Browsing by Author "Ahamed, Sharif"

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A review on relationship of SNP at rs7975232 (ApaI) of VDR gene and different diseases in different population
(BRAC University, 2023-08) Ahamed, Sharif; Haque, Md. Aminul; Haque, Md. Aminul
A variety of health conditions arise from changes in the gene responsible for the vitamin D receptor (VDR). This gene provides instructions for making a protein called the vitamin D receptor, which is important for how vitamin D works in the body. The way these molecules interact has important implications for predicting a range of health conditions. It's believed that the start of many health problems is connected to differences in the VDR gene. Researchers are particularly interested in studying the effects of these gene differences on various health conditions like osteoporosis, periodontist, hepatitis C, breast cancer, and childhood asthma. Additionally, a lot of research has shown that vitamin D also has a role in how our immune system functions better. This means that differences in the VDR gene could possibly be linked to the development of the health issues mentioned earlier. This study suggests that a specific type of genetic modification, called a single nucleotide polymorphism (SNP) at rs7975232 found the VDR gene, is connected to various health problems.
CLINICAL PREVALENCE OF DIFFERENT DISEASES IN CATTLE AND GOAT AND RISK FACTORS ASSOCIATER WITH PPR IN GOAT AT UPAZILLA VETERINARY HOSPITAL,DEBIDWAR,COMILLA.
(Chattogram Veterinary and Animal Sciences University Chattogram-4225, Bangladesh, 2017-11) Ahamed, Sharif
The study was undertaken to determine the general clinical prevalence of diseases and disorders in cattle and goats at the Upazilla Veterinary Hospital, Debidwar, Comilla during the period from 01.03.17 to 06.04.17 and from 05.07.17 to 03.08.17. A total of 102 clinical cases (35 cattle and 67 goats) were recorded and analyzed. Diagnosis of each of the clinical cases were made on general examination, physical examination, clinical examination and microscopic examination. Among 102 cases,34.31% and 65.69% cases were found in cattles and goats respectively. Among them 68.63% cases were medicinal and 31.37% cases were surgical. Clinical examination detected 13 different types of diseases and disorders in cattles.Whereas,14.29% FMD,17.14% Dermatitis,8.57% Mastitis,8.57% Fasciolosis,2.86% Paramphistomiasis,8.57% keratoconjunctivitis,5.71% Papillomatosis,8.57% abscess,5.71% Myiasis,2.86% Acidosis,2.86% Castration,5.71% Wound and 8.57% Calf scour were found in cattles. Adult males(54.23%) are more affected than young females(45.77%). Clinical examination also detected 11 different types of diseases and disorders in goats.Whereas,38.81% PPR,2.99% Mastitis,1.50% Fasciolosis,1.50% Paramphistomiasis,1.50% keratoconjunctivitis,2.99% abscess,4.48% Myiasis,7.47% Acidosis,26.87% Castration,1.50% Wound and 10.45% Dog biting cases were found in goats. Males(68.66%) are more affected than females(31.34%) and youngs (76.12%) are more affected than adult(23.88%) goats. It may conclude that a number of diseases have been occurring in the Debidwar upazila and this report may help to develop control strategies against major diseases reported in this study.
Design and Development of Chronic Kidney Disease Management System Using Machine Learning
(Daffodil International University, 23-01-29) Emon, Nafiz Ahmed; Ahamed, Sharif
Kidney disease is a chronic condition because it causes a progressive loss of kidney function over time. When kidney function is impaired, the body can no longer perform all of these essential functions, leading to a range of symptoms, including swelling, fatigue, and shortness of breath. That's why early detection of chronic kidney disease is important because it allows for early intervention, which can slow the progression of the disease and prevent or delay the development of end-stage renal failure. Early detection can also help identify treatments to reduce or prevent further damage to the kidneys. The study aims to develop an automated system to predict CKD, identify the stage of CKD, find out the probability of CKD, predict CKD progression, and manage chronic kidney disease. The study proposes a machine-learning-based system using supervised learning algorithms to predict the onset of CKD accurately. The system is designed to use a combination of patient data, such as age, gender, ethnicity, family history, lifestyle, and laboratory test results, to predict and determine the probability of the onset of CKD. In addition, the system is designed to provide personalized recommendations for lifestyle modifications and all the relevant information related to CKD, such as symptoms, risk factors, causes, nutrition, diagnosis and testing, and treatments, and to create awareness about CKD. The study also proposes using interactive visualizations to help patients understand their condition and make informed decisions about their health. The study also outlines a procedure for validating the accuracy of the system and provides recommendations for further development. To predict the CKD, we have applied different machine learning algorithms, including Decision Tree, Ada Boost, KNN, Random Forest, Gradient Boosting, Stochastic Gradient Boosting, XGBoost, and Extra Tree. Of these, Decision Tree and AdaBoost have higher accuracy, at 96.25% each.
Exploring Significant Family Income Ranges of Career Decision Difficulties of Adolescents in Bangladesh Applying Regression Techniques
(2nd International Conference on Electrical, Computer and Communication Engineering, IEEE, 2019-04-04) Satu, Md. Shahriare; Ahamed, Sharif; Chowdhury, Asive; Whaiduzzaman, Md
Career Decision Making is essential part of human life. Most of the people are thinking about this since adolescence. Therefore, we should analyze significant features about career decision difficulties of adolescents in Bangladesh. The goal of this work to explore the most affected class of adolescents about career decision difficulties considering family income ranges in Bangladesh. In this situation, we gathered several records of high school going adolescents at Faridganj, Chandpur, Bangladesh using career decision difficulties questionnaire which was proposed by I. Gati et. al. Hence, several regression algorithms were considered for experimental analysis based on the characteristics of our primary career decision difficulties dataset. After that, these algorithms were applied into career decision difficulties dataset of adolescents and explored the best regression algorithm based on experimental results from them. Then, our selected best algorithm was implemented throughout different datasets (split from primary dataset) and interpreted their findings. Finally, we observed that middle level family income ranges (10000-21000 BDT) of adolescents were faced more difficulties to take proper decision about career than others. This analysis is suggested as a complementary tool for further psychological treatment about career decisions
Exploring Significant Family Income Ranges of Career Decision Difficulties of Adolescents in Bangladesh Applying Regression Techniques
(2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019, 2019-04-04) Satu, Md. Shahriare; Ahamed, Sharif; Chowdhury, Asive; Whaiduzzaman, Md
Career Decision Making is essential part of human life. Most of the people are thinking about this since adolescence. Therefore, we should analyze significant features about career decision difficulties of adolescents in Bangladesh. The goal of this work to explore the most affected class of adolescents about career decision difficulties considering family income ranges in Bangladesh. In this situation, we gathered several records of high school going adolescents at Faridganj, Chandpur, Bangladesh using career decision difficulties questionnaire which was proposed by I. Gati et. al. Hence, several regression algorithms were considered for experimental analysis based on the characteristics of our primary career decision difficulties dataset. After that, these algorithms were applied into career decision difficulties dataset of adolescents and explored the best regression algorithm based on experimental results from them. Then, our selected best algorithm was implemented throughout different datasets (split from primary dataset) and interpreted their findings. Finally, we observed that middle level family income ranges (10000-21000 BDT) of adolescents were faced more difficulties to take proper decision about career than others. This analysis is suggested as a complementary tool for further psychological treatment about career decisions
NUTRITIVE VALUE OF COMMERCIAL BROILER STARTER FEEDS
(Chattogram Veterinary and Animal Sciences University Chattogram-4225, Bangladesh, 2017-11) Ahamed, Sharif
The present study was undertaken to estimate the variations in chemical composition of different broiler starter feeds produced by different feed companies in different areas of Chittagong, Bangladesh. Test results of one hundred four different broiler starter feed samples from different feed companies were collected and compiled in Poultry Research and Training Centre laboratory, Chittagong Veterinary and Animal Sciences University, Chittagong, Bangladesh during October 2014 to December 2016. Samples were analyzed in triplicate for dry matter (DM), crude protein (CP), crude fiber (CF), ether extract (EE), total ash (TA), calcium (Ca) and phosphorus (P) in the PRTC laboratory. Results indicated that, there were variations for different parameters in all the samples. DM content varied from 8.6 to 12.9 g/100g, CP varied from 18.7 to 25.5 g/100g, CF varied from 2.9 to 7.5 g/100g, EE varied from 5.0 to 8.1 g/100g, TA varied from 5.2 to 8.1g/100g, Ca varied from 0.7 to 3.2 g/100g and P varied from 0.4 to 1.0 g/100g. It was concluded that broiler starter feeds should be analyzed before supply to the birds.