Thesis
- Title
- Thesis
Collection Items
-
Influence of Perceived autonomy SUpport and Personality Traits on Accountability of Higher Secondary School Teachers
The term Accountability, has its origin in ethics. It deals with proper behaviour, newlinebeing responsible for one s actions towards other people and agencies. It has synonyms such as transparency, liability, answerability, and expectations of account newlinegiving (Levitt et al., 2008). Every teacher must respect each student, despite of their newlinebackground, race, gender and provide ample support to achieve excellence. The teacher must teach with highest standards without bias, teacher s primary concern must be students academic excellence, and finally teacher is expected to keep up the highest level of professionalism by being respectful to parents, colleagues, and students (College, 2011). Perceived autonomy support refers to the belief of teachers that administrators or principals consider them as competent, to have freedom of choice and the experience of belongingness and supporting environment. Perceived Autonomy Support has its root in Self-determination theory founded on three core psychological needs such as competence, autonomy, and relatedness (Deci et al.,1985). Personality trait refers to a combination of characteristics that are innate as well as characteristics that are developed due to specific life experiences. John et al., (2010) have summarized all the human personality traits under the umbrella term, the Big Five (openness, conscientiousness, extroversion, neuroticism, and agreeableness). This study examines the relationship among the three major variables such as Accountability of Teachers, Perceived Autonomy Support and Personality Traits. newlineFurther it explores whether Perceived Autonomy Support and Personality Traits have newlineany significant impact on Accountability of Higher Secondary School Teachers. Thirdly it identifies significance of Accountability, Perceived Autonomy Support and Personality Traits and its components across Type of schools, Gender, Age, Marital Status, Teaching Experience, Educational Qualifications and Subjects. -
A Novel Approach for Sensitive Crop Disease Prediction Based on Computer Vision Techniques
Agriculture is a vital sector that plays an essential role in ensuring global food security, supporting economic development, and promoting environmental sustainability. Sustainable agriculture is an essential approach that aims to address the diffculties posed by conventional farming practices and ensure the long-term viability of our food production systems. Worldwide, crop leaf diseases seriously threaten food security and agricultural production. Early and accurate detection of crop leaf diseases is essential for effective crop productivity management and food prevention. Computer vision approaches offer promising solutions for automating the identifcation and prediction of crop leaf diseases. Analyzing digital images of plant leaves enables the identifcation of disease characteristics, such as discoloration, lesions, and patterns, which are often imperceptible to the naked eye. Machine Learning (ML) algorithms, such as Convolutional Neural Networks (CNN), have been widely employed in this domain to learn from large datasets of annotated images and accurately classify leaf diseases. The process of crop leaf disease classifcation using computer vision involves several stages. Initially, highresolution images of plant leaves are acquired using cameras or mobile devices. Preprocessing techniques, including image enhancement and noise reduction, are applied to improve image quality. Subsequently, feature extraction approaches extract pertinent data from the images, including texture, shape, and color. Deep Learning (DL) models are then trained and fne-tuned using these extracted features. newlineAlthough computer vision techniques have shown effective results in the classifcation of plant diseases, however, several challenges remain. Tomatoes and Potatoes newlineare widely cultivated and consumed vegetables worldwide and are a primary economic newlinesource for many countries. These sensitive plants are prone to various diseases during newlinegrowth, leading to signifcant losses in productivity and fnancial impact on farmers. -
Intersecting Ecocriticism and Gender in Selected Writings of Easterine Kire
The research study, Intersecting Ecocriticism and Gender in Selected newlineWritings of Easterine Kire, analyses the intersection of histories, identities, gender, and ecology to understand the larger context of marginalisation and newlinerepresentation. Indigenous literature often subverts Western worldviews and mainstream discourses with counter-discourse narratives by placing their stories at the centre. In recent times, literature from Indigenous societies has established a position in which Indigenous people represent, resist, newlinedecolonise, and construct their identity. The Indigenous Naga community has experienced marginalisation for decades, having suffered multiple oppressions of their history, stories, knowledge, and lack of rights; however, contemporary literary writings challenged the silencing system through writing back and representation. In her fictional works, Naga author Easterine Kire explores the possibilities of reviving and restoring the Angami Naga community and their newlinelost cultures and identities. Focusing on analysing three important themes: Peoplestories, Ecopolitics, and Gender politics, the study represents Naga histories, emerging identities, gender, and ecological concerns as interpreted in the fiction of Easterine Kire. The objective is to represent Indigenous Naga voices using fictional narratives of Easterine Kire to reclaim, revive, and redefine Indigenous culture and history from an insider s perspective. It also examines how intersecting narratives contribute to the larger context of Naga identity construction. newlineEasterine Kire s writing is a culturally conscious and decolonial strategy in newlinewhich she incorporates her community s oral tradition and storytelling in her fictional narratives. Easterine Kire s narrative engages in a deep conscious cultural revival and reinvention of her community s cultural heritage. -
A Revocable Multi-Authority Attribute Based Encryption Scheme Based On Nonlinear Access Policy
Due to the tremendous increase of data, currently individuals and organizations are increasingly opting to store their data with third-party providers as a solution to their storage issues. Ciphertext Policy Attribute Based Encryption facilitates data outsourcing by encrypting the data at the source and uploading it to a third-party storage provider with some restricted access which is mentioned using access policy. In classical Identity-based Encryption (IBE), when a data owner needs to transmit a message to a data user, they would send it together with the data user's specific identity, such as their email address. This ensures that only the intended recipient can access and read the message. The primary issue is that the data owner must possess knowledge of the identity of each user. Other than the traditional IBE, a data owner can utilize attribute-based encryption to deliver a message to a group of individuals who have the same attributes. Here, the data owner does not need to be aware of every user's identity; instead, he can send messages using the attributes and access policies that have been provided, such as which users can access this message. This research work primarily focuses on three CP-ABE aspects: access policy, number of attribute authority, and revocation. The current access policies are insecure due to their linear character, as they always calculate shares using the same linear equation. For this particular issue in this work, a non-linear secret sharing model that enhances the security of the model is proposed. For addressing the key escrow problem, a solution using multiauthority systems were introduced. These systems involve multiple attribute authorities, each responsible for holding a specific subset of attributes for each user. And access policy will be based on non-linear secret sharing scheme. In the third aspect related to revocation, this work has addressed both user and attribute revocation so that it will make this model a perfect implementation model in terms of improved security. Some of the existing approach for revocation are re-encryption, periodic updating of ciphertext instead this work used a polynomial called Lagrange polynomial which helps to address this problem in less complex and more efficient way. These features will make the proposed scheme a real model that is secure and can be implement in any organization. -
Studies on the Culture Conditions, Nutritional Value of the Black Soldier Fly, Hermetia illucens (Diptera : Stratiomyid) and its Suitability as Aquaculture Feed
The Black Soldier Fly (BSF), Hermetia illucens, has emerged as a promising newlinesolution in aquaculture due to its remarkable ability to convert organic waste into newlineprotein-rich biomass. This has garnered interest among aquaculturists seeking costeffective and sustainable alternative ingredients for aqua feed. However, fully newlineharnessing the potential of this insect requires a deeper understanding of its life cycle and nutritional composition. A key challenge in utilising BSF larvae (BSFL) for newlineaquafeed production is the lack of standardized culture systems. This study addresses this gap by establishing a comprehensive culture system using two common organic wastes, fruit waste (FW) and vegetable waste (VW), as rearing substrates. By evaluating the growth performance of BSFL reared on these substrates, the research sheds light on optimal conditions for large-scale BSF production. The study investigated the impact of FW and VW substrates on BSFL growth through a thorough analysis of growth performance, morphometric measurements and newlineScanning Electron Microscopy (SEM). Results showed that BSFL reared on FW exhibited better growth (40 days) than those reared on VW (46 days). Morphometric analysis and SEM identified five larval stages and the prepupa, pupa, and adult stages. Additionally, the study analysed the nutritional composition of BSFL at different newlinedevelopmental stages, such as Instar 3 through instar 5, prepupa and pupa, including newlineprotein, carbohydrate, lipid, amino acids and fatty acids. This provided insights into newlinehow variations in substrate impact the nutritional quality of BSFL at different stages, which is crucial for ensuring that BSFL-derived feed meets the dietary requirements of target aquaculture species. Significant differences were found in the proximate composition of the substrates (FW and VW), resulting in significant variations in BSFL nutrition. BSFL reared on FW exhibited higher nutritional content especially crude newlineprotein (54.160.64%), than those reared on VW, except for crude lipids (2.200.01%). -
Physicochemical Modifications on Fibrous Substrates for Sensing and Separation Applications
Fibers are forms of matter characterized by flexibility, fineness, and a high length-tothickness ratio, embodying properties such as large surface-area-to-volume ratio, newlinecontinuity, flexibility in surface functionalities, superior mechanical performances, ability to absorb dye and moisture, etc. Fibers can be transformed into coils, yarns, or fabrics by twisting or overlapping, resulting in fibrous substrates that are self-standing, flexible, and possessing excellent mechanical properties and large specific surface areas. The porosity, functionality, hydrophobic and hydrophilic properties, and functional characteristics for desirable applications can be achieved by various modifications of the fiber substrates. Physical (e.g., composite material blending, coating) and chemical (e.g., surface hydrolysis, chemical crosslinking) methods have been used to modify fiber substrates. These physicochemical modifications render the newlinefibers suitable for specialized applications such as food packaging, food spoilage newlinedetection, and wastewater treatment. Existing modification strategies for preparing indicators for food quality monitoring are newlinenot user-friendly, equipment-free, and cannot be used without training and expertise. Newer approaches to the modification of fiber substrates are thus essential to provide newlinesuitable indicators for household settings. There is also a requirement for straightforward methods that quantifies the color to indicate the quality of food and newlinefacilitates its use in domestic environments without personal expertise or laboratory newlinesetup. In this regard, we focused on developing simple physicochemical modifications of fibrous substrates for food-quality monitoring. In our first work, natural jute fiber was subjected to delignification to incorporate pH-sensitive anthocyanins. This indicator was used as a point-of-care colorimetric indicator for monitoring fish quality. -
A Posthuman Analysis of Human - Machine Relationship in Select American Science Fiction Films
The research A Posthuman Analysis of Human Machine Relationship in Select American Science Fiction Films attempts to foreground the emerging posthuman scenario brought about by the explosion of Artificial Intelligence (AI) in contemporary life by analysing the posthuman representations achieved by depicting AI characters and their relationship with humans in the select American science fiction films. The primary texts for the study are Stephen Spielberg s AI: Artificial Intelligence (2001), Spike Jonze s Her (2013), Mathew Leutwyler s Uncanny (2015), and Drake Doremus Zoe (2018). The research analyses the posthuman newlinerepresentations in the select films using the methodological framework of philosophical posthumanism of Francesca Ferrando with its constituent elements of post-humanism, post-anthropocentrism, and post-dualism. The term posthuman in philosophical posthumanism refers to the critique of the notion of human preserved by the Western humanistic traditions. The three constitutive elements of philosophical posthumanism, namely, post-humanism, postanthropocentrism, and post-dualism, offer a revisit of the notion of human propagated by Western humanistic traditions and offer a renewed worldview of being human in the contemporary technocentric society where nonhuman agency is being widely newlinerecognized. From an epistemological perspective, this research adds to the evolving posthuman discussions, providing a new dimension to what it means to be a human and challenging the age-old assumptions about the human condition. -
Actualizing The Inner Self : Impact of An Online Signature Strengths Intervention On Well-Being
The PERMA Theory of Well-being states that exercising signature strengths one s most newlineprominent character strengths enhances five distinct dimensions of well-being, namely, newlinepositive emotions, engagement, relationships, meaning, and accomplishment. The present study tests this theory by examining the impact of an online signature strengths intervention on each of the aforementioned dimensions of well-being and overall well-being using an explanatory sequential mixed method experimental research design. The quantitative phase of the study implemented a randomized controlled trial (RCT) of the intervention with a wait-list control newlinegroup. A total of 82 participants recorded their levels of well-being and its dimensions at pretest and post-test using a standardized tool. Out of the 82 participants, 42 participants were in the experimental group and 40 participants in the wait-list control group. A one-month followup measure of well-being was also taken among participants in the experimental group to determine the long-term effectiveness of the intervention. Focus Group Discussions (FGDs) were conducted in the qualitative phase of the study among participants in the experimental group to explore the subjective experiences and mental processes underlying the identification and utilization of signature strengths. Results demonstrated medium to large increases in all the dimensions of well-being except for the dimension of engagement which did not show a newlinesignificant increase at either time points. Qualitative findings validated the quantitative findings and revealed important mental and emotional mechanisms underlying the experience of utilizing signature strengths, thereby providing a deeper insight into the nature and working of the intervention. Findings of the study carry far-reaching implications for organizations as well as educational and healthcare institutions to empower individuals to function optimally by utilizing their inner potential and experience the peak of well-being in all domains of life. -
Fuzzy Rule-Based Multimodal Health Monitoring System Leveraging Machine Learning Techniques Using Eeg Datasets For Human Emotion And Psychological Disorders
In recent decades, machine learning and data analysis have become increasingly important in mental health for diagnosing and treating psychological disorders. One area of particular interest is the use of electroencephalography (EEG) brainwave data to classify emotional states and predict psychological disorders. This study proposed a data fusion to enhance the precision of emotion recognition. A feature selection strategy using data fusion techniques was implemented, along with a multi-layer Stacking Classifier combining various algorithms such as support vector classifier, Random Forest, multilayer perceptron, and Nu-support vector classifiers. Features were selected based on Linear Regression-based correlation coefficient scores, resulting in a dataset with 39% of the original 2548 features. This framework achieved a high precision of 98.75% in identifying emotions. The study also focused on negative emotional states for recognizing psychological disorders. A Genetic Algorithm (GA) was used for feature selection, and k-means clustering organized the data. The dataset included 707 trials and 2542 unlabeled features. Resampling techniques ensured a balanced representation of emotional states, and GASearchCV optimized Gradient Boosting classifier hyperparameters. The Elbow Method determined the optimal number of k-Means clusters, and resampling addressed class imbalance. GA parameters and gradient- boosting hyperparameters were empirically determined. ROC curves and classification reports evaluated performance, resulting in a high accuracy of 97.21% in predicting psychological disorders. The proposed system employed fuzzy logic to calculate a health score that combines the outputs of the emotional and psychological disorder monitoring models for a multimodal health monitoring system. This approach provides a more comprehensive assessment of an individual's overall mental health status. The findings suggest that the system achieved high efficiency in predicting emotions, showcasing comprehensive progress in EEG-based emotion analysis and disorder diagnosis. These advancements have potential implications for mental health monitoring and treatment, particularly with the integration of the PHQ-9 Scale and fuzzy logic. -
Non-Invasive Early and Precise Detection of Breast Tumor with Novel UWB Radar Pulse
Impulse Radio Ultra-Wideband is emerging as a superior breast cancer detection technique compared to ultrasound, magnetic resonance newlineimaging and X-ray mammography due to its high resolution, nonionizing radiation, effectiveness in dense tissues and cost-effectiveness. Radar-based Ultra-Wideband technology is a viable, non-invasive newlinetechnique for detecting breast cancer. The Ultra-Wideband signal must be safe to penetrate deep into human breast with minimal attenuation and comply with Federal Communication Commission regulations to newlineensure early, precise detection of deep-rooted malignant tumor inside newlineheterogeneous breast. In this research work, a shaped Ultra-Wideband Gaussian pulse of newlineseventh order is employed in a radar-based breast cancer detection system. A sharp transition bandpass Finite Impulse Response filter is designed in this work for safe, deep penetration and optimal transmission through the heterogeneous breast. The pulse shaper filter design has a sharp transition with a low side lobe level and can be tuned newlineto any variable center frequency. This design is suitable for shaping very short-duration pulses, achieving higher data rate and less newlineinterference issues. Also, the pulse tightly fits the Federal Communication Commission spectral mask, thus achieving higher spectral utilization efficiency and meets the signal safety standards for transmission through the breast. The shaped pulse fed to the antenna of the radar system provides higher antenna radiation efficiency and radiating power due to the concentration of power in the main lobe. This research work employs bistatic and monostatic radar systems to detect the deep-rooted and smallest formation of the malignant tumor in the breast. Tumor detection is based on the time and frequency newlinedomain analysis of the backscattered signals from the malignant tumor. These signals have higher amplitude, higher electric field intensity variations and an increase in the scattering parameter values due to the newlinepresence of tumor. -
Construction of Prime Time Television News Discussions
Studies in the western context have shown consistent observations of Television News being one of their prime modes of news and current affairs in the past. In India, watching the news has been an age-old requirement, for many reasons. English news in a non-native English-speaking country like India has encouraged citizens to learn the language, engage in focused viewership and rely on Television news for stories, news, views, and the episodic reality. Ever since news reception was transitioned to the realm of social media and new media, Television prime time news strived to be in the limelight. To understand the existence of prime time news, the study focused on two objectives : to identify constituents of communicative techniques framed in prime time news discussions of Indian English Television News Channels and to establish the role of prime time News Discussions as creators of complex news narratives. With the help of Critical Discourse Analysis (CDA) as the umbrella theory, Multimodal Discourse Analysis (MDA), and Stuart Hall s Encoding and Decoding, the research progressed to understand the ways and means to analyse news. Each of the episodic news presentations from 5 December 2017 to 13 December 2017 pertaining to prime-time news debates of Republic TV and Times Now were used. were analysed using a qualitative method of textual analysis. The manifestation of all cues on the screen were deconstructed to comprehend their existence. Each episode was connotatively derived to understand conversations and use of graphics. There are multiple findings under each of the units. On understanding the manifestation and intermingling of various units of analysis with each other, it was unanimously concluded that polarization of opinions is the key to engage a concise news narrative of the day. Whilst important news is not the source, political debates, underestimation, and complex visualization enhance the brand name of the news channel. -
On the Way to Oneself : An Existential Study of the Select Plays of Sreeja K V and Sajitha Madathil
The perennial inquiries into human identity and the purpose of existence persist as enduring mysteries, often evoking a sense of introspection and existential angst. Amidst the quest for elucidation, individuals frequently find themselves entangled in the web of maya (appearance), wherein perceptions of reality become distorted, leading to emotional responses including jealousy, greed, guilt, and disappointment. However, amidst this labyrinth of existence, philosophical frameworks such as Existentialism and Advaita Vedanta offer invaluable lenses through which to perceive and engage with these existential inquiries. Existentialism prompts individuals to confront the subjective nature of their existence and assert autonomy in defining their identities and purpose. In contrast, Advaita Vedanta seeks to transcend the illusory veil of ego and perceive the ultimate reality of the Self (atman) as indistinguishable from the eternal consciousness (Brahman). Through the exploration of these philosophical paradigms, one can embark on a journey of Self- discovery, ultimately unveiling insights into the timeless questions of human existence. It is possible to identify this kind of crisis in the lives of the characters in the selected plays of Sreeja K V and Sajitha Madathil. Therefore, this thesis examines the selected plays of twenty-first-century Malayalam playwrights Sreeja K V and Sajitha Madathil through the lens of Simone de Beauvoir's existentialism and the pramana of Advaita Vedanta. It aims to explore the concept of the Self and how certain circumstances and experiences contribute to its realisation. By analysing the protagonists of these plays, the thesis seeks to uncover the notion that the Self is not merely a product of causality but rather the observer and creator of existence itself. This investigation raises further questions regarding the manifestation of the Self in one's life and the potential for misconceptions about its nature. The plays provide insights into the interaction between worldly illusions and the true essence of the Self, prompting consideration of how individuals often conflate these realms and succumb to materialistic temptations. Additionally, the thesis explores whether negative experiences are transient and whether individuals ultimately learn to overcome them. The selected plays open up the scope to understand the interplay of illusions of the world and the Self. This exploration leads to further questions like how does the Self appear in ones life? Is the Self mistaken? How often do people superimpose these two together and fall prey to the materialistic aspects? Is it true that the negative experiences are momentary, and often, one learns to survive from those experiences? Through the application of analytical frameworks of Existentialism and Advaita Vedanta into the select plays, this research endeavours to provide insights into these inquiries. -
Pharmaceutical Tablet Uniformity Prediction Using Spectroscopy-Based Data Fusion and Machine Learning Approaches
The pharmaceutical industry is highly regulated, and every manufacturer must demonstrate the drug product's quality, safety, and efficacy before market release. Quality control plays a vital role in ensuring drug products' consistency, purity, and potency through rigorous testing of raw materials in the process and the finished stages of manufacturing. Quality risk management and process understanding are critical to maintaining quality throughout manufacturing. Quality by Design (QbD) offers a structured approach, while Process Analytical Technology (PAT) facilitates real-time monitoring to control risk of product quality. Process analyzers, multivariate methods, process control, and continuous improvement tools are part of the PAT framework that enhances process understanding and aids risk mitigation strategies. Near-infrared (NIR) spectroscopy is a commonly used analytical technique in PAT environments for both qualitative and quantitative measurements; these are real-time and non-destructive process analyzers. Chemometrics helps extract information from this chemical data using mathematical and statistical methods. With the advent of Industry 4.0, machine learning models have gained popularity in spectroscopy due to their ability to handle complex, high-dimensional data and adapt to various applications. This research introduces a systematic approach to implementing machine learning models as an alternative to traditional chemical testing in predicting the content uniformity of pharmaceutical tablets. The objective is to improve the quality of data analysis and its predictive performance. This study also outlines the importance of using manufacturing information as stratified variables in predictive modeling and spectroscopic data, or sensor fusion data. To demonstrate the effectiveness of this approach, a real-world NIR dataset developed based on various characteristics such as manufacturing scale, tablet strength, dose proportion, and coating is utilized. This real-world application of the research makes the content more relatable and interesting to the reader. This allows the seamless use of the model across different known environments as the model is trained using sensor data fusion. A comparison of Partial Least Squares regression models and machine learning Neural Network models is evaluated for the model predictability. The work also delves into selecting and optimizing appropriate hyperparameters for a chosen optimal model. It explores the impact of model performance to ensure successful implementation in the production environment and discusses various approaches in monitoring during life cycle management. -
Dynamic Offloading Technique for Latency Sensitive Iot Applications Using Fog Computing
The Internet of Things (IoT) has evolved as one of the most popular technological newlineinnovations that offers processing power to different types of entities connected to it. IoT has made traditional applications smarter and easier to use. IoT offers reliable service to different sectors such as healthcare, industrial control, agriculture, autonomous vehicles, traffic management etc. IoT nodes are generally energy-constrained and hence depend on cloud platforms for storage and analytics of generated data. The cloud provides required services for the newlineconnected applications based on pay per use policy. But cloud datacenter being at remote location fails to accommodate the time requirements of delay-sensitive IoT newlineapplications. Edge/fog computing was designed to address the demands of timesensitive IoT applications. The IoT-Fog-Cloud architecture reduces the delay and response time incurred by the IoT-Cloud model. The fog layer in the three-tier architecture is distributed in nature. Hence the latency depends on how well the underlying offloading algorithms distribute the tasks among available fog nodes. Different offloading policies are mentioned in the literature to address this issue. This work initially tries to solve the offloading problem using one of the novel newlineoffloading approaches Flamingo Search Algorithm (FSA). Later, the results obtained from FSA are fine-tuned using another metaheuristic algorithm, the Honey Badger Algorithm (HBA). Finally, both FSA and HBA are hybridized to generate the HB-FS algorithm which effectively solves the task offloading problem. The performance evaluation of the proposed approach is done with different existing metaheuristic algorithms and the evaluations show that the newlineproposed work outperforms the existing algorithms in terms of latency, average newlineresponse time and execution time. The methodology also offers a lesser degree of newlineimbalance and standard deviation than the compared approaches. -
Process Development for Mass Production of Cordycepin Using Fermentation Technology
Cordyceps is a rare and exotic medicinal genus that has been utilised for generations in traditional Chinese medicine. China, Bhutan, Nepal, the Tibetan Plateau, and the newlinenortheastern parts of India are the main areas where they may be noticed. Cordycepin newline(C10H13O3N5), an adenosine derivative generated naturally by Cordyceps militaris, has essential pharmacological effects. Cordycepin has been shown to have anti-tumor/antiproliferative, anti-metastatic, apoptosis-inducing, anti-malaria, anti-microbial, antifungal, anti-diabetic/hypoglycemic, and anti-inflammatory qualities, among other things. The scarcity of native Cordyceps spp., as well as illicit commerce and a lack of growing methods in natural habitats, limit the supply of this prized fungus for therapeutic applications. As a result, an attempt was made to standardize the technique for large-scale cordycepin manufacturing in a laboratory setting. To measure the cordycepin, analytical methods by using High performance liquid chromatography (HPLC) and Ultraviolet Visible spectroscopy (UV Spec.) were established. Furthermore, different methods were optimised and established to successfully extract cordycepin from biomass. Solid state fermentation (SSF) was performed to grow the fruiting bodies of C. militaris in jars. A novel technology was developed using cotton in the SSF which improved the cordycepin content by 138.42 %. Different liquid culture methods (static, submerged, and mix) were also studied; the Static mode was chosen for future media optimization studies. Initially, different parameters like the effect of pH, light, media volume, and inoculum percentage were optimised that affect the cordycepin production. Further, numerous media components, including carbon newlinesources, nitrogen sources, metals, salts and also the impact of vitamins, amino acids, newlineand adenosine that can influence the cordycepin production were optimized employing the One Factor at a time (OFAT) method. -
Isolation, Screening and Characterisation of Endophytes from Madiwala Lake for Biosurfactant, Bioremediation and Plant-Growth Promotion Properties
The significant surge in population, combined with the degradation of the environment, has imposed substantial stress on worldwide food newlinesecurity. The concerning pace of population growth, along with escalating environmental harm due to heightened industrialization, newlinehas indeed exerted considerable pressure on the global food provision. Considering the existing situation, the sustainable approach to enhance agricultural yield and facilitate environmental bioremediation entails utilizing endophytes that reside within plants. Endophytic microorganisms possessing the capacity to promote plant growth and exert biocontrol can significantly boost plant development amidst fluctuating environmental factors, both biotic and abiotic in nature. The current research aimed to extract bacterial and fungal endophytes from Alternanthera philoxeroides and newlineAlternanthera paranichoides and evaluate their potential for enhancing plant growth and controlling pests. Among the isolated newlineendophytic bacteria, Klebsiella pneumoniae exhibited various characteristics conducive to plant growth, leading to enhanced newlinegermination and vegetative growth in Vigna unguiculata plants. The isolate exhibited good Indoleacetic acid (IAA) production newline(48.752.95 g/mL) and potassium solubilization (2.130.07 ppm). The IAA production by K. pneumoniae was further enhanced by 4- fold using the RSM optimization to 195.662.51 g/mL. The newlineendophytic bacteria Bacillus amyloliquefaciens and Bacillus subtilis newlineshowed good extracellular enzyme production and antimicrobial activity along with plant growth promotion. The endophytic bacterium B. amyloliquefaciens showed good newlinebiosurfactant production and bioremediation efficiency. The strain displayed notable resistance to Cr and Pb concentrations upto 2000 mg/L. It was found to possess maximum metal removal efficiency for Pb, 92.3% at pH 9 and 86.2 at 25 oC. -
Mechanisms Linking Gratitude to Life Satisfaction among Adults : A Mixed - Methods Study
The study examined the relationship between gratitude and life satisfaction in educated adults in an Indian context and the mediation of affect, schema and coping. The sample comprised 711 males and females (18-45 yrs). The research utilised a sequential explanatory mixed methods design, incorporating a follow-up explanation model (Creswell & Creswell, 2017). The initial quantitative phase addressed research questions concerning how the selected variables mediate the relationship between gratitude and life satisfaction. Mediation analysis revealed that positive affect and positive self/others partially mediated the relationship between gratitude and life satisfaction. There is no influence of gender in the role of gratitude in life satisfaction. The quantitative data held significance as it served as the foundation for subsequent qualitative analysis. The two-phased data collection facilitated a comprehensive exploration of the research questions, and integrating quantitative and qualitative data provided a better understanding of the relationships under investigation. A semi-structured interview was designed in the qualitative phase, incorporating insights from the survey results. The interview questions explored participants' perceptions and experiences regarding how various factors contribute to connecting gratitude with life satisfaction. A thematic analysis was performed to recognise the themes expressed by the participants, as outlined by Braun and Clarke in 2013. Three broader themes were derived, incorporating the 14 categories identified through coding. The three identified themes from the qualitative analysis are: 1. Life satisfaction through positive emotions; 2. Self-oriented schema promotes a sense of satisfaction, and 3. Positive connections with others enhance happiness. The qualitative data enrich our understanding by illustrating how participants who prioritise others' well-being and maintain meaningful social connections experience enhanced happiness. The quantitative findings are reinforced by the qualitative insights, which highlight that positive emotions serve as an emotional bridge that connects the feelings of gratitude to an overall sense of happiness, enhancing life satisfaction. This integrated approach enhances our understanding of how gratitude influences emotional well-being, ultimately contributing to overall life satisfaction. The identified themes of life satisfaction through positive emotions, self-oriented schema, and positive connections with others yield valuable implications. Implementing gratitude-focused interventions offers actionable steps for individuals, educators, and mental health practitioners to enhance overall well-being. -
Energy and Environmental Applications of Polymer Based Mixed Metal Oxide Nanocomposites
The dependence of human lives on fossil fuels is very inevitably high for the development of society. This leads to the exploitation of these non-renewable sources, which brings forth society, which is another major issue that has to be tackled. In this study, we have focused on addressing the energy and environmental needs of society using different catalysts. The polymer based mixed metal oxide catalysts are used for the utility towards multiple applications. The energy issues can be mitigated through newlinesupercapacitance studies and water splitting studies. The water splitting studies can newlineproduce hydrogen, an efficient and eco-friendly fuel, and supercapacitors can store newlineenergy effectively. Water pollution is another problem faced by our society, which newlinereduces the availability of freshwater sources. This can be overcome by following newlineeffective and cost-efficient adsorption techniques. Another major threat that prevails in our society is corrosion. Corrosion inhibition studies are followed to tackle this issue and provide a corrosion-free environment. The various polymers used in this study are polyaniline, polypyrrole, poly (3,4-ethylenedioxythiophene), and chitosan. These polymers are mixed with different metal oxides, and the synergy between the polymers and metal oxides provides efficiency towards the mentioned applications. The successful formation of composites is confirmed using various characterization techniques. Several electrochemical studies like cyclic voltammetry, galvanostatic charge-discharge studies, electrochemical impedance spectroscopy, linear sweep voltammetry, and potentiodynamic techniques are employed to analyze the efficacy of the composites towards supercapacitance, water splitting, and corrosion inhibition studies. The batch adsorption studies are executed for water purification studies. The synthesized multifunctional composites can be used as potential candidates for addressing the energy and environmental needs of our society in a sustainable manner. -
Antecedents of Behavioural Intention : Study of Indian Consumer Perceptions Towards P2P Lending Using Technology Adoption Model
Fintech is a rapidly developing area of the financial services business where tech-focused startups and other new players are upending how the sector has historically operated. One of the emerging fintech areas under digital lending is Peer to Peer lending or (P2P) lending; Consumers and authorities are both showing interest in this alternative lending innovation. Results of a literature review show that India is still in the early stages of P2P lending research. The study examines the association between behavioural intention to use P2P lending in India and technological and personal adoption factors. The study model was developed with the help of a literature review and tested using data from 536 respondents who completed an online survey and was tested using covariance-based structural equation modelling (SEM). The results confirm that personal innovativeness, performance expectancy, hedonic motivation, effort expectancy, social influence, and perceived risk are the antecedents of the adoption of P2P lending, except for facilitating conditions and price value. In addition, gender moderates the relationship between performance expectancy, hedonic motivation, personal innovativeness, and intention to adopt P2P lending. The study also throws light on the perceptions of both users and non users in terms of the antecedents. The study's conclusions significantly impact the P2P lending industry and provide practical insights for developers, platforms and regulators to improve and enhance the service. The study suggests looking at other moderating factors like age, voluntariness, experience, and actual usage behaviour for further research. Overall, the research contributes to the academic literature by confirming the predictive power of the extended unified theory of acceptance and use of technology (UTAUT). It highlights personal innovativeness after performance expectancy and motivation as an important factor in predicting the usage of P2P lending. Finally, the study lists managerial implications in the domains of technological adoption, which will assist in the P2P lending long-term success in India. -
Investment Decisions : Behavioral Biases in Selected Less Volatile Asset Classes
This study investigates the behavioral biases in selected less volatile asset classes and their influence on investment decisions(IDs). This study compares and contrasts demographic factors(DF) that influence behavioral biases(BB), examines the relationship between behavioral biases(BB) and risk-taking newlinebehaviors (RTB), determines whether BBs can be used to predict RTB and IDs, and looks at covariance patterns between factors that influence BBs, RTB, and IDs.A comprehensive analysis was conducted, considering various DF such as age, gender, education, annual income, marital status, total annual savings newlinepercentage, and the number of dependents in the family. The findings revealed no statistically significant interaction effects between these demographic variables and the combined dependent variables. Additionally, no significant main effects of age, gender, annual income, education, marital status, or paying tax were observed on the combined dependent variables. The study identified several correlations among the behavioral biases examined, including overconfidence(OC), representativeness(R), anchoring(A), herding(H), mental accounting(MA), and conservatism bias(CB). Positive correlations were found between OC and R, A and OC, A and R, H and OC, H newlineand R, MA and OC, MA and R, CB and OC, CB and R, CB and A, CB and H, CB and MA, risk-taking behaviors and overconfidence, risk-taking behaviors and representativeness, risk-taking behaviors and anchoring, risk-taking newlinebehaviors and herding, risk-taking behaviors and mental accounting, and risktaking behaviors and conservatism bias. Furthermore, herding and conservatism bias was significantly associated with risk-taking behaviors, while anchoring, herding, mental accounting, and conservatism bias were associated considerably with IDs. As part of the assessment techniques utilized in this study, seven characteristics or latent constructs were examined using various observable variables or scale items.