Volume 13 | Issue 1

 Abstract

Abstract: Pharmaceutical co-crystals have gained significant attention recently as a new solid form due to their ability to alter the physicochemical properties of Active Pharmaceutical Ingredients (APIs). However, advancing the pharmaceutical use of co-crystals remains challenging, with the need for high-throughput screening methods and techniques capable of producing co-crystals on an industrial scale still limiting their widespread use in the industry. This review offers a comprehensive overview of pharmaceutical co-crystals, focusing on the role of supramolecular chemistry, co-crystal design strategies, preparation methods, studies on physicochemical properties, mechanisms of solubility enhancement, and evaluation techniques. The article also discusses the impact of selecting the right process design and formulation in overcoming translational challenges. Finally, it briefly covers the applications and marketed drug products involving pharmaceutical co-crystals.

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Key Words- Co-Crystal Formers, Co-Crystals, Crystal Engineering, Solid-State Characterization, Supramolecular Chemistry.

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Tourism has undergone a significant transformation over time, evolving from a leisure oriented activity into a predominantly commercial enterprise. In developing nations, it has become a crucial driver of economic growth and a primary source of revenue. Tourism contributes to job creation, generates foreign exchange, and supports the development of local infrastructure. Moreover, sustainable tourism has the potential to address various socioeconomic challenges. Uttar Pradesh is a prominent international tourism destination, consistently attracting the highest number of Foreign Tourist Arrivals (FTAs) each year. In 2019, the state ranked first in domestic tourist visits and third in foreign tourist arrivals, welcoming nearly 4.7 million international visitors. The tourism industry plays a very dynamic anfd crucial role in Uttar Pradesh's economic growth. To further strengthen this sector, the state has introduced a new Tourism Policy focused on enhancing infrastructure, promoting development, and creating income and employment opportunities. Sambhal, a town located in Uttar Pradesh, holds historical and cultural significance but remains lesser-known on the tourism map compared to other cities in the state. Sambhal may not yet be fully developed as a main stream tourist destination, but its historical significance, combined with its vibrant local culture and craftsmanship, makes it a hidden gem for travelers looking to explore Uttar Pradesh's lesser-known destinations. Present study highlights opportunities of tourism entrepreneurship in Sambhal district along with financial study of tourism based entrepreneurs.

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Tourism Based Entrepreneurship, Financial stability

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This research used qualitative and quantitative surveys to gain deeper insight into how consumers felt and acted about health insurance before and after the COVID-19 outbreak. The findings revealed a significant gap in understanding health insurance products and benefits, as several participants indicated they did not know the available coverage options. Although interest rates were moderate, enrolment rates were disappointing, primarily due to perceived affordability, trust in providers, and the applicability of the insurance to personal circumstances. The analysis highlighted a range of barriers to effectively utilizing health insurance, including complex language, ignorance of basic insurance principles, and financial difficulties. While the pandemic heightened people's awareness of health risks and the need for financial security, many remained confused about the use of insurance. The study, therefore, emphasized the need for greater consumer education and simpler insurance processes to increase coverage and utilization of insurance in the post-pandemic period. Such a study would have influenced consumers' thoughts and preferences. It provided valuable information for policymakers and insurance providers to align with emerging market trends, making health coverage in India more accessible.

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Insurance, Policy Makers, COVID 19, Health Insurance

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Hearing loss is one among the many Socio-medical problems, which is considered as a hidden disability. Hearing impairment is the most frequent sensory deficit in human populations, it is also associated with decrease in cognitive impairment1. It is estimated that over 60% of such hearing loss could be avoided through preventive measures2.Among the people is a major issue and a person with hearing loss may be unable to hear doorbells, alarms, to respond while talking with anyone, etc. All this can make them feel frustrated, lonely, and depressed. Non-genetic causes can be intrauterine as diabetes, toxaemia, ototoxic drugs,3and infections such as rubella, measles, chickenpox, cytomegalovirus, and HIV4.Hearing loss can be improved by using the hearing aids but is not choice of treatment in all conditions. Hearing aids work well for some while for others; it may not be a perfect solution due to many reasons such as poor economic status, low maintenance, social stigma. Dissatisfaction is seen in hearing aid due to incorrect amplification adjustments, low custom design, etc. Badhirya is one among the 28 types of Karnaroga with clinical features of reduced hearing or hearing loss. The main line of treatment for Karnagata rogas is Karnapoorana, Karnaprakshalana, Karnadhupana etc. along with internal Rasayana therapy. There are two types of Badhirya mentioned in classics namely Vata and Vata Kaphaja. As the root cause of Badhirya lies in Shabda Vaha Srotas and the main dosha involved is Vata dosha, lack of specific medical treatment and the surgical intervention is not suitable for all in hearing-loss. There is a need of simple, cost-effective medical line of treatment for Badhirya. Hence the treatment of choice is Karnapoorana with Lashunadya taila is selected.

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Keywords: Badhirya, Sensorineural hearing loss, PTA, Karnapoorana, Lashunadhya Taila.

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Al the outset of Chapter IV it was noted that, due to similarities in performance technique employed on the sitar and surbahar, it is not uncommon for performers of the former instrument to also play the latter. In the Imdad Khani Sitar and Surbahar Gharana, artists have traditionally performed on both instruments, though recently the star has become the more popular of the two. This chapter begins with a look at the history of this gharana including the lives of its khandan and other leading exponents. This is followed by a discussion of the teaching method employed and an examination of the baj and chal of this tradition's sitar music.

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Sitar, Music, Gharana, Tradition, Instruments, Performance.

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STUDY ON PROBLEM FACED BY RURALWOMEN AT SEVVANDHINATHAPURAM, LALGUDI *Dr.N.HEMALATHA, M.A., MSW., MBA., MSC (Psy)., M.Phil.,Ph.D. Assistant Professor, Shrimati Indira Gandhi College, Trichy **MS.P.Selvi,MSW.,MBA.,MPhil., Assistant Professor Shrimati Indira Gandhi College,Trichy _____________________________________________________________________ ABSTRACT . Each one has different problem in the world but here only focus on the women. From the beginning women facing multiple problems in the world. The major problems are namely share in the land, lack of education, lack of opportunities, early and force marriage, lack of transport facilities, raped, abused in home, preference given to male child, lack of health treatment and no permission for job from family etc ,Kaur and Sharma (1991) told that Indian women, and especially rural women was play many social and economic roles inside and outside the home, but their participation is not well received due to recognition. They are excluded from various training and rural development programs. . To study about socio-economic status of the respondents.To study about the psychological problems & physical problems faced by the rural women. To study about the educational qualification of the respondents. The research has used descriptive research design for the study . The aim for having used this design was to analysis the problem as well as to increase the knowledge of the researcher about the problems faced by rural women hence descriptive design was adapted foe the present study.

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KEYWORDS: Problem Faced By Rural Women

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Graph Neural Networks (GNNs) are revolutionising anomaly detection in wireless networks by effectively utilising graph-structured data to model intricate relationships among network components. Unlike traditional techniques, GNNs excel in capturing both node-level and edge-level interactions, enabling the detection of subtle irregularities that may signify security breaches or performance issues. Their ability to learn dynamic graph representations through message-passing and feature aggregation enhances detection accuracy and scalability. GNN-based solutions address critical challenges in wireless networks, such as dynamic topology, high-dimensional data, and scalability. By strengthening network reliability, optimising resource allocation, and enhancing security, GNNs pave the way for robust monitoring and management of large-scale wireless systems. As wireless networks continue to grow in complexity, GNNs offer a promising approach to anomaly detection, fostering advancements in automation and intelligent network analysis. This paper explores the methodologies, applications, and challenges of applying GNNs for anomaly detection in wireless networks, highlighting their transformative potential in the field.

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Wireless Networks, Anomaly Detection, Graph Neural Networks, Network Security, Dynamic Topology, Machine Learning in Networks, Graph-Based Modelling, Deep Learning in Wireless Systems, Message Passing, Node Interaction, Network Performance Optimization, High-Dimensional Data Analysis.

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Ageing is an inevitable developmental phenomenon bringing along a number of changes in the physical, psychological, hormonal and social conditions. The house check focused on environmental hazards, sites and safety devices identified as most commonly associated with accidents or falls in older people. Hazards which are thought to increase the risk of falling, slipping or tripping and the absence of safety devices which may prevent falls made up the majority of items in the house check. Objectives: The objective of the study was to assess the awareness regarding home safety measures among elderly residing in selected areas of District, Ludhiana, Punjab. Methodology: A descriptive study was conducted on 60 elderly of age group 60-90 years in selected areas i.e. Shimlapuri and Mohar singh Nagar Ludhiana city. Convenience sampling technique was used to select the study sample. Data was collected by using socio- demographic profile sheet, modified structured checklist to assess home safety measures of elderly. Result: The socio- demographic profile of elderly revealed that out of 60 elderly more than half i.e. 51(85%) of elderly were from the age group 60-70 years, 32 (53%) were females, 36 (60%) were educated up to elementary level, 44 (73%) were married, more than half i.e. 57 (95%) were living with their children,31(52%) were doing moderate physical activity, 60 (100%) were have sedentary life style, 32 (53%) were homemaker, 51(85%) were unemployed, 39 (65%) were care giver, 40 (67%) were fully dependent and 59 (98%) were having personal monthly income <5,000. Conclusion: It was concluded that majority of the study subjects had good home safety measures.

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Elderly, Awareness, Home Safety Measures

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Bitcoin is known for its high volatility, making accurate price predictions challenging. This study aims to forecast Bitcoin prices for the upcoming month by incorporating exogenous variables specifically, interest rates and recession probabilities. The primary goal is to examine whether these external factors can improve the accuracy of Bitcoin price predictions. To achieve this, we employed two widely used time series forecasting models: Long Short-Term Memory (LSTM) and Facebook Prophet. We'll be implementing these project with several types of time series forecasting model like Arima model, eda model, lstm, facebook prophet, exponential smoothing, afima. Among all these models we'll be selecting one highly performing model. The research explores how the inclusion of interest rates and recession probabilities influences the performance of these models and compares their prediction results through visualizations and cross-validation techniques. We trained both models using historical Bitcoin price data combined with the selected exogenous variables and evaluated their predictive performance on a separate test dataset. Our findings reveal that the LSTM model outperforms Facebook Prophet in terms of prediction accuracy. While Facebook Prophet is optimized for statistical modeling, LSTM has the advantage of learning complex, non-linear patterns in data due to its deep learning architecture and ability to process sequential information effectively. Moreover, our results demonstrate that incorporating interest rates and recession probabilities significantly improves the forecasting accuracy of both models. This suggests that macroeconomic factors like interest rates and recession risks do have an impact on Bitcoin price movements. By integrating these external variables into the forecasting process, we show that predictive models can achieve better performance, making them more effective for forecasting Bitcoin prices. These findings highlight the importance of considering exogenous factors when predicting the behavior of highly volatile assets like Bitcoin.

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Bitcoin, cryptocurrency, exogenous variables, forecasting, interest rate, LSTM, machine learning, recession probability, time series. Bitcoin Price Prediction, Exogenous Variables, Time Series Forecasting, LSTM (Long Short-Term Memory), Facebook Prophet, Interest Rates, Recession Probability

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This paper delves into the comprehensive understanding of Alternate Investment Funds (AIFs) in the Indian financial market. The study addresses several key objectives, which include: evaluating the level of awareness and understanding among investors with respect to AIFs, assessing the risks and returns that go along with these investment vehicles, analyzing the challenges or obstacles faced by investors while investing or managing AIFs, and investor perceptions toward AIF investments. This paper goes more in-depth concerning different types of AIFs, such as hedge funds, private equity funds, venture capital funds, and Infrastructure funds that have the alternative scope for investor portfolios diversification and the increase of their return. This study further extends to a primary survey to reach the investor level of AIF investors to capture firsthand experience, perception, expectation & improvement regarding AIF investments, which can give an insight for investors, fund managers, and policymakers in their decision-making process to navigate AIF landscape more effectively.

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Alternative Investment fund, portfolio, category, HNI

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Dementia, a progressive neurodegenerative disorder, poses significant challenges for early detection and effective management due to its subtle initial symptoms. Early diagnosis is crucial for delaying disease progression and improving patients' quality of life. This study presents a machine learning (ML) approach for the early detection of dementia, leveraging advanced computational models to analyze clinical, cognitive, and behavioral data. By integrating diverse data sources, including medical history, cognitive tests, and imaging biomarkers, the proposed approach aims to identify patterns and anomalies indicative of early-stage dementia. The study employs a hybrid machine learning framework, combining supervised and unsupervised algorithms to enhance prediction accuracy. Techniques such as feature selection, dimensionality reduction, and cross-validation are utilized to ensure robust and interpretable models. Algorithms including Random Forest, Support Vector Machines, and Neural Networks are compared to identify the most effective model for detecting early signs of dementia. Initial findings indicate that the ML approach achieves high sensitivity and specificity in distinguishing between healthy individuals and those in the early stages of dementia. Furthermore, explainable AI techniques are incorporated to enhance the transparency of predictions, fostering trust in clinical applications. This research demonstrates the potential of machine learning to revolutionize dementia screening and contribute to timely interventions.

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Dementia, Early Detection, Machine Learning, Neurodegenerative Disorders, Cognitive Analysis, Predictive Modeling, Artificial Intelligence, Clinical Diagnosis, Explainable AI, Medical Data Analysis

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This research examines the technological dependency of postgraduate students on their study materials, focusing on gender and geographic location differences. A quantitative approach was employed, involving 100 postgraduate students from Raiganj University and the University of Gour Banga in West Bengal. Data were collected using structured questionnaires and analyzed through statistical methods, including independent samples t-tests. The results revealed no statistically significant differences in the technological dependency between male and female students (p = 0.279) or between rural and urban students (p = 0.176). Both groups demonstrated similar mean scores, indicating that technological tools benefit all demographics equally by improving access to resources, fostering flexible learning, and enhancing academic engagement. These findings emphasize the equitable potential of technology in higher education, highlighting its role in creating inclusive learning environments. The study provides actionable insights for educational policymakers and institutions to optimise the integration of digital tools, ensuring enhanced academic performance across diverse student populations.

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Technological Dependency, Study Materials, Postgraduate Students, Gender Differences, Rural-Urban Divide

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Fourier transform infrared spectroscopy (FTIR) spectroscopy provides a unique ability to detect and characterize complex chemicals in many industries, especially in medicine and pharmaceuticals, while reducing waste and reducing the need for extensive modeling or use of hazardous chemicals to minimize environmental damage. This review demonstrates the wide range of ex situ and in situ FTIR applications for species identification, characterization, and quality monitoring. The accuracy of ex situ FTIR spectroscopy in identifying impurities, monitoring crystallization processes, and modifying dosage forms can improve product quality, safety, and performance. In addition, its many capabilities, all based on green screening standards, have contributed to drug development, drug use processes, and quality control. On the other hand, in situ FTIR spectroscopy appears to be a new tool for real-time investigation of drug reactions and processes, monitoring drug release kinetics, crystallization kinetics, and surface contact, and provides valuable information. The combination of ex situ FTIR accuracy and in situ FTIR dynamic capability provides a comprehensive guide to green practices, quality control, and innovation in the pharmaceutical and medical industry. This review describes the widespread use of ex situ and in situ FTIR spectroscopy as a green medicinal chemistry tool in the chemical, pharmaceutical, and pharmaceutical industries. However, more research is needed to unlock the full potential of FTIR and develop new applications that will enhance sustainability in these areas.

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Finished Product; Purity; Pharmacopeias; Raw Material; Quality Control

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Children all over the world use smartphones for various purposes. Some children are seen talking to their friends for long hours, while others spend their time playing countless games on the phone. The internet is an abode of knowledge for children. Though the utility of smartphones cannot be debated, continued use and exposure can have harmful effects on the child. The aim of the study was to assess effectiveness of child-to-child approach through power point presentation on knowledge regarding ill effects of using mobile phone among (10 to 12 years) School children in selected schools. Methods: The research methodology adopted for the study was quantitative research approach. The investigator used pre-experimental one group pre-test post-test design. The setting for the study was selected schools. Accessible population selected for this study consisted, 10 to 12 years school going children who are available during the course of the study. Sample size was 120 children selected with purposive sampling technique then sampling as per the inclusion criteria from the selected schools. The data collection was carried out in three phases and the data was analyzed by using the descriptive and inferential statistics. Result: The study result depicted that, Majority 53% of samples were having good knowledge and 47% were having average knowledge. Mean score was 12.58 and 2.05 SD. In the present study, mean score in pre-test is 6.83 along with 2.56 SD. In post-test mean score is 12.58 which is more than pre-test mean score and SD is 2.05 which is less than from pre-test SD. DF is 119, T value is 21.43 and p value is less than 0.00001 which shows significant effectiveness of child-to-child approach through power point presentation about ill effect of mobile phone use. Conclusion: The findings of the present study indicate that the school going children had poor knowledge regarding ill-effects of using mobile phone during pre-test. But after providing them the information about ill effects of using mobile phones their knowledge is improved. Hence the child-to-child approach through ppt is effective

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child-to-child approach, power point presentation, knowledge, ill effects, mobile phone and School children

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The species Salmonella belongs to the family Enterobacteriaceae. They possess interesting phenotypic/genotypic characteristics, history, and nomenclature compared to other bacteria within and outside the family. The organism is what causes typhoidal salmonellosis (TS) and non-typhoidal salmonellosis (NTS). TS and NTS are serious diseases that affect people and animals in different ways and are important for public health around the world. The objective of this study is to isolate Salmonella from chicken samples and to evaluate the drug sensitivity of the food-borne Salmonella and its susceptibility. This study reviewed the characteristics, taxonomy, nomenclature, and nature of Salmonella, as well as the confirmation and biochemical tests (indole test, MR-VP test, citrate test, antibiotic resistance test, gram staining, and ESBL test) for the identification and characterization of Salmonella. The study utilized baseline data and information from peer-reviewed journals, textbooks, and articles from international regulatory bodies. Salmonella exerts huge health and economic impacts due to their virulence or carriage of antibiotic resistance traits. To address these significant issues about public health, the availability of adequate information on the prevalence and antibiotic resistance patterns of Salmonella and the establishment of adequate measures to control contamination and infection are needed. Samples were collected randomly and processed for identification and antimicrobial susceptibility testing of Salmonella.The study's data showed that Salmonella is a Gram-negative rod that doesn't make spores and is negative for oxidase, indole, urease, lactose, and sucrose. It can also live without oxygen and move around. Salmonella is the cause of NTS and TS in men and animals presenting enteritis, septicemia, abortion, and meningitis. Salmonellosis outbreaks have been reported from food, food products of animal origin, and animal contact settings with cross-infection between humans and animals. The objective of this study was to identify types of antimicrobial resistance and their associated genes, isolated from chicken and beef and confirmed to be Salmonella, using standard techniques. Continuous research on Salmonella and salmonellosis should be carried out to contribute to the body of knowledge on the organism and disease and, ultimately, improvement of preventive/therapeutic strategies for the disease.

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Keywords: Food-borne disease, Isolation, Biochemical test, Drug-sensitivity, Antibiotic- resistance

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The GST on building materials has streamlined the taxation structure, which is imposed by the government. Construction employs around thirty million people in the nation, therefore a comprehensive GST is essential. It also adds $200 billion in assets each year. Construction operations are governed by the idea of Work. In the context of GST on the construction process, the term "works contract" is used. The works contract is a wide term that refers to all transactions relating to the construction of a project on a plot of land. It also includes the specifications of the suppliers of raw materials needed to finish any job. The GST on residential house building will include the cost of brick, concrete, paint, wallpapers, and plumbing fixtures. Taxpayers are only obligated to pay GST on under-construction homes, according to the 2017 CGST, therefore there is no need to pay GST on ready-to-move-in residences. Implementation of GST harms the construction and service sectors because of the increased tax rates. The tax rates on the number of items have increased in the construction business. In the service industry, there is also an impact. Customers suffer because they bear the entire weight of the tax rate. It creates a burden on developers and end consumers.

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GST, Construction service, works contract, end consumers, developers, Tax rate, pre gst and post gst regime

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This project presents a fault detection methodology for the IEEE 9-bus system using MATLAB and Simulink. The IEEE 9-bus system is a well-established testbed for studying power system stability and fault analysis due to its complexity and interconnectivity. In this study, various types of faults, including single-line-to-ground (SLG), line-to-line (LL), double-line-to-ground (DLG), and three-phase faults, are simulated and analyzed. The primary objective is to develop a fault detection mechanism that accurately identifies and classifies fault types, location, and severity within the network. The system dynamics are modeled using MATLAB's Simulink environment, leveraging the capabilities of the Sim Power Systems toolbox for power systems simulation. The proposed fault detection algorithm employs wavelet transforms and signal processing techniques to analyze the transient response during fault conditions. By examining voltage and current waveforms at critical nodes, the algorithm pinpoint's fault locations and classify fault types based on characteristic transient features. The findings of this research are essential for advancing the reliability of protection systems, as the early detection of faults minimizes system downtime and ensures stable power delivery. The project concludes with a performance analysis of the fault detection approach, illustrating its effectiveness and accuracy across different fault scenarios in the IEEE 9-bus model.

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Fault Detection, IEEE 9-Bus System, Wavelet Transform

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Romantic artists like Wordsworth, Byron, Shelley, and Keats were enthused in a variety of dissimilar ways by ancient Greece. Stephen Larrabee, in his conclusion pictures the influence of Greek monument on the Romantics, analyses the main thrust of English Romantic Hellenism that the Romantic poets "wished to emulate the Greeks in making great art from the circumstances of their time." In the Romantic age, it was taken for expanded that the logical and imaginative acquirement of old-fashioned Greece and Rome was one of the bedrock of Western background. The conventional world permeated almost every portion of life, from political institutions and theoretical analysis to technical scheme and the basic forms of construction. The ancient Greeks as well as the glory and splendor of the middle ages attract the imagination of natural thirst. Being an artist of romantic age Keats' attitude towards nature developed as he grew up in his poems and it was a temper of merely aesthetic delight, and analyzed pleasure in the beauty of nature. Romantic poetry aims at the large indefinite quantity expression of the individualistic. The poetry of Keats is not a vehicle of prophecy but matter-of-fact. It is for the sake of nature and truth and most of his poems are devoted to the theme of quest for beauty, love chivalry, adventure, glow of imagination, and pathos. Poetry is divinity to Keats and he takes on his own way of communication.

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Hellenism, conventional, imagination, communication, Beauty, Aesthetic Delight

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This systematic review investigates the impact of Cognitive Behavioral Therapy (CBT) on neuroplasticity in individuals with Post-Traumatic Stress Disorder (PTSD). Targeting populations with trauma-induced neurocognitive alterations, this review synthesizes data from experimental studies employing Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG), identified through PubMed and manual cross-referencing of relevant journals. Sampling primarily focused on clinical participants with diagnosed PTSD, using purposive methods to ensure relevance. Hypothetical projections suggest CBT's potential to mitigate symptoms by enhancing neural pathways linked to emotional regulation and cognitive processing. Observed results validate these projections, demonstrating significant neurobiological adaptations, including improved connectivity and structural changes in key brain regions. Implications highlight the need for comparative studies involving alternative therapeutic approaches such as Eye Movement Desensitization and Reprocessing (EMDR) and mindfulness-based therapy, as well as investigations into the combined efficacy of CBT with pharmacological treatments for holistic and sustained recovery.

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CBT, Neuroplasticity, PTSD, Trauma Recovery

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