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Effect of heavy metals on germination, biochemical, antioxidant and withanolide content in Withania somnifera (L.) Dunal
Withania somnifera (L.) Dunal., commonly referred to as Ashwagandha, is a medicinal plant from the solanaceae family with a wide range of pharmacological properties. W. somnifera is a rich source of withanolides, such as withanolide A, withanolide B, withanolide D, withaferin A and many others which are attributed for a large number of pharmacological activities. In the present study, the impact of heavy metals such as cadmium (Cd), mercury (Hg) and lead (Pb) has been assessed on the growth, biochemical parameters, antioxidant activity and withanolide A and withaferin A content of W. somnifera. The seeds of W. somnifera were germinated in cocopeat and treated with different concentrations of Cd (20-200 ppm), Hg (10-100 ppm) and Pb (200-2000 ppm) for 21 days. There have been substantial differences between the heavy metal-treated plants and the control plants with the lowest germination of 20% observed in the plants treated with 2000 ppm Pb. The selected metals inhibited vegetative growth with lowest length of 3.07cm and lowest biomass of 0.74g in 180 ppm Cd and 200 ppm Cd treated plants respectively. With the addition of heavy metals, biochemical parameters like protein, carbohydrate, chlorophyll, total phenol, flavonoid and proline content varied significantly and showed metal tolerance by exhibiting antioxidant activity at lower concentrations. The metal accumulation occurred in a dose-dependent manner with highest Cd accumulation of 14.30mg kg?1, Hg accumulation of 42.45mg kg?1, and Pb accumulation of 217.46mg kg?1 of dry biomass of the plants. The withanolide content increased up to a specific metal concentration and decreased with a further increase in heavy metal concentration. The seeds treated with 1200 ppm of Pb showed the highest withanolide A content of 1.7mg g?1 dry weight (DW), and the seeds treated with 80 ppm of Cd showed the highest withaferin A content of 3.2mg g?1 DW. 2023 Horizon e-Publishing Group. All rights reserved. -
Effect of heavy metals on germination, biochemical, and L-DOPA content in Mucuna pruriens (L.) DC.
Mucuna pruriens (L.) DC. is a medicinal plant with a wide range of pharmacological properties that have been used in various medicinal preparations for centuries. M. pruriens is a rich source of levodopa (L-DOPA), mainly used to treat Parkinsons disease. The present study investigates the impact of heavy metals such as cadmium (Cd), mercury (Hg), and lead (Pb) on the growth parameters and biochemical characteristics, including the L-DOPA content of M. pruriens. The seeds of M. pruriens were treated with different concentrations of Cd (0250 ppm), Hg (0250 ppm), and Pb (02000 ppm) for 21 days. On exposure to heavy metals, the germination %, the vegetative growth, and the biochemical characteristics such as the protein, carbohydrate, chlorophyll, total phenol, flavonoid, and proline content varied significantly in the heavy metal-treated plants when compared to control. It was also observed that the L-DOPA content increased with increased metal concentration and then decreased further with higher concentration of metals. The metal accumulation increased with the increase in the metal concentration. The seeds treated with 1000 ppm of Pb showed the highest L-DOPA content compared with control and other treatments. 2022 Banadka and Nagella. -
Biotechnological approaches for the production of camptothecin
Abstract: Camptothecin (CPT), an indole alkaloid popular for its anticancer property, is considered the third most promising drug after taxol and famous alkaloids from Vinca for the treatment of cancer in humans. Camptothecin was first identified in Camptotheca acuminata followed by several other plant species and endophytic fungi. Increased harvesting driven by rising global demand is depleting the availability of elite plant genotypes, such as Camptotheca acuminata and Nothapodytes nimmoniana, crucial for producing alkaloids used in treating diseases like cancer. Conservation of these genotypes for the future is imperative. Therefore, research on different plant tissue culture techniques such as cell suspension culture, hairy roots, adventitious root culture, elicitation strategies, and endophytic fungi has been adopted for the production of CPT to meet the increasing demand without affecting the source plants existence. Currently, another strategy to increase camptothecin yield by genetic manipulation is underway. The present review discusses the plants and endophytes that are employed for camptothecin production and throws light on the plant tissue culture techniques for the regeneration of plants, callus culture, and selection of cell lines for the highest camptothecin production. The review further explains the simple, accurate, and cost-effective extraction and quantification methods. There is enormous potential for the sustainable production of CPT which could be met by culturing of suitable endophytes or plant cell or organ culture in a bioreactor scale production. Also, different gene editing tools provide opportunities for engineering the biosynthetic pathway of CPT, and the overall CPT production can be improved. Key points: Camptothecin is a naturally occurring alkaloid with potent anticancer properties, primarily known for its ability to inhibit DNA topoisomerase I. Plants and endophytes offer a potential approach for camptothecin production. Biotechnology approaches like plant tissue culture techniques enhanced camptothecin production. The Author(s) 2024. -
Bioactive Compounds and Biological Activities of Ensete Species
Ensete, commonly known as the false banana, is a plant of the subtropical and tropical regions of Asia and Africa. Ensete has received global attention in the past decade. The various parts of the plant, such as the fruits, fruit peel, corm, pseudostem, seed, leaves, flowers, sap, and roots, have been used in traditional medicine to treat various ailments. Starch and other minor/trace components found in Ensete plants have been used as tablet binders, disintegrants, pharmaceutical gelling agents, and sustained release agents in pharmaceuticals and nutraceuticals. Ensete has been used as a staple and co-staple food by Ethiopians and has many ethnomedicinal uses. The present chapter validates the historic use of various parts of Ensete in treating ailments by providing detailed information on the phytochemicals present in the plant and discussing various biological properties such as antioxidant, antimicrobial, antidiabetic, immunomodulatory, hypolipidemic, cytotoxic, antiurolithiatic, antiestrogenic, nephroprotective, and hepatoprotective properties. Springer Nature Switzerland AG 2024. -
The role of Syzygium samarangense in nutrition and economy: An overview
Syzygium samarangense (Blume) Merr & Perry is a tropical evergreen fruit tree from the family Myrtaceae majorly cultivated in South East Asia. The crispy and juicy fruits are highly nutritious and range from deep red to white color. This underutilized fruit is eaten raw or used in making jams, jelly, juice, salad, wine making and also used in garnishing. The cultivation of this fruit has been extended to a larger area with the improvement of technology. The fruit is rich in secondary metabolites like alkaloids, terpenes, and, tannins; minerals like calcium, copper, chlorine, iron, manganese, magnesium, phosphorus, potassium, sulfur, zinc, and vitamins such as niacin, riboflavin, thiamin, and vitamin C. The bark, fruit, and flower have pharmacological properties such as antibacterial, anticancer, antidiabetic, anti-inflammation, anti mutation, antinociceptive activity, antioxidation activities, antiulcerogenic effect, and wound healing activity. The present review discusses the biology, the improved varieties of fruit, and geographic distribution of S samarangense, the cultivation and harvesting practices, pharmacological activities, the industrial applications, and the economic importance of fruit. The review also emphasizes the future outlook and strategies that can be adopted to transform this underutilized fruit into a fruit of commercial importance. 2022 SAAB -
Food Detection and Recognition Using Deep Learning - A Review
Studies show poor lifestyle choices and unhealthy eating patterns cause issues like obesity and other ongoing illnesses that raise the risk of heart attacks, such as hypertension, abnormal blood sugar levels, and diabetes. To improve this situation a lot of health apps have been built which use modern dietary monitoring systems that automatically evaluate dietary intake using machine learning and deep learning techniques rather. For these reasons indepth investigations on food detection, classification, and analysis have been conducted. Some of the top methods for automatic food recognition created have been discussed in this paper. We also propose an idea for detection of Indian food items using image classification. According to our findings of the papers we reviewed, convolutional neural networks (CNN) have been extensively been used in food detection as it has been giving better results compared to other models. We also observed that Vision transformers perform better in situations where the dataset is large and a hybrid model would give better accuracy. A review of potential applications for food image analysis, shortfalls in the area, and open issues concludes the paper. 2022 IEEE. -
Brain Tumor Detection and Classification Using a Hyperparameter Tuned Convolutional Neural Network
Brain tumor detection using MRI scans when integrated with a deep learning approach can be immensely applied in identifying the tumor at early stages, with minimum medical professional aid. This research paper aims to develop an advanced predictive model that accurately classify brain tumors as benign or malignant using MRI scans. Here, a novel convolutional neural network (CNN) model is proposed to automate tumor detection and improve diagnosis accuracy. The model used a dataset of around 7000 brain cancer data classified into 4 labels which include glioma, meningioma, pituitary, and no tumor. Data wrangling and pre-processing are then applied to unify the images into a single format and remove any inconsistencies. Further the records are segregated into train and test samples with a 70-30 split. The proposed model recorded an optimum accuracy of 94.82%, precision of 94.2%, recall value of 93.7% and f-score metric of 93.9% respectively. In conclusion, the paper concluded that the proposed model can be applied to enhance the precision of both brain tumor diagnosis and prognosis. 2023 IEEE. -
Embedding behavioral biases into robo-advisory platforms-case of UAE investors
Purpose: This study aims to identify individuals' biases while making investment decisions and explore how these biases can be incorporated into a robo-advisory platform to help mitigate these biases. This paper identifies eight investment-related behavioral biases: mental accounting, gamblers fallacy, hindsight, regret aversion, disposition, trend-chasing, loss aversion and herding. Design/methodology/approach: This study uses primary data from 263 respondents across various age groups, of which approximately 50 were wealth management professionals in the UAE. A random sampling method from probability sampling is employed to gather the primary data. The identified biases serve as dependent variables; the age and income of individuals serve as the independent variables. Findings: Age and income are significantly related to mental accounting, herding, gambler fallacy and loss aversion. Existing studies on behavioral finance demonstrate that individuals who make investment decisions are susceptible to cognitive fallacies, leading to nonrational investment decisions. Practical implications: By studying these biases affecting individuals of varying ages and income levels, wealth management professionals can tailor their financial robo-advisory services to address these biases and help clients build wealth with consistent investment. Originality/value: This study uses survey-based sampling in the context of the UAE; hence, the data and analysis represent originality. 2024, Emerald Publishing Limited. -
Green space and mental well-being research in India: An urgent need for intervention
In recent years, numerous studies have highlighted the positive impact of green spaces on mental health and overall well-being. However, a closer examination reveals a skewed green space research contribution, with developed countries taking the lead. Despite substantial burden of mental health issues, there is a noticeable dearth of green space research within India's academic landscape. In the current paper, we address this gap through a brief review that positions the scope of green space psychology (GSP) in India. We conducted the literature review using a machine learning tool called Crawling Scholar. Our review comprised 325 studies, focusing on five key parameters: the year of publication, geographical context, research design, psychological variables examined, and study population. Our findings indicate a significant body of global research on GSP, while the contribution from Indian scholarship remains negligible. Based on this discrepancy, we propose that incorporating GSP as an intervention and preventive measure could play a crucial role in addressing India's mental health challenges. By integrating traditional practices with the emerging field of GSP, we can harness the potential of green spaces to promote mental well-being. Our findings further underscore the importance of expanding research on GSP within the Indian context and emphasize the need for further investigations into its efficiency. By shedding light on the current status of GSP research in India, we aim to raise awareness among researchers, policymakers, and mental health professionals, fostering a collaborative effort to leverage the benefits of green spaces for the betterment of mental health infrastructure in India. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Study of the Balmer Decrements for Galactic Classical Be Stars Using the Himalayan Chandra Telescope of India
In a recent study, Banerjee et al. (2021) produced an atlas of all major emission lines found in a large sample of 115 Galactic field Be stars using the 2-m Himalayan Chandra Telescope (HCT) facility located at Ladakh, India. This paper presents our further exploration of these stars to estimate the electron density in their discs. Our study using Balmer decrement values indicate that their discs are generally optically thick in nature with electron density (ne) in their circumstellar envelopes (CEs) being in excess of 1013 cm-3 for around 65% of the stars. For another 19% stars, the average ne in their discs probably range between 1012 cm-3 and 1013 cm-3. We noticed that the nature of the H? and H? line profiles might not influence the observed Balmer decrement values (i.e. D34 and D54) of the sample of stars. Interestingly, we also found that around 50% of the Be stars displaying D34 greater than 2.7 are of earlier spectral types, i.e. within B0B3. 2024 Societe Royale des Sciences de Liege. All rights reserved. -
Study of transient nature of classical Be stars using multi-epoch optical spectroscopy
Variability is a commonly observed property of classical Be stars (CBe) stars. In extreme cases, complete disappearance of the H? emission line occurs, indicating a disc-less state in CBe stars. The disc-loss and reappearing phases can be identified by studying the H? line profiles of CBe stars on a regular basis. In this paper, we present the study of a set of selected nine bright CBe stars, in the wavelength range of 62006700 to better understand their disc transient nature through continuous monitoring of their H? line profile variations for five consecutive years (20152019). Based on our observations, we suggest that four of the program stars (HD 4180, HD 142926, HD 164447 and HD 171780) are possibly undergoing disc-loss episodes, whereas one other star (HD 23302) might be passing through disc formation phase. The remaining four stars (HD 237056, HD 33357, HD 38708 and HD 60855) have shown signs of hosting a stable disc in recent epochs. Through visual inspection of the overall variation observed in the H? EW for these stars, we classified them into groups of growing, stable and dissipating discs, respectively. Moreover, our comparative analysis using the BeSS database points out that the star HD 60855 has passed through a disc-less episode in 2008, with its disc formation happening probably over a timescale of only two months, between January and March 2008. 2022, Indian Academy of Sciences. -
Optical spectroscopy of Galactic field classical Be stars
In this study, we analyse the emission lines of different species present in 118 Galactic field classical Be stars in the wavelength range of 3800-9000 We re-estimated the extinction parameter (AV) for our sample stars using the newly available data from Gaia DR2 and suggest that it is important to consider AV while measuring the Balmer decrement (i.e. D34 and D54) values in classical Be stars. Subsequently, we estimated the Balmer decrement values for 105 program stars and found that ?20 per cent of them show D34 ? 2.7, implying that their circumstellar disc are generally optically thick in nature. One program star, HD 60855 shows H? in absorption - indicative of disc-less phase. From our analysis, we found that in classical Be stars, H? emission equivalent width values are mostly lower than 40 which agrees with that present in literature. Moreover, we noticed that a threshold value of ?10of H? emission equivalent width is necessary for FeII emission to become visible. We also observed that emission line equivalent widths of H?, P14, FeII 5169, and OI 8446for our program stars tend to be more intense in earlier spectral types, peaking mostly near B1-B2. Furthermore, we explored various formation regions of Ca II emission lines around the circumstellar disc of classical Be stars. We suggest the possibility that Ca II triplet emission can originate either in the circumbinary disc or from the cooler outer regions of the disc, which might not be isothermal in nature. 2021 Oxford University Press. All rights reserved. -
Affiliate Marketing and the Symbiotic Relationship in the Pharma Industry
The objective of the study is to understand the dynamic relationship between customers and the healthcare industry giants in the Indian context. The purpose revolves around how the consumer is benefitting and at the same time, how the indirect third-party affiliates also earn marginal profits along with serving the customers. The study is backed by both primary and secondary data, which were collected from 173 individuals from various fields through a questionnaire. The convenience sampling method was used to select the respondents, and the Technology Acceptance Model (TAM) was used to propose the model for the study. There exists a parallel symbiotic relationship between consumers, pharmaceutical companies, and affiliates. The application of this research can be put to use for the startups, which want to explore and excel in this industry along with the future researchers who want to forecast and study the progress of the pharma companies in the long run. The empirical evidence of this paper highlights a unique relationship between affiliates, the pharma sector, and customers, which drives customer buying behavior and a combination that has not been explored yet. The study provides a unique understanding of how feedback from customers in third-party applications can benefit and produce huge profit margins down the line. 2025 Apple Academic Press, Inc. -
Visual encoding of nudge influencers and exploring their effect on sustainable consumption among children
With the growing number of nuclear families that have a higher disposable income, and a willingness to spend for disparate reasons possibly on the only child in the family, children are unquestionably emerging as a critical market segment that marketers would do well to target. However, while marketing to children is necessary, given the current focus on sustainability, encouraging responsible consumption seems to be a prerequisite. Making children environmentally literate would thereby, significantly help in the ongoing efforts to save our planet from environmental degradation. Based on this backdrop, this study investigates the significance of encouraging children to consume 'sustainably'. Drawing upon Richard H Thaler and Cass R Sunstein's Nudge theory, along with the United Nation's Sustainable Development Goals (UNSDG -12), we employ a novel methodology to visually encode information gleaned from the extant literature. Specifically, we discuss the significance of developing sustainable habits in children and analyze the 'nudges' that motivate children to adopt sustainable habits. Additionally, we specify different nudge elements derived from the extant literature and plot them in a RADAR chart. We observe that 'simplified process' and 'ease of access' nudging have the greatest effect when delivered in school. This study has academic, managerial, and societal implications. The findings of the study would help managers to focus on the nudges in their campaigns. Research scholars and academicians could understand the significance of using the 'RADAR' chart methodology and can expand their studies in various other domains. The present study also helps to understand the extant literature and plan for future research in the domain of sustainable consumption. The findings of the study would help schools and parents understand the effective nudges that result in creating responsible consumers that would largely benefit society. 2023 The Authors -
Fine-tuning Language Models for Predicting the Impact of Events Associated to Financial News Articles
Investors and other stakeholders like consumers and employees, increasingly consider ESG factors when making decisions about investments or engaging with companies. Taking into account the importance of ESG today, FinNLP-KDF introduced the ML-ESG-3 shared task, which seeks to determine the duration of the impact of financial news articles in four languages - English, French, Korean, and Japanese. This paper describes our team, LIPIs approach towards solving the above-mentioned task. Our final systems consist of translation, paraphrasing and fine-tuning language models like BERT, Fin-BERT and RoBERTa for classification. We ranked first in the impact duration prediction subtask for French language. 2024 ELRA Language Resource Association. -
Bacha Posh: Gender Construct in Afghan Culture Examined through the Lens of Children in Literature
With the fall of the Taliban in 2001 and their return in 2021, Afghanistan has undergone drastic socio-political changes. In many families, children are introduced to the practice of Bacha Posh (dressing up like a boy), an Afghan cultural custom where girls are dressed up as boys until they are married off. Despite children being central to this practice, it has not been studied through their eyes. This article examines the custom of Bacha Posh through the childrens perspective and situates it within the current socio-political scenario of the country. A textual and cultural analysis of three literary works is carried out through a study of their child characters to examine how Afghan culture creates its own gender construct. Two are significant works of childrens literature that revolve around real-life stories of Bacha Posh Nadia Hashimis One Half from the East (2016) and Deborah Ellis The Breadwinner (2000). The third work is The Underground Girls of Kabul (2014) by Jenny Nordberg, a seminal work in the study of Bacha Posh in which Nordberg focuses on the practice of Bacha Posh and presents the voice of children. This article then goes on to study the impact of the restrictive nature of the Taliban regime on girls and its influence on the cultural custom of Bacha Posh. It demonstrates how this practice creates an unstable gender construct among children, as evidenced by the gender dysphoria that some girls experience. It thus demonstrates the impact of culture on gender through filling in the gaps between culture, literature and politics. 2023, The International Academic Forum (IAFOR). All rights reserved. -
Computationally Efficient Machine Learning Methodology for Indian Nobel Laureate Classification
A computationally efficient methodology for Indian Nobel Laureate classification is proposed in this study, emphasizing the optimization of image categorization through supervised learning techniques. Leveraging advancements in Convolutional Neural Networks (CNNs), the research aims to enhance the efficiency and precision of image classification tasks. The study utilizes Logistic Regression for dataset analysis, initially employing browser extensions for mass downloading categorized image data. Haar cascade classifiers are then used for data wrangling, focusing on facial, nose, and mouth recognition. Following this, feature engineering through wavelet transformation reduces image dimensionality, preparing the dataset for the chosen ML model, Logistic Regression. The primary focus is to simplify technology for improved image categorization. Support Vector Machines (SVM), Random Forest, and Logistic Regression are examined, with Logistic Regression emerging as the most effective model, achieving an accuracy rate of 87.5%. A thorough evaluation using Confusion Matrices reveals Logistic Regression's superior performance in classifying images of Indian Nobel laureates. A strategic up-sampling approach is implemented to address dataset inconsistencies, ensuring balanced representation across classes. The Haar wavelet transform is then applied for feature extraction, optimizing the dataset for ML models. The dataset is split into training and testing sets (80-20), and the three models are trained and evaluated for accuracy. Logistic Regression proves to be the best performer, offering insights into prominent leaders' identification. The research offers a detailed pipeline for data preprocessing, feature engineering, and model assessment, culminating in a robust image categorization system. Logistic Regression emerges as a reliable method for biographical picture identification, demonstrating superior accuracy over SVM and Random Forest. This research underscores the importance of efficient and accurate image classification methodologies for practical applications in real-world scenarios, particularly in recognizing influential leaders. 2024 IEEE. -
Optimal ordering and discounting policy for a segmented market with price and freshness dependent demand for mixed quality product
Owing to various factors, fresh produce purchased by the retailer is initially of mixed quality. A random proportion of the lot would generally have lost some freshness before being received in stock, while the remaining items would still be fresh. This calls for some discount initially for the former, and later, when the latter product is not so fresh. For demand declining with increase in selling price and decrease in freshness, this paper deals with optimal ordering and discounting policy when the lot received is of mixed quality and the market has two segments differentiated by the initial product quality sold simultaneously at widely different prices. Sufficient conditions for existence and uniqueness of optimal cycle length and the optimal discount are obtained. Sensitivity analysis reveals that increase in freshness time and proportion of initially fresh items in the lot result in increased profit rate. Copyright 2024 Inderscience Enterprises Ltd. -
Is carbon neutrality a reality for India?
India, the third-largest carbon dioxide emitter in the world, aims to achieve zero emissions by 2070. India is committed to its Panchamrit and has launched various initiatives such as green bonds, carbon credits, carbon market, investing in green hydrogen, etc. However, given the present scenario with respect to the dependency on coal-based power generation and lack of green financing, the present article assesses the different solutions and their practicality in achieving carbon neutrality. (2024), (Indian Academy of Sciences). All rights reserved. -
The Shame of Ageing During Fourth Industrial Revolution: A Thematic Analysis of Indian Adults
The Fourth Industrial Revolution (4IR), a term popularised by Klaus Schwab in 2016, connected the physical-biological and the digital world. This is an era of artificial intelligence and computational technologies suited to satiate the needs of the human race. The emphasis is also on a digital identity we have developed alongside our physical and psychological entities. Millennials and Gen Z have a cognizant grip on their digital identity and are known to use the fruits of 4IR in their everyday livelihood. However, with the advent of Industry 4.0, the generation of Baby Boomers and Gen X have had to undergo much re-learning and accommodate the newer ways of integrating digitalization in their lives. The process has brought about occupational threats and shaming related to failure to upgradation and flexibility. This article explores the influences of these social experiences on the identity and self-concept of the quinquagenarians and the sexagenarians. The article follows a qualitative method where using a thematic approach, the emerging themes from the in-depth interviews will be analyzed in detail to form a theoretical framework for shaming among the Indian Baby Boomers and Gen X. The variables in focus are adjustment, coping styles, resilience, the purpose of life, and Self-Image. The study explores the themes of Indian adults, which emerge from interviewing 46 participants, who have been associated with full-time employment and are between 77 and 59 years of age, representing the Baby Boomers, and those between 43 and 58 years of age, representing Gen X. The analysis adopts a psychoanalytic approach, where the data is interpreted using an Eriksonian lens. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.