Volume 12 | Issue 2

 Abstract

In the case of BSC Class-II drugs, solubility is always a problem because of their lipophilic nature. To solve this pharmaceutical problem there are several ways but solid dispersion is the most promising one. Here Efavirenz was taken for increasing solubility. For this, we used PEG 4000, PEG8000 and PEG 20000 hydrophilic polymers in a 1: 0.5, 1: 1, 1: 1.5, 1: 2 and 1: 2.5 ratio by two techniques. The first technique was hot melt extrusion. Whereas the second one was lyophilization. The result came from dissolution and the result of DSC and FTIR also shows the same result.

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Efavirenz, PEG, BSC, hot melt extrusion, lyophilization.

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Chronic Kidney Disease, Ischemic Heart Disease, Hypertension, Modification of diet in Renal Disease, Glomerular Filtration Rate.

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The kingdom of Bahrain is an archipelago of 33 Islands located in the Arabian Gulf. The island covers 770 square kilometres of land which is connected to the kingdom of Saudi Arabia to the west through the king Fahd Causeway. In Arabic the word Bahrain is a dual form of bahar; it means sea. The name is derived from the topography of the island, as it is surrounded by two kinds of water, sweetwater springs and salty water. This island has started to build its architectural identity in the last 200 years. This paper focuses on the conservation, renovation and rehabilitation of the Amarat Ali Fakhro-I storehouse located in Muharraq, Bahrain. This storehouse devours distinguished architectural elements which are constructed using locally available traditional building materials. This paper throws a light on the structural conservation techniques used on the conservation and renovation of Amarat's storehouse.

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Conservation, Heritage buildings, Bahrain, Structural conservation.

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In this paper, flow of Hyperbolic tangent fluid through a porous medium in a planar channel with peristalsis the effect of Slip and Hall effects under the assumption of long wavelength is investigated. A Closed form solutions are obtained for axial velocity and pressure gradient by employing perturbation technique. The effects of various emerging parameters on the pressure gradient, time averaged volume flow rate and frictional force are discussed with the aid of graphs.

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Hall, Hyperbolic tangent fluid, Hartmann number, long wavelength, peristaltic pumping, Darcy number, porous medium, slip condition, Reynolds number, Weissenberg number, power-law index, pressure gradient, perturbation

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Abstract: The present studies focused mainly on the comparative phytochemical analysis and antimicrobial activity in the typical form of the Vitex negundo var. negundo (VN1) and its intraspecific variant Kali Nirgundi or Nalla vavili (VN2). In the traditional systems of medicines as well as in the local/folk medicine the kali Nirgundi is extensively used rather than the typical form of the species for its effective functioning as an antimicrobial and antirheumatic/anti-inflammatory. To find out the variations in the phytochemical components and their activity in the both typical form and variant the studies were carried out to strengthen the local knowledge and by providing scientific evidence. The powdered leaf materials of both were extracted by using Aqueous, ethanol, chloroform and pet-ether extracts the following chemical compounds were reported Alkaloids, Tannins, Saponins, Steroids, Triterpenoids, Glycosides, Flavonoids in VN1 & VN2. The only glycosides and flavonoids showing are absent in the aqueous and chloroform extracts in the VN1 differing with VN2. The antimicrobial activity was carried out by disk-diffusion method by using four different microorganisms with the nutrient agar medium. The high inhibitory activity was observed in the VN2 against all isolates in all extracts. This may be the presence of chemical compounds glycosides and flavonoids in the VN2. The Molecular docking studies were also applied to support the qualitative and quantitative variations in the presence of phytochemicals within the species due to change of geographic regions and environmental changes.

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Keywords: Antimicrobial activity, Comparative phytochemical analysis, Intraspecific variant, Molecular docking studies.

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Mandibular fractures represent a prevalent form of facial skeletal injury, often resulting in compromised occlusion and functional deformities. The primary objective of treatment involves restoring proper occlusal alignment and function while promoting direct bone healing through precise reduction and immobilization of the fracture site. Herein, we present the case of a 30-year-old male patient who sustained a mandibular parasymphysis fracture following an assault. Our treatment approach involved local anesthesia administration, followed by intermaxillary fixation (IMF) and open reduction internal fixation (ORIF) utilizing stainless steel plates. This method facilitated effective restoration of occlusal integrity and functional stability, thereby addressing the sequelae of the mandibular fracture.

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Mandibular fractures, parasymphysis fracture, assault, local anesthesia, intermaxillary fixation (IMF), open reduction internal fixation (ORIF), stainless steel plates, occlusion, functional deformity.

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For thousands of years, silk--known as the "Queen of Textiles"--has been an integral element of Indian culture and customs. The cultivation and production of silk through the rearing of silkworms, not only plays a crucial role in promoting regional economic development, but also holds immense potential for empowering women. By providing employment opportunities in the sericulture industry, women can gain financial independence and contribute to their household income. Additionally, sericulture offers women the chance to develop valuable skills in silk production and management, allowing them to take on leadership roles within the industry. This not only boosts their self-esteem and confidence but also promotes gender equality and women's empowerment. Furthermore, sericulture is particularly beneficial for rural women, as it offers them a sustainable and regular source of income without any discrimination based on caste, creed, gender, or religion. In West Bengal, Murshidabad is one of the districts that produces the most silk. Our present study was mainly conducted on 2 villages of Nabagram Block (Nagar & Balaspur) and 2 villages of Berhampore Block (Balarampur & krishnamati) as well. It is frequently seen that they are bearing the financial and familial burdens simultaneously, making it extremely challenging for women to work outside the home. They should engage in sericulture because most of the labor is done indoors. The study reveals that more than 60% of woman are engaged in various work of sericulture from planting to reeling & printing. It is found that women are doing their works successfully in every sector.

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silk, empowering women, finance, sector.

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Abstract: The present study is an attempt to study the effectiveness of Email writing skill in English language for B.Ed. trainees. The present study is developmental and experimental. The sample of the study comprised 30 B.Ed. trainees. Two equivalent groups of B.Ed. trainees were made. One is the control group which consists of 15 students and the second one is the experimental group which consists of 15 students. For this study pre-test posttest design was employed. Self constructed questionnaire which was validated by English language experts was used to collect data. Pre-tests were administered to both groups. Experimental group was subjected to Email writing skill in English Language training by providing intervention through a specially developed Email writing skill programme in the English language. After the treatment post test was administered to both groups. The collected data were subjected to statistical analysis and obtained results were interpreted. After analyzing the data it was found that the Email writing skill programme in English language was effective to enhance Email writing skill of B.Ed. trainees.

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Key Words : Writing Skill, Email writing skill,language, B.Ed. trainees.

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A study on the significance of data analysis tools in decision-making is crucial in the contemporary business landscape, where organizations are inundated with vast amounts of data

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Accuracy, Efficiency and Time Savings, Identification of Patterns and Trends, Risk Mitigation Strategies, Cost Reduction and Resource Optimization, Cost Reduction and Resource Optimization, Competitive Advantage

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In modern healthcare, identifying cancerous tissue is still a major challenge that affects patient outcomes, diagnosis, and course of treatment. Numerous analytical methods and imaging modalities have been created over time to improve the precision and effectiveness of cancer detection. Among them in younger women, this diagnosis is less accurate, particularly when it comes to dense breast cancers, which are harder to find. We perform a thorough analysis of recent developments in cancer detection in this review, with a special emphasis on the use of deep learning techniques and their combination with technological advances in medical imaging. We review recent studies and advancements in the development of deep learning-based models for cancer detection across different organs and cancer types. We examine the challenges associated with data scarcity, class imbalance, and generalization in training robust and reliable detection models. Additionally, we discuss the integration of multimodal imaging and the potential synergies between different imaging techniques for improving diagnostic accuracy.

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Image mining, Domain specific application, Data Mining, Image Segmentation, Histopathology, Machine learning; Convolutional Neural Network (CNN); Support Vector Machine (SVM); Logistic Regression (LR).

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Old age has now become a prevalent social problem in our society. In our modern society, where money is the scale of everything, the old age people are measured as an economic liability and a social burden. The main objective of this paper is to identify the socio-economic problems faced by the elderly population in rural and urban sectors. Data was collected from 400 respondents of the selected rural and urban areas through purposive sampling techniques. The data collected was statistically analyzed using SPSS version 20.0 Bivairate cross tabulation with chi square test. The results of the study revealed highest percent (37.6) from urban sector and (41.0) from rural sector belongs to the age group of 60-70 years respectively. Living with son/s (rural 70.5%) and urban 66.6%) was the most common type of living arrangement for elderly. However a slight rural urban differential in living arrangement of elderly was revealed. More males have higher income than females in both rural and urban sectors. Most of the respondents (72.1%) and (71.9%) stated that they possess the ownership of land/household property in both rural and urban areas respectively. However ownership of property did not influence their living arrangement. Furthermore, urban elderly respondents have higher levels of education and results also indicated that elderly individuals with higher levels of education tend to have more income. The analysis of the data reveals that due to old age, lack of financial support and lack of opportunities to earn for livelihood in the villages, the rural elderly experienced more problems in comparison to the urban counterparts.

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Socio-economic,elderly,rural,urban

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This paper explores the empowering narratives of Indian women as portrayed in Sudha Murthy's novels, particularly "Mahasweta" and "House of Cards." Focusing on the struggle against the oppressive mechanisms within closed societies, the research paper highlights the pervasive challenges faced by women in various facets of life, including employment, healthcare, and property rights, illustrating the distant dream of women's empowerment in India. The narratives within Sudha Murthy's novels vividly expose the violence, denigration, and exploitation endured by female characters, reflecting the broader global issues of violence, discrimination, inequality, and poverty faced by women and girls worldwide.

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Empowering Narratives of Indian Women in the Subversive Realms of Sudha Murthy's Novels

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Medical ethics is an intricate domain that frequently confronts practitioners with moral quandaries and ethical obstacles. Deontology is a notable method to tackle these problems. It is a moral framework that prioritizes the underlying morality or immorality of actions, regardless of their outcomes. This paper presents a comprehensive examination of how the deontological approach might be utilized to address medical ethics dilemmas. Deontological ethics, commonly linked to philosophers such as Immanuel Kant, focuses on the notion of duty and moral principles. Within the realm of medical ethics, this approach underscores the significance of strictly adhering to particular moral principles and duties, irrespective of potential consequences. Medical practitioners adhere to a set of ethical norms, including autonomy, beneficence, non-maleficence, and fairness. Deontology emphasizes the importance of maintaining these ideals. The paper analyzes real-world medical situations in which deontological principles clash with consequentialist or utilitarian considerations. The research examines scenarios including patient autonomy, end-of-life decisions, informed consent, and the allocation of limited resources. It sheds insight on the difficulties healthcare professionals encounter while making ethical decisions. Moreover, the study examines the importance of honoring patients' rights and dignity within a deontological framework, highlighting the ethical obligation of healthcare workers to follow these ideals.

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Deontology, Ethical Challenge, Medical Ethics, Patient Autonomy

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In the era of digital transformation, cloud computing has become the foundation of modern IT infrastructure providing never seen before scale, flexibility, and accessibility to users and companies around the globe. Although, along with the numerous advantages in cloud computing, comes great scrutiny in regard to the privacy and security of the users' data on cloud servers. Traditional cloud storage models commonly demand the consumers to rely on a third party, causing legitimate concerns around data breaches, access without authorization, and potential misuse. In such conditions, Private Information Retrieval (PIR) methods surface as a potential solution to ensure user privacy in cloud environments. This article discusses the complete implementation of the PIR protocol to safeguard users' privacy against the attacks by cloud servers. We go into the theoretical underpinnings, practical applications, and subsequent research avenues of PIR in the context of cloud computing. The paper starts with a short introduction on the fast growth of cloud computing as well as privacy issues it has introduced. It further presents PIR and how comes into play in cloud storage privacy preservation. Taking this framework as a starting point, the paper surveys the existing methodologies and techniques for PIR, such as Single-Server PIR, Multi-Server PIR, Homomorphic Encryption-based PIR, etc. Every method is analyzed w.r.t. its cryptographic foundation, performance metrics, security properties and scalability. A paper also studies architectural considerations of integrating PIR techniques to cloud storage systems where issues like data volume, access patterns, and deployment models are addressed.. In the next step, the paper reviews the security and privacy problems of PIR in cloud computing, considering intrusions like eavesdropping, inference attacks, and collusion against it. Necessary vulnerabilities and attack vectors are identified, encompassing the strategies for eliminating these threats and increasing the resilience of PIR-based cloud data storage systems. Besides, the document talks about troubles and limitations existent in existing PIR solutions for clouds, i.e. computational overhead, communication complexity and usability problems. It scrutinizes possible future research directions related to the challenges it had discussed and hopefully improves the performance and state-of-the-art in PIR as it focuses on improving the efficiency, scalability and practicality. In a nutshell, this research paper emphasizes the great importance of PIR techniques in the protecting of user privacy in the era of cloud computing. This study aims at elucidating the theoretical underpinnings of PIR, presenting its practical implementations, and sketching the directions for its future development, in an effort to expand on the existing conversation on privacy-preserving mechanisms in the cloud computing area.

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Cloud Computing, User Privacy, PIR, Cloud Data Security, Cryptography, Privacy-Preserving Protocols.

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 Abstract

The human teeth are the hardest structures in the body, with enamel as their outermost layer. Speech is greatly influenced by teeth, which typically emerge by the age of 13. However, by their mid-30s, more than 80% of people in the United States have at least one cavity, making tooth decay one of the most prevalent chronic diseases affecting individuals of all ages. Dental decay, which takes the form of pit and fissure, root, or smooth surface decay, can be avoided with good oral hygiene practices and regular dental cleanings. Periapical lesions can develop due to various causes, such as trauma, inflammation, or differences in the tooth's surrounding tissue, with treatment options varying depending on the lesion's size or location. Endodontics, or root canal therapy, is a dental technique used to treat infections in the tooth's pulp, allowing the preservation of the tooth that might otherwise need to be entirely extracted. Dental disorders are often diagnosed using X-ray imaging, and the segmentation and categorization of dental abnormalities using neural networks are proving beneficial to the dental field. Various machine learning algorithms are used to categorize and identify dental abnormalities, with CNNs being the preferred network architecture for recognizing objects in tasks like image recognition and pixel data processing. In summary, good oral hygiene practices and regular dental check-ups can help prevent tooth decay, while endodontics can save a tooth from extraction. The use of neural networks for dental abnormality diagnosis is proving beneficial to the dental field, with CNNs being the preferred network architecture for recognizing dental abnormalities.

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Tooth anomaly, Root canal, Periapical lesions, Endodontic therapy, Convolutional neural networks, X-ray images, Dental cavities.

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Human migration is the movement of people from one place to another with intentions of settling temporarily or permanently at a new location in the country or outside the country. The movement is often occurs over long distances which is the dominant form of human migration globally. It has a high potential to improve human development, and some studies confirm that migration is the most direct route out of poverty. The migration rate with in India between 2020-2021 was almost 29 percent, which means about 26.5 percent of the population in the rural areas of the country were migrants, while this was about 35 percent in urban areas. Females recorded a higher share of migration rate of 47.9%; with 48% in rural and 47.8% in urban areas. Migration rate for males was 10.7%, with 5.9% in rural and 22.5% in urban areas. Migration in India is on the rise because the unemployment rate in India is high (15 per cent), and there are not enough jobs for people who want a job. In Telangana also as per 2011 census nearly 30% or 307 million of population are migrants, majority of them are marginalized sections of the society i.e. SC/ST/OBC/Women who migrates to Hyderabad city in search of employment. This paper attempts to study the impact of MGNREGS on Rural-Out migration among Gond, Koya, Chenchu and Lambada tribes from selected villages in Telangana for the year 2015-16.

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Migration, Human Development, Unemployment, Marginalized Sections,

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Due to their fragility, high expense, and difficulty in performing procedures, brain disorders are among the hardest diseases to cure. However, since the outcomes are unknown, the procedure itself need not be successful.Adults suffering from one of the most prevalent brain diseases, hypertension may experience varying degrees of forgetfulness and memory issues.Because of these factors, it's critical to diagnose Parkinson's disease using brain MRI scans, as well as to assess the patient's degree of deterioration and memory loss.We address techniques and strategies for using deep learning to the diagnosis of Parkinson's in this research.The proposed method is applied to improve patient care, save costs, and facilitate rapid and precise analysis in large-scale studies. Parkinson's diseases progressive neuro degenerative disorder that affects millions of people worldwide. A brain MRI scan has demonstrated potential as a technique for early Parkinson's disease detection and early detection can improve patient outcomes. The analysis of brain MRI scans for Parkinson's disease has been using more and more deep learning techniques, like convolutional neural networks (CNNs), in recent years. An investigation of Parkinson's disease using brain MRI scans is suggested in this research using a CNN-based network. The suggested system consists of multiple steps: preprocessing the data, extracting features, training the CNN model, and assessing the model's performance on a test set.The proposed work outcomes shows how well the suggested CNN-based method performs in correctly identifying Parkinson's from brain MRI data. The suggested method may enhance Parkinson'sdisease early diagnosis and surveillance, which would benefit patients' outcomes.

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Deep Learning ,Parkinson Disease

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This paper presents a groundbreaking approach to classifying lung and colon cancer from high-dimensional histopathological images, employing an advanced hybrid deep learning model. Our dataset encompasses 20,000 high-resolution images across five distinct classes, posing significant challenges in terms of computational efficiency and model accuracy. The dual-CNN structure of our model ensures a comprehensive extraction of both fine-grained and global features, crucial for accurate cancer classification. Through innovative feature reduction techniques, we effectively mitigate the curse of dimensionality, enhancing the model's computational efficiency and robustness. The integration of global average pooling and dense layers with dropout regularization further contributes to the model's performance, preventing overfitting and ensuring generalizability. Our approach achieves an impressive classification accuracy of 99%, demonstrating the model's capability to handle high-dimensional datasets with precision. This work marks a significant contribution to medical image analysis, providing a reliable and efficient solution for cancer classification and setting a new standard in the field.

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Feature reduction,DL,ML,PCA,Rationale,Feature,F1-Score,Recall,Accuracy

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Stiff Person Syndrome (SPS) is a rare neuroimmunology disorder characterized by severe muscle spasms and stiffness, predominantly affecting axial and limb muscles. While the pathophysiology remains unclear, the presence of antibodies against glutamic acid decarboxylase (GAD) is commonly associated with SPS, although the exact role of these antibodies in disease development is still debated. Current treatment options, including pharmacological interventions and immunotherapy, aim to alleviate symptoms and modify the immune response. However, for patients refractory to conventional therapy, hematopoietic stem cell transplantation (HSCT) has emerged as a promising alternative. Autologous HSCT (AHSCT) involves resetting the immune system using the patient's own stem cells and has shown success in improving symptoms and quality of life in SPS patients. This review provides an overview of the epidemiology, clinical manifestations, diagnosis, immunopathogenesis, and current treatment strategies for SPS. Additionally, it discusses the significance and potential of HSCT, particularly AHSCT, in the management of refractory SPS. Further research is warranted to elucidate the long-term efficacy and safety of HSCT in SPS, as well as to explore its role in pediatric-onset cases and its economic implications compared to conventional therapies.

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 Keywords

1. Stiff Person Syndrome (SPS) 2. Neuroimmunological disorder 3. Muscle spasms 4. Glutamic acid decarboxylase (GAD) antibodies

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With growing environmental concerns, renewable energy sources are crucial in the production of electric power. Power electronics converters are used to interconnect renewable energy sources in order to enhance power quality at the common coupling point (CCP). Distribution Static synchronous compensators (DSTATCOM) is creatively used in this study, an interface unit between the grid and renewable energy source, and a technique for real power exchange between the dynamic load system, grid, and renewable energy source. This paper, titled "Analysis of PV-Based DSTATCOM" aims to investigate and evaluate the effectiveness of a Solar integrated Distribution Static Compensator (DSTATCOM) using the ICOS? method. The study will focus on the performance of the DSTATCOM in reducing problems with power quality such as voltage regulation, reactive power compensation power factor improvement and harmonics while integrating renewable energy sources. Through matlab simulation and analysis, this research will offer insightful information on the practical implementation of DSTATCOM systems with PV integration, contributing to improved power quality and the efficient utilization of renewable energy sources in the distribution network.

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Photovoltaic Cell (PV),Synchronous reference frame(SRF), PV-DSTATCOM, power quality (PQ), reference dc link voltage, MPPT technique,Voltage Source Converter

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