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Strategically designed multiwalled carbon nanotube/bismuth ferrite/polyaniline nanocomposites and unlocking their potential for advanced supercapacitors
Bismuth ferrite (BF) serves a potential electrode-active material due to its peculiar characteristics such as wide voltage window and high specific capacitance, excellent stability, facile synthesis routes, etc. to name a few. Herein we report the strategic design and facile synthesis of multiwalled carbon nanotubes (MWCNT)/BF/polyaniline (PANI) nanocomposites, particularly for application in advanced supercapacitors. The MWCNT/BF/PANI nanocomposite architecture is a strategic design in which the maximum available surface area is utilized for the electrode nanostructure with increased porosity that allows easy movement of electrolyte-ions through it. The uniform arrangement of BF on MWCNTs helps in mitigating the possible agglomeration, further augmenting the surface area for an enhanced charge storage. The strategic layout of PANI on BF-decorated MWCNTs has given a coral-like structure for the nanocomposite electrode which significantly increased the surface area, reduced ion pathways and facilitating better access to electrolytic K+ ions. The MWCNT/BF/PANI nanocomposite electrode exhibits a specific capacitance of 3640 F g?1 at a current density of 5 A g?1. The innovative design as well as the synergy between the individual components of the nanocomposite electrode play a pivotal role in attaining the enhanced electrochemical performance. 2024 Elsevier B.V. -
Performance analysis of semantic veracity enhance (SVE) classifier for fake news detection and demystifying the online user behaviour in social media using sentiment analysis
The increased propagation of fake news is the significant concern in the digital era. Identification of fake news from social media platforms is critical to strengthen public trust and ensure social stability. This research presents an effective and accurate framework for identifying fake news that combines different steps of natural language processing (NLP) technique along with a neural network architecture. A novel semantic veracity enhancement (SVE) classifier is designed and implemented in this work for detecting fake news. The proposed approach leverages the effectiveness of sentiment analysis for identifying misleading or deceptive content and its subsequent implications on the sentiment and behaviour of social media users. A BERT model is used in this research for analysing the sentiments and classifying the texts from the social media platform. By examining the sentiments, the SVE classifier differentiates between real news and fabricated content. To achieve this, three different datasets comprising both actual content and fabricated (tweaked) tweets are employed for training the SVE classifier. The potentiality of the SVE classifier is evaluated and compared with different optimization techniques. The outcome of the experimental analysis shows that the proposed approach exhibits an excellent performance in terms of classifying misinformation from the original information with an outstanding accuracy of 99% compared to other state of art methods. 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature. -
rGO-MoO3 Nanocomposite for superior methylene blue removal by adsorption and photocatalysis
Efficient MoO3 and rGO (0.5,1,2 wt.%)-MoO3 nanosorbent was prepared by facile hydrothermal method. X-ray diffraction (XRD) and Raman spectroscopy techniques confirms the orthorhombic phase. Remarkably in 10 ppm MB dye, complete removal was observed for 1:3, 1:5, 1:3.3, 1:3 (mass of catalyst: volume of dye solution) ratio for pure, 0.5 wt.%, 1 wt.%, 2 wt.% rGO-MoO3 nanocomposite, by merely stirring for one hour without any light exposure. The adsorption mechanism was examined in detail using different models including Langmuir isotherm and Pseudo second-order kinetic model. The composite sample, rGO (0.5 wt.%)-MoO3 is the most efficient nanosorbent whereas rGO (2 wt.%)-MoO3 showed the least adsorption. rGO (2 wt.%)-MoO3 was further used for time dependent study in the presence of UV and in the dark. The presence of UV enhances removal due to the combined effect of adsorption and photocatalysis. Scavenger studies were performed to analyze the mechanism of photocatalysis. 2024 Elsevier Ltd -
Augmentation of the energy storage potential by harnessing the defects of charcoal for supercapacitor application
The depletion of fossil fuel reserves coupled with an avalanche in the global energy demand has driven the need for developing facile techniques for energy storage devices to a large extent. Supercapacitors, has emerged as one of the most promising energy storage devices to address the demands of providing high energy density, quick charge discharge cycles and long cyclic stability. Although carbon based materials play an imperative role in the fabrication of electrode material of this device, the inherent defects are known to hinder the performance of the system. Even so, these defects can be engineered in a way to improve its overall functionality. The present work reports the tuning of the inherent defects of wood charcoal by surface functionalisation and doping via thermal annealing in order to incorporate substitutional impurities such as Nitrogen and Sulfur resulting in the improvement of the surface area and porosity of the system. The specific surface area of the system is observed to increase significantly from 4.2 m2/g of the bare material to 411.19 m2/g and 865.36 m2/g with the addition of Nitrogen and Sulfur respectively at a pyrolysis temperature of 900 C. Furthermore, the incorporation of Nitrogen exhibits a remarkable specific capacitance of 567 F/g and 193.24 F/g, and the addition of Sulfur exhibits 644 F/g and 255.1 F/g in the three-electrode and two-electrode systems respectively at a current density of 1 A/g. They also exhibit an energy density of 26.83 Whkg?1 and 17.36 Whkg?1 respectively with a capacitance retention of 88.5 % and 86.1 % for 5000 cycles. 2024 Elsevier Ltd -
Comprehensive investigations on spectral and temporal features of GX 5-1 using AstroSat observations
Comprehensive spectrotemporal analyses of the Z-type neutron star low-mass X-ray binary GX 5-1 were performed using 10 broad-band observations from AstroSat/Soft X-ray Telescope and Large Area X-ray Proportional Counter (LAXPC) instruments. The LAXPC-20 hardness-intensity diagram showed horizontal and normal branches (HBs and NBs) of the Z track which exhibited secular motion. The time-averaged spectra in the energy range 0.7-25.0 keV could be fitted with the model combination -Cconstant tbabs edge edge thcomp diskbb. This yielded ? ?2, kTe ?3.3 keV, and Fdisc/Ftotal ? 0.8 indicating the soft/intermediate spectral state of the source during the observations. Flux-resolved spectral analysis revealed a positive correlation between kTin and Fbol. However, a negative correlation was observed between them in one of the NBs. Time-averaged temporal analysis revealed multiple HB oscillations (HBOs) and NB oscillations (NBOs), and peaked noise components in the ?5-50 Hz range. Furthermore, flux-resolved temporal analysis showed that the frequency of the HBOs correlates positively whereas the strength of HBOs correlates negatively with Fbol, indicating their probable origin from the accretion disc. In contrast, the frequency and strength of NBOs remain fairly constant with Fbol, suggesting that they originate from a different region in the system. Using the relativistic precession model along with highest frequency of the HBO, the upper limits of the magnetic dipole moment (?) and field strength (B) at the poles of the neutron star in the system were found to be 25.60 1025G cm3 and 3.6408 G, respectively, for kA= 1. 2024 The Author(s). -
A comprehensive review on natural macromolecular biopolymers for biomedical applications: Recent advancements, current challenges, and future outlooks
Versatile material properties coupled with high degree of biocompatibility and biodegradability has made biopolymers as potential candidates for diverse applications in the biomedical field. Natural biopolymers derived from various plant, animal and microbial sources with different biochemical compositions are extensively used in biomaterial industry with or without further medication to their native form. Biopolymeric biomaterials have been employed in a wide range of biomedical applications like tissue engineering, drug delivery, bone regeneration, wound dressings and cardiovascular surgery. Carbohydrate based biopolymers and protein based biopolymers are extensively used for several applications in the biomedical field including cartilage regeneration, periodontal tissue regeneration, bone regeneration, corneal regeneration, drug delivery and wound healing. This review work presents a comprehensive outlook on the applications of various biopolymers in biomedical field. The work elaborates the biochemistry of these polymers with special focus on their crucial properties in the biomedical industry. Further a detailed description on the most recent application of various biopolymers in the biomedical filed is presented in this review. This work further summarizes the current challenges and future prospects in the use of biopolymers in biomedical field. 2024 The Author(s) -
Comparative efficiency analysis of RF power amplifiers with fixed bias and envelope tracking bias
RF power amplifier (RF PA) finds its application in almost all the areas of electronics, mobile communication being identified as a major area. The paper performs a comparative efficiency analysis of RF power amplifiers operating with a fixed bias and an envelope tracking bias. Simulations are performed using Keysight advanced design system (ADS) tool. A class a RF PA operating at a 12 dB gain is fixed for the work. 16 QAM LTE signal operating at 5 MHz input frequency, with a peak to average power ratio (PAPR) of 6.0 dB is used as input signal. An envelope simulation at 2.5 GHz is performed on the RF power amplifier. Simulation result shows an improvement of 12% in power added efficiency (PAE) at 6 dB back-off and 6.422% in mean PAE while using envelope tracking power amplifiers, compared to RF PA with fixed supply. Envelope tracking power amplifiers reduced AM/AM distortions also by a factor of 0.248. The results obtained are much better than that obtained using a conventional RF PA with fixed bias. RF PA being the most power dissipative block in a mobile handset, improving its efficiency contributes directly to a great improvement in the battery lifetime of mobile phones. The major challenges faced by envelope tracking PA (ETPA) designers in achieving this efficiency improvement is also delineated in the paper. 2024 Institute of Advanced Engineering and Science. All rights reserved. -
Exploring perceptions of psychology students in Delhi-NCR Region towards using mental health apps to promote resilience: a qualitative study
Background: Mental health apps (MHapps) have the potential to become an essential constituent for addressing mental health disparities and influencing the psychological outcomes of students in India. Though lauded as a practical approach to preventing various mental health issues, there are concerns that developing and utilizing MHapps standardized on Western populations produce ineffective results for the natives of Asian countries such as India due to a wide range of cultural differences. This research was conducted on psychology students living in the Delhi-NCR region of the Indian subcontinent. The study explored psychology students perceptions, needs, and preferences regarding mental health apps that promote resilience, identified barriers and facilitators for developing effective mental health apps, and explored the cultural relevance of the development of MHapps in India. Methods: This was an exploratory study utilizing focus group discussions among psychology students. Psychology students were sampled using snowball sampling from Delhi-NCR region colleges to participate in FGDs. We conducted six focus groups, which included a representation of 30 psychology students from full-time UG/PG courses. The study used a reflexive thematic analysis framework using the six-step Braun and Clarke process to develop themes. Results: Psychology students valued MHapps for their easy accessibility, 24*7 functionality, affordable costs, highly engaging features, and the option of being anonymous. However, students preferred the apps based on established psychological frameworks with strong empirical evidence and the availability of remote mental health professionals with relevant qualifications and training. The main barriers to using MHapps identified by students included difficulties in differentiating between real and fake MHapps, lack of progress tracking of the users due to minimal human interactions, and ethical and data privacy concerns. Students also emphasized the cultural relevance of MHapps. The interpretation of our findings indicates that students demanded transparency regarding the authenticity of MHapps. Conclusion: The findings of this exploratory investigation offer a better understanding of how college students perceive the usage of MHapps to improve resilience. This study highlights that further research should explore the specific needs and preferences of university students for developing and implementing effective MHapps for different contexts. The Author(s) 2024. -
Comprehensive study of the physicochemical properties of three-component deep eutectic solvents and their implications for microbial and anticancerous activity
Sustainable chemistry centers on substituting perilous solvents and materials with eco-conscious alternatives. Deep eutectic solvents (DES) hold substantial potential in this arena. This inquiry includes the formulation of three-component eutectic solvents and an exhaustive scrutiny of their physical and chemical attributes. These encompass solubility, boiling point, pH, density, viscosity, surface tension, refractive index, contact angle, conductivity, Fourier-transform infrared spectroscopy, polarized optical microscopy, thermogravimetric analysis, and differential scanning calorimetry. Furthermore, a biological exploration featured two bacterial strains and two fungal strains. The entire spectrum of ten three-component DES was administered to these microorganisms to discern plausible impacts. In addition, the biomedical promise of these DES was unveiled through anticancer assays employing MCF-7 and HeLa cell lines. The outcomes were favorable, underscoring robust anticancer potency, thereby hinting at future oncological utility. These interdisciplinary endeavors envelop the progression of sustainable solvent innovation, meticulous physicochemical scrutiny, microbial analysis, and anticancer appraisal. This study propels inventive resolutions with ecological and biomedical reverberations by amalgamating these distinct yet interconnected facets. 2024 Indian Chemical Society -
Adsorption and storage of hydrogen- A computational model approach
Due to the imperative global energy transition crisis, hydrogen storage and adsorption technologies are becoming popular with the growing hydrogen economy. Recently, complex hydrides have been one of the most reliable materials for storing and transporting hydrogen gas to various fuel cells to generate clean energy with zero carbon emissions. With the ever-increasing carbon emissions, it is necessary to substitute the current energy sources with green hydrogen-based efficient energy-integrated systems. Herein, we propose an input-output model that comprehends complex hydrides such as lithium and magnesium alanates, amides and borohydrides to predict, estimate, and directly analyse hydrogen storage and adsorption. A critical and thorough comparative analysis of the respective complex hydrides for hydrogen adsorption and storage is discussed, elucidating the storage applications in water bodies. Several industrial scale-up processes, economic analysis, and plant design of hydrogen storage and adsorption approaches are suggested through volumetric and gravimetric calculations. 2024 Elsevier Inc. -
Evaluation of an interprofessional collaborative practice training module for the management of children with autism spectrum disorder
Background: Protocols instituted for behavioral treatment and skills training programs for the management of autism spectrum disorder (ASD) suffer from lack of collaborative approaches. The tenets of interprofessional collaborative practice (IPCP) focus on preparing a panel of health care professionals (HCPs) from different professions who can work together to enable the common goal of ensuring that children with ASD can participate in society. This study was designed to pilot this approach through an IPCP training module on ASD for care providers from multiple professions. Methods: An interventional study with pre-post analysis began with formation of the interprofessional (IP) team, who developed an IPCP module, addressing the knowledge and skills needed for the collaborative management of neurodevelopmental issues of children with ASD. This module was delivered through an online training workshop using various teaching learning methods to the participants from seven different health professions after obtaining informed consent. Perceptions of interprofessional collaboration and competencies of IPCP were assessed using standard IP tools and reflective summaries and analyzed through a mixed-methods approach. Results: A total of 42 HCPs from seven professions, including speech and hearing, occupational therapy, clinical psychology, physiotherapy, pediatrics, nursing, and pedodontics, participated in the study. Pre-post analysis of PINCOM-Q and Dow-IPEC data and thematic analysis revealed a significant difference in the perceptions of interprofessional collaboration and competencies levels of IPCP. Conclusion: This study suggests that use of IPCP principles in the training of professionals working with ASD is a promising and feasible option to develop more competent health professionals. The training enhanced the abilities of professionals to work in field of ASD as conveyed by the participants. They also expressed confidence in the knowledge of IP core competencies after the completion of the module. 2022 -
Valorisation of coffee husk as replacement of sand in alkali-activated bricks
The coffee industry is known to generate voluminous amount of waste during its production process. Different types of waste such as coffee hush ash and spent coffee ground, to name a few, have been extensively researched as a substitute in the construction industry. However, the utilization of coffee husk as a substitute for construction materials has seen limited exploration. In particular, there are no studies which investigate the utilization of waste coffee husk (WCH) in alkali-activated bricks. Therefore, in this research WCH was employed as a substitute to sand in alkali-activated bricks. Alkali-activated bricks were synthesized with ground granulated blast furnace slag (GGBFS), fly ash (FA), sand, and sodium silicate solution (SS). Sand was replaced with WCH at replacement rates of 0 %, 5 %, 10 %, 15 %, 20 %, and 30 % by volume. The developed bricks were evaluated for strength, density, water absorption, porosity, and efflorescence. Additionally, structural and morphological characteristics of bricks were assessed by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Thermogravimetric analysis (TGA), and Scanning electron microscopy (SEM) analysis. The results indicate that bricks with WCH improve the compressive strength with a maximum value of 15.7 MPa, and reduce the density with a minimum value of 1509 kg/m3 for composites with 30 % WCH, respectively. The water absorption and porosity of bricks increased with incorporation of WCH due to porous structure of WCH. The physico-chemical analysis of the bricks shows effective geopolymerization in the composite system with WCH, and further the bricks with 30 % WCH depict thermal stability with insignificant weight loss at 575 ?. Finally, the composites with 30 % WCH classify as good quality bricks as per IS 1077: 1992 specifications, and this will improve practical feasibility of such materials in the construction industry. 2024 The Authors -
Discrimination Experiences of Old Settlers in Sikkim: A Qualitative Exploration
Race-based stigma and discrimination have been extensively studied from the perspective of the northeastern community due to their minority status in most states of India. Discrimination experiences of the mainland Indians in the northeastern states, where they are a minority, are little discussed. The Rajya Sabha (upper house of the parliament) Committee of Petitions in 2014 acknowledged that the old settlers were treated as second-class citizens in Sikkim. In the present study, we explored the existence and manifestation of discrimination experiences of old settlers who settled in Sikkim before 1975 and perceive themselves to be stigmatized. This study focused on Sikkim because the state merged with India in 1975 and has had less time integrating with migrants or mainlanders than other northeastern states. We conducted nine semi-structured interviews with seven male and two female participants from the Marwari, Bihari, and Punjabi mainland communities. Using thematic analysis, we developed 1 global theme, 2 organizing themes, and 24 basic themes. The analysis showed the existence of discrimination and racism against old settlers and their manifestations at institutional and interpersonal levels. The findings are important from a policymaking perspective as they provide evidence to the conclusion reached by the Rajya Sabha Committee on Petitions and provide valued suggestions for reports on race-based discrimination in India. The Author(s) under exclusive licence to National Academy of Psychology (NAOP) India 2023. -
Knowledge, Attitude, and Stigma Among Adolescents: Effect of Mental Health Awareness and Destigmatisation (MHAD) Program
Background: Stigma against mental health problems is a common issue for adolescents aged 1418 years. However, comprehensive programs that simultaneously address awareness and stigma reduction tailored to the specific needs of this age group are lacking. Method: This study investigated the effectiveness of the Mental Health Awareness and Destigmatisation Program (MHAD) in reducing stigma and improving knowledge and attitudes towards peers with mental health problems. A quasi-experimental pre-post design was employed among adolescents aged 1418 years from an educational institution in Bangalore. After excluding those with high baseline mental health symptoms (PSC-17 > 20), a preassessment was conducted on adolescents' knowledge, attitude, and stigma (n = 52) using the Mental Health Knowledge Schedule, Self-structured Case Vignettes, and Peer Mental Health Stigmatization Scale. After completing the 6-week program, three participants were excluded from the post-assessment, as their attendance was less than 50%. A total of 49 (mean age = 16 years) adolescents were included in the post-assessment. Results: The paired sample t-test revealed significant improvements in all stigma scores. The Wilcoxon signed-rank test indicated a significant improvement in Recognition of Mental Illness scores. Conclusion: Findings showed that MHAD, an education-based program, was effective in reducing adolescents' stigma towards peers with mental health problems and improving their overall recognition of mental health symptoms. Research across larger adolescent populations is essential to enhance these interventions' long-term impact and sustainability. By closely monitoring and expanding research efforts, we can gain deeper insights into how these programs foster self-awareness, a crucial factor in recognizing mental health needs, challenging stigma, and promoting help-seeking behaviors among adolescents. 2024 Wiley Periodicals LLC. -
Rejuvenating human resource accounting research: a review using bibliometric analysis
The current study attempts to map the intellectual structure of Human Resource Accounting to understand the research gaps and future trajectories. The study employs systematic literature review technique to extract relevant literature, bibliometric analysis to map the intellectual structure of research in human resource accounting, to identify underlying research themes and content analysis to identify avenues for future research. Based on 2438publications, author keyword co-occurrences extracted four themes namely, Human Resource Management, Intellectual Capital, Human Capital, and Voluntary Disclosure. The study also summarizes significant findings of papers under each cluster through content analysis identifying areas for future research. The study provides a birds eye view of the intellectual structure of academic research efforts in the field of human resource accounting. The study is one of the first attempt to comprehensively review the academic literature from Scopus database employing systematic literature review, bibliometric methods, and content analysis in the field of human resource accounting. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. -
Balancing cerebrovascular disease data with integrated ensemble learning and SVM-SMOTE
The paper addresses the challenge of imbalanced classification in the context of cerebrovascular diseases, including stroke, transient ischemic attack (TIA), and vascular dementia. The imbalanced nature of cerebrovascular disease datasets poses significant challenges to conventional machine learning algorithms, making precise diagnosis and effective management difficult. The aim of the paper is to propose a novel approach, the INTEL_SS algorithm, which combines ensemble learning techniques with Support Vector Machine-Synthetic Minority Over-sampling Technique (SVM-SMOTE) to effectively handle the imbalanced nature of cerebrovascular disease datasets. The goal is to improve the accuracy of diagnosis and management of cerebrovascular diseases through advanced machine learning techniques. The proposed methodology involves several key steps, including preprocessing, SVM-SMOTE, and ensemble learning. Preprocessing techniques are used to improve the quality of the dataset, SVM-SMOTE is employed to address class imbalance, and ensemble learning methods such as bagging, boosting, and stacking are utilized to improve overall classification performance. The experimental results demonstrate that the INTEL_SS algorithm outperforms existing methods in terms of accuracy, precision, recall, F1-score, and AUC-ROC. Performance metrics are used to assess the effectiveness of the proposed approach, and the results consistently show the superiority of INTEL_SS compared to state-of-the-art imbalanced classification algorithms. The paper concludes that the INTEL_SS algorithm has the potential to enhance the diagnosis and management of cerebrovascular diseases, offering new opportunities to apply machine learning techniques to improve healthcare outcomes. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024. -
Empowering BRICS economies: The crucial role of green finance, information and communication technologyand innovation in sustainable development
This study delves into the crucial role of green finance, information and communication technology (ICT), technological innovation, and renewable energy in the Brazil, Russia, India, and China (BRICS) countries from 2000 to 2021. The findings highlight the importance of green finance in reducing the ecological footprint and promoting eco-friendly initiatives, sustainable practices, environmental technology innovation, and heightened environmental awareness. This means 1% increase in green related finance has reduced ecological footprint by 0.72% in BRICS economies. Additionally, technological innovation and the consumption of renewable energy play a significant role in enhancing environmental sustainability. Conversely, the study reveals that ICT has a considerable impact on the ecological footprint, but the interaction effect with green finance helps to mitigate its negative effects and improve the environmental quality. Meanwhile, non-renewable energy, gross domestic product (GDP) per capita, and urbanization have an adverse effect on the environment. To strengthen green finance in BRICS countries, governments can establish comprehensive policy frameworks that prioritize sustainability and create a conducive climate for incentivizing investment in environmentally friendly endeavors. 2024 ERP Environment and John Wiley & Sons Ltd. -
Immobilized proline-based electro-organocatalyst for the synthesis of bis-?-diketone via Knoevenagel condensation reaction
In the quest for more sustainable chemical processes, we devised a technique using electro-organocatalysis to synthesize bis-?-diketone compounds via Knoevenagel condensation of benzaldehyde and dimedone. Our approach involves a modified electrode fabricated via anchoring L-proline onto a carbon fiber paper electrode supported by poly-3,4-diaminobenzoic acid (PDABA), which enhances efficiency in addition to the simple catalyst separation from the reaction mixture in heterogeneous catalysis. The electrochemical and surface topographical studies for the fabricated electrode were carried out, revealing high efficiency in comparison to the bare carbon fiber paper electrode. This electrochemical reaction operates under mild conditions utilizing lithium perchlorate and acetonitrile, yielding high amounts of the desired product. This study showcases a promising pathway for producing valuable organic compounds in an environmentally friendly manner, marking a significant stride forward in sustainable synthesis practices. 2024 Elsevier Ltd -
AttGRU-HMSI: enhancing heart disease diagnosis using hybrid deep learning approach
Heart disease is a major global cause of mortality and a major public health problem for a large number of individuals. A major issue raised by regular clinical data analysis is the recognition of cardiovascular illnesses, including heart attacks and coronary artery disease, even though early identification of heart disease can save many lives. Accurate forecasting and decision assistance may be achieved in an effective manner with machine learning (ML). Big Data, or the vast amounts of data generated by the health sector, may assist models used to make diagnostic choices by revealing hidden information or intricate patterns. This paper uses a hybrid deep learning algorithm to describe a large data analysis and visualization approach for heart disease detection. The proposed approach is intended for use with big data systems, such as Apache Hadoop. An extensive medical data collection is first subjected to an improved k-means clustering (IKC) method to remove outliers, and the remaining class distribution is then balanced using the synthetic minority over-sampling technique (SMOTE). The next step is to forecast the disease using a bio-inspired hybrid mutation-based swarm intelligence (HMSI) with an attention-based gated recurrent unit network (AttGRU) model after recursive feature elimination (RFE) has determined which features are most important. In our implementation, we compare four machine learning algorithms: SAE + ANN (sparse autoencoder + artificial neural network), LR (logistic regression), KNN (K-nearest neighbour), and nae Bayes. The experiment results indicate that a 95.42% accuracy rate for the hybrid model's suggested heart disease prediction is attained, which effectively outperforms and overcomes the prescribed research gap in mentioned related work. The Author(s) 2024. -
Terahertz-based optoelectronic properties of ZnS quantum dot-polymer composites: For device applications
Terahertz (THz) technology integration with nanomaterials is receiving excellent attention for next-generation applications, including enhanced imaging and communication. The excellent optical properties in THz domain can lead to preparation of low-cost CMOS camera which can convert THz radiation into optical signal in very efficient manner. In the present study, we have studied the properties of Zinc Sulfide quantum dots (ZnS QDs) embedded with Polyvinyl Alcohol (PVA) composites films using THz Signal at room temperature. The optical characterizations such as refractive index, absorption coefficients and dielectric constants of these samples were measured in the 0.12.0 THz range. Additionally, optical impedance, surface roughness, and reflection coefficient in TE and TM mode between 0.1 and 2.0 THz range were determined for these samples based on surface roughness-based reflection and scattering properties. The surface roughness factor was used to measure the optical impedance of the ZnS QDs based polymer films. The measured values of the absorption coefficient at 266 nm are compared with THz radiation, and the refractive indices of these samples range from 1.75 to 2.0. Finally, these samples were subjected to UV light excitation (?exe = 266 nm) of 0.15 ns duration and 400 nm for the fluorescence and corresponding life time measurements. We observed two numbers of fluorescence lines in nanosecond based excited domain whereas 400 nm excitation-based fluorescence life time lies between 13.811.39 ns range along with shift in fluorescence lines between 538.7 to 560.7 nm, respectively. 2024