Volume 12 | Issue 7 |

 Abstract

Predicting genomic disorder is a significant and crucial problem in biomedical research. Multivariate diseases with high global death rates, such as cancer, dementia, diabetes, cystic fibrosis, Leigh syndrome, etc., are brought on by genome defects. Historically, theoretical and explanatory Methods for predicting genetic disorders were introduced. As technology advanced, genetic data were expanded to nearly encompass the entire genome and proteins. Subsequently, machine learning and deep learning techniques were employed to forecast disorders related to the genome. Deep learning and machine learning techniques were introduced in parallel. Numerous studies on the prediction of genomic disorders have been carried out in the past utilizing supervised, unsupervised, and semi-supervised learning techniques; the majority of these studies used genetic sequence data to predict binary problems. These techniques' prediction findings were unclear because to due to their reduced accuracy rate and binary class prediction methods that use genome sequence data but do not use the medical history of patients with genome disorders. Consequently, an advanced genomic disorder prediction model (AGDPM) was developed in this study using a huge quantity of data by utilizing XGBoost and SVM, an efficient Machine Learning architecture. When compared to the pre-trained XGBoost model, AGDPM produces the greatest results, with training and testing accuracy rates respectively. Therefore, the advanced genome disease prediction model demonstrates the capacity to process a substantial quantity of data and forecast genomic disorders effectively. genetic disease data from patients using a multi-class prediction technique. According to a number of statistical performance metrics, AGDPM has demonstrated its ability to predict single gene inheritance disorders, mitochondrial gene inheritance disorders, and multifactorial gene inheritance disorders. Therefore, biomedical research will be enhanced with the aid of AGDPM in order to forecast genetic illnesses and control excessive death rates.

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ADVANCE GENOME DISORDER PREDICTION MODEL EMPOWERED WITH MACHINE LEARNING

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The drama Aurat,was first published in 1937 in its native Urdulanguage.Tutun Mukherjee and A.Z. Manzartranslated Auratinto Englishas Woman and published it in the book "Staging Resistance: Plays by Women in Translation" in 2005.The drama provides a profound understanding of the circumstances prevailing in the Muslim community. It is a significant piece of literature that explores the complex dynamics of gender oppression and the gradual awakening of female consciousness.It holds a significant place in Rasheed Jahan`s oeuvre because it not only talks about a women's pitiable condition but it goes a step further and shows her taking a stand which was quite unusual for that era. Through a close analysis of key moments and textual lines, this article examines center character Fatima's journey and transformation and its implications for gender discourse.

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Keywords: Rashid Jahan, 'Woman', Muslim community, Patriarchy, female consciousness.

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Alzheimer's disease (AD) poses a significant global health challenge with limited therapeutic options. Acetyl cholinesterase (Ache) inhibitors represent a cornerstone in AD treatment by enhancing cholinergic neurotransmission. Through in silico techniques, such as molecular docking and molecular dynamics simulations, a library of quinazoline derivatives was screened against the active site of AChE to predict binding affinities and interactions. Structural modifications were systematically explored to optimize inhibitor binding and pharmacokinetic properties. The computational results identified several promising candidates demonstrating potent inhibitory activity against Ache. These compounds exhibited favourable interactions within the enzyme's catalytic site, suggesting their potential efficacy in enhancing cholinergic neurotransmission.

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Alzheimer's disease, neurotransmission, pharmacokinetic, enzyme's catalytic site

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In the present study water sample of Kishore Sagar Lake,Kota from three different sites i.e Near KST Boating Ramp(S1), Near Bhagwan Mahaveer Children's Park(S2), Near Shree Tejaji Maharaj Temple(S3) has been physicochemically evaluated for its suitability for domestic and irrigation purposes. In Physical and Chemical Parameters Such as Temperature, turbidity, pH, T.D.S., Alkalinity, Total hardness, Chloride, Nitrate, Dissolve Oxygen, and B.O.D., were analyzed in the laboratory.The Physico Chemical parameters of water were determined as per standard methods of APHA (2012). The results indicate that the lake water quality is suitable and safe for domestic and irrigation purposes.

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Physicochemical parameters, Kishore Sagar Lake

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Skills were developed in response to the demands of the twenty-first century, which led to a paradigm shift away from traditional teaching methods and towards M-learning in higher education. Students are using their mobile devices for instructional purposes more and more. The purpose of this inquiry is to determine the attitudes of students towards mobile learning by administering a survey. A survey was conducted by research students at the College of Arts, Science, and Commerce, emphasising their perceptions of mobile learning. Online surveys were used to collect the data, and 175 valid answers were chosen for the study. The findings of this study could potentially provide investigators with some understanding of present advances in mobile learning research. In order to improve teaching strategies and learning outcomes in higher education institutions, the current research examines a study on m-learning using mobile devices to determine students' opinions in various dimensions of mobile techniques and perceive the viability of mobile technologies for academic and social purposes.

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Attitude, Mobile Learning, M-learning, Higher Education

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The present era is considered to be a period of the technology- revolution. Information technology is playing a crucial role in bringing this change worldwide. The technological change in this competitive scenario has instigated innovation in products and services. In this respect, the Indian economy has witnessed a prodigious change in its currency from the barter system to the digital payment system. This cash crunch persuaded people to embrace the idea of "My bank, My Money, My Wallet". E-wallet is one of the types of electronic payment systems being widely used these days. This study is centric to customers' perception towards digital wallet, also known as e-wallet with particular emphasis on the twin cities i.e. Hyderabad and Secunderabad. For data collection, structured questionnaires were prepared and distributed to the respondents. It is an empirical study that explains customer's perception towards e-wallet based on their gender, age, occupation, and educational qualification.

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Information technology, Digital Payment System, Customer's Perception, E-Wallet

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Teaching strategies are very important to make classroom instruction very effective and fruitful. In the case of instruction on the Bengali language at the primary level, there are many approaches. But instruction of Bengali language through Group Interactive Strategy and Expository Teaching Strategy may provide an effective output as a result it can be estimated the effectiveness of an instructional strategy for the development of Basic skills in Bengali language. In the Expository teaching approach, students get a narrative about a subject as well as they observe the subject matter through effective demonstration and meaningful learning programs. In Group interactive strategy students can learn the language by interacting among themselves guided by the teacher to minimize the ambiguity in language skills. In teaching new vocabulary, and grammar in Bengali along with prose and poetry and four basic skills of language, an Expository teaching strategy can be used by putting logical descriptions and the inner meaning of prose and poetry in the syllabus. Hence in this paper, the author intends to present the analysis of models and the nature of outcomes by conducting a pilot experiment with two teaching strategies in teaching the Bengali language at the primary level.

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Teaching strategy, Group Interactive Strategy, Expository Strategy, Steps of model, Basic skills of language.

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Education has now witnessed enigmatic changes with the arrival of rapidly developing technology in all possible ways. From the introduction of primitive technology like teaching machines or basic instructional technology to today's artificial intelligence, technology is set to transform the futuristic notion of education across the world. India, being an emerging hub of world education is now most likely to adopt Artificial Intelligence as a part of teaching learning and curriculum transaction. Teachers are the most crucial stakeholders and have the sheer responsibility of adopting Artificial Intelligence into their teaching-learning practices through AI-integrated curricula or professional development mechanisms. This paper will cover 435 relevant studies based on publishing years, publishing mode, type of documents, and index type to formulate a systematic review of using artificial intelligence in Continuous professional development. This systematic Bibliographic review will eventually show the current scenario, scopes, and challenges of integrating Artificial Intelligence in the professional development mechanism of teachers at different levels.

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Artificial Intelligence, Teacher Education, Continuous Professional Development, Systematic Bibliographic reviews

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As more and more DNA sequences are becoming available day by day, storing and transmitting them may require a huge amount of space. This paper introduces a new DNA sequence compression programme which is based on Huffman Technique of compression routine. DNA and RNA sequences can be considered as tests over a four letter alphabet, namely {a,t,g and c} ( note that t is replaced with u in the case of the RNA). For complete genomes, these texts can be very long. Huffman's code also fails badly on DNA sequences both in the static and adaptive model, because there are only four kind symbols in DNA sequences and the probabilities of occurrence of the symbols are not very different[1]. Huffman coding is known to compress not very efficiently [2].This program is developed mainly to merge with dynamic Look up Table method, where sixty eight kind symbols are present. This merge techniques are developed to increase the compression rate/bases. This algorithm can approach a compression rate of 2.1 bits /base and even lower. This compression rate is defined as the compressed file size divided by base number[3]. This algorithm can approach a compression ratio is better than other method. The definition of the compression ratio is the same as in [4] i.e.,1- (|O|/2| I|), where |I| is number of bases in the input DNA sequence and |O| is the length (number of bits) of the output sequence. Compression of these genome sequences will help us increase the efficiency of their use. We use Huffman coding to encode the nucleotide genome sequence , a greedy algorithm that constructs an optimal prefix code called a Huffman code. The algorithm builds the tree T corresponding to the optimal code in a bottom-up manner. It begins with a set of |c| leaves and perform |c|-1 "merging" operations to create the final tree. The total running time of Huffman on the set of n characters is O( n log n). We tested the program on standard benchmark data used in[4]. The greatest advantage of this progrmme is fast execution, small memory occupation and easy implementation. Since this program have been written both in the C language, (Windows platform, and TC compiler) and MATLAB, it is possible to run in other microcomputers with small changes (depending on platform and Compiler used). The program runs on the IBM personal computer, requires 512K, without additional hardware except for disk drives and printer. The execution is quite fast, all the operations are carried out in fraction of seconds, depending on the required task and on the sequence length.

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Huffman algorithm, Biology and genetics, Data Compression

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Thyroid is an essential endocrine gland. Thyroid hormones controls body's fundamental metabolic rate, currently hypothyroidism possessing a measure challenge to medical fraternity in developing as well as developed country. Hypothyroidism is the common clinical condition of thyroid hormone deficiency and if left untreated, can lead to serious adverse health effect on multiple organ systems. Primary hypothyroidism is defined as elevated thyroid stimulating hormone (TSH) concentration in combination with free thyroxin (T4) concentration below the reference range. Hypothyroidism usually associated with the symptoms like weight gain, face puffiness, fatigue, hair loss, constipation. In the conventional system there is no permanent solution for this disease. Hence there is an urgent need for safe and effective alternate solutions where ayurveda can play vital role to resolve the issues. As per classics, Punarnavadi kwatha is one of the potent herbal preparation which acts on sarvanga shopha (~anasarca), Pandu, Udara etc. Though, Punarnavadi kwatha is not indicated directly in hypothyroidism but based on clinical presentation in hypothyroidism like mixed edema, Pandu which are the indications of Punarnavadi kwatha. Hence same medicine used in hypothyroidism associated with these symptoms.

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Hypothyroidism, Thyroid stimulating hormone (TSH), Srotoshodhana, Punarnavadi kwatha

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