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ITIHAS Vol. 25 Issue No. 2
No full textNEWSLETTER FROM SASTRA DEEMED UNIVERSITYhttps://knowledgeconnect.sastra.edu/itihas/1001/thumbnail.jp
Fresh and Mechanical Properties of Self-Compacting Concrete using Kaolin Limestone Blend and Hybrid Slag Blend
Get PDFThis study examined the consequences of mono and hybrid natural fibers on the mechanical and fresh properties of self-compacting concrete (SCC), in response to the growing demand for environmentally friendly building materials. In mono fiber, Abaca fiber (AF) at 0.25% and 0.5% dosage, basalt fiber (BF) from 0.25% to 2% at 0.25% increments, and sisal fiber (SiF) from 0.25% to 1.5% at 0.25% increments were evaluated through slump flow diameter, T500, compressive and tensile strength. AF at 0.25% ensured good flow with 6.6% and 4.16% higher compressive and tensile strength over 0.5% AF. SiF up to 1% improved strength but reduced flow due to high hemicellulose content. BF peaked at 1.25% dosage but still underperformed over the control SCC.
From hybrid fiber mixes, M_A0.25_B0.25 mix met EFNARC guidelines and showed the peak compressive strength of 45.4 MPa, whereas M_A0.25_B1.75 improved its tensile strength by 21.42% over control SCC. AF-BF mixes improved the strength but reduced flow at higher dosages due to fiber interlocking. AF-SiF hybrid mixes showed poor flow (330-375 mm) due to the clustering effect. However, M_A0.25_S0.5 improved compressive and tensile strength by 22.22% and 26.08% over the control SCC, respectively.
Hybrid fibers improved the hardened characteristics; however, the key fresh characteristics of SCC were not met under constant HRWR. To address economic and workability limitations, a non-fibered SCC with two tailor-made SCMs was developed. A hybrid slag blend (HSB-ultrafine slag and GGBS in a 2:1 ratio with 1.5% gypsum) and kaolin limestone blend (KLB-calcined kaolin and limestone powder in a 2:1 ratio along with 1% gypsum) for the cement substitution from 10% to 50%. HSB at 40% (HSB.4) enhanced flow with reduced HRWR, while KLB mixes demand 0.6% to 2% HRWR.
HSB.4 and KLB.5 mixes improved strength, impact resistance, and durability, though increased brittleness at higher dosages. Microstructural analysis, such as SEM, XRD, and FTIR, confirmed stable carbo aluminate formation in KLB with reduced porosity and negligible chloride penetration. Hence, the KLB.5 mix is a viable approach for producing high-strength, high-performance SCC with a better economy index and enhanced sustainability
Extraction of Contact Resistivity for Transition Metal Oxide-Based Silicon Heterojunction Solar Cell
No full textContact resistivity quantifies the charge transport barrier, which is one of the key parameters for choosing the carrier selective contact for silicon solar cells. Optically transparent and electrically selective contacts such as Transition Metal Oxide (TMO)–based contacts are employed in solar cell applications. Therefore, extracting contact resistivity for such Schottky contacts requires apposite validation.
In this work, the contact resistivity of TiOx/LiFx/Al stack over an n-type c-Si wafer is extracted using two conventional techniques: i) Shockley’s Transfer Length Method (TLM) and ii) Cox and Strack Method (CSM). The extracted contact resistivity is validated by comparing it with the solar cell’s contact resistivity (true contact resistivity) using Sentaurus TCAD-based simulations. It is found that TLM overestimates the contact resistivity for highly resistive TiOx films due to the asymmetric nature of the TMO barrier, which is correlated with the reported experimental data.
In contrast, CSM extracts more accurate contact resistivity for TiOx contacts when total resistance is extracted closer to the Jmpp (38 mA cm-2). Besides, it is recommended to include the passivating layer along with the contacts (in case of passivating contacts) to extract the actual contact resistivity felt by the solar cell. This work is extended to propose a strategy for accurate extraction of the partial contact resistivity ( ) of a solar cell with Ohmic (or linear) and Schottky (or nonlinear) contacts. This work demonstrates how the CSM can accurately estimate the of a solar cell using Sentaurus TCAD-based simulations.
The simulation predicts that for linear contact solar cells, is approximately constant when the contact fraction is varied, whereas for non-linear contact, decreases with contact fraction as opposed to the previously reported works. The experimentally reported data is also shown to support the claim for the linear contacts further.
Despite the larger full-contact resistivity of non-linear contacts, the contact resistivity and fill factor (FF) of both linear and non-linear partial contact solar cell is almost similar to ~(3.5 − 5) Ω −2 and ~75% respectively, at a 0.3% contact fraction due to the decreasing contact resistivity with the contact fraction for non-linear contacts
A Contemporary Approach for Exploring the Influence of Detoxification and Standardization of Traditional Metallopharmaceutical Product Pharmacological and Toxicological Aspects
No full textPolyherbomineral formulation possess unique medicinal properties due to the presence of metals and minerals as integral part, as processed in addition to specific herbals. There is an increased interest in metallopharmaceuticals in clinical and research areas, because of their immense therapeutic efficiency towards multiple diseases and evidence for non-toxic claim. Sivanar Amirtham is one of the polyherbomineral Siddha medicine recommended for the treatment of various respiratory diseases and other ailments including antidote therapy for poisonous bites. The present research work attempted for standardization of Sivanar Amirtham preparation as per the traditional standard protocols (including the detoxification process of raw materials) followed by characterization through modern analytical techniques to assess the physicochemical properties responsible for the stability, quality and efficacy, and the in-vivo toxicity studies to evidence the safety of administered dose.
The foremost step was the detoxification of the ingredients viz., Sulphur, Mercury, Arsenic trisulphide, Borax, Dryopteris filix-mas and Aconitum ferox, as per Siddha texts to remove the physical and chemical impurities. Secondly, Kajjali was prepared with the combination of Sulphur and Mercury, followed by the addition of other ingredients in the appropriate ratio to obtain the final product of Sivanar Amirtham. To understand the significance of detoxification process and quality of the preparation, the characterization studies were performed for the raw materials, processed materials, intermediate samples, finished product and commercial samples through analysis of particle size and zeta potential by zeta sizer, surface morphology by SEM, chemical interactions by FTIR, thermal behavior and stability by TG-DSC, crystalline property by XRD, elemental composition by EDAX and XPS, herbal composition by HPTLC and sulphur analysis by Raman spectroscopy.
In-vitro pharmacological screening was performed to elucidate the therapeutic efficacy of Sivanar Amirtham for anti-bacterial, anti-tuberculosis and anti-HIV therapeutics, and toxicity profile by hemolytic assay. The anti-bacterial study was performed against both gram-positive and gram-negative pathogens including Staphylococcus aureus (ATCC 29213 - MSSA), Methicillin-resistant Staphylococcus aureus (ATCC 43300 - MRSA), Enterococcus faecalis (ATCC 29212), Pseudomonas aeruginosa (PA14) and Vibrio cholerae (MTCC 3905) by agar well diffusion assay, wherein the highest zone of inhibition was identified for MRSA (20.7 mm) and V. cholerae (34.3 mm) at 25 mg/mL. The anti-tuberculosis activity experimented by microtitre alamar blue assay against M. tuberculosis (ATCC 27294) had demonstrated significant activity at the concentration range of 12.5 - 100 μg/mL. The anti-HIV efficacy was carried out by syncytia inhibition method using C8166 cell lines infected with HIV-1IIIB showed a significant therapeutic efficacy. The in-vitro toxicity assay proved Sivanar Amirtham to be non-haemolytic and haemocompatible.
In-vivo toxicity studies were performed to evaluate acute and sub-acute toxicity profile in wistar rat models as per the OECD guidelines. The acute study was conducted by administering single oral dose administration of 2000 mg/Kg for the animals, followed by observation for 14 days. The sub-acute study was carried out for 28 days using 7 groups of rats, administered with different doses of Sivanar Amirtham. From the histopathology, hematology and biochemical parameters, the formulation was found to be non-toxic at the recommended dose. The findings of the research could provide scientific proof-of-evidence to overcome the limitations of the product owing to the standard quality and safety concern of the metal- mineral ingredients that are present in the polyherbomineral formulation
Management concepts in Shishupalavadha
No full textManagement of organizations, people, and entities has been a subject matter of great interest today. Schools of business and management were established in the West about 125 years ago, and countries in other parts of the world, including India, simply followed these practices. Consequently, there is a widespread feeling today that management concepts originated in the West. All Indian business schools teach management concepts propounded by Western scholars in the last 100 years or so.
Going by the first principles, whenever multiple people, resources, entities, and institutions are involved, there is a requirement for Management. This implies that management as a concept must be as old as rocks and rivers. While civilizations flourished in the West only in the last two millennia, countries such as India has had established civilizations running to several millennia in the past. This naturally raises the question of whether management thoughts and concepts were practised in ancient times in India. This thesis makes an effort to address this critical question. In particular, the thesis seeks to explore the following questions in some detail:
(a) Are there management concepts and practices that were practised in India in ancient times?
(b) Based on a study of a specific text pertaining to the ancient tie period, is it possible to distill some management concepts?
(c) What can current-day organizations learn from the insights gathered from such a study? Are there a few workable ideas that current-day organizations need to imbibe?
(d) India has a vast repository of literary resources spanning more than three millennia. Therefore, choosing a specific scripture to study for the purpose of this thesis requires careful consideration. Based on the scrutiny of the existing studies about management thoughts in Indian scriptures and discussion with some experts, the following criteria were applied to identify the scripture to be taken up for the current study:
a) It must be more than one thousand years old.
b) It must have more than one thousand slokas, providing a greater opportunity for investigating management concepts.
c) It should be a well-known literary work – this will ensure a certain standard of the work and greater appeal for the insights derived from the study.
d) It should not have been studied extensively by earlier researchers – popular scriptures such as Rāmāyanām, Mahābhāratam, and Gitā have been studied by many to distill management thoughts. By taking up such works that others have already considered, the marginal value addition may be minimal.
e) A preliminary list of works was shortlisted for our consideration. The list includes Rāmāyanā, Mahābhārathā, Bhagavad Gitā, Arthaśāstrā, Viduranīti and Śiśupālavadha.
Researchers have already provided enough research reports on management concepts from Rāmāyanā, Mahābhārathā, Bhagavad Gitā & Arthaśāstrā. Earlier researchers have submitted various concepts on principles of good governance, such as respect management, decision, reputation, team & character management, management sciences from Sundara Kandam, leadership lessons from Rāmāyanā, etc.
Hence, based on a thorough analysis and considering all the above criteria, it was finally decided to take up Śiśupālavadha for a detailed study. This excellent poem by Māgha shows us his fantastic vocabulary, comparisons, and significant meanings. We should all be immensely proud to have had these kinds of marvellous poets, fabulously wealthy in literacy, knowledge, and culture, in the past centuries
A Predictive Framework for Early Detection and Personalised Monitoring of Parkinson’s Disease Using Artificial Intelligence and Large Language Models
No full textParkinson’s Disease (PD) is a multifaceted and progressive neurodegenerative disorder that presents a spectrum of motor and non-motor symptoms. Early and accurate diagnosis is essential for effective disease management and improved patient outcomes, yet remains clinically challenging due to symptom overlap and diagnostic limitations. This thesis proposes a comprehensive and interpretable artificial intelligence (AI)-driven diagnostic framework that aims to transform the early detection, personalised monitoring, and treatment recommendation process for PD. The proposed solution integrates deep learning, radiomics, evolutionary optimisation, and large language models (LLMs), ensuring a highly accurate and clinically adaptable system.
The research begins by analysing T2-weighted 3D Magnetic Resonance Imaging (MRI) scans sourced from the Parkinson’s Progression Marker Initiative (PPMI) database. A robust preprocessing pipeline comprising brain extraction, registration, bias correction, normalization, and segmentation is applied. From the segmented subcortical brain regions, 107 radiomics features are extracted, of which the top 20 most predictive are selected using Pearson correlation, recursive feature elimination, and ranking techniques. Statistical validation is conducted using ANOVA, pairwise t-tests, and Kruskal-Wallis H-tests.
Multiple machine learning algorithms are evaluated, and the Gradient Boosting (GB) model, enhanced by the Synthetic Minority Oversampling Technique (SMOTE), attains an improved diagnostic accuracy of 96.8 % up from 86 %. To enhance transparency and clinical trust, Explainable AI (XAI) methods such as, SHAP and LIME are implemented, offering interpretable visual insights into model predictions. For advanced volumetric analysis, a custom 3D Convolutional Neural Network (3D-CNN) is designed and optimised through architectural refinement and hyperparameter tuning, achieving an accuracy of 93.4%. This model outperforms the baseline and complements an existing 3D-ResNet, which independently achieves 90% accuracy. Canonical Correlation Analysis (CCA) is then employed to fuse high-level features from both networks, yielding a combined accuracy of 95%. Further enhancement is achieved through the application of the Whale Optimisation Algorithm (WOA), a biologically inspired evolutionary technique, which boosts the final classification accuracy to 97%.
Recognising the multi-dimensional nature of PD, the thesis expands into multimodal data integration, encompassing MRI, SPECT scans, cerebrospinal fluid (CSF) protein biomarkers, and clinical scores. A 1D-CNN model is developed using 121 multimodal features and initially achieves an accuracy of 94.9%. With the inclusion of biologically derived ratio-based biomarkers, this accuracy increases to 96.9%. The integration of a fine-tuned ChatGPT-4.0 Mini model bridges AI-driven insights with clinical narratives, enabling personalised report generation, improved patient engagement, and real-time clinical decision support. A cloud-based platform is developed to enable scalable deployment with features like real-time inference, chatbot-assisted communication, and automated medical summaries.
Overall, this thesis presents a unified, explainable, and clinically deployable AI framework that significantly enhances the capabilities of PD diagnosis and personalized care. By integrating deep learning, radiomics, evolutionary optimization, and Large Language Models within a cloud-enabled platform, the proposed system establishes a novel benchmark for future clinical AI applications in the management of neurodegenerative disease
Hypergraph Association with Lie Algebra of Upper Triangular Matrices and its Application to Wireless Networks
No full textA hypergraph is a generalized graph characterized by edges spanning more than one vertices describing multiple relationships among them. It provides a mathematical framework for comprehending and learning about a wide range of real-world challenges. On the other side, the theory of non-associative algebras, such as Jordan, Octonions, Malcev, and Lie, has found significant impetus in recent years. These structures proved intriguing from an algebraic standpoint; they generated novel concepts and approaches that aided in solving specific classic algebraic problems, also progressing towards application.
A preeminent observation that galvanizes this thesis is that hypergraph association is still unexplored in Lie algebra and its application in real-world scenarios. In this thesis, the association of hypergraph theory with Lie algebra of upper triangular matrices is carried out, followed by an application to wireless networks. We analyzed the relationship of a graph with the Lie algebra of upper triangular matrix, which leads to the association of the hypergraph with Lie algebra of upper triangular matrix. Furthermore, as the use of Lie algebra in engineering applications has yet to be adopted, we intend to apply this theory to the problem of wireless network routing.
Wireless networks are chosen due to the explosive growth of hand-held wireless devices and technologies such as mobile phones, laptops, iPads, WiFi, IoTs, etc. The data transfer in the wireless network is a highly challenging issue because of its intermittent communication. So, this study involves designing the cluster-based routing protocol for two distinct types of networks with the variation in the theory: one has nodes with static placement and the other with increased mobility nodes.
Wireless Sensor Networks has nodes with static placement, utilize Lie hypergraph theory, while Vehicular Ad hoc Networks nodes with high mobility, use Variable Lie hypergraph theory. The proposed work clusters the network with hypergraph construction, hypergraph transversal is employed to elect the cluster heads and Lie commutators are utilized to find the path with the best relay nodes for routing. Simulation is carried out to assess the performance of the proposed protocol using the metrics of average delay, packet delivery ratio, energy consumption, network lifetime, and throughput.
In addition to addressing routing challenges, ensuring secure communication among nodes is essential for the overall robustness and reliability of a network. To achieve this, a novel 2D-Henon Sine Cosine chaotic map has been developed to generate the keys required for encryption and decryption. The study evaluates various metrics, including Lyapunov exponent analysis, trajectory analysis, NIST test suite analysis, encryption and decryption time, the randomness of key, plain and cipher text values, delay, throughput, and so on
Effect of Osmolytes on the Interplay of Water Protein and DNA in EcoRI DNA Recognition using Molecular Dynamics Simulations
No full textEcoRI is a type II restriction endonuclease that has been widely used as a model system to study protein-DNA interaction owing to its high degree of specificity. This enzyme does not recognize even a single basepair change in its recognition sequence, (GAATTC)2, under normal conditions. However, in the presence of osmolytes, such as glycerol and DMSO, the specificity of EcoRI is slightly relaxed and recognizes sequences that differ from its cognate sequence in the first basepair position. This relaxed specificity has been attributed to the dehydration of the EcoRI-DNA which presumably results in tighter complex formation and subsequent catalysis. However, it may be noted this is insufficient to explain the lack of recognition of DNA sequences that differ at second position or sequences that differ by more than one basepair.
In this thesis, we hypothesized that the relaxation in specificity is not only because of the dehydration of the EcoRI-DNA interface, but also because of its combined effect on the free EcoRI, free DNA and the EcoRI-DNA complex. To investigate this, we performed molecular dynamics simulations of free EcoRI, free DNA and the protein-DNA complex in the presence and absence of different concentrations of two osmolytes, viz., glycerol and DMSO. We used noncognate DNA sequences that differ from the cognate sequence in the first basepair (CAATTC, AAATTC and TAATTC) and as well used a non-specific sequence (TAGCTA) in our study. Our results show the following: (i) In free DNA, there is a sequence-dependent dehydration of the DNA sequence. This is also associated with a transition of the DNA conformation from the BI to BII state which may facilitate the binding of EcoRI.
Further, we observed that while glycerol interacts with DNA directly, DMSO does not as much as glycerol indicating that the two osmolytes may be exerting their action through different modes. Further analyses show that DMSO probably facilitates protein binding by the entropic advantage of the release of water, whereas Glycerol may facilitate protein binding through an entropically favourable displacement of glycerol, contributing to a net decrease in the free energy of binding (ΔG). (ii) The essential dynamics of the free EcoRI is altered in the presence of osmolytes to that similar to that when bound to cognate DNA.
Further, osmolytes slow down the tumbling motion of the interfacial waters, which, in turn, slows down the break-and-make of hydrogen bonds of the interfacial waters with functionally important residues. These results point to the idea that osmolytes may poise the EcoRI for binding to DNA sequences. (iii) In EcoRI-DNA complex systems, our results shows that the osmolyte-induced dehydration of the protein-DNA interface is associated with a number of attendant changes including retarded water dynamics, restored DNA kinking, partially restored protein-DNA hydrogen bonds and altered conformational landscape of EcoRI.
These attendant changes possibly help in relaxing the protein-DNA specificity. The gamut of changes in the structure and dynamics of the biomolecules in the presence of osmolytes not only shows the complex interplay underlying in the osmolyte-EcoRI-DNA-water systems, but also provides a framework to understand the extent of relaxation of protein-DNA specificity in the presence of osmolytes in general. In other words, this thesis contributes the literature on EcoRI-DNA specificity as well as points out to the need to dissect and understand the complex interplay that underlies biomolecular recognition in the presence of other cosolutes such as osmolytes
Hindcasting the Occurrence Time of Major Earthquakes using Machine Learning and Time Series Analysis
No full textAn earthquake is an intense shaking of the ground that typically occurs when tectonic plates move beneath the surface of the Earth. Scientists analyze historical seismic records and geophysical and atmospheric signs to build models estimating the probability of major earthquakes by detecting patterns and anomalies in data such as ground deformation and seismic waves. This study would help in predicting earthquakes to minimize risks of people and buildings. The present study investigates the devastating earthquakes along the Chilean subduction zone in South America, linking non-seismic data to machine learning predictions of Outgoing Longwave Radiation (OLR) and Relative Humidity (RH) anomalies.
Tectonic activity is highly variable in space, therefore the study region must be defined. The first stage which is getting the clusters done by the proposed method Local Maxima-based Spatio Cluster Analysis Network (LMSCAN). In this clustering method, the main quake are taken into consideration to classify the data into the seismology parameters of interest (magnitude and latitude) and the grouping of microshocks. To assess the efficacy of the clustering process, the effectiveness of their proposed technique will be measured against of conventional clustering algorithms such as K-means, Agglomerative Hierarchical Clustering, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN).
By providing detection of Outgoing Longwave Radiation (OLR) as non-seismic precursor, the Singular Spectrum Analysis - Percentile-median Absolute Deviation Method (SSA-PADM) has been proposed, proving a new technique, for predicting the anomaly activity up to 6 months prior to the occurrence of major earthquakes. The existing techniques which include Isolation Forest, 2 Sigma, Median Absolute Deviation and Percentile algorithms are compared for performance against this technique on detecting anomalies preceding a major earthquake.
Moreover, the correlation of atmospheric parameters, OLR and RH are also implicated as predictors of the estimated seismic events through the Proposed Atmospheric and Radiative Anomaly Detection (ARAD) approach. The analysis explores the relationship between the drop of RH flux index value related to the raise of the flux index of OLR near the epicenter as a possible precursor of major earthquakes, with advance times from 3 to 40 days. Accuracy improvements are found compared to wellknown methods like One-Class SVM (Support Vector Machine), Elliptic Envelope and Isolation Forest.
With OLR and RH considered reliable predictors, the atmospheric variables are being forecasted with a hybrid machine learning model called Multi-Layer Perceptron with Expanded Window Cross-Validation (MLP-EWCV). The established methods, including Extreme Gradient Boosting (XGBoost), Random Forest Regressor, and Support Vector Regression (SVR), were used for comparison in order to evaluate the improvement in hindcasting accuracy and efficiency offered by the MLP-EWCV model. The study of anomalous behaviour of OLR and RH may help to detect anomalies before earthquakes, thereby possibly functioning as an early warning for disaster management systems. The current research study attempts to understand Chile (South America) possible micro shocks with respect to tectonic model as a whole because it falls in the inter plate region where usually micro shocks are observed just before the major earthquakes
Factors Influencing the Performance of Farmer-Producer Organizations (FPOs) and Their Societal Impact in Tamil Nadu
No full textFarmer Producer Organizations (FPOs) are formed mainly for the farmers to have better institutional access to acquire them. They are also under the inspiration of the director\u27s abstinence and the incentive of getting more money. These are socio-psychological individual differences and thus of importance to markets, the perception of markets, and market relevance of group interaction. Self-esteem, attitude to participation in group activities, and willingness to participate in these types of activities are of some significance for his/her performance because they have an effect on their performance afterward.
Farmer social empowerment increased but not farmer economic empowerment did so much after joining FPO. ANOVA results indicate that both age and farming experience will add a substantial element in shaping each individual’s perception, awareness, satisfaction, involvement in challenges, innovation, and socio-economic empowerment. The findings therefore show that there are significant differences in these factors depending on the varying levels of farming experience.
However, overall, age and farming experience may influence many things. Post hoc analysis was also carried out on significant factors outcome from ANOVA for better understanding. PLS-SEM analysis confirms that Business innovation, Economic empowerment, Entrepreneurial traits, FPO Performance in terms of Benefits to society, Farm factors, and social empowerment are statistically significant predictors of FPO Performance. In contrast, awareness, problems, and perception are not statistically significantly correlated with FPO Performance using available data.
Farmer Producer Organizations (FPOs) are a key force in transforming the agricultural industry, at least by increasing the production and marketing of farm products. Besides leading to much larger production and logistics efficiencies, which then result in a higher margin for the farmer, FPOs can be implemented at relatively low cost. However, this success is inseparably bound to the resolution of different issues, such as financial limitations, regulatory concerns, or the need for better capacity building.
Sustained policy, infrastructure, and selective interventions are likely to be essential to fully realize FPO contribution to the Indian agrarian economy and to establish and sustain the efficiency of FPOs in delivering growth and innovation to the agricultural economy