Volume 12 | Issue 7 |

 Abstract

In today's society, gratitude is a well-established tradition that has been left by the ancestors who lived before us. Gratitude always carries a deep human value as it is the heart of human values that we must follow to make a harmonious human society. Gratitude is considered a feeling of appreciation a person receives from others, which could have been material or immaterial. Regardless of religious faith, gratitude is regarded as a significant human attribute. People acknowledge the goodness in their lives with gratitude, which can also be cultivated by continuously practicing it. Moreover, as per the Buddha's teachings, gratitude is considered the spiritual practice to attain the ultimate goal of human life and a manifestation of loyalty and is referred to as a sense of affection or a feeling that an act of kindness should be positively responded to by others. In this paper, the researcher aims to emphasize the Buddhist perspective of gratitude as a noble virtue in contemporary society to encourage intellectual and personal exploration of this new fertility field of study.

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Gratitude, Buddhism, Four Debts of Gratitude, Moral Value...

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The goal of this article is to design a Agri rover: An affordable agro vehicle for precision farming." India's agriculture industry has a long history of manufacturing commodities of excellent quality and serving as one of the primary economic drivers of the nation. But since most farmers run smaller farms and are poor, we need to develop a portable agricultural vehicle that is affordable for even these farmers. Furthermore, the agricultural vehicles of today are restricted to a single task, such ploughing, water/fertilizer spraying, or sowing. The battery, DC motor, pH meter and pump are the main components of the car. The gem based sunlight based charger is use to charge a battery-powered battery of 12 volts. The engine changes electrical energy over completely to mechanical energy and this energy is utilized to perform various activities like water splashing, furrowing, seed planting with the assistance of switch control instrument. This vehicle is primarily valuable for little size ranches to expand the efficiency.

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Agriculture vehicle, pump, DC motor, battery, Mechanism, Agrirover.

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ABSTRACT The aim of the study is to investigate the predominant factors correlated to the play-ing ability among college level female volleyball players in the Telangana state. To achieve the purpose of the study, 100 female volleyball players who played inter collegiate tournament from various colleges were selected as subjects. The age of the subjects ranged from 18 to 25 years. The anthro-pometric measurements, motor fitness, physiological variables and skill variables were selected as dependent variables and playing ability of female volleyball players as independent variable for this study. The dependent variables were tested with standard testing procedures. To determine the relationship between criterion variable and determinant variables Pearson product moment correlation was used. The computation of multiple regressions was also used. In multiple regres-sions, a criterion variable was predicted from a set of predictors. Step wise selection method of multiple regressions was used in this study to find out the predictor variable that has the highest correlation with the criterion variables and it is entered into the equation first. The rest variables are entered into the equation depending on the contribution of each predictor. In all the cases 0.05 level of significance was fixed to test the hypothesis.

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Key Words: Prediction, Spiking, Muscular Endurance, Shoulder Strength

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ABSTRACT Background: The present research is based on formulation of celecoxib emulgel and determines in-vitro drug release and swelling index of prepared emulgel. Material and Methods: Pure drug of celecoxib was identified by using FTIR spectroscopy and preformulation study of emulgel was performed by using various methods like determination of lamba max, drug solubility studies, melting point of pure drug etc. The present formulation is based on carbapol 934 polymer and other key ingredient and excipients which was used in preparation of anti emulgel. Result: Evaluated the prepared emulgel by their physical appearance, PH, Rheology, Swelling index, microscopic studies, Drug content, % drug release. In all formulation batch, F3 batch formulation was give satisfactory result like that drug content 95.3%, cumulative drug release 92.9 %. Conclusion: As a result, the current study's results unambiguously showed that celecoxib emulgel presents a promising alternative to the traditional dose form. Nevertheless, additional clinical research is required to evaluate the effectiveness of this technique. After taking into account everything mentioned above, it was determined that the current research study's goal could be effectively met.

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Emulgel, Celecoxib, Gel, Jelly Etc.

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This paper explores the firewall security and performance relationship for different firewall systems. The firewall is a important component of the network for safe communication. A firewall acts as a barrier that provides security by controlling security threats. Through a thorough investigation of different firewall technologies, this research aims to recognize the strengths and weaknesses of each firewall system, determining the algorithm and method of network security. This paper is a structural study of research papers which have been carried out on the different Firewall technologies. This research paper focuses on comparative analysis of different methodologies used, accuracy in packet filtration, and the comprehensive evaluation of the performance of various firewall systems.

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Firewall security, Packet filter firewalls, Kernel-based firewalls, Pre-filtering ACL, Cloud-based firewalls, Two-stage algorithm, Redial algorithm, Virtual Machine.

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The increasing popularity of wearable devices like smart watches, smart phones, and wristbands has generated a need to analyze user patterns and activity relationships. This study utilizes the MHHBA Physical Activity Monitoring dataset, consisting of data from 12 different physical activities performed by 10 subjects wearing 3 inertial measurement units and a heart rate monitor. The dataset is invaluable for activity recognition, intensity estimation, and the development of algorithms for data processing, segmentation, feature extraction, and classification. To enhance accessibility, the original data has been transformed and merging all the datasets into a comprehensive CSV file. Leveraging this enriched dataset, we apply machine learning techniques to accurately predict the specific activity a user is engaged in. We employ the K-Nearest Neighbors (KNN) algorithm, Random Forest algorithm, Robust Scalar to standardize the features and Grid Search CV for best neighbors.

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MULTI-SENSOR BASED PHYSICAL ACTIVITY RECOGNITON AND CLASSIFICATION USING MACHINE LEARNING TECHNIQUES

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Bhaarat mein samaan naagarik sanhita (ucc) kaa kryanvayan ek ja?il chunauti pesh karata hai kyonki yah vividh kaanooni pra?aaliyon men saamanjasy sthaapit karanaa owr laingik samaanataa, nyaay aur vyaktigat adhikaron ke muddon ko sambodhit karana chahataa hai. UCC kaa lakshy dhaarmik aur prathaagat prathaon par aadhaarit vyaktigat kaanuunon ko sabhii naagarikon par laaguu naagarik kaanuunon ke ekal se? se badalanaa hai, chaahe unakii dhaarmik yaa saansk?tik p?sh?habhuumi kuchh bhii ho. Haalaanki, ucc ko laagu karane men shaamil vyaavahaarik chunautiyaan mahatvapuur? hain, jinmein mowjuudaa vyaktigat kaanuunon ke saath ucc ko santulit karana, dhaarmik samvedanashiilataaon kaa prabandhan karanaa owr samvaidhaanik owr raajaniitik vichaaron ko dhyaan mein rakhana shaamil hai. UCC ke saamaajik-aarthik nihitaarth bhii mahatvapuur? hain, kyonki yah samaaj ke vibhinn pahaluon, jaise vivaah, talaak, viraasat aur god lene ko prabhaavit kar sakataa hai. Bhaarat ke 22ven vidhi aayog ne haal hi mein is vishay par phir se vichaar kiyaa hai aur sudhaar aur kanooni jaagarukataa kii ja?ilataa ko dur karane ke lie vyaapak paraamarsh aur aam sahamati nirmaa? kii aavashyakataa par prakaash ?aalate hue ucc par janataa kii raay aur vichaar maange hain.

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Laingik Samanata, Samajik Nyaya, Dharmanirpekshta, Vyaktigat Kaanoon, Karyaanvayan Chunoutiyon

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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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