The commercial use and unrestricted disposal of synthetic dyes in soil and water-bodies, following the industrial revolution, has led to a major threat towards environmental safety. The azo-dye, Remazol Black B (RBB) is one of the most commonly used synthetic reactive dyes in textile industries. In the present study, the decolourization and biodegradation of RBB were investigated using a bacterium isolated from the marine environment, which was later identified as Pseudomonas aeruginosa AR-7 by 16S rRNA analysis. P. aeruginosa AR-7 showed 99% decolourization at 100mg/L dye concentration when cultured at optimum conditions of incubation i.e., 96h at 37⁰C under static conditions using minimal salts medium (pH 7-9) supplemented with 0.1% glucose and yeast extracts. However, the dye degradation ability of the isolate was reduced to 29% on increasing the dye concentration to 500mg/L. In addition, P. aeruginosa AR-7 showed decolourization and degradation of RBB in wastewater obtained after dyeing a cotton fabric. In further experiments, the Fe3O4 nanoparticles were synthesized using co-precipitation method and were used to immobilize the cells of P. aeruginosa AR-7 by adsorption, in order to compare the RBB degrading abilities of the free and coated cells. The prepared nanoparticles (50-150nm) were characterized by FTIR and SEM analysis to study its structural properties. Also, upon magnetization studies using SQUID magnetometer, Fe3O4 nanoparticles were shown to have a magnetization of about 63emu/g. Interestingly, the coated cells not only showed better degradation ability of RBB but also produced simpler products such as alkane, carboxylic acids, ketone, etc. on complete degradation. On the other hand, the free cells mainly produced esters as indicated by the comparison of GC-MS results.
Abstract. The increasing rate of occurrence of extreme events (droughts and floods) and their rapid transition magnify the associated socio-economic impacts with respect to those caused by the individual event. Understanding of spatio-temporal evolution of wet–dry events collectively, their characteristics, and the transition (wet to dry and dry to wet) is therefore significant to identify and locate most vulnerable hotspots, providing the basis for the adaptation and mitigation measures. The Upper Jhelum Basin (UJB) in South Asia was selected as a case study, where the relevance of wet–dry events and their transition has not been assessed yet, despite clear evidence of climate change in the region. The standardized precipitation evapotranspiration index (SPEI) at the monthly timescale was applied to detect and characterize wet and dry events for the period 1981–2014. The results of temporal variations in SPEI showed a strong change in basin climatic features associated with El Niño–Southern Oscillation (ENSO) at the end of 1997, with the prevalence of wet and dry events before and after 1997 respectively. The results of spatial analysis show a higher susceptibility of the monsoon-dominated region towards wet events, with more intense events occurring in the eastern part, whereas a higher severity and duration are featured in the southwestern part of the basin. In contrast, the westerlies-dominated region was found to be the hotspot of dry events with higher duration, severity, and intensity. Moreover, the surrounding region of the Himalaya divide line and the monsoon-dominated part of the basin were found to be the hotspots of rapid wet–dry transition events.
Abstract. Bias correction (BC) is often a necessity to improve the applicability of global and regional climate model (GCM and RCM, respectively) outputs to impact assessment studies, which usually depend on multiple potentially dependent variables. To date, various BC methods have been developed which adjust climate variables separately (univariate BC) or jointly (multivariate BC) prior to their application in impact studies (i.e., the component-wise approach). Another possible approach is to first calculate the multivariate hazard index from the original, biased simulations, and bias-correct the impact model output or index itself using univariate methods (direct approach). This has the advantage of circumventing the difficulties associated with correcting the inter-variable dependence of climate variables which is not considered by univariate BC methods. Using a multivariate drought index (i.e., SPEI) as an example, the present study compares different state-ofthe- art BC methods (univariate and multivariate) and BC approaches (direct and component-wise) applied to climate model simulations stemming from different experiments at different spatial resolutions (namely CORDEX, CORDEX-CORE and CMIP6). The BC methods are calibrated and evaluated over the same historical period (1986–2005). The proposed framework is demonstrated as a case study over a transboundary watershed, i.e. the Upper Jhelum Basin (UJB) in the Western Himalaya. Results show that (1) there is some added value of multivariate BC methods over the univariate methods in adjusting the inter-variable relationship, however, comparable performance is found for SPEI indices. (2) The best performing BC methods exhibits a comparable performance under both approaches with a slightly better performance for the direct approach. (3) The added value of the high-resolution experiments (CORDEX-CORE) compared to their coarser resolution counterparts (CORDEX) are not apparent in this study.
<p>Global warming and anthropogenic activities have significantly altered the hydrological cycle and amplified the extreme events (floods and droughts) in many regions of the world, with associated environmental, economic, and social losses. For effective hydro extremes hazards management, it is significant to understand how climate change influences the occurrence, duration, and severity of the regional dryness/wetness conditions (droughts/floods). The present study was carried out over Upper Jhelum Basin (UJB) in Pakistan which lies in the western Himalaya, a most effected mountainous range by Climate Change. Firstly, a suitable gridded precipitation dataset was selected/chosen among various datasets (APHRODITE, CHIRPS, ERA5, PGMFD, MSWEP) through spatio-temporal comparison against in situ data at monthly, seasonal, and annual scale. Secondly, selected gridded data was adjusted for biases using linear (Linear scaling-LS, Local intensity scaling-LOCI) and nonlinear (Power transformation-PT and Distribution mapping-DM) statistical methods. Finally, standardized precipitation index (SPI) at multiple time scale was used to analyses dryness/wetness conditions in the Upper Jhelum Basin over a 35-year period (1981&#8211;2015). Results show the higher capability of ERA5 data to represent the UJB precipitation patterns with correlation coefficient (r=0.79) and normalized standard deviation (nSD=1.1), despite of overestimation especially during peak months. Regarding precipitation bias adjustment, all methods were able to correct the mean values while LOCI and DM take advantage over other two methods to correct wet-day probability and precipitation intensity. The SPI analysis at different time scales showed that wet periods occurred more in the first half of the study period, but at later years, drying periods ranging from moderate to severe continue to be seen with increasing frequency. A strong change in dry/wet conditions was observed around years 1997/1998. This change may be the result of the strongest El Nino event (1997-98) occurred in the history. However, further studies are still needed to check whether there is only a large multi-decadal variation or dry conditions will prevail in future. Overall, these findings would assist to better understand the changing pattern of extreme events with climate variability and help water resources managers to develop basin wide appropriate mitigation and adaptation measures to combat climate change and its consequences.&#160;</p>
Abstract. Bias correction (BC) is often a necessity to improve the applicability of global and regional climate model (GCM and RCM, respectively) outputs to impact assessment studies, which usually depend on multiple potentially dependent variables. To date, various BC methods have been developed which adjust climate variables separately (univariate BC) or jointly (multivariate BC) prior to their application in impact studies (i.e., the component-wise approach). Another possible approach is to first calculate the multivariate hazard index from the original, biased simulations and bias-correct the impact model output or index itself using univariate methods (direct approach). This has the advantage of circumventing the difficulties associated with correcting the inter-variable dependence of climate variables which is not considered by univariate BC methods. Using a multivariate drought index (i.e., standardized precipitation evapotranspiration index – SPEI) as an example, the present study compares different state-of-the-art BC methods (univariate and multivariate) and BC approaches (direct and component-wise) applied to climate model simulations stemming from different experiments at different spatial resolutions (namely Coordinated Regional Climate Downscaling Experiment (CORDEX), CORDEX Coordinated Output for Regional Evaluations (CORDEX-CORE), and 6th Coupled Intercomparison Project (CMIP6)). The BC methods are calibrated and evaluated over the same historical period (1986–2005). The proposed framework is demonstrated as a case study over a transboundary watershed, i.e., the Upper Jhelum Basin (UJB) in the Western Himalayas. Results show that (1) there is some added value of multivariate BC methods over the univariate methods in adjusting the inter-variable relationship; however, comparable performance is found for SPEI indices. (2) The best-performing BC methods exhibit a comparable performance under both approaches with a slightly better performance for the direct approach. (3) The added value of the high-resolution experiments (CORDEX-CORE) compared to their coarser-resolution counterparts (CORDEX) is not apparent in this study.
No abstract
Background of the Study: Cardiovascular Disease (CVD) is affecting millions of people in both developed and developing countries. Although the rate of death attributable to the disease has declined in developed countries in the past several decades, it is still the leading cause of death and extorts a heavy social and economic toll globally. In low-middle income countries, the prevalence of CVD has increased dramatically. By 2020, the disease is forecasted to be the major cause of morbidity and mortality in most developing nations. The Global Burden of Disease study estimate of age-standardized CVD death rate of 272 per 100000 populations in India is higher than the global average of 235 per 100000 populations. CAD was estimated to account for around 15%–20% and 6%–9% of all deaths in India and the US. In addition to mortality, CAD is also responsible for morbidity and loss of quality of life Materials and Methods: Qualitative cross-sectional study design with a descriptive research approach was adopted for the present study. The study was conducted in D. Y. Patil Hospital and Terna Multi-Speciality Hospital and Research Centre, Nerul, Navi Mumbai with a sample size of 75. A Non-probability purposive sampling technique was used. In this study samples were patients who underwent Percutaneous revascularization for coronary artery disease. Data was collected using an Interview technique. The data was tabulated and analysed in terms of objectives of the study, using descriptive and inferential statistics. Results: The study results show that the majority of the respondents belonged to the age group 46 - 65 years with a frequency of 27 (36%) and were married 57 (76%). Representation of male respondents was 44 (59%) and the rest of the respondents belonged to female gender. They were educated up to high school and employed (service staff); their monthly income was <30,000. They were currently diagnosed as STEMI 22 (29.33%), NSTEMI 17 (22.66%) and CAD/IHD 36 (48%). All the respondents had undergone PCI for CAD. Majority of them presented with the selected risk factor variables mentioned in the data collection tool. The respondents had knowledge about the classical symptoms of heart attack. However, they were unable to identify the other associative symptoms of heart attack. 97.33% of the respondents verbalized the correct response that is sudden pain and heaviness on the chest (n=73) which reciprocates to and sudden pain at the back of chest bone with pain moving towards the left or both arms (n=18) which reciprocates to 24%. However, few respondents have identified that heart attack is a sudden weakness of the upper arm and lower limb on one side of the body (n=26) which reciprocates to 35% and this option remains incorrect. Although from this (n=8) which reciprocates to 10% of the respondents have also managed to verbalize the right response which suggests that they may not have complete knowledge about heart attack symptoms. There was a significant difference between the number of people who were confident and those who were not confident, also there was a significant difference between confidence to some extent and versus confident (that is P<0.05) about the items on the lifestyle modifying factors. The results indicate that fewer patients were confident about the lifestyle modifying factors. Also, the respondents showed positive correlation (< +1.0) and negative correlation (<-1.0) with risk factor variables. The study findings revealed that, patient did not verbalize complete knowledge and confidence regarding secondary lifestyle modification through the statistical analysis. There is a significant difference between the number of people who were confident versus those who were not confident and there was a significant difference between confidence to some extent versus confidence about the items on the lifestyle modifying factors. Also, there is a significant difference between risk factors and all the lifestyle modifying variables. Conclusion: There were substantial disparities in the confidence levels associated with lifestyle modification and recognition/response to heart attack. These gaps need to be studied further and disseminated to improve awareness in terms of health education in the population which will eventually increase their level of confidence.
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