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Genetic Diversity of Garcinia gummi-gutta and Sustainable Utilization
The chapter discusses the consequences of using Garcinia gummi-gutta, often known as Malabar Tamarind, sustainably while diving into the complex web of genetic variation inside the crop. Giving a thorough overview, the chapter starts by detailing the botanical and genetic traits of this enigmatic species, revealing the morphological quirks and genetic differences that make it distinct. Examining the range and preferred habitats helps to highlight the ecological niches that are essential to its existence. It delves intently into the complex web of phytochemicals found in various plant parts and explains their range of biological functions. A crucial component of this study is a thorough examination of the techniques used to gauge the genetic diversity of populations of G. gummi-gutta. The assessment of G. gummi-gutta's conservation status indicates that threats to the species genetic richness need to be taken seriously and quickly addressed. The difficulties in attaining sustainable use are examined in detail, offering a comprehensive grasp of the nuances related to overexploitation and conservation initiatives. This study of G. gummi-gutta offers evidence of the complex interplay in the field of botanical resources between genetic diversity, conservation, and sustainable use. 2025 Hosakatte Niranjana Murthy. -
Eco-Conscious Silver Nanoparticles via Quassia indica: Characterization and Multifaceted Applications
This research work explores the green synthesis of silver nanoparticles using Quassia indica (QI-Ag NPs), a natural plant extract, as a stabilizing and reducing agent. The synthesized QI-Ag NPs were characterized using various analytical techniques, including UV-Visible spectroscopy, X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), Transmission Electron Microscopy (HR-TEM) and Selected Area Electron Diffraction (SAED). The UV-Visible analysis revealed a characteristic peak at 430 nm, indicating the successful formation of AgNPs. XRD analysis unveiled the crystalline nature of the nanoparticles, with four distinctive peaks corresponding to the silver crystallographic planes. SEM and EDX provided insights into the morphology and chemical composition of the QI-AgNPs. Moreover, TEM and SAED elucidated the structural attributes and crystallinity of the nanoparticles. The Ag NPs exhibited a spherical structure and crystalline nature, as supported by both SAED and XRD findings. The zeta potential of QI-Ag NPs exhibited a value of-24.2 mV. The synthesized QI-Ag NPs were evaluated for their photocatalytic potential, demonstrating a remarkable 97% degradation of Crystal Violet dye. Furthermore, comprehensive studies encompassing antioxidant, antimicrobial and cytotoxicity assessments were conducted, showcasing the multifaceted applications of these nanoparticles. This research underscores the promising potential of Q. indica-mediated silver nanoparticles as environmentally benign and versatile nanomaterials. 2024 World Scientific Publishing Company. -
Novel biocompatible zinc oxide nanoparticle synthesis using Quassia indica leaf extract and evaluation of its photocatalytic, antimicrobial, and cytotoxic potentials
Prognostic research points to the necessity and relevance of revamping polluted environments. The toxic effect of textile dyes released into waterbodies can be reduced by the degradation process and alternate methods in nanotechnology are used to lessen the gravity of the situation. Compared with chemical and physical NP synthesis, plant extract-based nanoparticle synthesis is an environmentally friendly alternative method, and the use of waste leaves in this process is an added advantage. Quassia indica zinc oxide nanoparticles (QI-ZnO NPs) were synthesised in the current work employing a simple and cost-effective process using Q. indica leaf extract. The surface plasmon peak was visible in the UV-Vis absorption spectrum of the decreased reaction mixture at 346 nm. The average crystallite size of the QI-ZnO NPs was found to be 16.66 nm. The QI-ZnO NPs were found to have a stable zeta potential of ?28.4 mV. The surface morphology of the optimised QI-ZnO NPs was observed to be hexagonal using field emission scanning electron microscopy and high-resolution transmission electron microscopy. Under UV light irradiation, the photocatalytic degradation of industrial textile dyes Reactive Blue-220, Reactive Yellow-145, Reactive Red-120, and Reactive Blue-222 showed degradation efficiency of 8090%. Antibacterial and antifungal activity was assessed using well diffusion on gram-positive and gram-negative microorganisms. When administered to the A549 and MDA-MB-231 cancer cell lines, QI-ZnO NPs displayed significant anticancer activities. Limited studies in the area of plant extract-based nanoparticle synthesis mark the novelty of this attempt and this trailblazing and pioneering approach using non-toxic QI-ZnO NPs synthesised through green synthesis is futuristic and sustainable helping in effective wastewater treatment. Graphical abstract: [Figure not available: see fulltext.] 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
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Unveiling the Quassia indica derived synthesis of Co3O4/ZnO nanohybrids for efficient dye degradation and cytotoxicity assessment
While there are exciting possibilities in nanotechnology, creating environmentally safe nanoparticles with a variety of uses in photocatalysis and biomedicine continues to be a significant issue. This work addresses the gap by introducing Quassia indica leaf extract as a bio reductant and stabilizer in the green synthesis of cobalt oxide-zinc oxide nanoparticles (QI: Co3O4/ZnO NP). The synthesized nanoparticles were characterized using various techniques, including UVvisible spectroscopy, X-ray diffraction (XRD), dynamic light scattering (DLS), high resolution transmission electron microscopy (HR-TEM), selected area electron diffraction (SAED), Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FE-SEM), and energy dispersive X-ray spectroscopy (EDX). The existence of hexagonal zinc oxide and cubic cobalt oxide phases in the synthesized nanoparticles was verified by XRD analysis. The elemental composition was confirmed by EDX, which showed that oxygen, zinc, and cobalt were present. The average hydrodynamic diameter of 244.5 d. nm was found via DLS measurements, indicating well dispersed nanoparticles. Under UV light irradiation, photocatalytic activity of QI: Co3O4/ZnO NP was assessed for the degradation of textile dyes (Reactive Blue-222, Reactive Blue-220, Reactive Red-120, and Reactive Yellow-145). Phytotoxicity tests were conducted to examine the possible environmental impact of the deteriorated dye solution, revealing promising results in mitigating the detrimental impact of industrial dyes. QI: Co3O4/ZnO NP was also assessed for cytotoxicity studies in DLA and EAC cells which showed a concentration-dependent cytotoxic effect. The research outcomes emphasize the significant potential of these nanoparticles in diverse arena by offering a sustainable and efficacious resolution to the present-day problems. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025. -
Genetic Diversity of Garcinia gummi-gutta and Sustainable Utilization
The chapter discusses the consequences of using Garcinia gummi-gutta, often known as Malabar Tamarind, sustainably while diving into the complex web of genetic variation inside the crop. Giving a thorough overview, the chapter starts by detailing the botanical and genetic traits of this enigmatic species, revealing the morphological quirks and genetic differences that make it distinct. Examining the range and preferred habitats helps to highlight the ecological niches that are essential to its existence. It delves intently into the complex web of phytochemicals found in various plant parts and explains their range of biological functions. A crucial component of this study is a thorough examination of the techniques used to gauge the genetic diversity of populations of G. gummi-gutta. The assessment of G. gummi-gutta's conservation status indicates that threats to the species genetic richness need to be taken seriously and quickly addressed. The difficulties in attaining sustainable use are examined in detail, offering a comprehensive grasp of the nuances related to overexploitation and conservation initiatives. This study of G. gummi-gutta offers evidence of the complex interplay in the field of botanical resources between genetic diversity, conservation, and sustainable use. 2025 Hosakatte Niranjana Murthy. -
Novel biocompatible zinc oxide nanoparticle synthesis using Quassia indica leaf extract and evaluation of its photocatalytic, antimicrobial, and cytotoxic potentials
Prognostic research points to the necessity and relevance of revamping polluted environments. The toxic effect of textile dyes released into waterbodies can be reduced by the degradation process and alternate methods in nanotechnology are used to lessen the gravity of the situation. Compared with chemical and physical NP synthesis, plant extract-based nanoparticle synthesis is an environmentally friendly alternative method, and the use of waste leaves in this process is an added advantage. Quassia indica zinc oxide nanoparticles (QI-ZnO NPs) were synthesised in the current work employing a simple and cost-effective process using Q. indica leaf extract. The surface plasmon peak was visible in the UV-Vis absorption spectrum of the decreased reaction mixture at 346 nm. The average crystallite size of the QI-ZnO NPs was found to be 16.66 nm. The QI-ZnO NPs were found to have a stable zeta potential of ?28.4 mV. The surface morphology of the optimised QI-ZnO NPs was observed to be hexagonal using field emission scanning electron microscopy and high-resolution transmission electron microscopy. Under UV light irradiation, the photocatalytic degradation of industrial textile dyes Reactive Blue-220, Reactive Yellow-145, Reactive Red-120, and Reactive Blue-222 showed degradation efficiency of 8090%. Antibacterial and antifungal activity was assessed using well diffusion on gram-positive and gram-negative microorganisms. When administered to the A549 and MDA-MB-231 cancer cell lines, QI-ZnO NPs displayed significant anticancer activities. Limited studies in the area of plant extract-based nanoparticle synthesis mark the novelty of this attempt and this trailblazing and pioneering approach using non-toxic QI-ZnO NPs synthesised through green synthesis is futuristic and sustainable helping in effective wastewater treatment. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. -
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Secure magnetic resonance image transmission and tumor detection techniques
The transmission of important medical diagnostic, MRI (Magnetic Resonance Imaging) images are vulnerable to third party hackers who does spoofing and they are able to introduce faulty and noisy data that damage the transmission data, which hinders the proper medical diagnostics, research and credibility of labs and doctors, there is a clear lack of awareness and lack of proper security measures taken in transmission of MRI images in the present labs, hospitals and research centers. This project is helpful to reduce the problem of secure transmission of medical images. There are many algorithms which can be applied to these medical images. This project is helpful to provide good security to medical images during transmission. Tumor detection or prediction in medical science is a very complex and expensive job, which is not yet been addressed properly and no proper graphical user interface exists in an open source environment. This project is dedicated to analyze the best tumor detection from an MRI brain image after several segmentation methods such as K-means Clustering and Watershed segmentation. Security is realized considering various techniques for encryption and decryption of the image. The encryption technique finally selected after the survey was based on Rivest, Shamir & Adleman [RSA] algorithm. 2016 IEEE. -
Stock market prediction using DQN with DQNReg loss function
There have been many developments in predicting stock market prices using reinforcement learning. Recently, Google released a paper that designed a new loss function, specifically for meta-learning reinforcement learning. In this paper, implementation is done using this loss function to the reinforcement learning model, whose objective is to predict the stock price based on certain parameters. The reinforcement learning used is an encoderdecoder framework that is useful for extracting features from long sequence prices. The DQNReg loss function is implemented in the encoder-decoder model as it could provide strong adaptation performance in a variety of settings. The model can buy and sell the index, and the reward is the portfolio return after the days trading has concluded. To maximize yield the model must optimize reward function. The DQNReg loss implemented DQN network and the Huber loss DQN network is compared with the Sharpe ratio considered for return. 2024 selection and editorial matter, Arvind Dagur, Karan Singh, Pawan Singh Mehra & Dhirendra Kumar Shukla; individual chapters, the contributors. -
Stock market prediction using DQN with DQNReg loss function
There have been many developments in predicting stock market prices usingreinforcement learning. Recently, Google released a paper that designed a new loss function,specifically for meta-learning reinforcement learning. In this paper, implementation is doneusing this loss function to the reinforcement learning model, whose objective is to predict thestock price based on certain parameters. The reinforcement learning used is an encoderdecoderframework that is useful for extracting features from long sequence prices. TheDQNReg loss function is implemented in the encoder-decoder model as it could providestrong adaptation performance in a variety of settings. The model can buy and sell the index, and the reward is the portfolio return after the days trading has concluded. To maximizeyield the model must optimize reward function. The DQNReg loss implemented DQN network and the Huber loss DQN network is compared with the Sharpe ratio considered for return. 2024 The Author(s). -
Breast Cancer Survival Prediction using Gene Expression Data
Breast cancer is one of the most common forms of cancer in the world.[1]. Breast, skin, colon, pancreatic, and other 100 types of cancer have founded globally. An accurate breast cancer prognosis can save many patients from having unnecessary treatment and the huge medical costs that come with it. Multiple gene mutations can possibly transform a normal cell into a cancerous one. Genomic variations and traits have a significant effect on cancer. Genetic abnormalities caused by various circumstances drive numerous efforts to find biomarkers of breast cancer advancement. Early Detection of Cancer types is the only way to recover the patients from this acute disease. In this paper, a proposed Deep learning algorithm and Machine learning algorithms are used to predict the survival of cancer patients using clinical data and gene expression data. The Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset is split into clinical and gene data for detailed preprocessing. This proposed method gives a better understanding of the condition and assesses how effective treatment methods are by using Deep Learning and Machine Learning models on gene data. Logistic Regression is the most accurate method identified. Grenze Scientific Society, 2022. -
From data to decisions: Harnessing AI and big data for advanced business analytics
This chapter focuses on the idea of business analytics through AI and aims to address how AI has emerged as a powerful force in augmenting and replacing traditional human-computer interactions in the realm of business analytics. AI-powered analytics can uncover hidden patterns, detect anomalies, and automate decision-making processes, significantly augmenting the efficiency and accuracy of data analysis. Thus, the purpose of this chapter is two-fold. First, the chapter sheds light on business analytics, big data, and big data analytics through AI. It delves into the theories of machine and deep learning and their synergy with big data analytics. Secondly, the authors analyze a case study to substantiate our theory. ML-based prediction models using stock market data are developed to underline the significance of adopting AI-driven approaches for business analytics. 2024, IGI Global. All rights reserved. -
Isolation of Plant Growth-Promoting Bacillus cereus from Soil and Its Use as a Microbial Inoculant
Modernization has introduced intensive agricultural practices wherein the pesticides play an important role both in stabilization and in increase of agricultural products. As a consequence, humans and members of other ecosystems are exposed to increased levels of compounds that have detrimental effects on their health, thereby signifying the importance of microbial inoculants. In order to achieve this goal 7 different bacterial species were initially screened for isolation of plant growth-promoting Bacillus sp. The isolate CUAMS116 was confirmed to be Bacillus cereus through biochemical and molecular characterization. The in vitro plant growth-promoting ability of the isolate was screened through standard tests. Different concentrations of bacterial inoculant (25%, 50%, 75%, 100%) were evaluated for its plant growth promotion ability using Phaseolus vulgaris L., under pot culture conditions. At the harvest stage, the mature control plants measured 16.53cm and mean treated plant height was measured to be 27.75cm, showing a maximum percentage increase in length of 67.87%. The results suggested that the B. cereus CUAMS116 isolated in this study can be extended as a PGPM through further field trials in other plants for improving crop yield and tolerance to biotic and abiotic stresses. 2020, King Fahd University of Petroleum & Minerals. -
An investigation on structural and optical properties of reduced graphene oxide-tin oxide nanocomposite
Graphene-metal oxide composites have attracted tremendous research interest in recent days due to their unique and fascinating properties. In the present study, rGO and SnO2 were synthesized separately by modified Hummers' method and nitrate-citrate gel combustion technique respectively. One step hydrothermal method was used to prepare reduced graphene oxide-tin oxide nanocomposite of various concentrations of rGO and SnO2.The obtained samples were characterized by XRD, FTIR, Raman Spectroscopy, UV-Vis spectroscopy, SEM and TEM. The results of different characterization techniques showed the successful formation of SnO2, rGO and SnO2-rGO composites. X-ray analysis pattern indicates formation of the SnO2 nanoparticles in the graphene matrix. The size of the particles prepared is in nanoscale and was found to be 10-20 nm range. TEM images reveal the incorporation of crystalline SnO2 nanoparticles in graphene layers. Upon incorporation of tin oxide to graphene matrix, one could easily tailor the energy gap of the composite matrix. 2020 World Research Association. All rights reserved. -
Impedance, Electrical and Dielectric behaviour of Tin Oxide Nanoparticle doped with Graphite, Graphene Oxide and Reduced Graphene Oxide
Nanostructured materials have attained incredible interest in recent days due to their distinctive chemical, physical, mechanical, magnetic and optoelectronic properties. In the present study, metal nano particle (SnO2) was doped with graphite, graphene oxide (GO) and reduced graphene oxide (rGO) with various composition (1:100), (1:1) and (100:1) by weight ratio. The citrate-nitrate gel combustion method was used to prepare nanocrystalline SnO2 while GO and rGO were synthesized through modified Hummer's method. The preparation of SnO2-rGO composites was done using a one-step hydrothermal process. The electrical and structural behaviour of the composites of graphite, GO and rGO mixed with SnO2 were elucidated by the impedance analyzer in the frequency range from 10Hz to 1MHz. It is observed that the composite of SnO2 with graphite and reduced graphene oxide have similar broad characteristics while SnO2 mixed with GO is exhibiting different properties which could be attributed to the presence of oxygen functionaries. 2021 The Authors. Published by ESG. All Rights Reserved. -
Synthesis of nano-crystalline tin dioxide and its effect on calcination
Nitrate-citrate gel-combustion method was used in this study to prepare nano-crystalline tin dioxide. The samples were calcined at a temperature range of 543-1173 K. The prepared powder was characterized by SEM, TEM and X-ray diffraction. On increasing the temperature with limited supply of air (calcination), there is a systematic increase in tin content accompanied by a reduction in oxygen. The tetragonal nano tin structure formed during the process has about 20 nm in lateral size. With increase in calcination temperature, the carbon content systematically decreased. 2017, Chemical Publishing Co. All rights reserved. -
Compendium of Qubit Technologies inQuantum Computing
Quantum computing is information processing based on the principles of quantum mechanics. Qubits are at the core of quantum computing. A qubit is a quantum state where information can be encoded, processed, and readout. Any particle, sub-particle, or quasi-particle having a quantum phenomenon is a possible qubit candidate. Ascendancy in algorithms and coding demands knowledge of the specificities of the inherent hardware. This paper envisages qubits from an information processing perspective and analyses core qubit technologies. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Pendant number of graphs
A decomposition of a graph G is a collection of its edge disjoint sub-graphs such that their union is G. A path decomposition of a graph is a decomposition of it into paths. In this paper, we define the pendant number ?p as the minimum number of end vertices of paths in a path decomposition of G and determine this parameter for certain fundamental graph classes. 2018 Academic Publications. -
Date Palm: Genomic Designing for Improved Nutritional Quality
Date palm (Phoenix dactylifera L.) is one of the oldest fruit trees known where a significant amount of breeding has been carried out to improve various agronomic and nutritional characteristics. Numerous studies have been done to improve the nutritional composition and quality of the fruit due to its significant biological properties. Various strategies have been formulated for improving the agronomic characters through biofortification as well as preserving through postharvesting techniques. Modern breeding practices using molecular markers have significantly helped to identify the phenotypic, as well as genotypic, diversity for the selection of superior date palm cultivars, advanced agronomic characters like nutritional quality, disease resistance, and yield. Availability of the whole genome sequence, organellar sequence, and genetic map of date palm has helped breeders in modification and improvement of the characteristics. With the availability of bioinformatic tools and gene editing knowledge, the nutritional composition of date palm can be effectively manipulated to develop better crops along with good agronomic characters and resistance to diseases. The authors have compiled the nutritional composition of date palm fruits and detail the strategies to edit the genome and improve nutritional quality. Springer Nature Singapore Pte Ltd. 2023.