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Hybrid architecture of Multiwalled carbon nanotubes/nickel sulphide/polypyrrole electrodes for supercapacitor
A hybrid electrode structure consisting of amino functionalised multi-walled carbon nanotube, nickel sulphide, and polypyrrole is successfully synthesized using a two-step synthesis such as hydrothermal and in-situ polymerization method. The resulting MWCNT/NiS/PPy composite exhibits a distinct tube-in-tube morphology with excellent stratification. The combination of different components and the unique structure of the composite contribute to its impressive specific capacitance of 1755 F g?1 at 3 A g?1. The prepared ternary composite enables ample exposure of numerous active sites while improving structural stability, ultimately leading to enhanced energy storage capabilities. They do this by combining the advantages of constituent components, a hierarchical assembly approach, and an integrated composite structure. Furthermore, even after undergoing 10,000 charge-discharge cycles, the supercapacitor retains more than 97% of columbic efficiency. An asymmetric coin cell was fabricated using MWCNT/NiS/PPy//AC device which delivered an energy density and power density of 33.12 Wh Kg?1 and 6750 W kg?1 respectively. These findings highlight the exceptional potential of the fabricated device for future applications in hybrid energy storage systems. 2024 Elsevier Ltd -
Analysis of unsteady flow of blood conveying iron oxide nanoparticles on melting surface due to free convection using Casson model
Iron oxide nanoparticles have great importance in future biomedical applications because of their intrinsic properties, such as low toxicity, colloidal stability, and surface engineering capability. So, blood containing iron oxide nanoparticles are used in biomedical sciences as contrast agents following intravenous administration. The current problem deals with an analysis of the melting heat transfer of blood consisting iron nanoparticles in the existence of free convection. The principal equations of the problem are extremely nonlinear partial differential equations which transmute into a set of nonlinear ordinary differential equations by applying proper similarity transformations. The acquired similarity equalities are then solved numerically by Runge-Kutta Felhsberg 45th-order method. The results acquired are on the same level with past available results. Some noteworthy findings of the study are: the rate of heat transfer increases as the Casson parameter increases and also found that the temperature of the blood can be controlled by increasing or decreasing the Prandtl number. Hence, we conclude that flow and heat transfer of blood have significant clinical importance during the stages where the blood flow needs to be checked (surgery) and the heat transfer rate must be controlled (therapy). 2020 Wiley Periodicals LLC -
A parallel approach for region-growing segmentation
Image Segmentations play a heavy role in areas such as computer vision and image processing due to its broad usage and immense applications. Because of the large importance of image segmentation a number of algorithms have been proposed and different approaches have been adopted. In this theme I tried to parallelize the image segmentation using a region growing algorithm. The primary goal behind this theme is to enhance performance or speed up the image segmentation on large volume image data sets, i.e. Very high resolution images (VHR). In parliamentary law to get the full advantage of GPU computing, equally spread the workload among the available threads. Threads assigned to individual pixels iteratively merge with adjacent segments and always ensuring the standards that the heterogeneity of image objects should be belittled. An experimental analysis upon different orbital sensor images has made out in order to assess the quality of results. 2015 IEEE. -
Dynamic Load Scheduling Using Clustering for Increasing Efficiency of Warehouse Order Fulfillment Done Through Pick and Place Bots
The domain of warehouse automation has been picking up due to the vast developments in e-commerce owing to growing demand and the need to improve customer satisfaction. The one crucial component that needs to be integrated into large warehouses is automated pick and place of orders from the storage facility using automated vehicles integrated with a forklift (Pick and Place bots). Even with automation being employed, there is a lot of room for improvement with the current technology being used as the loading of the bots is inefficient and not dynamic. This paper discusses a method to dynamically allocate load between the Pick and Place BOTs in a warehouse during order fulfillment. This dynamic allocation is done using clustering,an unsupervised Machine Learning algorithm. This paper discusses using fuzzy C-means clustering to improve the efficiency of warehouse automation. The discussed algorithm improves the efficiency of order fulfillment significantly and is demonstrated in this paper using multiple simulations to see around 35% reduction in order fulfillment time and around 55% increase in efficiency. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Patient Monitoring System for Elderly Care using AI Robot
The use of robots in numerous industries has expanded in recent decades. Self-guiding robots have started to arise in human life, particularly in sectors pertaining to the lives of old people. Age-related population growth is accelerating globally. As a result, there is a rising need for personal care robots. The purpose of this requirement is to increase opportunities for mobility and support independence. To meet this demand, a robot with specific functionalities to help older people has been designed. The standard values of healthcare parameters are stored in the database by recording and comparing the current values the system will give an alarm and also sends a message to the doctor or caretaker so that a proper care would be given to the patients. We are including a preset distance value to monitor the elder people. Here we are using some sensors to detect the health parameters from the person. Robot have designed to intimate the family members if any changes occur in the health parameters. It helps the people to stay alone in home with safe manner. 2022 IEEE. -
Metal-Based Nanoparticles for Infectious Diseases and Therapeutics
Infectious diseases that are easily transmitted by microorganisms like bacteria, protozoa, fungus, etc. are a menace to humans. The greatest threat to human race is to mitigate the impact of these diseases. People with less immunity and children are prone to these diseases. Even healthy people get infected due to its easy transmission. Microorganisms causing these diseases are becoming more resistant to the drugs that are available in the market. So, there is a need to find new therapeutic which is facile, sensitive, and selective, is an important challenge for the medical field and this is where nanotechnology is having a greater chance. Nanoparticles especially metal-based nanoparticles have the ability to act against infectious and non-infectious diseases, this is because of their unique properties like small size, high surface area, etc. They do not have a specific binding site on the bacterial cell, which lead to the failure of bacterial resistant towards the nanoparticle mechanism. There are many nanoparticles which are efficient against particular diseases. In this review we are discussing about the advanced nanomaterials as therapeutics for infectious diseases. We have also discussed about antiviral activities which gives us a ray of hope for the solution of the SARS-COV-2. The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2022. -
Implementing artificial intelligence agent within connect 4 using unity3d and machine learning concepts
Nowadays, we come across games that have unbelievably realistic graphics that it usually becomes hard to distinguish between reality and the virtual world when we are exposed to a virtual reality gaming console. Implementing the concepts of Artificial Intelligence (AI) and Machine-Learning (ML) makes the game self-sustainable and way too intelligent on its own, by making use of self-learning methodologies which can give the user a better gaming experience. The use of AI and ML in games can give a better dimension to the gaming experience in general as the virtual world can behave unpredictably, thus improving the overall stigma of the game. In this paper, we have implemented Connect-4, a multiplayer game, using ML concepts in Unity3D. The machine learning toolkit ML-Agents, which depends on Reinforcement Learning (RL) technique, is provided using Unity3D. This toolkit is used for training the game agent which can distinguish its good moves and mistakes while training, so that the agent will not go for same mistakes over and over during actual game with human player. With this paper, authors have increased intelligence of game agent of Connect 4 using Reinforcement Learning, Unity3D and ML-Agents toolkit. BEIESP. -
Study of Bard-Marangoni Convection in a Microfluid with Coriolis Force
The convection of micro-structured fluid particles and the Coriolis force has been investigated in the problem. The eigenvalues are calculated for upper free velocity and adiabatic temperature boundary conditions and lower rigid velocity and isothermal temperature boundary conditions. The analysis is based on solving linear disturbance equations. The impact of different micropolar fluid variables and the Taylor number based on the convection has also been investigated. The study could observe that while the coupling and micropolar heat conduction parameters along with rotational parameters have a stabilizing effect, the couple stress parameter results in a destabilizing effect. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
The impact of slip mechanisms on the flow of hybrid nanofluid past a wedge subjected to thermal and solutal stratification
This investigation aims to inspect the flow and thermal characteristics of hybrid nanoparticles under the effect of thermophoresis and Brownian motion. The hybrid nanofluid is formed by dispersing the silver nanoparticles into the base fluid composed of tungsten oxide and water. The resulting hybrid nanofluid is assumed to flow over a moving wedge. The wedge is a geometry that can be commonly seen in many manufacturing industries, moulding industries, etc., where friction creates more heat and cooling becomes a necessary process. This study currently focuses on such areas of the industries. In this regard, the flow expressions in the form of Partial Differential Equations (PDEs) are obtained by incorporating the modified Buongiorno's model and using boundary layer approximations. The modified Buongiorno model helps us analyze the impact of volume fraction along with the slip mechanisms. Suitable transformations are used to achieve the nondimensional form of governing equations, and further, it transforms the PDE to Ordinary Differential Equation (ODE). The RKF-45 is used to solve the obtained ODE and the boundary conditions. Furthermore, graphic analysis of the solutions for fluid velocity, energy distributions and dimensionless concentration is provided. It was noted that the behavior of the Nusselt and Sherwood numbers was determined by analyzing numerous parameters. The conclusions show that they decrease with greater values of the stratification factors. Additionally, with higher values of the wedge parameter, the magnitude of the velocity field and the thermal boundary layer diminish. 2023 World Scientific Publishing Company. -
Adopting Metaverse as a Pedagogy in Problem-Based Learning
Pedagogical practices vary from time to time based on the requirement of various academic disciplines. Course instructors are constantly searching for inclusive and innovative pedagogies to enhance learning experiences. The introduction of Metaverse can be observed as an opportunity to enable the course instructors to combine virtual reality with augmented reality to enable immersive learning. The scope of immersive learning experience with Metaverse attracted many major universities in the world to try Metaverse as a pedagogy in fields such as management studies, medical education, and architecture. Adopting Metaverse as a pedagogy for problem-based learning enables the course instructors to create an active learning space that tackles the physical barriers of traditional pedagogical practices of case-based learning facilitating collaborative learning. Metaverse, as an established virtual learning platform, is provided by Meta Inc., providing the company a monopoly over the VR-based pedagogy. Entry of other tech firms into similar or collaborative ventures would open up a wide array of virtual reality-based platforms, eliminating the monopoly and subsequent dependency on a singular platform. The findings of the study indicate that, currently, the engagements on Metaverse are limited to tier 1 educational institutions worldwide due to the initial investment requirements. The wide adoption of the Metaverse platform in future depends on the ability of the platform providers to bridge the digital gap and facilitate curricula development. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Pemetrexed loaded gold nanoparticles as cytotoxic and apoptosis inducers in lung cancer cells through ROS generation and mitochondrial dysfunction pathway
Supramolecular nanoparticles containing peptides and drugs have recently gained recognition as an effective tumor treatment drug delivery system. A multitarget drug termed pemetrexed is effective against various cancers, including nonsmall cell lung cancer. The work aims to establish the capability of pemetrexed gold nanoparticles (PEM-AuNPs) to induce apoptosis and explore molecular changes. X-ray diffraction, Fourier-transform infrared spectroscopy, ultravioletvisible spectroscopy, scanning electron microscope, and transmission electron microscope were used to investigate the synthesized nanoparticles. The MTT assay was utilized to investigate the anticancer properties of PEM-AuNPs at varying concentrations (50, 100, and 200M). PEM-AuNPs demonstrated a decrease in cell viability with 55.87%, 43.04%, and 25.59% for A549 cells and 54.31%, 37.40%, and 25.84% for H1299 cells at the respective concentrations. To assess apoptosis and perform morphological analysis, diverse biochemical staining techniques, including acridine orange-ethidium bromide and 4?,6-diamidino-2-phenylindole nuclear staining assays, were employed. Additionally, 2?,7?-dichlorofluorescein diacetate staining confirmed the induction of reactive oxygen species generation, while JC-1 staining validated the impact on the mitochondrial membrane at the IC50 concentration of PEM-AuNPs. Thus, the study demonstrated that the synthesized PEM-AuNPs exhibited enhanced anticancer activity against both A549 and H1299 cells. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
Training multi-layer perceptron with enhanced brain storm optimization metaheuristics
In the domain of artificial neural networks, the learning process represents one of the most challenging tasks. Since the classification accuracy highly depends on the weights and biases, it is crucial to find its optimal or suboptimal values for the problem at hand. However, to a very large search space, it is very difficult to find the proper values of connection weights and biases. Employing traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local optima. Most commonly, back-propagation is used for multi-layer-perceptron training and it can lead to vanishing gradient issue. As an alternative approach, stochastic optimization algorithms, such as nature-inspired metaheuristics are more reliable for complex optimization tax, such as finding the proper values of weights and biases for neural network training. In this work, we propose an enhanced brain storm optimization-based algorithm for training neural networks. In the simulations, ten binary classification benchmark datasets with different difficulty levels are used to evaluate the efficiency of the proposed enhanced brain storm optimization algorithm. The results show that the proposed approach is very promising in this domain and it achieved better results than other state-of-the-art approaches on the majority of datasets in terms of classification accuracy and convergence speed, due to the capability of balancing the intensification and diversification and avoiding the local minima. The proposed approach obtained the best accuracy on eight out of ten observed dataset, outperforming all other algorithms by 1-2% on average. When mean accuracy is observed, the proposed algorithm dominated on nine out of ten datasets. 2022 Tech Science Press. All rights reserved. -
Application of XAI in Integrating Democratic and Servant Leadership to Enhance the Performance of Manufacturing Industries in Ethiopia
This study tests the conceptual model theorizing democratic leadership, servant leadership, learning organization, and performance of manufacturing industries using Structural Equation Modeling (SEM). The impact of democratic and servant leadership on learning organizations and the performance of manufacturing industries in Ethiopia is analyzed, and the role of learning organizations as a mediating variable is examined. Confirmatory Factor Analysis was performed, which includes a well-established Chi-square test, the Chi-square ratio to degrees of freedom, the goodness-of-fit index, the TuckerLewis index, the comparative fit index, the adjusted goodness-of-fit, and the root mean square error of approximation. Further, the performance of manufacturing industries has been assessed using XAI which helps in having a higher clarity on understanding the complexities in production. Based on linear regression, two methods SHAP and LIME have been used for precise predictions and forecast for future production plans in the manufacturing industry. This research contributes to the existing body of knowledge by dissecting the nuanced relationships between the two leadership styles and learning organization and further, their implications for an organizations performance. The findings of the study would provide insights for policymakers and practitioners to improve the performance of manufacturing industries. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Semilinear fractional elliptic equations with combined nonlinearities and measure data
This study focuses on semilinear fractional elliptic problems with concave-convex type nonlinearities and measures as data. Suitable iteration techniques and embedding results are employed to ensure the existence and multiplicity of solutions. 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Harnessing the Power of Climate Activism: Insights from Psychological Perspectives on Climate Change EngagementA Systematic Review
Scientific evidence has validated the inevitability of global warming and its effect in the form of climate change. There has been an increase in climate strikes and other forms of climate activism in recent years. It is important to understand the research landscape in psychological literature with regards to climate change and climate activism, to help guide future researchers. The databases of PubMed (Keywords: climate activism, climate change, psychology, n?=?1), Google Scholar (Keywords?=?climate activism, climate change, psychology, n?=?200) and Scopus database (Keywords: climate activism AND climate change AND psychology, n?=?160) were searched to create the pool of research documents. This was further filtered according to the inclusion and exclusion criteria. In the first section of this article, we have tried to explore the temporal and geographic growth trends of climate change research and collaborations using R (Bibliometric package). In the second section, we have used a text-mining approach to identify the research topics being explored in the climate change literature. R package tm along with associated packages were used to do the processing and subsequent grouping of the themes. In order to refine the classification the identified groupings were supervised by the authors. The final documents have been scoured to extract an overall understanding of the existing concepts explored so far and gauge their impact in the realm of climate change research. This systematic study casts light on the psychological views on climate activism and offers insightful information about the underlying causes that affect peoples involvement in the fight and struggle against climate change. The creation of more effective techniques for encouraging climate activism and utilizing its capacity to inspire significant action to address climate change can be influenced by an understanding of these elements. In order to address the complex issues of climate change, this chapter emphasizes the value of multidisciplinary collaboration amongst psychologists, policymakers, educators, and activists. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Deciphering the global research trends and significance of moral intelligence via bibliometric analysis
Introduction: Moral Intelligence (MI) as a concept has gained importance in recent years due to its wide applicability in individual, organizational, and clinical settings or even policy making. The present study employed Bibliometric analysis to understand the emerging topics associated with MI and its global research trend. This papers primary aim was (i) to explore the temporal and geographic growth trends of the research publication on MI. (ii) to identify the most prolific countries, institutions, and authors, working on MI, (iii) to identify the most frequent terminologies, (iv) to explore research topics and to provide insight into potential collaborations and future directions, and (v) to explore the significance of the concept of moral intelligence. Method: Bibliometric analysis was used to understand the emerging topics associated with MI and its global research trend using the SCOPUS database. VOS viewer and R were employed to analyze the result. Through the analysis conducted, the development of the construct over time was analyzed. Results: Results have shown that Iran and the United States and these two combined account for 53.16% of the total country-wise publications. Switzerland has the highest number of Multi-county publications. Authors from Iran and Switzerland have the most number of publications. Emerging topics like decision-making, machine ethics, moral agents, artificial ethics, co-evolution of human and artificial moral agents, green purchase intention etc were identified. Discussion: The application of MI in organisational decision-making, education policy, artificial intelligence and measurement of moral intelligence are important areas of application as per the results. Research interest in MI is projected to increase according to the results delineated in this article. Copyright 2024 Bagchi, Srivastava and Tushir. -
Challenges of Treating Bilingual and Multilingual Stuttering
[No abstract available] -
Therapists Issues in Understanding Stuttering
[No abstract available] -
Current Trends in Career Decision in Youth: Opportunities and Challenges
In todays times, career is a crucial life decision. Due to its paramount importance in our lives, the youth experience diverse kinds of stresses and pressures while choosing their career in life. Contrary to earlier handful career options, current trends offer an unlimited mix of traditional as well as unconventional career roles which further create confusion and anxiety while making the final decision. Newer factors, challenges and opportunities have forced a change of frameworks and perspectives to career decision-making. In career counselling, current trends are shifting away from the traditional practice of matching skill-sets to the job. Todays career decision-making takes an inclusive approach by discussing the various internal influences, emotional management, cognitive thinking styles, coping strategies, adaptability, etc. as well as external influences of uncertainty, evolving lifestyle demands, changing economic tapestry, etc. In addition, the influences of gender, family and culture affect the nature of the goals and their acceptability. The current chapter throws light on the evolving scenario in the field of career decision-making among the youth and attempts to offer solutions to the challenges being faced by the youth. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Understanding the role of HR practices in the improvement of MSMEs in India
Human resource practices are one of the most valuable practices that help the firm to achieve a competitive advantage. With the passage of time, MSME have shown a major shift in its functioning. Employees are at the center if organizations need to climb the ladder of survival, success, and growth. The present study intends to investigate the role of HR practices in the improvement of MSME performance. The study has analyzed double- blind peer- reviewed research papers on the role of HR practices on micro, small, and medium enterprises. With the help of existing research studies, job satisfaction is identified as a mediating variable. The findings of the study suggest that HR practices directly impact employee performance and outcomes attributes. The mediating role of job satisfaction was found to be significant. Empirical results of the study are presented through reliability, correlation, regression, and mediation analysis using SPSS and HAYES PROCESS Macro software. 2024, IGI Global. All rights reserved.