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Iron-pulsing, a novel seed invigoration technique to enhance crop yield in rice: A journey from lab to field aiming towards sustainable agriculture
Bulk fertilizer application is one of the easiest means of improving yield of crops however it comes with several environmental impediments and consumer health menace. In the wake of this situation, sustainable agricultural practices stand as pertinent agronomic tool to increase yield and ensure sufficient food supply from farm to fork. In the present study, efficacy of iron-pulsing in improving the rice yield has been elucidated. This technique involves seed treatment with different concentrations (2.5, 5 and 10 mM) of iron salts (FeCl3 and FeSO4) during germination. FeCl3 or FeSO4 was used to treat the sets and depending on the concentration of the salts, the sets were named as C2.5, C5, C10 and S2.5, S5, S10 (where C and S stands for FeCl3 and FeSO4 respectively and the numbers succeeding them denotes the concentration of salt in mM). Our investigation identified 72 h of treatment as ideal duration for iron-pulsing. At this time point, the seedling emergence attributes and activities of ?-amylase and protease increased. The relative water uptake of the seeds also increased through upregulation of aquaporin expression. The treatment efficiently maintained the ROS balance with the aid of antioxidant enzymes and increased the iron content within the treated seeds. After transplantation in field, photosynthetic rate and chlorophyll content enhanced in the treated plants. Finally, the post-harvest agro-morphological traits (represented through panicle morphology, 1000 seed weight, harvest index) and yield showed significant improvement with treatment. Sets C5 and S5 showed optimum efficiency in terms of yield improvement. To our best knowledge, this study is the first report deciphering the efficacy of iron-pulsing as a safe, cost effective and promising technique to escalate the yield of rice crops without incurring an environmental cost. Thus, iron-pulsing is expected to serve as a potential tool to address global food security in years to come. 2021 Elsevier B.V. -
Iron pulsing, a cost effective and affordable seed invigoration technique for iron bio-fortification and nutritional enrichment of rice grains
Rice being a major staple food for millions of people, it has been one of the major targets for bio-fortification and iron bio-fortification in rice has been in prime focus to address global micronutrient malnutrition. Commonly practiced methods for obtaining Fe biofortified rice includes soil amendments and foliar spray with iron salts, breeding and development of transgenic rice varieties with Fe-enriched grain are associated with impediments like high cost, labor intensiveness, sub-optimal outcome and approval for commercialization respectively. Iron pulsing technique has reportedly enhanced the carbon and nitrogen assimilation in rice seedlings, which has been translated in yield. Based on the previous findings, in the present study, we have undermined the efficacy of iron pulsing, in improving the iron content and nutritional status of rice kernel obtained from pulsed plants. The present study documents that kernel of seeds obtained from iron pulsed plants have a higher amounts of iron, carbohydrate, protein, lipid, vitamins, nutrient and anti-oxidants than that of non-treated ones. The iron localization studies revealed that iron was mostly present in the endosperm and embryo. Besides, the ferritin expression levels also validated the fact that, the treated grains have accumulated more iron. Thus, iron-pulsing can serve as a novel and propitious sustainable agricultural innovation for iron bio-fortification and improvisation of the overall nutritional value of the rice grains that is affordable, user and consumer friendly in years to come. 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
School Counseling in India : School Counselor Roles, Policy and Implementation
With a lack of comprehensive policy and literature on stakeholders perspectives and the counseling program s implementation, there is much to be known about the present status of school counseling in India. Three research questions examined in two phases were the perception of actual and preferred roles of the school counselors from the perspective of school administrators, school counselors, teachers, students, and parents; awareness and implementation of school counseling policy from the perspective of administrator and counselors; and implementation of the school counseling program. Quantitative phase I met newlineobjectives one and two using cluster sampling to select 1029 participants. School newlineadministrators and counselors completed the Survey on Knowledge and Implementation of newlinePolicies Regarding School Counseling which was developed and validated by two experts in newlinethe study. All participants completed the International Survey of School Counselor Activities (ISSCA) (Fan et al., 2018). Statistical analysis included descriptive statistics, the KruskalWallis H test, and post-hoc Bonferroni-Dunn. Qualitative phase II met objective three using purposive sampling to recruit 14 participants for a semi-structured interview. Qualitative newlinecontent analysis indicated that school counseling in India is still developing, with newlineinconsistencies in understanding the counselor s role among stakeholders. There were differences in awareness and knowledge about the responsibility of implementing school counseling policies. School counseling programs were affected by role ambiguity, stigma about mental health issues, lack of comprehensive structure to the counseling program, and lack of research and evaluation. Implications of the study are discussed. -
A study on the portrayal of women characters in Zoya Aktar's films /
Leaving behind the social fabric which has time and again labelled Indian women merely as good wives, home makers and mothers , Indian women took it in their stride to take up the duties which are essentially thought of being male only, and proved that they are equal to their male counterparts; if not better in some cases. -
Representation of print media in films /
This research is a study on Representation of print media in films. Creating awareness about the representation is one of the objectives of the study. Before forming an opinion about the representation of print media in films it is important to know what those representations represent. Today there are online newspapers and it co-exists with the traditional print media. Thus the researcher has found it more important to study the portrayal of the print media in films in the context of todays time and space. The researcher is not trying to appeal that print media should be potrayed in a certain way. The research contains analysis some films to study the representation. Researcher is not being judgemental about the representations but only investigating what is the depiction of print media, journalists and professions in films as films are a different medium from print. -
Forecasting Bitcoin Price During Covid-19 Pandemic Using Prophet and ARIMA: An Empirical Research
Bitcoin and other cryptocurrencies are the alternative and speculative digital financial assets in today's growing fintech economy. Blockchain technology is essential for ensuring ownership of bitcoin, a decentralized technology. These coins display high volatility and bubble-like behavior. The widespread acceptance of cryptocurrencies poses new challenges to the corporate community and the general public. Currency market traders and fintech researchers have classified cryptocurrencies as speculative bubbles. The study has identified the bitcoin bubble and its breaks during the COVID-19 pandemic. From 1st April 2018 to 31st March 2021, we used high-frequency data to calculate the daily closing price of bitcoin. The prophet model and Arima forecasting methods have both been taken. We also examined the explosive bubble and found structural cracks in the bitcoin using the ADF, RADF, and SADF tests. It found five multiple breaks detected from 2018 to 2021 in bitcoin prices. ARIMA(1,1,0) fitted the best model for price prediction. The ARIMA and Facebook Prophet model is applied in the forecasting, and found that the Prophet model is best in forecasting prices. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Analysing Crypto Trends: Unveiling Ethereum and Bitcoin Price Forecasts Through Analytics-Driven Weighted Moving Averages
This research meticulously analyses the performance dynamics of two paramount cryptocurrencies, Bitcoin and Ethereum, over 2,682 observations. Preliminary findings indicate a near alignment in the mean returns of both assets, with Ethereum marginally outperforming Bitcoin. Interestingly, Ethereums superior returns are accompanied by heightened volatility, underlined by its more significant standard deviation. Both cryptocurrencies manifest negative skewness, hinting at a proclivity for negative returns, with Bitcoin showing a sharper skew. Their pronounced kurtosis values attest to the potential for extreme price swings. Regarding forecasting efficacy, the Weighted Moving Average (WMA) method emerges as superior for both assets, yielding the most accurate predictions. At the same time, the Exponential Moving Average (EMA) demonstrates the highest forecast errors. Further, the Relative Strength Index (RSI) evaluation suggests Ethereum may be oversold, alluding to potential investment opportunities. In contrast, Bitcoin, with its mid-range RSI, resides in a neutral zone devoid of clear market signals. The findings shed light on the nuanced performance and forecasting landscape of these leading cryptocurrencies, offering pivotal insights for potential investors. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
An impact of AI and client acquisition strategies in real capital ventures
In the contemporary business environment, marked by rapid changes, client acquisition stands out as a pivotal factor for companies aiming at sustained growth, particularly in sectors such as finance and real estate. The ability to attract and retain clients is not only a measure of a company"s current success but also a fundamental driver for its future viability. This study focuses on Real Capital Ventures LLP, a company operating at the intersection of finance and real estate, aiming to unravel the intricacies of its client acquisition strategies. The overarching goal is to conduct an exhaustive examination of the current approaches employed by the firm and provide nuanced recommendations for refinement. By doing so, the study aspires to contribute to the enhancement of the effectiveness of Real Capital Ventures LLP"s client acquisition, ensuring its continued success in a fiercely competitive market. 2024 by IGI Global. All rights reserved. -
Multi-Model Traffic Forecasting in Smart Cities using Graph Neural Networks and Transformer-based Multi-Source Visual Fusion for Intelligent Transportation Management
In the intelligent transportation management of smart cities, traffic forecasting is crucial. The optimization of traffic flow, reduction of congestion, and improvement of theoverall transportation systemefficiency all depend on accurate traffic pattern projections. In order to overcome the difficulties causedby the complexity and diversity of urban traffic dynamics, this research suggests a unique method for multi-modal traffic forecasting combining Graph Neural Networks (GNNs) and Transformer-based multi-source visual fusion. GNNs are employed in this method to capture the spatial connections betweenvarious road segments and to properly reflect the basic structure of the road network. The model's ability to effectively analyse traffic dynamics and relationships between nearby locations is enhanced by graphsrepresenting the road layout, which also increases theoutcome of traffic predictions. Recursive Feature Elimination (RFE) is employed to improve the model's feature selection process and choose the most pertinent features for traffic prediction, producing forecasts that are more effective and precise. Utilizing real-time data, the performance of the suggested strategywasassessed, enabling it to adjust to shifting traffic patterns and deliver precise projections for intelligent transportation management. The empirical outcomes show exceptional results ofperformance metrics for the proposed approach, achieving anamazing accuracy of 99%. The resultsshow that the suggested techniques findings have the ability to anticipate traffic and exhibit a superior level of reliability whichsupports efficient transportation management in smart cities. The Author(s), under exclusive licence to Intelligent Transportation Systems Japan 2024. -
Camera-based tri-lingual script identification at word level using a combination of SFTA and LBP features
This paper exhibit the identification of scripts at word level from the camera-based multi-script document images. The Camera-based document images suffer from noise while capturing documents and scripts are challenging to identify when noise is present. The scripts like Tamil, Punjabi, English, Oriya, Telugu, Gujarathi, Malayalam, Kannada, Hindi, Bengali, and Urdu combinations considered. The experiment conducted on a large dataset consisting of 77,000-word images and each script has 7000-word images word images. The texture features are combined to get the highest recognition accuracy. The recognition rate is 77.94% and 82.39% from SFTA features and 89.82% and 93.94% from LBP features, by using KNN and SVM classifiers, for combined feature vector KNN has given 94.45%, and SVM has given 93.88% recognition accuracy. 2019 SERSC. -
DFT studies on D?A substituted bis-1,3,4-oxadiazole for nonlinear optical application
In the present work, we have synthesized novel D?A substituted bis-1,3,4-oxadiazoles derivatives and studied nonlinear optical properties using density functional theory (DFT). The FT-IR and 1H NMR data confirmed the structure of the molecule. The HOMOLUMO, energy band gap, molecular electrostatic potential map, and global chemical reactivity descriptors were estimated using the DFT and TD-DFT with B3LYP, CAM-B3LYP and WB97XD using 6-31G (d) levels basis set and results show all synthesized molecules have excellent chemical hardness, chemical potential, excellent chemical strength, and excellent chemical stability. The static and dynamic linear polarizability, first hyperpolarizability and second hyperpolarizability components were estimated using time-dependent density functional theory. The first-order hyperpolarizability ? (2x; x, x) computed at a wavelength of 1064nm was found to be 55 times greater than the urea molecule. The dynamic molecular second-order hyperpolarizabilities ? (?3x;x,x,x) suggested good nonlinear properties for the designed molecule. The Author(s), under exclusive licence to The Optical Society of India 2024. -
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Identifying 'Self' Through Society : A Socio-Psychological Perspective of A Song of Ice and Fire
The Socio-Psychological Character Analysis Model (SPCAM) is developed to analyse complex literary characters. It helps readers of Literature understand the characters psyche and behaviour by keeping in mind their social background and influences. To develop the literary model, SPCAM, concepts from two theories are synthesised, which are Symbolic Interactionism (SI) and Cognitive newlineBehavioural Theory (CBT). The common threads between the two theories weave them together, and the complementary threads strengthen the developed model. SPCAM studies how characters make meaning while interacting with themselves and others in the society, while also identifying and evaluating their thoughts and beliefs. Using SPCAM helps the user to systematically extract necessary data newlinefrom the text, tabulate it according to the parameters set by the model, and examine the character s internal and external factors, as provided in the text, leading to a comprehensive review of the character and a character conceptualisation. SPCAM helps the users to substantiate their claims about a newlinecomplex character by helping them be more methodical and thorough. The introductory chapter establishes the need and scope of the research. It reviews the benefits of collaborating with Social Psychology for a literary analysis. After which, it defines the theories merged to build the model. The newlinedeveloped model, SPCAM is then explained in detail. This is followed by the rationale for using fantasy fiction, a brief about the author, George R.R. -
KnowSOntoWSR: Web Service Recommendation System Using Semantically Driven QoS Ontology-Based Knowledge-Centred Paradigm
Web services have significantly expanded and become a key enabling technology for online data, application and resource sharing. Designing new methods for efficient and reliable web service recommendation has been of tremendous importance with the growing usage and prominence of web services. It would be ideal for a system to suggest online services that are in line with consumers preferences without requesting specific query information from them. Quality of Service (QoS) is vital for characterising non-functional aspects of Web services as they become more prevalent and widely used on the World Wide Web. The KnowSOntoWSR framework, which is built on a knowledge-driven and semantically inclined model that adheres to QoS ontology, is proposed in this research. AWS and WebSphere are employed as knowledge tags, and the powerful machine learning classifier XGBoost is applied. The features and recommendations are computed using the Twitter semantic similarity. The proposed framework outperforms the baseline models estimates with an accuracy of 95.94% and average F-measure of 95.93%. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Emotional Inhibition and Personality as Predictors of Anxiety and Depression in Young Adults
Purpose: Anxiety and depression have been major contributors to the global burden of disease, and the impact has been exacerbated following the COVID-19 pandemic. Therefore, the aim of this study was to understand the association between emotional suppression and the introverted-extraverted dimension of personality in young people and anxiety and depression. Method: Participants were 152 Indian females between the age group of 18-25 years who provided basic demographic details and completed three questionnaires via a google form. Findings: Results described a significant negative correlation of anxiety r (152) = .500, p <0.01and depression r(152)=.471, p <0.01 with emotional inhibition. There was also a significant positive correlation of anxiety r (152) = .288,p < 0.01 and depression r(152)= .288, p <0.01 with personality. While Emotional inhibition emerged as a significant negative predictor of anxiety (R2= .250) as well as of depression (R2=.222), personality (R2=.243) emerged as a significant predictor of depression. Conclusion/Value: Contrary to popular belief, the results of this study suggest that anxiety and depression are inversely related to emotional inhibition. It restores the complexity of emotions and the need to investigate their role in various pathologies. These findings provide an initial basis for further investigation into the role of emotional expression and suppression in the Indian population. 2024 RJ4All. -
A comprehensive survey on machine learning techniques to mobilize multi-camera network for smart surveillance
Deploying a web of CCTV cameras for surveillance has become an integral part of any smart citys security procedure. This, however, has led to a steady increase in the number of cameras being deployed. These cameras generate a large amount of data, which needs to be further analyzed. Our next step is to achieve a network of cameras spread across a city that does not require any human assistance to detect, recognize and track a person. This paper incorporates various algorithmic techniques used in order to make surveillance systems and their use cases so as to enable less human intervention dependent as much as possible. Even though many of these methods do carry out the task graciously, there are still quite a few obstructions such as computational resources required for model building, training time for the models, and many more issues that hinder the process and hence, constrain the possibility of easy implementation. In this paper, we also intend to shift the paradigm by providing evidence toward the use of technologies like Fog computing and edge computing coupled with the surveillance technology trends, which can help to achieve the goal in a sustainable manner with lesser overheads. 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature. -
Parental Perspectives on Stress and Challenges in Raising Autistic Children: A Meta-Synthesis
Raising autistic children can be challenging, and the current meta-synthesis explores the stress and challenges the parents encounter across life domains. Database searches (JSTOR, ProQuest, EBSCO, PsycINFO, and Google Scholar) were done using the SPIDER method, and 463 articles published between 2011 and 2021 were reviewed. The meta-synthesis adhered to the PRISMA guidelines and included 28 eligible studies centered on stress in parents of children up to the age of 12 years diagnosed with autism. This comprehensive analysis encompassed a collective participant pool of n-505 individuals. Eight stressors were derived using the line of argument synthesis method, which include parental stress due to emotional impact, diagnosis process, social stigma, financial aspects, work-life balance, lack of resources and social support, marital life, and academic setting. Multiple stressors exert a combined effect of individual and systemic factors across domains of life, leading to parental stress. Interventions must be designed considering the complex nature of the parental stress and its interaction with the environment. Psycho-education for awareness and empowerment contribute to parental well-being. The Author(s), under exclusive licence to Springer Nature India Private Limited 2024. -
Surviving Under Stress: Exploring Zea mays Adaptive Responses to Cadmium Toxicity and Mitigation StrategiesA Review
Cadmium (Cd) toxicity poses a significant threat to Zea mays, disrupting its normal physiological functions and metabolic processes. This chapter summarises current studies on the sources of contamination, Cd intake mechanisms, and the effect of Cd toxicity on critical physiological systems in maize. It then thoroughly investigates Zea mays physiological and adaptive responses to Cd toxicity. The section outlines how Cd inhibits vital metabolic processes, such as photosynthesis and the absorption of nutrients uptake in maize plants, leading to a reduction in biomass, yield, and growth. The adverse impacts on plant growth and development are amplified by anatomical changes brought on by Cd exposure, such as modifications to the roots and leaves. Furthermore, a thorough examination of biochemical modifications is conducted, such as adjustments to protein composition, glucose metabolism, and amino acid levels. The chapter additionally examines how enzymatic activity responds to Cd stress, focusing on modifications in the activity of enzymes involved in antioxidants and metabolism. Under the influence of Cd toxicity, maize plants display a range of intricate adaptive responses. These include upregulation of genes linked to the production of ethylene and the synthesis of peptides that bind metals, such as phytochelatins. The study covers the effectiveness of several mitigation techniques employed to reduce Cd accumulation and improve Cd tolerance in maize crops. These techniques include microbial remediation, phytohormone administration, biostimulant treatments, and designed nanoparticles and mineral ions. With everything considered, this chapter offers insightful information about Zea mays physiological and adaptive responses to endure and mitigate the impact of cadmium toxicity. To ensure sustainable maize production and food security in areas polluted by Cd, it is essential to understand these mechanisms and create appropriate mitigation techniques. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Stress strain characteristics of reinforced hollow concrete block masonry melded with mesh reinforcement
Plain Masonry similar to unreinforced concrete, is resilient in compression and weak in tension. Masonry gains strength with age similar to concrete. Inspite of these resemblances, there exist numerous differences between masonry and concrete. The major difference is the regular pattern of horizontal joints(known as bed joints) at specific intervals along the height of walls introduce due to the method of construction of masonry. These bed joints make masonry a direction dependent material possessing orthotropic properties, unlike concrete which is usually regarded as isotropic atleast in the elastic range. Mechanical properties such as compressive strength, tensile strength, flexural strength are a pre-requisite as part of the design of masonry walls. The present study deals with the experimental study to evaluate the mechanical properties of hollow concrete block masonry specimens for varying cement mortar proportions melded with mesh reinforcement at bed joints. Parameters such as compressive strength, modulus of elasticity, failure pattern have been studied and compared for reinforced and unreinforced hollow concrete block prisms. The study showed higher compressive strength and improved elastic modulus for specimens with higher grade of mortar Published under licence by IOP Publishing Ltd.