Background Breast cancer (BCa) is a leading cause of mortality among women in Bangladesh. Many young women in Bangladesh have poor knowledge about breast cancer screening, including risk factors, warning signs/symptoms, diagnosis and early detection. We investigated awareness about breast cancer risk factors as a screening tool among women at the Sheikh Hasina Medical College (SHMC) of Tangail district in Bangladesh. Methods A cross sectional survey was conducted to collect data via a structured questionnaire from SHMC during the period of February to December 2019. A total of 1,007 participants (aged 33.47 (±12.37 years)) was considered for data analysis. Results Of the 1,007 women, about 50% were knowledgeable about the risk factors. Pain in the breast was identified as the most commonly warning sign/symptom of breast cancer. Only 32.2% of respondents knew at least one breast cancer screening method. The mean knowledge was scored 3.43 ± 2.25 out of a total possible score of 8. Awareness of BCa was associated with residence, family history of breast cancer, marital, literacy and socio-economic status (p <0.05). Only 14.7% of women who knew about BSE said they were conducting regular breast self-examination. Unmarried women (aOR: 2.971; 95% CI: 1.108–7.968) were more likely to have performed BSE compared to married women (p <0.05). Conclusion Although most participants were aware of breast cancer; knowledge about risk factors, warning signs/symptoms, early diagnosis and detection was relatively poor. Knowledge about performing BSE was particularly low. This highlights the importance of increasing awareness about breast cancer risk factors and early detection among young women in Bangladesh.
Water quality is one of the main indicators of the quality of service provided to consumers. Quality has an impact on both the public health and aesthetic value of water as a consumable product. Kenya is classified as a water-scarce country with only 647 cubic meters of renewable freshwater per capita. Water distributed in Nairobi is faced with a myriad of challenges leading to a compromise to its quality. This study focused on evaluating quality of drinking water since human health depends on adequate, clean, reliable water. Analyses were carried out at National Environmental Management Authority (NEMA) accredited Jomo Kenyatta University of Agriculture and Technology (JKUAT) laboratories to determine the chemical, bacteriological and physical characteristics of consumed water in Umoja Innercore Estate in Nairobi. In the study area, 7 HH and 6 BH sites were randomly distributed. pH, turbidity and temperature measurements were analyzed in-situ while bacteria and chemicals were analyzed in laboratories. The study found that 100% of boreholes recorded unsatisfactory water with up to 1100 of Escherichia coli (E. coli) showing high contamination with faecal coliforms and 83% of boreholes recording pH of up to 9.53. Dissolved oxygen was 5.08 mg/L below recommended 12.0 mg/L, salinity of 0.47 mg/L and 0.03 mg/L for boreholes and households respectively. The study reveals the deprived quality of water available to the residents of Umoja Innercore, Nairobi. The study recommends the use of biosand filtration methods for septic tanks, digging of deeper boreholes and lining septic tanks with impermeable materials to prevent contamination of ground water with raw water from septic.
Water is one of the most vital elements of ecosystem and human being, but unfortunately nowadays, the pollution of surface and drinking water is an alarming problem. The present work deals with the assessment of physicochemical and bacteriological profile of several pond, jar and tube-well water samples to ensure its suitability for using and drinking. Total 30 samples were randomly selected and collected from Nakla Paurosova of Sherpur district by following the standard procedure. Bacteriological analysis was carried out by following the standard bacteriological methods. Most of the surface water sampling points were polluted by dumping of waste, cattle wash and were not suitable for drinking or other domestic purposes. Among three heavy metals, only Iron was detected in six tube-well water samples, one was also positive to arsenic, rest of the water bodies were negative to all of these metals.
Genetic variation is a key component for improving a stock through selective breeding programs. Randomly amplified polymorphic DNA (RAPD) marker was used to assay genetic variation in two river populations (Halda and Padma) as well as in three hatchery populations of the commercially important Indian major carp, C. catla. Five specimens of each population were collected from each location. Genomic DNA was isolated from the muscle tissue. Five primers were used and in total, 117 bands were obtained of which 51.57% bands were polymorphic. Overall proportions of polymorphism obtained from different populations were found to be 75%, 62%, 50%, 37.5% and 33.33% for BoluharBaor hatchery, Halda and Padma River, Kapotakkha hatchery, and Ma-Fatema hatchery respectively. The highest percentage of intrapopulation genetic similarity was found to be 61.81% in case of Baluhar Baor hatchery and the lowest was found to be 25.63% in case of Kapathakha hatchery. The highest percentage of interpopulation genetic similarity was found to be 85.21% between Kapathakha and Ma-Fatema hatchery population; and the lowest was found to be 46.00% in case of Kapathakha and BaluharBaor hatchery population. The dendrogram on Average Unweighted Pair Group Method of Arithmatic Mean (UPGMA) showed two clusters, the Halda River and BaluharBaor hatchery population forming one cluster and the other populations the second cluster. Genetic variation obtained in different population of C.catla in the present study is highly satisfactory and indicates that the species can be very easily employed for exploitation for genetic improvement through selection.DOI: http://dx.doi.org/10.3126/10.3126/ijls.v9i1.11924 International Journal of Life Sciences Vol.9(1) 2015 37-42
In this paper, we describe novel encoding and decoding methods for multi-scale difference equation (MSDE) signal models. Recently, MSDE signal models have been introduced to exploit self-similarities in signals. The encoding process for MSDE models requires an adaptive signal representation from the dictionary of translations and dilations of the signal to be modeled. Here, we propose a new iterative technique that tries to select an 'active' set under the modeling constraints so that the portion of the signal representation due to the 'inactive' set has small or zero norm. Using methods similar to 'line searches and backtracking' used for global non-linear optimization, this method yields the global minima for exact representation. The decoding process involves an eigenvector analysis of a particular matrix. We provide a fast algorithm to obtain the required eigenvector in O ( N 2 log N ) operations. We also provide a perturbation analysis of MSDE models that gives a bound on the reconstruction error due to errors in the MSDE coefficients.
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