Relationship Between Industry-Associated Value Premium and Firm Risk Charaterstics on Stock Returns : Evidence From Indian Stock Market
The body of academic literature consistently debates that firms with low PB (price to book) outperform firms with high PB characteristics. This study examines whether the academic literature-promised value premium has any industry association in the Indian equity market and tests the existence of other anomalies: size, investment, profitability, and R&D, in explaining the cross-sectional variability of stock returns. The study considers all BSE-listed firms actively trading between 1999-2021, using time-series, multivariate, and cross-sectional models on each industry-level portfolio. Results indicated that a significant value premium exists in 18 out of 21 industry groups. Both industry and firm-level value premiums are identified; however, the firm-level premium seems more prominent. The value premium is most substantial in small-cap value stocks of value-and-growth-oriented industries, large-cap value stocks of value-oriented industry groups, then small-cap growth stocks of value-and growth-oriented industries and large-cap growth stocks of value- and growth-oriented industries. Interestingly, the sub-period analysis revealed variation in the value premium, indicating that the industry-associated value premium has been relatively low in the current decade. It is due to decreasing tendencies in industry returns and increasing PB in industries. The study explores R&D premium and compares existing factor premiums. Results showed that India's annualized average R&D premium is significantly higher than the current value, profitability, size, and investment premiums, particularly for highly R&D intensive firms. To check the robustness of the findings, the study used the multivariate GRS (Gibbons Ross Shanken) test and the regression models. It confirmed that size and value premiums are the most prominent determinants of industry-level equity returns. The profitability and investment premiums also influence industries' returns. Investors who seek to allocate assets within and across industries are likely to have predictable and stable returns.
Volatility Spillover Effects in Cryptocurrencies
Cryptocurrencies' growing use has increased investors and decision- makers interest. Cryptocurrencies' volatility and how it impacts others is most intriguing. Arguments include speculative pressures, valuation uncertainty, and lack of regulation. These traits cannot fully explain cryptocurrency volatility and volatility spillovers, suggesting other relevant factors. In this study, currency volatility and spillovers, as well as their relationship with the sentiment of global investors, were investigated. The study analysed 22 cryptocurrencies from 01/01/2018 to 31/12/2022. The study used FIGARCH and FIEGARCH, a GARCH family model to analyse the long-memory and leverage effects on cryptocurrency volatility, the ADCC-GARCH framework, and the Diebold-Yilmaz spillover index to analyse cryptocurrency volatility spillovers. The long-memory and leverage impacts on bitcoin volatility were analysed using the FIGARCH and FIEGARCH models from the GARCH family. Both the Chow-test and the Pai-Berron Test found structural breaks in the cryptocurrencies. Cryptocurrencies such as Adacordono, Aertinity, ARK, BAT, BCH, BNT, BTC, Dogecoin, Ethereum, Funtoken, ICON, KMD, KNC, NEO, PIVX, QTUM, SNT, TRX, ZCASH, have positive (difference) FIGARCH coefficient values. It indicates a long memory in currencies, and volatility shocks affect future volatility. On the other hand, the FIGARCH coefficient of BTG cryptocurrency (difference) is negative (-0.035), which suggests that the individual has a short memory. In this scenario, the effects of volatility shocks are only temporary. When extreme volatility is promptly followed by low volatility or vice versa, this indicates anti- persistence. The study also found that both positive and negative news has a significant impact on the volatility of specific cryptocurrencies such as BCH (0.015), BNT (0.0016), BTG (0.01972), DOGE (0.2296), EOS (0.0112), KNC (0.0366), PIVX (0.0021), TRX (0.0013), Adacordono (- 0.027), Aertinity (-0.0393), ARK (-0.0377), BAT (-0.028058), and BTC (-0.0665). Ethereum has the largest spillover (4.09), followed by QTUM (4.06), EOS (4.05), Adacordono (4.05), and Dogecoin (2.4). All cryptocurrencies show fundamental instabilities (P-values less than 0.05). Hence the alternative hypothesis is accepted, and the null hypothesis is rejected. The hill estimator tail index value is ? > 0, fat tail or heavy tail; high chance of catastrophic event which is observed in all the 22 cryptocurrencies. Both investors and speculators can use sentiment analysis to forecast market volatility and generate gains. Policymakers can also utilize this information to establish laws that reduce market volatility. As a result, the study contributes to the ongoing discussion on the factors that cause bitcoin's volatility.3
Development of Privacy Preserving Machine Learning Techniques Using Secure Multi-Party Computation
Machine learning (ML) has brought about a paradigm shift in insight generation across various domains, including healthcare, finance, and pharma, by leveraging historical data. However, the effectiveness of ML solutions hinges on the seamless collaboration between data owners, model owners, and ML clients while ensuring that privacy concerns are meticulously addressed. Unfortunately, existing privacy-preserving solutions have not been able to offer efficient and confidential ML training and inference. This has led to an increased focus on Privacy-Preserving Machine Learning (PPML), which has become a flourishing area of research aimed at safeguarding the privacy of machine learning stakeholders. In this regard, the present research introduces novel techniques for private ML inference and training of models using Secure Multi-Party Computation (SMPC) and Differential Privacy (DP) methods on horizontally and vertically partitioned datasets. The proposed techniques are implemented using Python with open-source libraries such as SyMPC and PyDP to ensure confidential inference and model protection. The findings across various parameters illustrate the effectiveness of the suggested techniques in addressing the privacy concerns of model owners and inference clients, with no significant impact on accuracy and a linear influence on performance as the privacy parameters, such as secure nodes count within the SMPC cluster. are increased. Furthermore, the privacy gain is substantiated by information privacy measures such as Mutual Information and KL-Divergence across different privacy budgets, which demonstrate empirically that privacy can be preserved with high ML accuracy and minimal performance cost.
Comparative Study of Product Liability and Data Confidentiality in Case of Intermediaries with Special Reference to India and The European Union
Technology has played a major role in human development. The advent and invention of wheel and fire changed the coverage of human society. On a similar note in 90 s a technology called internet was developed and it changed all rules of the game. This technology removed all hindrances of place and time. It created faceless market place wherein; consumer not only have huge choices and varieties but also, they can create goods and services on their own. This was the origin of Electronic Business and it gave birth to new breed of middleman / intermediaries to facilitate it. These intermediaries are application provider, ISP, network service provider etc. The mantras of success were wide choices and data. But this mantra created a new legal challenge of data handling and liability for defects in goods and services. Researcher has studied and analysed all dimensions of intermediaries newlineand how they handled the two new legal challenge of data confidentiality and newlineproduct liability. In addition, researcher has examined the legal framework of India and compared it with legal framework of European Union and finally concluded on the coverage and effectiveness of Indian legal structure and what India learn and implement from European Union. This thesis mainly focusing on generic business model used by intermediaries. Issues like IPR, industry specific domain like financial systems and medical domain are excluded. Researcher followed the doctrinal research methodology to understand the evolution of intermediaries, product liability, data confidentiality in India by various primary resources like the Indian Laws i.e., Consumer newlineProtection Act, 2019, Indian Contract Act, 1872, Information Technology Act, 2000 and other various statutes. This thesis compares Indian legal framework with European Union and test the hypothesis of coverage and effectiveness of Indian legal structure with European Union.
Design, Training, and Implementation of A New Individualized Education Plan (IEP) Format For Special Educators And Students With Intellectual Disabilities At Selected Special Schools
An individualized Education Plan (IEP) is a multidisciplinary, teamdeveloped plan required for every child receiving special education services. The researcher delved into concerns surrounding Individualized newlineEducation Programs (IEPs) for students with intellectual disabilities. Two significant hurdles were discovered: existing IEPs lacked essential intervention areas, and special education teachers felt inadequately newlineequipped to construct effective plans. newlineThe study tackled these concerns head-on through a multi-pronged approach. Firstly, a meticulous analysis of existing IEPs revealed crucial sections missing from intervention plans, hindering their effectiveness. newlineThis analysis served as the blueprint for crafting a more comprehensive IEP format that addressed the identified gaps and provided a robust framework for intervention. Next, the study focused on empowering special education teachers. Sixty special education teachers certified by the Rehabilitation Council of newlineIndia, participated in training sessions on the new format, undergoing a vital skills and knowledge upgrade in IEP development. This equipped them with the tools and understanding necessary to create more effective plans tailored to individual student needs. The theory then transitioned to practice. Students with intellectual newlinedisabilities were included in interventions based on the improved IEPs, with their progress closely tracked and evaluated. The results were highly promising. Teachers demonstrated a tangible improvement in knowledge, translating into their ability to create more effective IEPs. More importantly, students thrived with the enhanced format. Those involved in interventions using the improved IEPs exhibited significant progress in various domains, highlighting the positive impact of the new approach. The study culminated in key recommendations for further newlineimprovement. Ongoing teacher training sessions were suggested to ensure teachers remain updated on best practices and evolving methodologies.
Forcing Parameters and Propagation Time of Certain Graph Classes
A branch of mathematics that treats vertices and edges of a graph is called graph theory. This theory is used to replicate many real-life situations and physical problems. Graph coloring problem is one of the prominent studies in extremal graph theory. Suppose information has to be communicated in a network or some product has to be marketed to all the people in a cluster then there are two types of cost that needs to be encountered, one the cost of selecting the initial set of vertices in a network and the second is, time it takes to propagate the information through the entire network. The sum of these two parameters is known as the total cost. Optimizing the total cost, which is the sum of vertices and the time it takes to propagate information through the entire network, is a challenging problem for any newlinegraph. Such an interesting and well-studied problem is called the dynamic coloring newlineproblem. The forcing problem also known as infecting or spreading problem is one newlinesuch dynamic coloring problem where two colors- white and black are used. Assume that a fxed set of vertices in a graph G are initially black and that the remaining vertices are considered white vertices. The aim of the forcing process is to obtain, fully black-colored vertices of the graph G by progressively applying the color change law, making sure that at least one white vertex is forced black in every discrete time interval. The forcing index is the minimum cardinality of the forcing sets. Diand#64256;erent types of forcing, such as one forcing, connected one forcing, k-forcing connected k-forcing etc., are defned based on the color change law. The one forcing is the basic form of forcing. A generalised form of one forcing is known as k-forcing where k lt V (G). The time taken by a forcing set to force the entire vertices of the graph G black is the propagation time or iteration index. The subject of study aims to fnd the one forcing number and k-forcing number of diand#64256;erent types of graph classes and derived graph classes.
Clonning and Characterization of An Exported Protein Present in the RD7 Region of Clinical Isolates of Mycobacterium Tuberculosis
The bacterium Mycobacterium tuberculosis is responsible for causing the disease newlinetuberculosis in mammals, which is regarded as one of the oldest diseases haunting the human race. The only available tuberculosis vaccine Bacillus Calmette-Guerine (BCG), is effective against childhood tuberculosis but is regarded as having low efficacy in conferring protection in the case of tuberculosis in adults. A comparison of the M. tuberculosis H37Rv strain and clinical isolates from Kerala had earlier revealed that the clinical strains have a distinctive 4.5 kb genomic sequence that is lacking from the H37Rv strain in the RD7 region. The RD7 is a distinctive genomic region that is absent in M. tuberculosis H37Rv and Mycobacterium bovis BCG strain. The 4.5 kb genomic sequence is projected to include 6 potential ORFs by newlineNCBI ORF prediction tool, one of which Novel Hypothetical Protein (NHP2) is anticipated to encode an exported protein with a length of 268 amino acids. Studies demonstrate that Mycobacterium tuberculosis secretory proteins such as the Ag85 complex, the ESAT-6 family protein, and the PE-PPE family proteins were newlineeffective vaccine candidates because they trigger T cells. Here, we present an indepth analysis of the exported protein, which is 268 amino acids long. The putative exported protein with a gene 807 bp long was PCR amplified and cloned in the expression vector pET-32a for expression. The protein was over expressed using Isopropyl D-1-thiogalactopyranoside (IPTG) and was isolated and purified using column chromatography. Bioinformatics studies were conducted to study the characteristics of the expressed protein. A novel putative mycobacterial protein discovered by subtractive hybridization was studied for its potential as a vaccine candidate using cutting-edge computer technologies.
Respiratory Motion Prediction of Lung Tumor Using Artificial Intelligence
Managing respiratory motion in radiotherapy for lung cancer presents a formidable and newlinepersistent challenge. The inherent dynamic movement triggered by respiration introduces a notable degree of uncertainty in target delineation, impacting the precision of image-guided radiotherapy. Overlooking the impact of respiratory motion can lead to the emergence of artifacts in images during image acquisition, resulting in inaccuracies in tissue delineation. Moreover, the motion between treatment fractions can induce blurriness in the dose distribution within the treatment process, thereby introducing geometric and dosimetric uncertainties. Additionally, inter-fraction motion can result in the displacement of the distribution of administered doses. Given these complexities, the precise prediction of tumor motion holds the utmost importance in newlineelevating the quality of treatment administration and minimizing radiation exposure to healthy tissues neighboring the pertinent organ during radiotherapy. Nonetheless, achieving the desired level of precision in dose administration remains a formidable task due to the inherent variations in internal patient anatomy across varying time scales and magnitudes. While notable advancements have been witnessed in radiotherapy, attributed to innovations like image guidance tools, which have streamlined treatments, the challenge of accommodating lung tumor motion remains critical, particularly in cases related to newlineradiotherapeutic intervention. Substantial limitations endure despite integrating respiratory-gated techniques in radiation oncology to manage lung tumor motion. Moreover, lung cancer prognosis remains low, irrespective of the recent advancements in radiotherapy. The practice of expanding newlinetreatment margins from the Clinical Treatment Volume (CTV) to encompass the Planning newlineTreatment Volume (PTV) has been adopted as a strategy to amplify treatment outcomes. newlineHowever, this strategy necessitates a trade-off, as it inevitably exposes larger volumes of healthy tissues to radiation.
Modified Carbon Based Electrodes for Electrochemical Sensing of Biomolecules
Now-a-days a large variety of biological analytes are detected by highly sensitive newlineelectrochemical sensors which are inexpensive and simple as compared to conventional methods such as UV-vis absorption spectroscopy, spectrofluorometry, HPLC and gas chromatography. Electrochemical analysis is exceptional owing to its economical, low energy consuming and unique approach in the method design, and high sensitivity for the analyte determination. Carbon based electrochemical sensors are commonly used because of their low cost, good electron newlinetransfer kinetics, good chemical stability, and biocompatibility. Recently electrochemical properties of pencil graphite electrodes (PGEs) have been explored in the analysis of various organic compounds. High electrochemical reactivity, easy modification, commercial accessibility, fine rigidity, disposability and low-cost of PGE make it ideal to be used as an effective working electrode. The thesis presented explains different modified PGEs have been employed in the electrocatalytic determination biomolecules such as cholesterol, cortisol, Vitamin B6 and morin. newlineThe modified electrodes are effectively used for the ultra-level sensing of these biomolecules in real samples. The electroactive surface area and the conduvtivity of bare PGE is enhanced newlinedifferent electrode modifiers such as and#946;-CD, graphene, conducting polymer, metal oxides and metal nanoparticles. The modified electrodes are found to exhibit good electrocatalytic behavior towards the target biomolecules. Cyclic voltammetric (CV) studies and electrochemical impedance spectroscopic (EIS) technique were used to investigate the electrochemical properties of the modified sensing platform. The newlinemorphology and step wise fabrication process of the modified electrodes were characterized byvii Ramana spectroscopy, X-ray photoelectron spectroscopy (XPS),scanning electron microscopy (SEM), Transmission electron microscopy (TEM), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR).
Mindfulness-Based Emotional Intelligence : Impact on Psychological Well-Being of School Teachers
Psychological well-being of school teachers is vital for healthy student engagement and a conducive classroom environment. This study sought to understand the role of mindfulness and emotional intelligence in the newlinepsychological well-being of school teachers. It was conducted in two phases. The first phase, through the survey method, sought to establish the relationship between mindfulness, emotional intelligence, and newlinepsychological well-being of school teachers. 125 female school teachers from Bangalore, India, drawn through convenience sampling, were surveyed. The tools used were the Five Facets of Mindfulness Questionnaire, Assessing Emotions Scale, Scales of Psychological WellBeing, and demographic details sheet. Results revealed positive and newlinemoderate to strong associations between the variables (r = 0.38 to 0.65). Moreover, mindfulness and emotional intelligence explained 45% of the variance in psychological well-being, as opposed to 42% by mindfulness alone. The second phase was a pre and post-experimental study. After random assignment to study (N = 19) and comparison (N = 29) groups, the study group underwent a seven-session mindfulness-based emotional newlineintelligence intervention through an online platform. The participants were assessed on mindfulness, emotional intelligence, and psychological well-being before and after the intervention. Results revealed that emotional intelligence showed a significantly increased post-intervention, but mindfulness and psychological well-being did not.
Tertiary Packaging Issues and Their Influence on Repurchase Intention and Loyalty of Customers Towards E-Retailers
his thesis investigates the significance of tertiary packaging in the context of e-retail business and its influence on customer preference, repurchase intention, and loyalty towards e-retailers. With the rapid growth of e-retail, it is expected to become the dominant form of retail worldwide, surpassing traditional brick and mortar establishments. While e-retail offers convenience and flexibility to customers, intensifying competition among e- retailers raises concerns about how they will effectively manage it. As e- retailers resort to increased marketing efforts to attract customers, certain aspects, including tertiary packaging, may be inadvertently overlooked. Tertiary packaging plays a critical role in the e-retail process, and this study analyses its impact on customer perception and satisfaction. By exploring the issues related to tertiary packaging that affect customers, this research aims to provide insights to e-retailers for developing a more efficient and sustainable tertiary packaging model. The anticipated outcomes of this research are expected to enhance e-retailers' ability to attract customers, increase repurchase intention, and foster loyalty towards the e-retailer, ultimately contributing to their long-term success in the evolving e-commerce landscape.
Effectiveness Of Internet-Delivered Dialectical Behavior Therapy Skills Training On Perceived Cognitive Functions Among College Students With Borderline Personality Traits : A Non-Randomized Controlled Trial
As emotions have a profound effect on cognitive functions, individuals with Borderline Personality Disorder (BPD) exhibit significant deficits in higher order thinking abilities. College students with BPD are susceptible to emotional experiences that may challenge their abilities to gain control over intrusive thoughts/emotions and flexibly cope during emotionally demanding situations. Emotional experiences may thereby weigh down newlinetheir capacity for effective affect-laden cognitive processing. In view of the high newlineprevalence of BPD among college students and the efficacy of Dialectical Behavior Therapy (DBT) in treating emotional dysregulation, the present study aimed to investigate the effectiveness of internet-delivered DBT - Skills Training (DBT-ST) on perceived executive functioning and affect-laden cognitive processing among college students with the traits/presence of BPD. In this non-randomized controlled trial, 36 college students with the traits/presence of BPD were included. Thirteen DBT-ST sessions were attended by the study group, while thirteen Behavioral Activation sessions were attended by the control group. The DBT-ST protocol included the Mindfulness and Emotion Regulation modules. The Behavior Rating Inventory of Executive Functions for Adults was used to evaluate executive functioning based on self-report. Affect-laden cognitive processing was assessed using the Cognitive Control and Flexibility Questionnaire. The impact of the intervention on the outcome variables was examined using two-way repeated measures analysis of variance. The results of the study showed that participants in the study group who underwent DBT-ST significantly improved their abilities to initiate, plan and organize current and future-orientated task demands as well as to organize everyday environment, while the participants in the control group showed no such improvements.
A Study on Near Proper Coloring of Graphs
An equitable coloring of a graph G is a proper vertex coloring in which the number of vertices in any two color classes are equal or almost equal. In this graph coloring, there is a partition of tasks into subsets which perform at the same time. Equitable coloring play an important role when there is a requirement of dividing a system with binary conand#64258;ict free subsystems with equal or newlinenearly equal elements. The non-availability of sufcient number of colors leads to diand#64256;erent defective coloring problems. An equitable near proper coloring of a graph G is an improper coloring in which the vertex set can be partitioned into k color classes V1, V2, . . . , Vk ; (1 lt k lt and#967;e(G)) such that the number of vertices in any two color classes diand#64256;er by at most one and the resulting monochromatic edges are minimised by restricting the number of color classes that can have adjacency among their own elements. The minimum number of monochromatic newlineedges obtained from an equitable near proper coloring of G is called equitable defective number. This study introduces the notion of equitable near proper coloring of a graph G and investigates the equitable defective number for a few graph classes. In this study, the equitable near proper coloring of various graph classes and derived graphs are discussed, and the corresponding equitable newlinedefective number for any k where 2 and#8804; k and#8804; and#967;e(G) and#8722; 1 is obtained.
Isolation, Identification and Characterization of A Potential Probiotic Bacteria and its Application in Aquaculture
In the current study, Bacillus subtilis PKB1 was isolated from dried anchovies and identified using morphological and biochemical analysis followed by 16S rRNA sequencing and phylogenetic analysis. The antibacterial and anti- haemolytic properties of the bacteria were also examined. Probiotic qualities were assessed by measuring the isolated strain's tolerance to artificial gastric juice. To assess the isolated strain's capacity for stress tolerance, additional exposure to varied pH, temperature, and organic solvent concentrations was given. Bacillus subtilis in MRS medium produced exopolysaccharide (EPS) which was purified and a maximum yield of 1928mg/L was achieved. The novel exopolysaccharide was purified and characterized to be a heteropolysaccharide. The polysaccharide present had a molecular weight of about 20 kDa overall. FTIR spectroscopy revealed the presence of carboxyl, hydroxyl, and methylene groups in the EPS. The extremely cross-linked structure of the EPS with lumps that resembled spikes was revealed by atomic force microscopy. Scanning Electron Microscopy (SEM) revealed that it possessed rough, asymmetrical lumps. Emulsification activity was also observed in the EPS. The current study's findings suggested that this EPS might make a good candidate for further applications. Utilizing probiotics derived from unconventional sources may improve the variety of probiotics accessible for use in aquaculture procedures. Probiotics are used in the field of aquaculture in order to improve immunity and to protect against pathogenic microbes. Species such as Aeromonas hydrophila and Vibrio parahaemolyticus are responsible for increasing mortality, decreasing production efficiency and forcing antibiotic overuse. In this study, the role of the isolated probiotic in promoting growth performance in Nile tilapia was examined using growth and challenge studies. The experiment was conducted for a duration of 30 days. Weight gain, histology and mortality rates were studied in the presence and absence of pathogenic microbes. Bacillus subtillis PKB1 supplementation for Nile tilapia helped to maintain the integrity of gill filaments and improved survivability and weight gain when used at a concentration of 1x104 CFU/ml. The study showed that the isolate improved the survival rate of Nile Tilapia against Vibrio parahaemolyticus and Aeromonas hydrophila.
Occupational Exposure to Cooking Oil Fumes : Biochemical, Cytogenetic and Molecular Signatures
Occupational exposure to Cooking Oil Fumes (COFs) is a widespread concern in the newlineculinary industry, and it has raised significant health apprehensions due to its potential adverse effects on individuals working in kitchens. This current research presents a comprehensive analysis of the biochemical, cytogenetic, and molecular analysis observed in individuals exposed to COFs in their workplace. The study employed a cross-sectional approach, involving a cohort of kitchen personnel working in diverse culinary settings. Biochemical assessments focused on analyzing blood parameters, such as lipid profiles, liver enzymes, and markers of oxidative stress, to gauge the impact of COFs on the participants systemic health. Cytogenetic investigations encompassed the assessment of chromosomal aberrations and micronuclei frequency in peripheral blood lymphocytes, shedding light on potential genotoxicity associated with COF exposure. Moreover, molecular analyses involved the examination of ApoE and BMAL1 gene expression patterns related to inflammation, oxidative stress response, and detoxification pathways also this aspect aimed to uncover the newlineunderlying molecular mechanisms influenced by COFs. Preliminary results suggest a significant association between COF exposure and alterations in biochemical parameters, newlineparticularly an increase in oxidative stress markers and changes in lipid profiles, indicative of potential cardiovascular risks. Cytogenetic assessments revealed an elevated frequency of chromosomal aberrations and micronuclei formation, highlighting genotoxic effects linked to COF exposure. Molecular investigations demonstrated differential expression patterns of ApoE and BMAL1 genes involved in inflammation and oxidative stress responses, further corroborating the adverse effects of COFs on cellular processes. The findings of this research underscore the importance of addressing occupational exposure to COFs and implementing appropriate safety measures in cooking area.
Risk and Return Analysis of Socially Responsible Equity Investment for Optimum Portfolio
The sustainable development goals of industry, innovation and infrastructure aims at building sustainability by paving way for socially responsible investing. Socially responsible investing identifies investment newlineavenues that considers social and environmental responsibilities along with newlinefinancial return. The question of risk and return relationship and whether socially responsible investment outperforms conventional investment has been keen area of interest to empirically drive investors in order to establish an optimal portfolio for socially responsible equity investments. The aim of the study is identifying Equity investments which are Socially Responsible newlinefrom listed Equity investments in India, to examine whether socially responsible equity investments outperformed conventional equity newlineinvestments, to assess the equity investments performance which are socially responsible and equity investments which are conventional across different sectors based on the risk adjustment metrics for establishing an Optimal Equity portfolio which are Socially responsible with Sharpe Index newlineOptimization Model. The study identified socially responsible companies which adhered to sustainability reporting and disclosures of ESG from the total companies listed newlinein BSE and NSE as on 31.12.2021. Annual average return rate, standard deviation, beta and different risk adjustment metrics for evaluating the performance of equity investments which are socially responsible and the equity investments which are conventional was utilized by the study. The newlinesample period of the research between lies between 2012 to 2022. Correlation analysis as well as t-test have been performed using E-views software. Socially responsible equity companies showed significant strong positive newlinerelationship of risk and return than conventional companies. Commodities, Health care, Industrials, Information Technology and Telecommunication sectors outperformed conventional companies of similar sector.
Isolation of Fungal Endophytes From Hulimavu Lake Flora and Characterization and Optimization of Fungal Enzymes
The present work was aimed at isolating fungal endophytes from Hulimavu Lake, newlineextracting their secondary metabolites and fungal enzymes to subsequently probe the newlinebiological properties of these fungal endophytic bioactive compounds and enzymes. newlineHulimavu Lake, known for its notoriously high levels of pollution contributed by newlineanthropogenic factors, was chosen for this study with the literature-evidence backed newlinehypothesis that plant habitat stress also positively favors the type and quanta of bioactive compounds with novel features produced by its endophytes. Literature survey was performed to identify the probable types of plants found in this lake that could be used for the study and these were subsequently collected, identified and processed under laboratory conditions. These plants were authenticated by a certified botanist and were identified as Alternanthera philoxeroides, Ricinus communis and Persicaria glabra. Fungal endophytes were then isolated from different plant parts collected and were screened using preliminary LCB staining followed by DNA sequencing analysis. Based on ITS region sequencing, nucleotide homology and phylogenetic tree mapping, these fungal endophytic cultures were identified as Aspergillus niger, Talaromyces amestolkiae, Cladosporium phaseolorum and Diaporthe phaseolorum. Crude extracts obtained from these fungal endophytes displayed bacterial growth inhibition and significant free radical scavenging/ reduction potential that was comparable to standard ascorbic acid, hence depicting antioxidant activity of these extracts. Owing to their biological properties these crude extracts were further tested for cytotoxic properties on newlinedifferent models like that of Saccharomyces cerevisiae (Baker s yeast), Artemia salina newline(Brine shrimp) and MCF-7 cell line. The presence of fungal endophytic enzymes like newlineprotease, amylase, laccase and lipase was detected qualitatively and estimated newlinequantitatively.
Rate Adaptation Mechanism for Multirate WLAN with Background Traffic Awareness
In recent times wireless communication has become more popular with its commercial usage. WLAN has evolved over the years to facilitate wireless communications for commercial usage. IEEE 802.11 working group focuses on developing global standards that can support the WLAN evolution. There are many features that IEEE 802.11 working group emphases on to provide the best experience for the Wi-Fi user. The popularity of Wi-Fi among commercial users has demanded more importance in terms of traffic and congestion. IEEE 802.11 have come with many updates enhancing with additional spectrum space, method of spectrum utilization, and so on. There are a few aspects of Wi-Fi adoption that have been kept outside the scope of the 802.11 standards, which are open for research. Wi-Fi rate adaptation is one of newlinethe important aspects of research. Many researchers have contributed with effective newlinemethodologies to improve user experiences. The literature review proves the importance of rate adaptation in the performance of wireless communication. The different version of the IEEE 802.11 standard provides a set of transmission rates to choose from for single-stream transmission. It is important to switch the transmission rate dynamically for more efficient utilization of the physical medium in a fluctuating environment. Dynamically identifying the optimal transmission rate from a list of single-stream transmission rates is a tedious task. There are different causes for the change in channel conditions and packet loss in the network. Identifying the best data transfer rate for the next transmission is a tedious task in such a network. It requires identification of the exact cause of loss. Improper channel estimation may lead to the channel may be underutilized or overused. Both situations will degrade the newlineperformance of the network. Evaluating and identifying the latest channel condition is newlineimportant.
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.
Mind-Set In Mathematics Learning : Role of Teacher-Student Interaction on Student Engagement, Wellbeing and Achievemrent
Mathematics learning is an integral part of the school curriculum. Children learn basic concepts in mathematics and then gradually reach the abstract level. Challenges in mathematics learning are largely observed after grade seven. Students may show disinterest towards the subject due to several reasons including past learning experiences, teacher-student interaction (TSI), anxiety and self-efficacy levels. If the students cannot connect what they learn, it impacts their interaction in the classroom, and it acts as a reason for losing interest. The literature review reveals the importance of mathematics anxiety, self-efficacy, and utility value and contribute to the construct of mind-set. Student engagement is influenced by mind-set in mathematics learning and TSI, and predicts achievement and wellbeing. The study adopts a mixed-method design with the qualitative study aiming to support the quantitative study and strengthen the validity of the results. The quantitative study sample consists of 774 eighth graders from various English medium schools in Bengaluru, Karnataka. The qualitative phase seeks to determine the students' perception of mathematics learning through their classroom experiences among 17 students using semi-structured interviews. The tested conceptual model shows an excellent fit. It shows mind-set in mathematics affects TSI, influences student engagement and leads to student-wellbeing. There was no indirect effect for the achievement and other variables. The findings related to the open-ended questions indicate the importance of teachers and content. There is a lack of understanding among students about the practical application of the learning content. The thematic analysis results provided five main themes: student attributes, teacher attributes, classroom environment, content-related and utility value. Integration of the findings leads to the importance of TSI and student engagement in the mathematics classroom. Also, the connection between variables related to mathematics learning and student wellbeing. The results of the study have important implications for developing engaging pedagogies.