complex Nb2O5 nanostructures, including thin sheets, thick flakes, spiky and elongated spiky sea urchin morphologies using urotropin as a growth-directing and hydrolyzing agent in various mixed and pure solvents. The detailed structural and chemical composition, surface morphology and crystallinity of as-synthesized Nb2O5 nanostructures are presented. The urotropin concentration, reaction time, and water-ethanol solvent mixture play a critical role for obtaining the elongated spiky sea urchin morphologies. The spiky Nb2O5 structures show a pseudohexagonal phase with less urotropin content, while thin sheets are obtained with a higher urotropin concentration and are primarily amorphous. These structures undergo transformation in their crystal phase and morphologies during calcination at higher temperatures revealing the active role of urotropin in stabilizing them. A composite of spiky sea urchin Nb2O5-carbon nanospheres (suNb2O5-CNS) is achieved by in-situ growth of Nb2O5 in the presence of CNS without compromising on morphology, phase, and crystallinity. suNb2O5-CNS composite is shown to possess higher charge storage capacity compared to its constituents for supercapacitor applications. 2023 Wiley-VCH GmbH. -
Effective Groundnut Crop Management by Early Prediction of Leaf Diseases through Convolutional Neural Networks
Groundnut (Arachis hypogaea L.), is the sixth-most significant leguminous oilseed crop grown all over worldwide. Groundnut, due to its high content of various dietary fibers, is classified as a valuable cash, staple and a feed crop for millions of households around the world. However, due to varied environmental factors, the crop is quite prone to many kinds of diseases, identifiable through its leaves, for which Groundnut producers have to suffer major losses every year. An early detection of such diseases is essential in order to save this significant crop and avoid huge losses. This paper presents a novel Machine Learning based Deep Convolution Neural Network (CNN) model CNN8GN. The model uses transfer learning technique for detection of such diseases in Groundnuts at an early stage of crop production. A Groundnut real image data set containing a total of 5322 real images for six different classes of Groundnut leaf diseases, captured in the fields of Gujarat state (India) during September 2022 to February 2023, is generated for training, testing and evaluation of the proposed model. The proposed deep learning model architecture is designed on eight different layers and can be used on varied sized images using simple ReLu and Softmax activation functions. The performance of the proposed CNN8GN model on Groundnut real image dataset is examined using a detailed experimental analysis with other six pre-trained models: VGG16, InceptionV3, Resnet50, ResNet152V2, VGG19, and MobileNetV2. CNN8GN results are also examined in detail using different sets of input parameters values. The proposed model has shown significant improvements for disease detection in comparative analysis with 99.11% training and 91.25% testing accuracy. The Author(s) 2024. -
Stability Analyses of BrinkmanBard Convection in Hybrid-Nanoliquid Saturated-Porous Medium Using Local Thermal Non-equilibrium Model
This paper carries out linear and weakly non-linear stability analyses of natural convection in a Newtonian hybrid-nanoliquid saturated porous medium. The Boussinesq approximation is assumed to be valid in the study, and a two-phase energy model is used. The weighted residual Galerkin technique is employed to obtain the expression for the Rayleigh number and Lorenz model by using a truncated double Fourier series solution. The quadratic non-linear Lorenz model is solved numerically by using the RungeKuttaFehlberg method. Water is considered as a carrier liquid, and copper and alumina nanoparticles are considered with dilute concentration. Linear stability analysis reveals the onset of convection prepones in a hybrid nanoliquid-saturated porous medium. The amount of heat transport is maximum in a hybrid nanoliquid saturated porous medium and minimum in a liquid-saturated porous medium. Local thermal non-equilibrium situation ceases at higher rates of interphase heat transfer coefficient. The assumption of local thermal non-equilibrium is prominent in hybrid nanoliquid saturated porous medium. The results of the hybrid-nanoliquid channel, a hybrid nanoliquid saturated porous medium with the local thermal assumption, are presented as a limiting case of the study. 2024, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Deposition and characterization of ZnO/CdSe/SnSe ternary thin film based photocatalyst for an enhanced visible light-driven photodegradation of model pollutants
A heterogeneous photocatalytic pathway is a possible approach to global energy and environmental issues. Sol-gel spin coating and physical vapour deposition were used to create a new ternary ZnO/CdSe/SnSe nanocomposite thin film photocatalyst. X-ray diffractometry, energy-dispersive X-ray spectroscopy (EDS), field emission-scanning electron microscopy, UV-Vis, and photoluminescence (PL) spectrophotometers were used to characterize the deposited films. When exposed to solar light, the ternary photocatalyst exhibits high photocatalytic activity in photocatalytic dye degradation processes. it demonstrates excellent visible light absorption, enhanced charge carrier separation, and solar light simulation. It was proposed that the charge in the ternary ZnO/CdSe/SnSe photocatalyst moves in a double type-II and cascade manner between the various components. In this study, ternary thin film heterostructures are synthesized, exhibiting outstanding stability and solar light-induced photocatalytic activity.The thin film composed of ZnO/CdSe/SnSe exhibits a degradation efficiency of 96% when exposed to visible light, and a degradation efficiency of 90% for methylene blue under sunlight within a time period of 150 min. Graphical Abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
AI-based online proctoring: a review of the state-of-the-art techniques and open challenges
So far, this pandemic has severely affected the education sector. As education undergoes a brilliant transformation with advancing technology, the digital acquisition of knowledge has yet to find widespread use - virtual exams. Faraway Proctoring offers several advantages of using manual and primarily based technology. Although this allows students to take an exam in any field with specific technical requirements, it eliminates the need for physical research centers. It is cost-effective and easy to plan, which can be challenging to manage, especially during aggressive trials. Finally, the paper discusses the performance characteristics of different styles of web-based inspection systems, along with their limitations and challenges. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
Ricci solitons on Riemannian manifolds admitting certain vector field
In this paper, we initiate the study of impact of the existence of a unit vector ?, called a concurrent-recurrent vector field, on the geometry of a Riemannian manifold. Some examples of these vector fields are provided on Riemannian manifolds, and basic geometric properties of these vector fields are derived. Next, we characterize Ricci solitons on 3-dimensional Riemannian manifolds and gradient Ricci almost solitons on a Riemannian manifold (of dimension n) admitting a concurrent-recurrent vector field. In particular, it is proved that the Riemannian 3-manifold equipped with a concurrent-recurrent vector field is of constant negative curvature -?2 when its metric is a Ricci soliton. Further, it has been shown that a Riemannian manifold admitting a concurrent-recurrent vector field, whose metric is a gradient Ricci almost soliton, is Einstein. Universitdegli Studi di Napoli "Federico II" 2021. -
Comparing the Accuracy of CNN Model with Inception V3 for Music Instrument Recognition
Identification of music instruments from an audio signal is a complex but useful task in music information retrieval. Deep Learning and traditional machine learning models are extremely very useful in many music related tasks such as music genre classification, recognizing music similarity, identifying the singer etc. Music Instrument recognition and classification would be helpful in categorizing different categories of music. Many researchers have proposed models for classifying western music instruments. But very little research has been done in identifying instruments accompanied with South Indian music. This research aims at identifying string instrument such as violin and woodwind instrument such as flute accompanied in a Carnatic music concert and also in other categories of music. In order to identify the instruments accompanied, Convolutional Neural Network model and Inception V3 models were used. The Mel Frequency Cepstral Coefficients images were extracted from the audio input and fed in to the neural network model. The model has been trained for the above mentioned instruments, tested and validated on different types of audio input. This research also evaluates the performance of Inception V3 transfer learning model with CNN model in recognizing the instruments used in different categories of music. 2024, Ismail Saritas. All rights reserved. -
A novel approach to study generalized coupled cubic SchringerKorteweg-de Vries equations
The Kortewegde Vries (KdV) equation represents the propagation of long waves in dispersive media, whereas the cubic nonlinear Schringer (CNLS) equation depicts the dynamics of narrow-bandwidth wave packets consisting of short dispersive waves. A model that couples these two equations seems intriguing for simulating the interaction of long and short waves, which is important in many domains of applied sciences and engineering, and such a system has been investigated in recent decades. This work uses a modified Sardar sub-equation procedure to secure the soliton-type solutions of the generalized cubic nonlinear SchringerKorteweg-de Vries system of equations. For various selections of arbitrary parameters in these solutions, the dynamic properties of some acquired solutions are represented graphically and analyzed. In particular, the dynamics of the bright solitons, dark solitons, mixed bright-dark solitons, W-shaped solitons, M-shaped solitons, periodic waves, and other soliton-type solutions. Our results demonstrated that the proposed technique is highly efficient and effective for the aforementioned problems, as well as other nonlinear problems that may arise in the fields of mathematical physics and engineering. 2022 -
A hybrid crypto-compression model for secure brain mri image transmission
Medical image encryption is a major issue in healthcare applications where memory, energy, and computational resources are constrained. The modern technological architecture of digital healthcare systems is, in fact, insufficient to handle both the current and future requirements for data. Security has been raised to the highest priority. By meeting these conditions, the hybrid crypto-compression technique introduced in this study can be used for securing the transfer of healthcare images. The approach consists of two components. In order to construct a cutting-edge generative lossy compression system, we first combine generative adversarial networks (GANs) with oearned compression. As a result, the second phase might address this problem by using highly effective picture cryptography techniques. A randomly generated public key is subjected to the DNA technique. In this application, pseudo-random bits are produced by using a logistic chaotic map algorithm. During the substitution process, an additional layer of security is provided to boost the techniques fault resilience. Our proposed system and security investigations show that the method provides trustworthy and long-lasting encryption and several multidimensional aspects that have been discovered in various public health and healthcare issues. As a result, the recommended hybrid crypto-compression technique may significantly reduce a photos size and remain safe enough to be used for medical image encryption. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
On families of graphs which are both adjacency equienergetic and distance equienergetic
Let A(G) and D(G) be the adjacency and distance matrices of a graph G respectively. The adjacency energy or A-energy EA(G) of a graph G is defined as the sum of the absolute values of the eigenvalues of A(G). Analogously, the D-energy ED(G) is defined to be the sum of the absolute values of the eigenvalues of D(G). One of the interesting problems on graph energy is to characterize those graphs which are equienergetic with respect to both the adjacency and distance matrices. A weaker problem is to construct the families of graphs which are equienergetic with respect to both the adjacency and distance matrices. In this paper, we find the explicit relations between A-energy and D-energy of certain families of graphs. As a consequence, we provide an answer to the above open problem (Indulal in https://icgc2020.wordpress.com/invitedlectures, 2020; http://www.facweb.iitkgp.ac.in/rkannan/gma.html, 2020) The Indian National Science Academy 2022. -
Exploring Mortality Salience and Pandemic Impact in the Context of COVID-19
Mortality salience refers to a state of conscious awareness of death and the inevitable conclusion of life, associated with psychological terror. The COVID-19 pandemic generated increased awareness of illness and death, and effectuated changes in death cognitions and peoples experiences around psychological or sociocognitive domains of media and life goals. To understand these changes, this study administered the Multidimensional Mortality Awareness Measure (Levasseur et al., 2015) to 103 emerging adults in India, post which 6 participants proceeded for a semi-structured interview exploring pandemic experiences, news consumption and goal prioritization, to examine specific areas in relation to death cognition. The thematic analysis demonstrates psychological effects, and discusses developments in health and death-related psychological processes. Focus on career goals and health maintenance, cautious news consumption and disadvantageous impacts on mental health are seen, significant in navigating healthcare measures for emerging adults, as we move forward into this new normal. The Author(s) 2021. -
Photocatalytic driven self-cleaning IPN membranes infused with a host-guest pair consisting of metal-organic framework encapsulated anionic nano-clusters for water remediation
Traditional water treatment membranes frequently encounter challenges in attaining an ideal equilibrium between permeability and selectivity. The performance of membranes is further hampered by hydrophobicity, scalability, and fouling problems, as well as excessive energy consumption. Hence, the current research is dedicated to the development of highly effective antifouling membranes, aiming for a significant balance between water permeance and separation efficiency, and featuring exceptional photocatalytic self-cleaning properties to ensure the sustainable reuse of membranes. In this study, a unique nanocomposite-based membrane is designed containing metal-organic frameworks (MOFs) MIL-101 (Fe) encapsulated copper-containing polyoxometalate (Cu-POM) incorporated into an interpenetrating polymer networks (IPNs) membrane. POMs are highly electronegative, oxo-enriched nanosized metal-oxygen cluster species and when composited with MOF yields POMOF which can help in the removal of pollutants from water through electrostatic site-specific binding. The IPN membrane designed by polymerizing aniline in the presence of polyvinylidene fluoride (PVDF) offers tunable pores of the membrane. The infusion of POMOF imparts a strong negative charge to the membrane surface, improving membrane hydrophilicity. This enhances pollutant removal through the Donnan exclusion principle and adds anti-fouling properties. Furthermore, the reduced pore size achieved by the IPN architecture in the POMOF@IPNs membrane effectively sieves out both cationic and anionic dyes, as well as pharmaceutical pollutants. Additionally, POMOF enhances the photocatalytic degradation of CR and MB dyes, coupled with essential self-cleaning attributes vital for separation processes. The IPNs structure, apart from housing POMOF, fortifies the membrane's mechanical strength with its distinctive network-like configuration. Furthermore, these advanced membranes showcase robust antibacterial and antiviral characteristics, while remaining non-cytotoxic to mammalian cells. Our findings indicate that the state-of-the-art POMOF@IPNs membrane is scalable and holds substantial promise for industrial wastewater treatment. 2024 Elsevier B.V.