Suchergebnisse

Abstract
Background
The concentration of heavy metals and their spatial distribution in surface sediments collected from the Thondi coast, Palk Bay, South India were analysed in this study. The sediment grain size, pH, EC, and major elements (Fe, and Al), heavy metal concentrations (Mn, Cr, Zn, Cd, Ni, Cu, and Pb) were determined and the values for the geoaccumulation index (Igeo), enrichment factor (EF), potential contamination index (Cp), potential ecological risk index (RI), contamination factor (CF), modified contamination degree (mCd), degree of contamination (Cd), and potential contamination factors (Cp) were calculated based on their background values to determine the pollution level of the study area. Multivariate analysis such as Pearson's correlation coefficient, principal component analysis/factor analysis (PCA/FA), cluster analysis, and regression analysis are a versatile method for identifying heavy metal sources and determining the relationship between pollutants in marine sediment.

Results
The pollution indices, namely EF, CF, Cd, mCd, CP, RI, and Igeo, revealed that the heavy metal contamination was due to Cd, while a moderate level of contamination was caused by Cu, Zn, Pb, and Cr. The principal component analysis and correlation matrix analysis showed a strong positive loading for Cd due to its high level of contamination in the study area. Anthropogenic inputs such as municipal wastewater, domestic sewage discharge, fishing harbour activities, and industrial and aquaculture wastes led to the increased Cd concentration in the study area. Moreover, the pollution load index revealed that the sediments were polluted by heavy metals.

Conclusion
The findings of this study revealed that the increased concentration of heavy metals in the study area increases the toxicity in the marine environment, thus affecting the ecosystem.

BACKGROUND: Posttraumatic stress disorder (PTSD) and hearing loss are hallmark public health issues related to military service in Iraq and Afghanistan. Although both are significant individual contributors to disability among veterans, their co-occurrence has not been specifically explored. METHODS: A total of 1179 male U.S. military personnel who sustained an injury between 2004 and 2012 during operations in Iraq or Afghanistan were identified from clinical records. Pre- and postinjury audiometric data were used to define new-onset hearing loss, which was categorized as unilateral or bilateral. Diagnosed PTSD was abstracted from electronic medical records. Logistic regression analysis examined the relationship between hearing loss and PTSD, while adjusting for age, year of injury, occupation, injury severity, injury mechanism, and presence of concussion. RESULTS: The majority of the study sample were aged 18–25 years (79.9%) and sustained mild-moderate injuries (94.6%). New-onset hearing loss was present in 14.4% of casualties (10.3% unilateral, 4.1% bilateral). Rates of diagnosed PTSD were 9.1, 13.9, and 29.2% for those with no hearing loss, unilateral hearing loss, and bilateral hearing loss, respectively. After adjusting for covariates, those with bilateral hearing loss had nearly three-times higher odds of PTSD (odds ratio = 2.92; 95% CI, 1.47–5.81) compared to those with no hearing loss. Unilateral hearing loss was not associated with PTSD. CONCLUSIONS: Both PTSD and hearing loss are frequent consequences of modern warfare that adversely affect the overall health of the military. Bilateral, but not unilateral, hearing loss was associated with a greater burden of PTSD. This has implications for warfighter rehabilitation and should encourage collaboration between audiology and mental health professionals.

AbstractUttar Pradesh (UP), with more than 220 million people, is the most populous state in India. Despite a high unmet need for modern family planning methods, the state has experienced a substantial decline in fertility. India has also seen a decline during this period which can be attributed to the increased prevalence of modern methods of family planning, particularly female sterilisation, but in UP, the corresponding increase was marginal. At the same time, Traditional Family Planning Methods (TMs) increased significantly in UP in contrast to India, where it was marginal. The trends in UP raise questions about the drivers in fertility decline and question the conventional wisdom that fertility declines are driven by modern methods, and the paper aims to understand this paradox. Fertility trends and family planning practices in UP were analysed using data from different rounds of National Family Health Surveys (NFHS) and the two UP Family Planning Surveys conducted by the UP Technical Support Unit to understand whether the use of TMs played a role in the fertility decline. As per NFHS-4, the prevalence of TM in India (6%) was less than half that of UP (13%). The UP Family Planning Survey in 25 High Priority Districts estimated that 22% of women used TMs. The analysis also suggested that availability and accessibiility of modern contraceptives might have played a role in the increased use of TMs in UP. If there are still couples who make a choice in favour of TMs, they should be well informed about the risks associated with the use of traditional methods as higher failure rate is observed among TMs users.

Abstract Background Uttar Pradesh (UP) is the most populous state in India with historically high levels of fertility rates than the national average. Though fertility levels in UP declined considerably in recent decades, the current level is well above the government's target of 2.1. Data and methods Fertility and family planning data obtained from the different rounds of Sample Registration System (SRS) and the National Family Health Survey (NFHS). We analyzed fertility and family planning trends in India and UP, including differences in methods mix, using SRS (1971–2016) and NFHS (1992–2016). Bivariate and multivariate regression analyses were used. Results From 2000, while the total fertility rate (TFR) declined in UP, it is still well above the national level in 2015–16 (2.7 vs 2.18, respectively). The demand for family planning satisfied increased from 52 to 72% during 1998–99 to 2015–16 in UP, compared to an increase from 75 to 81% in India. Traditional methods play a much greater role in UP than in India (22 and 9% of the demand satisfied respectively), while use of sterilization was relatively low in UP when compared to the national averages (18.0 and 36.3% of current married women 15–49 years in UP and India, respectively in 2015–16). Within UP, district fertility ranged from 1.6 to 4.4, with higher fertility concentrated in districts with low female schooling, predominantly located in north-central UP. Fertility declines were largest in districts with high fertility in the late nineties (B = 7.33, p < .001). Among currently married women, use of traditional methods increased and accounted for almost one-third of users in 2015–16. Use of sterilization declined but remained the primary method (ranging from 33 to 41% of users in high and low fertility districts respectively) while condom use increased from 17 and 16% in 1998–99 to 23 and 25% in 2015–16 in low and high fertility districts respectively. Conclusions and implications Greater reliance on traditional methods and condoms coupled with relatively low demand for modern contraception suggest inadequate access to modern contraceptives, especially in district with high fertility rates. Family planning activities need to be appropriately scaled according to need and geography to ensure the achievement of state-level improvements in family planning programs and fertility outcomes.

Part 8: High Performance Computing and BigData ; International audience ; The National Computational Infrastructure (NCI) at the Australian National University (ANU) has co-located a priority set of over 10 PetaBytes (PBytes) of national data collections within a HPC research facility. The facility provides an integrated high-performance computational and storage platform, or a High Performance Data (HPD) platform, to serve and analyse the massive amounts of data across the spectrum of environmental collections – in particular from the climate, environmental and geoscientific domains. The data is managed in concert with the government agencies, major academic research communities and collaborating overseas organisations. By co-locating the vast data collections with high performance computing environments and harmonising these large valuable data assets, new opportunities have arisen for Data-Intensive interdisciplinary science at scales and resolutions not hitherto possible.