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A Bibliometric Analysis of Asset Allocation for Retirement
Allocation of investment assets is key in attaining a sustainable retirement portfolio. In this research article, the authors analyzed the most recent research publications in the area related to asset allocation for retirement and identified those which have the highest impact. The authors research was conducted using the bibliometric analysis technique of research articles collected from the Scopus database. Most of the research articles were published in reputed journals in the United States, United Kingdom, Australia, and Germany. It was also observed that most of the highly cited research articles in the research area of asset allocation for retirement are focused on financial literacy, increase in retirement age, aging, and pension reforms. The authors findings identified six research themes in asset allocation for retirement such as 1) asset allocation for retirement planning, 2) methods to increase efficiency, 3) investment preferences for retirement savings 4) financial literacy and retirement planning, 5) reforms on retirement savings, and 6) annuities for retirement income. Furthermore, nineteen future research directions are also provided. In conclusion, the authors aim to assist future researchers in identifying highly cited articles, key authors, contributing countries and research themes in asset allocation for retirement. Overall, the analysis provides comprehensive information in addressing research questions in the field of asset allocation for retirement. Copyright 2024 With Intelligence LLC. -
A novel chemical route for low-temperature curing of natural rubber using 2,4 dihydroxybenzaldehyde: improved thermal and tensile properties
A novel method for chemically curing natural rubber (NR) using 2,4-dihydroxybenzaldehyde (DHB) at low temperatures has been discovered. Adding varying amounts of DHB to NR increases the crosslinking between the NR molecular chains. The chemical reaction between NR molecular chains and DHB was confirmed through Fourier transform infrared (FTIR) and proton nuclear magnetic resonance (NMR) spectra. From the thermogravimetric analysis (TGA), the thermal stability and activation energy of degradation were determined. The variation in glass transition temperature (Tg), as an indication of increased crosslink density, reducing the mobility of rubber chains, has been confirmed through differential scanning calorimetry (DSC). The addition of DHB to latex significantly enhanced the thermal stability of the rubber. An increase in the activation energy of 5.52% was observed upon the addition of 80mL DHB into NRL when compared to the uncured one. Furthermore, the tensile properties, in terms of tensile strength and modulus of elasticity of rubber, were drastically increased through DHB crosslinking. Tensile strength values of rubber were found to increase by reducing its elongation at break due to the formation of crosslinks between the macromolecular chains. NR cured with 80mL DHB exhibited superior tensile and thermal properties among the series of cured samples. By adding 80mL of DHB, the tensile strength increased by 390% and the elongation at break decreased by 10%. The advantage of this curing method is that, it is an effective technique for crosslinking NR directly from NR latex at comparatively low temperature. Graphical abstract: (Figure presented.) Iran Polymer and Petrochemical Institute 2024. -
Circular supply chains in manufacturingQuo vadis? Accomplishments, challenges and future opportunities
Circular approach in manufacturing supply chain (SC) operations yields multiple benefits through optimal utilisation and consumption of resources. This study maps the scope and structure of circularity in the manufacturing SC discipline and explores the evolution of the domain over time. We review 946 journal articles published between 2013 and September 2023. Our study identifies key drivers and barriers to circular economy (CE) deployment in manufacturing SC operations, bibliometric parameters, emerging research themes, decision support tools, theories and applications. Using the theory extension approach, we propose a strategic framework to fortify the deployment of circularity in SCs. This comprehensive study renders a methodological contribution through combined descriptive content analysis and bibliometric and network analyses to evaluate the circular manufacturing SC operations concepts, theories and applications. We posit that manufacturing firms require to deploy innovation-led approaches to embed the CE strategies in their SC operations. We find that the studies investigating green skill development and circularity-culture adoption can facilitate manufacturers to understand the efficacy of circularity in their SC operations. The findings of this study can facilitate the practitioners to identify the links between the CE approaches and their strategic implications and examine CE implementation at the strategic level. 2024 The Authors. Business Strategy and The Environment published by ERP Environment and John Wiley & Sons Ltd. -
Constraining the physical parameters of XTE J1701-462 through NuSTAR observations
The spectral properties of the transient neutron star low-mass X-ray binary XTE J1701-462 were studied using the data obtained from FPMA/B detectors onboard NuSTAR during its second known outburst (2022 September). The physical parameters of the system were derived from the analysis of the data in the 3.0-30.0 keV energy range. The patterns displayed on the hardness-intensity diagram of the three observations closely resembled the banana branch/normal branch, a vertex of horizontal and normal branch of the Z-track and a transition from normal branch to flaring branch. Spectral analysis of the source revealed the presence of Fe K emission complex. The source spectra were fitted with a multitemperature blackbody () component in conjunction with the reflection model (). The values of temperature (kTin) and radius (Rin) of the inner accretion disc obtained from the spectral fitting with the model combination - + showed the source to be in its soft spectral state during the observations. The inclination angle (?) of the source was estimated to be between 19 and 33 and the inner disc radius (Rin) was found to be 17.4 km. Assuming the case of magnetic truncation of accretion disc, the upper limits for the magnetic dipole moment (?) and the magnetic field strength (B) at the poles of the neutron star in the system were found to be 5.78 1026 G cm3 and 8.23 108 G, respectively, for kA = 1. 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. -
Machine Learning and Deep Learning Analysis of Vehicle Carbon Footprint
Clearly climate change is one of the most significant hazards to mankind nowadays. And daily the situation has become worse. No other way characterises climate change except through changes in the patterns of temperature and weather. Human activity generates the primary greenhouse gas emissions. Among these activities are burning coal, oil, natural gas, as well as other fuels; agricultural techniques, industrial operations, deforestation, burning coal, oil. Mostly resulting from human activities, the average temperature of the planet has significantly increased by almost 1.1 degrees Celsius since the late 1800s. One theory holds that internal combustion engines affect roughly thirteen percent. The objective of this work is to do an analysis of a complicated dataset involving fuel consumption in urban and highway environments as well as mixed combinations since the relevance of these variables in modelling attempts dictates. Reduced CO2 emissions emissions and environmental impact follow from reduced fuel use. The project used numerous machine learning and deep learning approaches to comprehend data analysis. Moreover, this work investigates the dataset to acquire knowledge and concurrently solves problems such overfitting and outliers. Control of complexity is achieved using several methods like VIF, PCA, and Cross-Validation. Models combining CNN and RNN performed really well with an accuracy of 0.99. The R-squared metrics are utilized in order to do the evaluation of the model. Apart from linear regression, support vector machines, Elastic Net with a rewardable accuracy, random forest was applied. It has rather good 0.98 accuracy. We can therefore state that our model analyzed the data properly and generated accurate output since the results we obtained during the assessment phase exactly the same ones we obtained during the training stage. Mass data cleansing is required as well as further study to increase machine learning model accuracy and performance. 2024 The authors. -
Psychological adjustment, choice of game genre and living arrangements among adolescents with and without IGD
In India, the prevalence of internet gaming disorders ranges from 8 to 9%. Adolescents are more likely to become addicted to online games. This study compares teenage gamers with and without Internet Gaming Disorder (IGD) in terms of game genre, psychosocial adjustment, and living conditions with a sample of 80 in each group. The results demonstrate that adolescents with this disorder had significantly higher scores for depression, anxiety, and psychosocial deterioration than adolescents without gaming disorder. Even though the prevalence of males is high, both genders do not significantly differ from one another in psychological adjustment. Another finding is that adolescents with gaming disorders play multiplayer online role-play games and Battle Royal games more frequently than average players. The prevalence of this disorder is also influenced by living conditions; teenagers who stay in hostels or pay guest rooms are more likely to develop a gaming addiction. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Facile fabrication of 3D-?-Fe2O3@2D-g-C3N4 heterojunction composite materials: Effect of iron oxide loading on the electrochemical performance
Designing heterojunction nanocomposites is crucial for optimizing supercapacitor electrodes. This study addresses the challenge by introducing a facile synthesis method for creating 3D-?-Fe2O3@2D-g-C3N4 heterojunctions through a bulk carbon nitride-assisted hydrothermal process. During this process, the growth of ferric oxide particles coincides with the exfoliation and deposition of carbon nitride, leading to simultaneous structural changes in both iron oxide and carbon nitride phases. The resulting composite's properties strongly correlate with the iron oxide loading. Comprehensive characterization using XRD, FTIR, SEM-EDAX, XPS and TEM identified three distinct structures for ?-Fe2O3/g-C3N4 composites based on iron oxide loading: low, medium, and high. The medium-loaded sample demonstrated superior electrochemical performance, attributed to better interfacial contact and the formation of 3D-Fe2O3@2D-g-C3N4 heterojunctions. This composite, with an optimized 22 wt% iron oxide loading, exhibited a maximum specific capacitance of 925.1 Fg?1 at 5 mVs?1 and 498.6 Fg?1 at 6 Ag?1 in charge-discharge analysis, with stable performance over 2000 cycles. Overall, this research presents an enhanced hydrothermal method for facile preparation of effective ?-Fe2O3/g-C3N4 heterojunction materials. 2024 Elsevier B.V. -
Does risk management components influence on project success? Evidence from IT sector
All organizations and stakeholders would ideally like to see an information technology (IT) project managed successfully. Many researchers have strongly debated the importance of risk management in project management about the size of the project since it gives project managers a forward-looking view of risks and chances to increase the project's success. The main aim of the study is to determine how risk management parameters and their mediated effects impact the effectiveness of IT projects. Data was collected from 261 IT professionals involved in projects through a structured questionnaire and analyzed using regression and SEM to test their statistical significance and prove the hypothesis. The study arrived at some significant results which showed the relationship of Risk Identification and Risk Analysis on Risk Assessment, which impacts Project Success. It also showed that the success of the project depended on Stake-holders Tolerance and Risk Implementation. In addition to this, the study provides evidence that risk management does not influence the success of the project. The study's discovery of the intervening impact of risk management practices clarifies preconceived conceptions in the risk management sector. 2024 Growing Science Ltd. All rights reserved. -
Artificial intelligence talent acquisition in HEIs recruitments
Purpose: The current research study aims to examine the application feasibility and impact of artificial intelligence (AI) among higher educational institutions (HEIs) in talent acquisitions (TA). Design/methodology/approach: A systematic sampling method was adopted to collect the responses from the 385 staff working across the various levels of management in HEIs in metropolitan cities in India. JAMOVI & SmartPLS 4 were applied to validate the hypothesis by performing the simple percentage analysis and structural equation modelling. The demographic and construct variables considered were adoption, actual usage, perceived usefulness, perceived ease of use and talent management. Findings: The key indicators of perceived usefulness are productivity, perceived ease of use, adaptability, candidate experience with the adoption of AI, frequency in decision-making in its actual usage and career path of development in the HEIs. These are the most influential items impacting the application of AI in TA. Originality/value: AI has the potential to revolutionize TA in HEIs in the form of enhanced efficiency, improved candidate experience, more objective hiring decisions, talent analytics and risk automation. However, they facilitate resume screening, candidate sourcing, applicant tracking, interviewing and predictive analytics for attrition. 2024, Emerald Publishing Limited. -
Computational study of charge transfer iso-surface in first three excited states, electron-hole transition effects, chemical nature and bond order analysis investigations of chrysogine
This work presents the theoretical DFT (Density Functional Theory) studies and the biological application of chrysogine, a marine alkaloid. Energy minimisation and additional DFT evaluations were performed for vacuum and solvent media. It has been observed that solvation with polar solvents has resulted in a slight variation in the molecule's properties. The Multiwfn software was employed to carry out various topological analyses. Among these, the charge transfer studies show that the second and third excited states are the most significant. From the reactivity analysis, the least energy gap (4.9624 eV) is obtained in water, indicating that chrysogine is most reactive in aqueous media. Theoretical UV studies show that the trends in ?max values correspond to n >?* and n >?* electronic transitions within the molecule. An increase in medium polarity has demonstrated in the MEP (Molecular Electrostatic Potential) maps an increase in the potential range from ?6.619 10?2 a.u. to 6.619 10?2 a.u. in the gas phase, to a sharp rise to ?8.036 10?2 a.u. to 8.036 10?2 a.u. in ethanol, ?8.098 10?2 a.u. to 8.098 10?2 a.u. in methanol, ?8.130 10?2 a.u. to 8.130 10?2 a.u. in DMSO, and ?8.127 10-2 a.u. to 8.127 10?2 a.u. in water. The most significant transition contributing to molecular stability from NBO (Natural Bond Orbital) analysis is: (O2-C9) ?* ? ?* (C7-C8) with the energy of 258.13 kcal mol?1. The ADMET profile for the molecule was assimilated with the help of online servers. The molecule was docked against lung cancer target proteins (PDB ID: 1NTK, 3QFB) using software such as AutoDock Tools and PyMOL. The respective illustrations and data were visualised using Discovery Studio Visualizer. Good binding affinities (?5.69 kcal mol?1 for 1NTK and ?6.64 kcal mol?1 for 3QFB proteins) and interactions were achieved with the selected targets. 2024 Elsevier B.V. -
Enhancing authenticity and trust in social media: an automated approach for detecting fake profiles
Fake profile detection on social media is a critical task intended for detecting and alleviating the existence of deceptive or fraudulent user profiles. These fake profiles, frequently generated with malicious intent, could engage in different forms of spreading disinformation, online fraud, or spamming. A range of techniques is employed to solve these problems such as natural language processing (NLP), machine learning (ML), and behavioural analysis, to examine engagement patterns, user-generated content, and profile characteristics. This paper proposes an automated fake profile detection using the coyote optimization algorithm with deep learning (FPD-COADL) method on social media. This multifaceted approach scrutinizes user-generated content, engagement patterns, and profile attributes to differentiate genuine user accounts from deceptive ones, ultimately reinforcing the authenticity and trustworthiness of social networking platforms. The presented FPD-COADL method uses robust data pre-processing methods to enhance the uniformness and quality of data. Besides, the FPD-COADL method applies deep belief network (DBN) for the recognition and classification of fake accounts. Extensive experiments and evaluations on own collected social media datasets underscore the effectiveness of the approach, showcasing its potential to identify fake profiles with high scalability and precision. 2024 Institute of Advanced Engineering and Science. All rights reserved. -
Shared Mobility and Indias Generation Z: Environmental Consciousness, Risks, and Attitudes
Shared mobility platforms have built scalable digital marketplaces that facilitate the allocation and sharing of transportation and promote sustainable urban travel. Generation Zs attitude toward shared consumption is closely linked to their perceptions of the importance of sustainability. This study identifies Generation Zs awareness of shared mobility platforms in India and the factors that influence their use. Data were collected from 318 respondents from Generation Z in India and analyzed using partial least squares structural equation modeling. Findings indicate that Generation Zs intention to use shared mobility is influenced by environmental consciousness, social aspects, economic benefits, and perceived risks. Results also show that perceived risks have an indirect effect on intention, which is mediated by attitude. The novel conceptual model developed and tested in this research can be used to inform policies and business models for the adoption of shared mobility services for Generation Z, ultimately promoting more sustainable transportation systems and improved urban mobility. 2024 by the authors. -
Covid-19, macroeconomic policies, and analysis of the inflation-unemployment dynamics in india
Indian economy could largely withstand the adversities of 2008 recession, the signs of a downturn were clearer by 2017 following the arrival of twin policies, Demonetization as well as the Goods and Services Tax. The COVID-19 pandemic has deepened the crisis leading to a significant reduction in production and total expenditure. Although India has resorted to a combination of conventional policies monetary as well as fiscal injections to face the economic crisis, it has had serious negative consequences on production and employment. We investigate the nature of relationship between inflation and unemployment during the recession and the pandemic times using the non-linear regression analysis. The results reveal that the recessionary phase has given way to a stagflationary situation owing to inflation persistence in the short run. We suggest the usefulness of a more comprehensive term structure strat?gy to deal with the adverse supply shocks and policy failures. Indian Institute of Finance. -
Strain-Induced Tribocatalytic Activity of 2D ZnO Quantum Dots
The use of low-frequency vibration or high-frequency ultrasound waves to create polarization and an inherent electric field in piezo-tribocatalysts has recently been shown to be a novel advanced oxidation process. In this study, we have demonstrated the synthesis of two-dimensional (2D) ZnO quantum dots (QDs) and their strain-induced tribocatalytic effect, where the triboelectric charges generated under the influence of friction and strain are used to facilitate the decomposition of organic dye molecules. The catalytic performance of 2D QD catalysts can be tuned by modulation of the strain-induced band-gap variation, which are typically regarded as the active sites. The underlying mechanism for the strain-induced catalytic performance is due to the presence of defective dipole moments. Detailed theoretical investigations reveal strain-induced charge-transfer-dependent catalytic properties of the 2D ZnO QD-polymer interface. We believe that the present work provides a fundamental understanding of the design of high-performance catalysis applications for water cleaning and emerging technologies. 2024 American Chemical Society. -
Subsume Pediatric Headaches in Psychiatric Disorders? Critiques on Delphic Nosology, Diagnostic Conundrums, and Variability in the Interventions
Purpose of Review: Tension-type headache (TTH) continues to be the most prevalent type of headache across all age groups worldwide, and the global burden of migraine and TTH together account for 7% of all-cause years lived with disability (YLDs). TTH has been shown to have a prevalence of up to 80% in several studies and presents a wide range and high variability in clinical settings. The aim of this review is to identify gaps in diagnostics, nosology, and variability in the treatment of children and adolescents who present with headaches without an identifiable etiology. Recent Findings: Migraine and TTH have been debated to have more similarities than distinctions, increasing chances of misdiagnosis and leading to significant cases diagnosed as probable TTH or probable migraine. The lack of specificity and sensitivity for TTH classification often leads to the diagnosis being made by negating associated migraine symptoms. Although pathology is not well understood, some studies have suggested a neurological basis for TTH, in need of further validation. Some research indicates that nitric oxide signaling plays an integral part in the pain mechanisms related to TTH. Analgesics and non-steroidal anti-inflammatories are usually the first lines of treatment for children with recurring headaches, and additional treatment options include medication and behavioral therapies. Summary: With high prevalence and socioeconomic burden among children and adolescents, its essential to further study Tension-type headaches and secondary headaches without known cause and potential interventions. Treatment studies involving randomized controlled trials are also needed to test the efficacy of various treatments further. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Enhancing photocatalytic performance through surfactant-assisted electrochemical synthesis: Surface modification of hierarchical ZnO morphologies with Ag/ZnWO4 nanoparticles
This study presents the synthesis of surface-decorated CTAB-capped ZnO nanoparticles doped with Ag/ZnWO4 through a surfactant-assisted electrochemical synthesis approach. The development of surface-decorated composites is of considerable interest for enhancing photocatalytic efficiency. We report the synthesis of pristine, binary, and surface-decorated ZnO catalysts, specifically Zn, Zn/Ag, Zn/ZnWO4, and Zn/Ag/ZnWO4. Various methods for physicochemical characterization have been utilized to verify the catalysts' structural, optical, and morphological properties. The results demonstrate the successful surfactant capping and metal doping. The synthesized nanoparticles have been tested for their photocatalytic performance against Malachite Green, an environmentally harmful organic dye, across various reaction conditions. Scavenger studies reveal that the photodegradation process is primarily driven by superoxide and hydroxyl radicals and, to a lesser extent, by photogenerated holes. The decrease in electron-hole pair recombination in the Zn/Ag/ZnWO4 photocatalyst results in an enhanced degradation of Malachite Green when exposed to visible light. 2024 Elsevier B.V. -
Universal vortex statistics and stochastic geometry of Bose-Einstein condensation
The cooling of a Bose gas in finite time results in the formation of a Bose-Einstein condensate that is spontaneously proliferated with vortices. We propose that the vortex spatial statistics is described by a homogeneous Poisson point process (PPP) with a density dictated by the Kibble-Zurek mechanism (KZM). We validate this model using numerical simulations of the two-dimensional stochastic Gross-Pitaevskii equation (SGPE) for both a homogeneous and a hard-wall trapped condensate. The KZM scaling of the average vortex number with the cooling rate is established along with the universal character of the vortex number distribution. The spatial statistics between vortices is characterized by analyzing the two-point defect-defect correlation function, the corresponding spacing distributions, and the random tessellation of the vortex pattern using the Voronoi cell area statistics. Combining the PPP description with the KZM, we derive universal theoretical predictions for each of these quantities and find them in agreement with the SGPE simulations. Our results establish the universal character of the spatial statistics of point-like topological defects generated during a continuous phase transition and the associated stochastic geometry. 2024 authors. Published by the American Physical Society. -
Electrochemical characteristics of Co3O4 nanoparticles synthesized via the hydrothermal approach for supercapacitor applications
Cobalt oxide (Co3O4), a transition metal oxide known for its favourable capacitive properties and surface characteristics, is a promising candidate for electrode materials in supercapacitive energy storage applications. This study presents a comprehensive analysis of cobalt oxide nanoparticles synthesized through the hydrothermal method at varying synthesis temperatures, focusing on their structural, optical, electrochemical, and surface properties. X-ray diffraction analysis confirmed the cubic spinel structure of Co3O4, while Raman spectroscopy verified the phase composition of the nanoparticles. X-ray photoelectron spectroscopy offered insights into the near-surface chemistry of the synthesized material. The study determined two direct bandgaps of Co3O4 through absorption spectra and Tauc plots. To assess surface morphology and particle size distribution, field-emitting scanning electron microscopy and transmission electron microscopy were employed. Electrochemical investigations involved cyclic voltammetry and Nyquist plots, while galvanostatic chargedischarge tests demonstrated a specific capacitance (Csp) of 450 Fg?1 at 1 Ag?1. Impedance analysis indicated favourable capacitive behaviour with low charge transfer resistance. Furthermore, the study observed cyclic stability with a capacitive retention rate exceeding 88% at a current density of 20 Ag?1 over 10,000 cycles. The paper also discusses the capacitive and diffusion-controlled charge storage mechanisms at lower scan rates, emphasizing the potential of Co3O4 nanoparticles as the electrode material in the development of supercapacitor devices. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. -
Further studies on circulant completion of graphs
A circulant graph C(n, S) is a graph having its adjacency matrix as a circulant matrix. It can also be interpreted as a graph with vertices v0, v1,,vn?1 that are in one-to-one correspondence with the members of Zn and with edge set {vivj: i ? j ? S}, where S known as the connection set or symbol, is a subset of non-identity members of Zn that is closed under inverses. This work extends the study of circulant completion and general formulae for calculating circulant completion numbers in two different perspectives, one in terms of circulant span and the other in terms of the adjacency matrix. (2024), (SciELO-Scientific Electronic Library Online). All Rights Reserved. -
A review on quantum utility for secure authentication protocol towards cryptographic standard in quantum dot cellular automata
QCA, which stands for Quantum Dot-Cellular Automata, is a nanotechnology model that offers an alternative solution to the widely used CMOS technology. Unlike CMOS, QCA is a semiconductor-less technology that transmits information based on the charge of electrons and the electrostatic repulsion between them. This technology provides several advantages over CMOS, including higher device density, faster switching speed, and lower power consumption. When it comes to cryptographic applications, QCA circuits can be extremely useful. Both encryption and decryption processes can be implemented using logic circuits based on QCA. The research paper describes a basic method for generating ciphertext in QCA, which is useful in secure nano communication based on QCA. The paper discusses how to achieve secure authentication in encrypted communication using QCA. To evaluate the performance and test the proposed method, the researchers used the QCA Designer-2.0.3 tool. This is a software tool specifically designed for designing and simulating QCA circuits. It enables researchers to model and analyze the behavior of QCA-based systems, allowing them to evaluate the effectiveness and feasibility of their proposed encryption technique. Overall, the research paper aims to present a secure encryption method using QCA and demonstrates its implementation and testing using the QCA Designer-2.0.3 tool. By leveraging the unique properties of QCA, such as high device density and low power consumption, the researchers aim to provide a novel approach for secure nano communication and cryptographic applications. Taru Publications.