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Antibacterial efficiency of carbon dots against Gram-positive and Gram-negative bacteria: A review
The nontoxic characteristics and inherent antibacterial potency of Carbon dots (CDs) have earned immense attention in the last few years. As the increasing antibiotic resistance of bacterial strains create critical health risks, replacement of conventional antibiotics with alternative antibacterial agents is highly encouraged. The light-driven antibacterial action CDs is a safe process with minimal side effects. Direct interaction of CDs with bacterial cells also contribute to the overall antibacterial activity. Unique and complex mechanisms of antibacterial activity of CDs involve ROS generation, degeneration of cell structure, and leakage of the cytoplasm because of DNA binding and modulation of gene expression. This review provides a systematic overview of the antibacterial potency of CDs to eradicate Gram-positive and Gram-negative bacteria. Various mechanisms of antibacterial activity and factors that contribute to antibacterial action of CDs also discussed. It also highlights the synergistic effects on the antibacterial performance of modified CDs and significant future research concerns. 2021 Elsevier Ltd -
Family Caregiving in Dementia in India: Challenges and Emerging Issues
This chapter would provide an overview of the caregiving scenario in India with a focus on families as the mainstay of support and care for people with dementia. The various aspects of caregiving in dementia would be discussed in the light of the Indian sociocultural context. The impact of caregiving and challenges faced by the family and informal caregivers would be described in the light of the changing demographics and urbanization in India. The need for different kinds of caregiver education and training programmes tailored to the domiciliary and socioeconomic status of the family would be discussed. The resources available for family caregivers, like existing programmes for psychoeducation, family self-care, online and other resources for support would be described. We would discuss the challenges faced in developing culturally appropriate interventions for India that can be delivered within existing resources, such as supporting families in their role as caregivers and providing training and support for them. The chapter would discuss the emerging issues in the models of care for low- and middle-income countries like India, where the care is primarily home-based. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021. -
Citrus Medica-derived Fluorescent Carbon Dots for the Imaging of Vigna Radiate Root Cells
Bio-imaging is a crucial tool for researchers in the fields of cell biology and developmental biomedical sector. Among the various available imaging techniques, fluorescence based imaging stands out due to its high sensitivity and specificity. However, traditional fluorescent materials used in biological imaging often suffer from issues such as photostability and biocompatibility. Moreover, plant tissues contain compounds that cause autofluorescence and light scattering, which can hinder fluorescence microscopy effectiveness. This study explores the development of fluorescent carbon dots (Cm-CDs) synthesized from Citrus medica fruit extract for the fluorescence imaging of Vigna radiata root cells. The successful synthesis of CDs with an average size of 6.7nm is confirmed by Transmission Electron Microscopy (TEM). The X-ray diffraction (XRD) analysis and raman spectroscopy indicated that the obtained CDs are amorphous in nature. The presence of various functional groups on the surface of CDs were identified by Fourier transform infrared (FTIR) spectra. The optical characteristics of Cm-CDs were studied by UV-Visible spectroscopy and photoluminescence spectroscopy. Cm-CDs demonstrated strong excitation-dependent fluorescence, good solubility, and effective penetration in to the Vigna radiata root cells with multicolor luminescence, and addressed autofluorescence issues. Additionally, a comparative analysis determined the optimal concentration for high-resolution, multi-color root cell imaging, with Cm-CD2 (2.5mg/ml) exhibiting the highest photoluminescence (PL) intensity. These findings highlight the potential of Cm-CDs in enhancing direct endocytosis and overcoming autofluorescence in plant cell imaging, offering promising advancements for cell biology research. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Bio-waste derived multifunctional carbon dots for white light generation, forensic and antibacterial applications
The synthesis of multi-colour emitting solid-state fluorescent (SSF) carbon dots (CDs) is a challenging task due to the phenomenon of aggregation-induced self-quenching. However, this study presents an efficacious method to synthesize CDs from the sap stain of the cupressus lusitanica tree (cl-CDs) via a simple one-step microwave treatment. The resulting SSF CDs exhibited a particle size of approximately 3 nm, high stability, and remarkable efficacy in light conversion when coated on a UV light emitting diode (UV LED). The ensuing coating generated white light with CIE colour coordinates of (0.33, 0.34) and a high luminescence efficiency of approximately 671 L/W. The fluorescence capabilities exhibited by the cl-CDs in response to 254 nm and 365 nm UV light excitation make them an ideal choice for developing fluorescent inks to prevent counterfeiting. Moreover, the study investigated the notable fluorescence properties of cl-CDs as a luminescent fingerprint powder for the recognition of latent fingerprints on various surfaces. Additionally, the antibacterial potential of cl-CDs was evaluated against gram-positive and gram-negative bacteria, where the cl-CDs were utilized as an antibacterial dusting powder for fluorescent imaging of latent fingerprints on different substrates. Therefore, we believe that our present work offers a plethora of exciting possibilities for the multifunctional application of SSF green CDs with significant implications in white light generation, counterfeiting prevention, forensic applications, and healthcare. 2024 Elsevier B.V. -
Antibacterial Effect of Phosphorous-Doped Carbon Nanomaterial Derived from Alstonia Venenata
Antibiotics have been widely used as fundamental medicine for several decades to treat various bacterial infections. However, bacteria develop different mechanisms to defeat the action of antibiotics, which has become a significant issue that endangers infectious therapy. To reduce the consumption of antibiotics and thus combat the increasing antibiotic resistance, it is necessary to implement safe and effective alternatives to conventional antibiotics. Though nanomaterials have become an emerging hope in infectious treatments, they have limited application due to aggregation, toxicity issues, and problems related to their dispersibility. However, carbon nanomaterials (CNMs) offer high solubility, biocompatibility, and minimum toxicity with their inherent antibacterial properties. The selection of natural precursors as the carbon source is an eco-friendly and economical route for synthesizing antibacterial carbon nanomaterials. In the present work, fluorescent CNMs have been synthesized by the hydrothermal treatment of Alstonia venenata leaf extract. The antibacterial capability of the bare extract (AVE), hydrothermally treated extract (AVH), AVH doped with nitrogen (N-AVH), and AVH doped with phosphorous (P-AVH) are tested against gram-positive Staphylococcus aureus (S. aureus) and gram-negative Escherichia coli (E. coli) bacteria. Except for P-AVH, all other samples showed nontoxicity towards the tested bacterial species. In contrast, P-AVH inhibited bacterial growth with minimum inhibitory concentration (MIC) values of 2.5 and 2mg/ml on S. aureus and E. coli, respectively. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Nanocomposites in Combating Antimicrobial Resistance
Extensive and improper usage of antibiotics has resulted in the outbreak of multidrugresistant microorganisms and increasing antimicrobial resistance (AMR), which has become a significant threat to global health and health care. Resistant microorganisms adapt various resistance mechanisms like modifying the structure of antibiotics, altering the target, inhibiting the internalization of antibiotics, ejection of antibiotics from bacterial cells, etc. By lowering or completely disabling the efficacy of antibiotics, AMR may become a primary cause of mortality if left unattended. Developing effective antiresistance strategies to combat AMR is an urgent need of time. Nanomaterials have great potential to inactivate pathogens, and their mechanism of antimicrobial activity is different from antibiotics. With these unique mechanisms of antimicrobial action, nanomaterials are less prone to develop AMR. Developing nanocomposites can provide synergistic effects to improve the properties and strengthen the antimicrobial capability of individual nanomaterials. In this chapter, contemporary developments in the application of antimicrobial composites such as carbon nanocomposites, metallic nanocomposites, nonmetallic nanocomposites, metalloid nanocomposites, polymer nanocomposites, ceramic nanocomposites, and their hybrid forms to prevent the evolution of AMR will be discussed. The current research direction, prospects, and possible strategies to explore nanocomposites as potent antimicrobial agents to conquer AMR will be highlighted. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Carbon dots-Zno/TiO2 ternary nanocomposite as a proficient material to enhance the performance of natural DSSC
A novel sustainable approach for enhancing the efficiency of dye-sensitized solar cells (DSSCs) involves the utilization of a combination of ZnO and carbon dots (CDs) derived from Citrus medica fruit extract, along with microwave-synthesized TiO2 nanoparticles for the preparation of the photoanode. Natural dyes such as Hibiscus rosa-sinensis and Allium Cepa peel are employed as sensitizers to reduce production costs. This co-activation method has demonstrated a significant improvement in the output parameters of the devices. Notably, the photoanode co-activated with ZnO-CD composite (ZnO-CD/TiO2) exhibits the most favorable output parameters when combined with Hibiscus rosa-sinensis dye (open circuit voltage (Voc) = 0.80 V, short circuit current density (Jsc) = 6.62 mA/cm2, fill factor (FF) = 64.20 %, photo conversion efficiency (PCE) = 3.40 %) and Allium Cepa peel dye (Voc = 0.81 V, Jsc = 6.79 mA/cm2, FF = 65.70 %, PCE = 3.61 %). When paired with Allium Cepa dye, the CD modified photoanode (CD/TiO2) offers Voc = 0.73 V, Jsc = 6.64 mA/cm2, FF = 61.27 % and PCE = 2.97 %. Similarly, when combined with Hibiscus rosa-sinensis dye, the output parameters of the CD/TiO2 photoanode are Voc = 0.72 V, Jsc = 6.54 mA/cm2, FF = 64.4 % and PCE = 3.03 %. In comparison to all tested devices, the unmodified photoanode (TiO2) displayed the lowest performance, with parameters such as Voc = 0.59 V, Jsc = 6.45 mA/cm2, FF = 52.5 %, PCE = 2.10 % using Allium Cepa peel dye, and Voc = 0.66 V, Jsc = 6 mA/cm2, FF = 51.60 %, PCE = 2.04 % using Hibiscus rosa-sinensis dye. Furthermore, the co-activation process has been shown to enhance the stability of the devices. While the unmodified photoanodes ceased to operate after eight days, the ZnO-CD composite co-activated photoanodes retained their initial efficiencies up to 61.50 % and 68.53 % with the Allium Cepa peel dye and Hibiscus rosa-sinensis dye, respectively. Therefore, this study underscores the potential of the synthesized composite material in enhancing the performance of natural DSSCs. 2024 Elsevier Ltd -
Cocos nucifera L.-derived porous carbon nanospheres/ZnO composites for energy harvesting and antibacterial applications
Carbon nanomaterials (CNMs) have been the subject of extensive research for their potential applications in various fields, including photovoltaics and medicine. In recent years, researchers have focused their attention on CNMs as their high electrical conductivity, low cost, and large surface area are promising in replacing traditional platinum-based counter electrodes in dye-sensitized solar cells (DSSC). In addition to their electrical properties, CNMs have also displayed antibacterial activity, making them an attractive option for medical applications. The combination of CNMs with metal oxides to form composite materials represents a promising approach with significant potential in various fields, including energy and biology. Here, we introduce porous carbon nanospheres (PCNS) derived from Cocos nucifera L. and its ZnO composite (PCNS/ZnO) as an alternative material, which opens up new research insights for platinum-free counter electrodes. Bifacial DSSCs produced using PCNS-based counter electrodes achieved power conversion efficiencies (PCE) of 3.98% and 2.02% for front and rear illumination, respectively. However, with PCNS/ZnO composite-based counter electrodes, the efficiency of the device increased significantly, producing approximately 5.18% and 4.26% for front and rear illumination, respectively. Moreover, these CNMs have shown potential as antibacterial agents. Compared to PCNS, PCNS/ZnO composites exhibited slightly superior antibacterial activity against tested bacterial strains, including gram-positive Bacillus cereus (B. cereus) and Staphylococcus aureus (S. aureus), and gram-negative Vibrio harveyi (V. harveyi) and Escherichia coli (E. coli) with MIC values of 125, 250, 125, and 62.5g/ml, respectively. It is plausible that the outcomes observed were influenced by the synergistic effects of the composite material. Graphical abstract: (Figure presented.) The Author(s), under exclusive licence to Korean Carbon Society 2024. -
Challenging the Representation of the HumanAnimal Relationship in The Elephant Whisperers
[No abstract available] -
Fluorescent carbon nanoparticle hybrids: synthesis, properties and applications
The development of materials in nanoscale morphologies with novel compositions is one of the major focuses of nanoscience and technology, as these materials are imbibed with unique properties that make them suitable for specific applications in a large variety of fields. Combining two or more chemically distinct constituents into a single nanostructure helps to attain desirable attributes of physical and chemical responses that can be efficiently utilized for specific applications. Hybrid nanomaterials constituted as a combination of multiple components into single nanostructures are known to showcase the properties of the individual components in tandem or synergy. Novel functionalities are also known to arise from integrating Fluorescent carbon nanoparticles (FCNPs) with other counterparts. FCNPs, when combined with other materials to form nanohybrids, provide copious functional attributes due to their inherent properties and the augmentation in properties due to the presence of the other materials. Integrating hybrid counterparts with FCNs improves the functional properties, which can be utilized for various applications such as photocatalysis, bioimaging, bio/chemo sensing, and many more. Herein we present an overview of recent and relevant works related to the synthesis, properties, and applications of fluorescent carbon nanoparticle (FCNP) hybrids. Various synthetic routes of FCNP hybrids via physical and chemical methods are summarized. The properties of the hybrid systems and the influence of hybridization on the properties are discussed. Applications of FCNP hybrids in various fields are also discussed in detail. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
In vitro Analytical Techniques as Screening Tools to investigate the Metal chelate-DNA interactions
Deoxyribose nucleic acid (DNA) is found to be the most efficient pharmacological target of many synthetic molecules which are deemed as potential drugs with clinical applications. DNA binding agents are known to regulate several cell functions (gene expression and replication) by adopting various protocols which include the annihilation of the cell membrane, interruption in protein synthesis, and irreversible binding to cell receptors. Recently, several studies have explored fundamental aspects of drug-DNA interactions, providing new insights into the driving forces that render the formation of the drug-DNA complex. In order to study and understand these biologically important reaction mechanisms, several screening tools have been devised and the specificity of drug molecules binding to DNA were studied in detail. This review will discuss the utilization of various analytical tools which include UV-vis spectroscopy, fluorescence spectroscopy, circular dichroism, viscosity measurement, Raman spectroscopy, cyclic voltammetry, and DNA fragmentation assay used for studying drug binding mode and the mechanism involved. 2023 Wiley-VCH GmbH. -
Question-answering versus machine reading comprehension: Neural machine reading comprehension using transformer models
Teaching machines to read and learn natural language documents and seek answers to questions is an elusive task. Traditional question-answering systems were based on rule-based and keyword-searching algorithms without proper natural language understanding. Machine reading comprehension (MRC) belongs to reading comprehension models and facilitates the machines learning from context. MRC can infer the answer from the context through language understanding. Neural machine reading comprehension has built reading comprehension models by employing the advancements of deep neural networks that have shown unprecedented performance compared to other non-neural and feature-based models. The article comprises the MRC span extraction tasks using Transformer models and, in addition, the illustration of the MRC tasks, trends, modules, benchmarked datasets, implementation, and empirical results. 2024 selection and editorial matter, Muskan Garg, Sandeep Kumar and Abdul Khader Jilani Saudagar chapters. -
Unveiling the potential of large language models: Redefining learning in the age of generative AI
Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are transforming industries by fostering innovation, automating tasks, and enhancing creativity. By enabling personalized user interactions, sophisticated content creation, and advanced data analytics, they are revolutionizing industries such as healthcare, education, and customer service. As these technologies evolve, they can fundamentally change communication and decision-making processes and incorporate AI into everyday life. The objective of this book chapter is to examine the architecture and components, features, functionality, domain-specific applications, recent advances, and future developments of LLMs. Ongoing research aims to reduce biases, increase energy efficiency, and facilitate interpretation. As LLMs continue to evolve, they have the potential to transform many industries, including education, customer service, content creation, and more. As a result, they will be essential for the development of future AI-powered applications. 2024, IGI Global. All rights reserved. -
A Novel Approach for Machine Reading Comprehension using BERT-based Large Language Models
Teaching machines to learn the information from the natural language documents remains an arduous task because it involves natural language understanding of contexts, excerpting the meaningful insights, and deliver the answer to the questions. Machine Reading Comprehension (MRC) tasks can identify and understand the content from the natural language documents by asking the model to answer questions. The model can extract the answer from the given context or other external repositories. This article proposes a novel Context Minimization method for MRC Span Extraction tasks to improve the accuracy of the models. The Context Minimization method constitutes two subprocedures, Context Reduction and Sentence Aggregation. The proposed model reduced the context with the most relevant sequences for answering by estimating the sentence embedding between the question and the sequences involved in the context. The Context Reduction facilitates the model to retrieve the answer efficiently from the minimal context. The Sentence Aggregation improves the quality of answers by aggregating the most relevant shreds of evidence from the context. Both methods have been developed from the two notable observations from the empirical analysis of existing models. First, the models with minimal context with efficient masking can improve the accuracy and the second is the issue with the scatted sequences on the context that may lead to partial or incomplete answering. The Context Minimization method with Fine-Tuned BERT model compared with the ALBERT, DistilBERT, and Longformer models and the experiments with these models have shown significant improvement in results. 2024 IEEE. -
The Efficiency of Ensemble Machine Learning Models on Network Intrusion Detection using KDDCup 99 Dataset
With the advent of data communication the increased usage of the technologies results in network intrusions and associated attacks. Consequently, the data violation rates are increased abundantly and that sacrifices Confidentiality, Integrity and Availability. This article focused on the network Intrusion Detection System (IDS) that detects various attacks and types. Machine learning (ML) has the potential to spot known-experience and Zero-day attacks. Consequently, the article has considered ML and ensembled models for the various attack classification. The major contributions of the current article are 3-fold. Initially, to understand the relevance and sufficiency of the dataset through exploratory data analysis. Second, the comprehensive understanding of the various attacks, its nature, various types and classifications and finally, the empirical analysis of the dataset through the potential of various ML models. The article utilized various discriminative models for the execution and all of the models have shown better accuracy. The tree-based ensemble model, Random Forest has outperformed the rest of the models with higher accuracy in the training and testing samples of 99.997 % and 99.969 % respectively. 2023 IEEE. -
A Low-Complexity Multiplier-Less Filter Bank Based on Modified IFIR for the SDR Channelizer
Digital filter banks are extensively used in an SDR channelizer for channelization. The objective of this research work is to design a low computational complexity FIR filter bank for generating sharp transition width channels for SDR. The design of unified and variable bandwidth channels for SDR using the proposed structure is based on the modified IFIR filter structure and cosine modulation technique (CMT). The performance of the proposed structure is demonstrated with the help of an example. The results show that the multiplier complexity of the proposed structure is less than those of other state-of-the art methods. The optimization techniques are incorporated in this work to further reduce the complexity of the proposed structure. With the help of canonical signed digit (CSD), multi-objective artificial bee colony (MOABC) and shift inclusive differential coefficients (SIDC) common sub-expression elimination (CSE) optimization, the filter used in this structure is made multiplier-less. 2024 IETE. -
Design of Reconfigurable Filter Structure Based on FRM for Wideband Channelizer?
A reconfigurable FIR bank of filters are essential for digital channelizer in wideband system. FRM is a extensively used method to generate a sharp transition width sub-bands or channels for digital channelizer. The aim of this work is to design multiple non-uniform sharp transition width FIR bank of filters with reduced number of multipliers and group delay for wideband channelizer. The design parameters of the proposed structure are evaluated in an efficient way. The proposed structure is designed based on FRM filters and exponential modulation (EM) technique. The performance of the proposed structure is illustrated with the help of an example. Result shows that the number of multipliers of the proposed structure is less compared to other existing techniques. 2022 IEEE. -
Design of Computationally Efficient FRM Based Reconfigurable Filter Structure for Spectrum Sensing in Cognitive Radio for IoT Networks
A low computational complexity FIR bank of filters are essential for spectrum sensing in wireless networks. FRM is a widely used method to generate a sharp transition width sub-bands or channels. The intention of this work is to design multiple non-uniform sharp transition width FIR bank of filter with low computational complexity for spectrum sensing in cognitive radio for IoT networks. The design parameters of the proposed structure are calculated in an efficient way. The proposed structure is designed based on the FRM filter and complex exponential modulation technique (CEMT). The performance of the proposed structure is illustrated with the help of an example. Result indicates that the number of multipliers of the proposed structure is less compared to other existing techniques. 2022 IEEE. -
Design of Computationally Efficient IFIR based Filter Structure for Digital Channelizer'
A low computational complexity digital channelizer is essential for a wide band system. FRM is a widely used method to generate a sharp transition width sub-bands or channels in a digital channelizer. The aim of this work is to design a uniform and non-uniform sharp transition width FIR filter bank with low computational complexity compared to FRM based digital channelizer. The design parameters of the proposed structure are evaluated in an efficient way. The proposed structure is designed based on IFIR filter and complex exponential modulation technique (CEMT). The performance of the proposed structure is demonstrated with the help of an example. Results show that the number of multipliers of the proposed structure is less compared to other existing methods. 2022 IEEE. -
An efficient reconfigurable band tuning filter design for channelizer in transponder satellite system
For improved performance in a variety of applications, the transponder in satellite systems must be very flexible. The channelizer-dependent transponder system significantly boosts the operation of a satellite system. When channelizing wideband input signals, a digital filter bank is typically used to extract several small sub-bands. In this research, a reconfigurable band tuning (RBT) design for the channelizer in the satellite transponder system is designed and implemented. Cosine modulation, exponential modulation and IFIR filter are the techniques behind the RBT design. The RBT design facilitates the generation of many channels enabling channelization with non-uniform narrow transition width. A number of examples are presented to illustrate how well the RBT design performs. Findings indicate that there are fewer filter coefficients in the RBT design than there are in the current approaches Effective implementation of a properly designed RBT design lowers power consumption and simplifies the hardware. 2024 The Franklin Institute