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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. -
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. -
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. -
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. -
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%). -
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. -
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 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. -
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. -
Influence of ChatGPT in professional communication moderating role of perceived innovativeness
Purpose: ChatGPT, a cutting-edge language model, stands as an unparalleled, unmatched conversational ally, showcasing novel versatility and intelligence in its responses. This research delves into the incorporation of ChatGPT, a powerful generative AI tool, into professional communication. This study utilizes the information system success model (ISSM) to examine the role of ChatGPTs in strengthening information quality (IQ), system quality (SQ) and service quality (SEQ) for improving customer usage intention (UI) and satisfaction (SAT). The study also investigates the moderating impact of perceived innovativeness between these relationships. Design/methodology/approach: The research collected data from a sample of 400 customers through an online survey and validated the hypothesized relationships using structural equation modelling (SEM). Process Macros 4.1 in SPSS 22.0 is used to test the moderating role of perceived innovation between IQ, SQ and SEQ and UI and SAT. Findings: The results of SEM analysis indicate that IQ, SQ and SEQ all positively support UI to use ChatGPT for professional communication with SAT. The result also establishes that perceived innovativeness positively moderates the relationship between IQ, SQ and SEQ and UI and SAT. Originality/value: This research study offers novel contributions to the literature and body of knowledge by establishing the moderating role of perceived innovativeness in strengthening the relationship between IQ, SQ and SEQ and UI and SAT. Further, this study also proposes a 2*2 matrix to segment the UI and SAT of ChatGPT users in professional communication with varying degrees of perceived innovativeness. 2024, Emerald Publishing Limited. -
Routing TQM through HR strategies to achieve organizational effectiveness: themediating role of HR outcomes in India
Purpose: The present research focuses on improving the awareness related to soft total quality management (TQM) practices by looking from the viewpoint of strategic human resources (HR). In addition, it is intended to reflect on the resulting soft TQM-HR outcomes and determine the mediating effect between soft TQM-HR strategies and organizational effectiveness (OE). Design/methodology/approach: An exploratory research methodology with an online survey technique was adopted for the study. Three hundred and three managerial-level personnel from nine large Indian manufacturing organizations participated in the research. A theoretical model is projected and verified using correlation and mediation analysis. Findings: The results show that commitment, reduced turnover intentions and satisfaction levels of employees mediate the relationship between resources, development and retention strategies and OE. However, the retention strategy has the strongest association with the OE of the three strategies. Also, of the three HR outcomes, satisfaction was strongly associated with OE. The analysis proved that the proposed model is an acceptable fit. Practical implications: Implementing HR-related TQM strategies will likely impact OE since it elicits positive HR outcomes such as commitment, reduced turnover intention and satisfaction. Recognizing human resources as a unique strategic asset will help HR managers devise adequate resourcing, development and retention strategies instrumental in executing TQM. Originality/value: The present micro study is unique in scrutinizing the influence of soft TQM-HR practices on organizational effectiveness by analysing the mediating effects of commitment, reduced turnover intention and satisfaction in Indian large-scale manufacturing organizations. The study is unique since no literature deciphers the linkages between HR strategies and organizational effectiveness in the Indian manufacturing sector. 2023, Emerald Publishing Limited. -
Bounds on Sombor index of graph operations
Operations in graph theory have a significant influence in the theoretical and application aspect of the domain. Topological indices serve as a crucial component in chemical graph theory linked with some molecular structure. Recently, Gutman initiated the study on the Sombor index. In this paper, the computation of some bounds for Sombor index of graph operation notably join, cartesian product, corona product, lexicographic product, tensor product and strong product is carried out. The computation has been utilized to determine the upper bounds of the index for the specified graph operations for some standard graphs like the path and cycle graphs. 2025 World Scientific Publishing Company. -
Embedding behavioral biases into robo-advisory platforms-case of UAE investors
Purpose: This study aims to identify individuals' biases while making investment decisions and explore how these biases can be incorporated into a robo-advisory platform to help mitigate these biases. This paper identifies eight investment-related behavioral biases: mental accounting, gamblers fallacy, hindsight, regret aversion, disposition, trend-chasing, loss aversion and herding. Design/methodology/approach: This study uses primary data from 263 respondents across various age groups, of which approximately 50 were wealth management professionals in the UAE. A random sampling method from probability sampling is employed to gather the primary data. The identified biases serve as dependent variables; the age and income of individuals serve as the independent variables. Findings: Age and income are significantly related to mental accounting, herding, gambler fallacy and loss aversion. Existing studies on behavioral finance demonstrate that individuals who make investment decisions are susceptible to cognitive fallacies, leading to nonrational investment decisions. Practical implications: By studying these biases affecting individuals of varying ages and income levels, wealth management professionals can tailor their financial robo-advisory services to address these biases and help clients build wealth with consistent investment. Originality/value: This study uses survey-based sampling in the context of the UAE; hence, the data and analysis represent originality. 2024, Emerald Publishing Limited. -
Lung cancer prediction with advanced graph neural networks
This research aims to enhance lung cancer prediction using advanced machine learning techniques. The major finding is that integrating graph convolutional networks (GCNs) with graph attention networks (GATs) significantly improves predictive accuracy. The problem addressed is the need for early and accurate detection of lung cancer, leveraging a dataset from Kaggle's "Lung Cancer Prediction Dataset," which includes 309 instances and 16 attributes. The proposed A-GCN with GAT model is meticulously engineered with multiple layers and hidden units, optimized through hyperparameter adjustments, early stopping mechanisms, and Adam optimization techniques. Experimental results demonstrate the model's superior performance, achieving an accuracy of 0.9454, precision of 0.9213, recall of 0.9743, and an F1 score of 0.9482. These findings highlight the model's efficacy in capturing intricate patterns within patient data, facilitating early interventions and personalized treatment plans. This research underscores the potential of graph-based methodologies in medical research, particularly for lung cancer prediction, ultimately aiming to improve patient outcomes and survival rates through proactive healthcare interventions. 2025 Institute of Advanced Engineering and Science. All rights reserved. -
Rheostatic effect of a magnetic field on the onset of chaotic and periodic motions in a five-dimensional magnetoconvective Lorenz system
This paper deals with a weakly nonlinear study of two-dimensional RayleighBard magnetoconvection using a simplified five-dimensional Lorenz model. The governing equations of the system are nondimensionalized and formulated in terms of the stream function and the scalar magnetic potential. A five-modal Fourier truncation scheme is employed and the resulting equations are scaled to obtain a five-dimensional autonomous dynamical system. The Hopf-Rayleigh number, signifying Hopf bifurcation, is numerically evaluated from the analysis of weakly nonlinear stability. Chaotic and periodic motions are depicted by plotting bifurcation diagrams, largest Lyapunov exponent (LLE) diagrams and three-dimensional projections of the phase-space. For a fixed set of parameter values, increasing the strength of the applied magnetic field is found to increase the Hopf-Rayleigh number, thereby delaying the destabilization of the system's equilibrium points. It is shown that while low magnetic field strengths favor the onset of chaotic motion directly from the steady state, stronger magnetic field strengths favor the onset of periodic convection from the steady state prior to the appearance of chaotic motion. We observe here that the applied magnetic field regulates the onset of chaotic and periodic motions in the system and therefore, has a rheostatic control over chaotic and periodic behaviors. 2025 Elsevier Ltd -
Beyond the basics: mapping the inflation response to fiscal deficit in India with smooth transition autoregressive model
Purpose: Indias historical fiscal performance has featured elevated deficit levels. Driven by the imperative need for fiscal stimulus measures in response to the crisis, efforts toward fiscal consolidation from 2003 to 2008 were reversed in 20082009 due to the financial crisis. These stimulus actions are believed to have wielded a notable influence on inflation dynamics. Presumably, a high inflation rate hinders growth and inflicts severe welfare costs. Accordingly, the principal objective of this paper is to scrutinise the threshold effects of fiscal deficit on inflation within the context of the Indian economy. Design/methodology/approach: We employed the Smooth Transition Autoregressive (STAR) Model, a robust tool for capturing non-linear relationships, to discern the specific threshold level of fiscal deficit. Our analysis encompasses annual data spanning from 1971 to 2020. Additionally, we have leveraged the Toda-Yamamoto causality test to establish the existence and direction of a causal connection between fiscal deficit and inflation in the Indian economy. Findings: Our analysis pinpointed a critical threshold level of 3.40% for fiscal deficit, a value beyond which inflation dynamics in India undergo a marked transition, signifying the presence of significant non-linear effects. Moreover, the results derived from the Toda-Yamamoto causality test offer substantiating evidence of a causal relationship originating from the fiscal deficit and leading to inflation within the Indian economic framework. Research limitations/implications: The findings of our study carry significant implications, particularly for the formulation and execution of both fiscal and monetary policies. Understanding the threshold effects of fiscal deficit on inflation in India provides policymakers with valuable insights into achieving a harmonious balance between these two critical economic variables. Originality/value: To the best of our knowledge, this study is the first of its kind to empirically investigate threshold effects of fiscal deficit on inflation in India from a non-linear perspective using the Smooth Transition Autoregression (STAR) model. 2024, Emerald Publishing Limited. -
Surface modified CaO nanoparticles with CMC/D-carvone for enhanced anticancer, antimicrobial and antioxidant activities
The rising prevalence of antimicrobial resistance and the continued challenge to cancer therapy are in desperate need of developing innovative therapeutic strategies. In this regard, the present research work focuses on the development of CaO NPs and CaO-CMC-Dcar nanocomposites for enhanced antimicrobial and anti-cancer activities. CaO nanoparticles were synthesized by facile one pot chemical approach and eventually functionalized with CMC and D-carvone biomolecules. XRD analysis revealed that the crystallite size for CaO and CaO-CMC-Dcar nanoparticles was found to be 21.18 nm and 17.02 nm respectively. The band gap values obtained for CaO and CaO-CMC-Dcar nanoparticles were 4.44 eV, and 4.25 eV respectively. The CaO-CMC-Dcar nanoparticles show absorption maxima at 292 nm, slightly red-shifted from bare CaO nanoparticles. HRTEM and SEM analysis revealed that the prepared samples were roughly spherical and agglomerated in nature. Antimicrobial activity was evaluated against methicillin-resistant Staphylococcus aureus (MRSA) and Candida albicans. The zone of inhibition (ZOI) for CaO-CMC-Dcar nanoparticles against MRSA and C. albicans was 20.1 0.3 mm and 21.1 0.2 mm, respectively, significantly higher than that of pure CaO nanoparticles (14.1 0.2 mm and 13.2 0.1 mm) and comparable to standard anti-bacterial streptomycin and antifungal fluconazole discs. Anticancer activity was assessed via MTT assay against MOLT-4 blood cancer cells, where the IC50 values for CaO and CaO-CMC-Dcar nanoparticles were 22.6 ?g/mL and 21.54 ?g/mL, respectively. Additionally, CaO-CMC-Dcar nanoparticles exhibited enhanced antioxidant activity (80 %) compared to CaO (70 %) at 20 ?g/mL, with performance comparable to that of Vitamin C. Experimental results revealed that the CaO-CMC-Dcar nanoparticles exhibited superior biological activity compared to pure CaO nanoparticles. 2025 Indian Chemical Society -
A method for identification of restarted radio sources from large radiosurveys
Active galaxies hosting radio jets can exhibit distinct active phases marked by two sets of radio lobes. Typically, these episodic radio sources have been identified through morphological observations. In addition, spectral characteristics-based methods are also employed wherever multi-frequency deep radio observations are available. However, these methods are inefficient in detecting restarted radio sources that do not exhibit a clear morphology. To address this, a method of using the spectral curvature (SPC=?150MHz1400MHz-?74MHz150MHz) to identify restarted radio sources is presented. This is based on the fact that restarted radio sources with significant remnant emission are expected to have concave spectra in contrast to the convex or straight spectra observed in most radio sources. We use available wide area radio surveys in the range of frequencies from 74MHz to 1.4GHz to search for episodic radio sources and to shortlist 9,405 sources based on the criteria of SPC?0.5. The candidates thus identified can be followed up for detailed morphological and spectral index studies. This method will find application in the automated identification of episodic radio sources in large radio sky surveys from telescopes like LOFAR and SKA. Indian Academy of Sciences 2025. -
Unfolding the aggression and locus of control paradigm in sportspersons and non-sportspersons
The present study investigated Aggression and Locus of Control on Combat Sports Persons, Non-Combat Sports Persons, and Non-Sports Persons. In this study, a sample of 240 individuals (80 Combat sports, 80 Non-Combat Sports & 80 Non-Sportspersons) was used through purposive sampling. The tools administered were the Buss and Perry Aggression Questionnaire by Arnold H. Buss and Mark Perry and Rotters Locus of Control Scale by Julian Rotter respectively. The objective of the study was to investigate Aggression and Locus of Control in males and females from Combat, Non-Combat, and Non-Sports persons. This research also aims to explore the relationship between Aggression and Locus of Control. Mean, t-test, F-value (ANOVA), and correlation have been computed over SPSS-16. Results suggest that males from Combat have higher Aggression than people from non-sports and non-combat sports. There is also a significant difference between non-sports persons and sports people over the Locus of Control, sports persons showed internal locus of control compared to non-sports persons who were higher on external locus of control. The result also indicates a significant relationship between the anger dimension of the Aggression and Locus of Control. 2025 ARD Asociaci Espala. -
Electrical transport and magnetoresistance studies on the magnetic moment compensated Mn2V1-xCoxZ (Z=Ga, Al; x=0, 0.25, 0.5, 0.75, 1) Heusler alloys
We report the electrical resistivity and magnetoresistance properties of arc-melted Mn2V1-xCoxZ (Z=Ga, Al; x =0, 0.25, 0.5, 0.75, 1) alloys, which possess compensated ferrimagnetic behaviour with high TC when x=0.5. Apart from metallicity, the alloys in the Ga series with x= 0, 0.75, 1 composition showed a positive to negative crossover in the magnetoresistance versus temperature curves. This crossover was absent for Mn2V0.75Co0.25Ga and the fully compensated ferrimagnet Mn2V0.5Co0.5Ga. In contrast to this, Co-substituted Mn2VAl exhibits distinctly different resistive behaviour. While the alloys Mn2VAl and Mn2CoAl exhibit metallic and semiconducting behaviour respectively, the intermediate compositions show a gradual metallic to semiconducting transition as the Co concentration increases. The compensated ferrimagnet Mn2V0.5Co0.5Al showed a mixed transport behaviour of metallic and semiconducting nature with a resistivity minimum at 140 K. In contrast to this mixed response of the arc-melted bulk sample, the Mn2V0.5Co0.5Al melt-spun ribbon shows a clear semiconducting nature throughout the temperature range, indicating that the sample preparation methods could highly influence the electrical properties of the investigated compensated ferrimagnets. 2024 Elsevier B.V.