Md. Kamruzzaman

Drought analysis and its implication in sustainable water resource management in Barind area, Bangladesh

The study analyzes drought using Standardized Precipitation Index (SPI) and Mann-Kendall (MK) Trend Test in the context of the impacts of drought on groundwater table (GWT) during the period 1971-2011 in the Barind area, Bangladesh. The area experienced twelve moderate to extreme agricultural droughts in the years 1972, 1975, 1979, 1982, 1986, 1989, 1992, 1994, 2003, 2005, 2009 and 2010. Some of them coincide with El Niño events. Hydrological drought also occurred almost in the same years. However, relationship between all drought events and El Niño is not clear. Southern and central parts of the area frequently suffer from hydrological drought, northern part is affected by agricultural drought. Trends in SPI values indicate that the area has an insignificant trend towards drought, and numbers of mild and moderate drought are increasing. GWT depth shows strong correlation with rainy season SPI values such that GWT regaining corresponds with rising SPI values and vice versa. However, 2000 onwards, GWT depth is continuously increasing even with positive SPI values. This is due to over-exploitation of groundwater and changes in cropping patterns. Agricultural practice in Barind area based on groundwater irrigation is vulnerable to drought. Hence, adaptation measures to minimize effects of drought on groundwater ought to be taken.

Modeling of agricultural drought risk pattern using Markov chain and GIS in the western part of Bangladesh

The aim of the study is to assess the agricultural drought risk condition in the context of global climate change in the western part of Bangladesh that covers about 45% area of the country for the period of 1960–2011. Drought Index (DI) and Drought Hazard Index (DHI) have been calculated by Markov Chain analysis and that of Drought Vulnerability Index (DVI) from socioeconomic and physical indicators. The DI values show that the northern part in general is more drought-prone, having less crops prospect, whereas the southern part is less drought-prone with high crop potentiality. The probability of extreme drought occurrence increases in recent decades in some parts as a result the drought events become more frequent in the areas. The DHI ranges from 15 to 32, and northern part suffers from more extreme drought hazards than that of southern part. DVI also indicates that northern part is exposed to high to very high drought vulnerability as higher percentage of illiterate people are involved in agricultural practices and high percentage of irrigation to cultivable land, but southern part exposed to moderate to low vulnerability because of low values of vulnerability indicators. Finally, agricultural drought exists at high risk condition in northern part and low in southern parts and 21.63, 26.54 and 29.68% of the area poses very high, high and moderate risk, respectively. So, immediate adaptation measures are needed keeping in mind climate features like rainfall and temperature variability, drought risk and risk ranking to make viable adaptation measures.

Structure modeling to function prediction of Uncharacterized Human Protein C15orf41

The dyserythropoietic anemia disease is a genetic disorder of erythropoiesis characterized by morphological abnormalities of erythroblasts. This is caused by human gene C15orf41 mutation. The uncharacterized C15orf41 protein is involved in the formation of a functional complex structure. The uncharacterized C15orf41 protein is thermostable, unstable and acidic. This is associated with TPD (Treponema Pallidum) domain (135 to 265 residue position) and three PTM sites such as K50 (Acetylation), T114 (Phosphorylation) and K176 (Ubiquitination). C15orf41 is paralogous to isoform-1 (gi|194018542|) and open reading frame isoform-CRA_c (gi|119612744|) of Homo sapiens located at chromosome 15. It interacts with the human ATP (Adenosine Triphosphate) binding domain 4 (ATPBD4) having similarity score 0.725 as per protein-protein interaction (PPI) network analysis. This data provides valuable insights towards the functional characterization of human gene C15orf41.

Prediction of Protein Acetylation Sites using Kernel Naive Bayes Classifier Based on Protein Sequences Profiling

Lysine acetylation is one of the decisive categories of protein post-translational modification (PTM), it is convoluted in many significant cellular developments and severe diseases in the biological system. The experimental identification of protein-acetylated sites is painstaking, time-consuming and expensive. Hence, there is significant interest in the development of computational approaches for consistent prediction of acetylation sites using protein sequences. Features selection from protein sequences plays a significant role for acetylation sites prediction. We describe an improved feature selection approach for acetylation sites prediction based on kernel naive Bayes classifier (KNBC). We have shown that KNBC generated from selected features by a new feature selection method outperforms than the existing methods for identification of acetylation sites. The sensitivity, specificity, ACC (Accuracy), MCC (Matthews Correlation Coefficient) and AUC (Area under Curve of ROC) in our proposed method are as follows 80.71%, 93.39%, 76.73%, 41.37% and 83.0% with the optimum window size is 47. Thus the kernel naive Bayes classifier finds application in acetylation site prediction.

MULTILEVEL LINEAR REGRESSION ANALYSIS OF FACTORS INFLUENCING BODY MASS INDEX AMONG BANGLADESHI MARRIED NON-PREGNANT WOMEN.

The aim of this study was to investigate the socioeconomic and demographic factors influencing the body mass index (BMI) of non-pregnant married Bangladeshi women of reproductive age. Secondary (Hierarchy) data from the 2011 Bangladesh Demographic and Health Survey, collected using two-stage stratified cluster sampling, were used. Two-level linear regression analysis was performed to remove the cluster effect of the variables. The mean BMI of married non-pregnant Bangladeshi women was 21.60±3.86 kg/m2, and the prevalence of underweight, overweight and obesity was 22.8%, 14.9% and 3.2%, respectively. After removing the cluster effect, age and age at first marriage were found to be positively (p<0.01) related with BMI. Number of children was negatively related with womens BMI. Lower BMI was especially found among women from rural areas and poor families, with an uneducated husband, with no television at home and who were currently breast-feeding. Age, total children ever born, age at first marriage, type of residence, education level, level of husbands education, wealth index, having a television at home and practising breast-feeding were found to be important predictors for the BMI of married Bangladeshi non-pregnant women of reproductive age. This information could be used to identify sections of the Bangladeshi population that require special attention, and to develop more effective strategies to resolve the problem of malnutrition.