Bacterial contamination of Saudi Arabian paper currency: A report from Al-Kharj

Background: Currency is a public support tool for exchange of commodity and services. It’s prevalent practice for acquiring bread to broast and bath to bed has connected all human being together irrespective of race and occupation. Currency notes along with their denomination values also carry pathogens if contaminated and will act as an agent for infection transference. Therefore the objective of this cross-sectional study was to assess the load microbial pathogens of paper currency collected in selected public places of Al-Kharj, Saudi Arabia.Methods: Currency notes under study were assessed through microbiological culture, microscopic and biochemical visualization techniques.Results: The results from this cross-sectional study suggested that lower the currency denominations higher was the microbial contaminations, frequency percentage was lower with higher isolations. Small eateries were the biggest source of contaminated currency from the ten selected centres. Percentage microorganism occurrence for Bacillus sp., Staphylococcus sp., Klebsiella sp. and E. coli was 56.84%, 25.03%, 13.40% and 04.71% respectively in all currency notes under study.Conclusions: The outcomes of this study revealed that currency notes can be a source for microbe transmission causing infectious diseases represent public health hazards to the community and individuals

On secrecy performance of mixed generalized Gamma and Málaga RF-FSO variable gain relaying channel

The emergence of an array of new wireless networks has led researchers to evaluate the prospect of utilizing the physical properties of the wireless medium in order to design secure systems. In this paper, the physical layer secrecy performance of a mixed radio frequency-free space optical (RF-FSO) system with variable gain relaying scheme is investigated in the presence of an eavesdropper. We assume that the eavesdropper can wiretap the transmitted confidential data from the RF link only. It is further assumed that the main and eavesdropper RF links are modeled as generalized Gamma (GG) fading channel, and the free space optical (FSO) link experiences Málaga turbulence with pointing error impairment. Our primary concern is to protect this confidential information from being wiretapped. Besides pointing error, the atmospheric turbulence and two types of detection techniques (i.e. heterodyne detection and intensity modulation with direct detection) are also taken into consideration. Utilizing amplify-and-forward (AF) scheme, the novel mathematical closed-form expressions for average secrecy capacity, lower bound of secrecy outage probability, and strictly positive secrecy capacity are derived. As both the links (RF and FSO) undergo generalized fading channels, the derived expressions are also general. We present a unification of some existing works utilizing the proposed model to better clarify the novelty of this work. Finally, all the derived expressions are justified via Monte-Carlo simulations

A newly developed integrative bio-inspired artificial intelligence model for wind speed prediction

Accurate wind speed (WS) modelling is crucial for optimal utilization of wind energy. NumericalWeather Prediction (NWP) techniques, generally used for WS modelling are not only less cost-effective but also poor in predicting in shorter time horizon. Novel WS prediction models based on the multivariate empirical mode decomposition (MEMD), random forest (RF) and Kernel Ridge Regression (KRR) were constructed in this paper better accuracy in WS prediction. Particle swarm optimization algorithm (PSO) was employed to optimize the parameters of the hybridized MEMD model with RF (MEMD-PSO-RF) and KRR (MEMD-PSO-KRR) models. Obtained results were compared to those of the standalone RF and KRR models. The proposed methodology is applied for monthly WS prediction at meteorological stations of Iraq, Baghdad (Station1) and Mosul (Station2) for the period 1977-2013. Results showed higher accuracy of MEMD-PSO-RF model in predicting WS at both stations with a correlation coefficient (r) of 0.972 and r D 0.971 during testing phase at Station1 and Station2, respectively. The MEMD-PSO-KRR was found as the second most accurate model followed by Standalone RF and KRR, but all showed a competitive performance to the MEMD-PSO-RF model. The outcomes of this work indicated that the MEMD-PSO-RF model has a remarkable performance in predicting WS and can be considered for practical applications

Optimising the detectability of H5N1 and H5N6 highly pathogenic avian influenza viruses in Vietnamese live-bird markets

Live bird markets (LBMs) are major targets for avian influenza virus (AIV) surveillance programmes. While sampling the LBM environment has become a widely used alternative to the labour-intensive sampling of live poultry, the design of surveillance programmes and the interpretation of their results are compromised by the lack of knowledge about the effectiveness of these sampling strategies. We used latent class models and a unique empirical dataset collated in Vietnamese LBMs to estimate the sensitivity and specificity of five different sample types for detecting AIVs subtypes H5N1 and H5N6: oropharyngeal duck samples, solid and liquid wastes, poultry drinking water and faeces. Results suggest that the sensitivity of environmental samples for detecting H5N1 viruses is equivalent to that of oropharyngeal duck samples; however, taking oropharyngeal duck samples was estimated to be more effective in detecting H5N6 viruses than taking any of the four environmental samples. This study also stressed that the specificity of the current surveillance strategy in LBMs was not optimal leading to some false positive LBMs. Using simulations, we identified 42 sampling strategies more parsimonious than the current strategy and expected to be highly sensitive for both viruses at the LBM level. All of these strategies involved the collection of both environmental and oropharyngeal duck samples

Quantitative response of wheat to sowing dates and irrigation regimes using ceres-wheat model

An experiment was conducted at Punjab Agricultural University, Ludhiana during 2014–15 and 2015–16, keeping four sowing dates {25th Oct (D1), 10th Nov (D2), 25th Nov (D3) and 10th Dec (D4)} in main plots and five irrigation schedules {irrigation at 15 (FC15), 25 (FC25), 35 (FC35) and 45 (FC45) % depletion of soil moisture from field capacity (FC) and a conventional practice} in sub plots. The objective of the study was to evaluate the performance of CERES-Wheat model for simulating yield and water use under varying planting and soil moisture regimes. The simulated and observed grain yield was higher in D1, with irrigation applied at FC15 as compared to all other sowing date and irrigation regime combinations. Simulated grain yield decreased by 19% with delay in sowing from 25th October to 10th December because of 8% reduction in simulated crop evapotranspiration. Simulated evapotranspiration decreased by 16%, wheat grain yield by 23% and water productivity by 15% in drip irrigation at 45% depletion from field capacity as compared to drip irrigation at 15% of field capacity. It was further revealed that the model performed well in simulating the phenology, water use and yield of wheat

Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results demonstrate widespread moderate improvements in overall anemia prevalence but identify only three LMICs with a high probability of achieving the WHO GNT by 2030 at a national scale, and no LMIC is expected to achieve the target in all their subnational administrative units. Our maps show where large within-country disparities occur, as well as areas likely to fall short of the WHO GNT, offering precision public health tools so that adequate resource allocation and subsequent interventions can be targeted to the most vulnerable populations

Global mortality from dementia : Application of a new method and results from the Global Burden of Disease Study 2019

Introduction Dementia is currently one of the leading causes of mortality globally, and mortality due to dementia will likely increase in the future along with corresponding increases in population growth and population aging. However, large inconsistencies in coding practices in vital registration systems over time and between countries complicate the estimation of global dementia mortality. Methods We meta-analyzed the excess risk of death in those with dementia and multiplied these estimates by the proportion of dementia deaths occurring in those with severe, end-stage disease to calculate the total number of deaths that could be attributed to dementia. Results We estimated that there were 1.62 million (95% uncertainty interval [UI]: 0.41-4.21) deaths globally due to dementia in 2019. More dementia deaths occurred in women (1.06 million [0.27-2.71]) than men (0.56 million [0.14-1.51]), largely but not entirely due to the higher life expectancy in women (age-standardized female-to-male ratio 1.19 [1.10-1.26]). Due to population aging, there was a large increase in all-age mortality rates from dementia between 1990 and 2019 (100.1% [89.1-117.5]). In 2019, deaths due to dementia ranked seventh globally in all ages and fourth among individuals 70 and older compared to deaths from other diseases estimated in the Global Burden of Disease (GBD) study. Discussion Mortality due to dementia represents a substantial global burden, and is expected to continue to grow into the future as an older, aging population expands globally.Peer reviewe

Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results demonstrate widespread moderate improvements in overall anemia prevalence but identify only three LMICs with a high probability of achieving the WHO GNT by 2030 at a national scale, and no LMIC is expected to achieve the target in all their subnational administrative units. Our maps show where large within-country disparities occur, as well as areas likely to fall short of the WHO GNT, offering precision public health tools so that adequate resource allocation and subsequent interventions can be targeted to the most vulnerable populations.Peer reviewe