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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. -
Graphene-metal oxide composites for electrochemical energy storage and conversion
The development of clean and renewable alternative energy sources is essential due to the rising energy consumption. Advancements in energy conversion and storage technologies, such as fuel cells, batteries, and solar cells, are currently the subject of active research. The unique structure and properties of two-dimensional graphene materials are explored in developing energy devices. The efficient utilization of graphene's enormous specific surface area and exceptional electrical, chemical, and mechanical properties still remains a challenge to researchers due to the agglomeration of its layers. The introduction of metal oxides into these 2D layers helps to enhance their structural and electrochemical stability, which helps in the production of energy storage devices. This chapter discusses the synthesis protocols, tunable properties, as a function of size and shape, and characterization tools. It also provides a deeper understanding of graphene-metal oxide composites in various energy storage devices, highlighting the importance of the synergistic effects between graphene and metal oxides. The chapter concludes with the prospects and potential of graphene-metal oxide composites for energy storage applications. The Royal Society of Chemistry 2025. -
Bithiophene and 3,4-Ethylenedioxythiophene Copolymers with Biphenyl and Bis-[octyloxy]benzene acceptors for NLO Application
Two groups of thiophene-based donoracceptor (DA) type conjugated copolymers with low band gaps were designed and synthesized through direct arylation. Biphenyl and bis(octyloxy)benzene were incorporated as electron-deficient units to effectively lower the band gaps. The HOMOLUMO energy levels of the resulting copolymers were theoretically determined using DFT calculations at the HSE06 and B3LYP levels with a 631G(d,p) basis set. The copolymers were characterized by UVVis, FT-IR, fluorescence, and H NMR spectroscopy. Their thermal stability was assessed using thermogravimetric analysis, which confirmed that the bithiophene-based copolymers P(BT-BP) and P(BT-DOB) were highly thermally stable. Additionally, P(BT-DOB) and P(EDOT-DOB) exhibited solvatochromic behavior in varying toluene/acetonitrile solvent mixtures. Third-order nonlinear optical properties of P(BT-BP), P(EDOT-BP), P(BT-DOB), and P(EDOT-DOB) were studied using an open-aperture Z-scan method at 532 nm in DMSO. These copolymers showed reverse saturable absorption with low optical threshold values. 2025 Elsevier B.V. -
Human factors and social engineering in IoT attacks
This chapter explores how social engineering and human factors contribute to IoT assaults, emphasizing how human mistake and psychological manipulation weaken linked systems. Cybercriminals are increasingly using social engineering techniques to trick people into disclosing private information or jeopardizing security measures as IoT devices become more and more integrated into everyday life and vital infrastructure. This study examines important strategies like baiting, pretexting, and phishing, highlighting their unique uses in Internet of Things settings. It also looks into how human behavior affects security procedures, showing how dangers are increased by insufficient awareness and training. The chapter offers important insights into how human factors and IoT security interact by examining current case studies and actual attack scenarios. It ends with tactical suggestions for enhancing security awareness, fortifying authentication procedures, and putting in place efficient defenses against social engineering risks in IoT ecosystems. Future research should focus on developing AI-driven security measures, flexible defense strategies, and strong policy frameworks to strengthen IoT security. Tackling these human-related vulnerabilities is essential to building a safer and more reliable IoT ecosystem. 2026 Elsevier Inc. All rights reserved.. -
Psychosocial Group Interventions for Older Adults: A Systematic Review
Older adults are facing complex, multifaceted psychosocial issues, such as loneliness, social isolation, financial stress, and cognitive decline, which crucially impact their mental health and quality of life. Group-based psychosocial interventions have gained recognition as valuable tools for strengthening peer interaction and collective healing. The review aims to map the important literature on psychosocial group interventions for older adults. Six electronic databases were searched from March to June 2025. Inclusion criteria are: psychosocial interventions within the last 10 years and group interventions in English research papers only. Review papers, conference proceedings, medical interventions, and individual interventions have been excluded. After the screening process, eight articles were identified as psychosocial group interventions for older adults from eight different countries. Each intervention is unique, and 90% of them effectively address the psychosocial needs of older people. The results are explained and grouped under three themes that have emerged from the research questions underlying the review. They are: (a) the efficacy of psychosocial group interventions on cognitive and mental well-being; (b) addressing social isolation, loneliness, and enhancing social connection; and (c) impact of environmental and socio-cultural contexts on older adults psychosocial interventions. A significant observation is the need for a structured intervention model to promote the well-being of older adults. This review provides a foundation for developing new insights into psychosocial interventions for older adults. The Author(s) 2026 -
Examining the Impact of TRIPS Agreement on Innovation: A Review and Research Agenda
[No abstract available] -
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. -
Charting the Course of Leadership Through the Digital Era: A Synergy of Leadership Styles, Technology Integration, and Deep Learning
This chapter aims to provide actionable strategies for empowering leaders in leveraging technology to amplify their leadership efficacy in contemporary business environments by employing extensive literature review and deep learning models, a method in Artificial Intelligence (AI). It investigates the effectiveness of three leadership approachesTransformational, Transactional, and Servant Leadershipin meeting high-performance expectations within organizational contexts. The performance of these leadership styles based on their effectiveness scores have been analyzed using data analysis techniques and neural network models, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). Furthermore, Deep Convolutional Generative Adversarial Networks (DCGANs), have been utilized to visualize complex leadership dynamics. The findings from this comprehensive analysis provide valuable insights into the strengths and limitations of each leadership approach, guiding strategic leadership development initiatives and organizational decision-making processes. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Navigating leadership and technology integration in the digital age: Success factors and determinants
This chapter explores the importance of leadership in building an environment that encourages technological innovations and developments, the role of organizational leaders in inspiring employees to accept and use new technologies and the future for business organizations concerning technological advancements. Through a comprehensive literature review analysis, the need for technology embracing leaders who can adopt and help adapting to intelligent communication technologies for facilitated communication, manage the new change and implement strategic solutions have been emphasized. The chapter also includes two case analysis of Cleveland Clinic and Arizona State University demonstrating successful leadership and technology integration and a machine learning approach based on correlation matrix using SUV to assess the relationship between transformational leadership, knowledge-based work passion and organizational citizenship behaviour. The implications of this study are beneficial as it explores the multi-facets of successful technology-integrated leadership in the digital age. 2025, IGI Global Scientific Publishing. All rights reserved. -
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]