Fast and Accurate Background Reconstruction Using Background Bootstrapping

The goal of background reconstruction is to recover the background image of a scene from a sequence of frames showing this scene cluttered by various moving objects. This task is fundamental in image analysis, and is generally the first step before more advanced processing, but difficult because there is no formal definition of what should be considered as background or foreground and the results may be severely impacted by various challenges such as illumination changes, intermittent object motions, highly cluttered scenes, etc. We propose in this paper a new iterative algorithm for background reconstruction, where the current estimate of the background is used to guess which image pixels are background pixels and a new background estimation is performed using those pixels only. We then show that the proposed algorithm, which uses stochastic gradient descent for improved regularization, is more accurate than the state of the art on the challenging SBMnet dataset, especially for short videos with low frame rates, and is also fast, reaching an average of 52 fps on this dataset when parameterized for maximal accuracy using acceleration with a graphics processing unit (GPU) and a Python implementation.

Control Strategy Research of Based on Resonance Feedforward and Current Estimate of the Photovoltaic Grid Inverter

Due to poor quality of grid-connected current and large impedance value of grid are caused in weak grid environment. Therefore, a control strategy combining multiple resonant feedforward and current estimation method is adopted in this paper. Firstly, in order to make the positive feedback channel have the feedback effect only at the main background harmonics, the low-order harmonics of the grid are extracted by using the method of multi-resonance feedforward control. At the same time, under the premise that the suppression effect of LCL natural resonant frequency remains unchanged, the current estimation method is added into the control strategy, so as to reduce the system cost. Finally, the simulation results show that thus verifying the correctness and effectiveness of the control strategy.

Fast and Accurate Background Reconstruction Using Background Bootstrapping

The goal of background reconstruction is to recover the background image of a scene from a sequence of frames showing this scene cluttered by various moving objects. This task is fundamental in image analysis, and is generally the first step before more advanced processing, but difficult because there is no formal definition of what should be considered as background or foreground and the results may be severely impacted by various challenges such as illumination changes, intermittent object motions, highly cluttered scenes, etc. We propose in this paper a new iterative algorithm for background reconstruction, where the current estimate of the background is used to guess which image pixels are background pixels and a new background estimation is performed using those pixels only. We then show that the proposed algorithm, which uses stochastic gradient descent for improved regularization, is more accurate than the state of the art on the challenging SBMnet dataset, especially for short videos with low frame rates, and is also fast, reaching an average of 52 fps on this dataset when parameterized for maximal accuracy using GPU acceleration and a Python implementation.

Elemental Composition and Cell Mass Quantification of Cultured Thraustochytrids Unveil Their Large Contribution to Marine Carbon Pool

The element stoichiometry of bacteria has received considerable attention because of their significant role in marine ecosystems. However, relatively little is known about the composition of major structural elements of the unicellular heterotrophic protists—thraustochytrids, despite their widely recognized contribution to marine nutrient cycling. Here, we analyze the cell volume and elemental C, N, H, and S cell content of seven cultured thraustochytrids, isolated from different marine habitats, in the exponential and stationary growth phases. We further derive the relationships between the cell volume and elemental C and N content of the cultured thraustochytrids. The cell volumes varied significantly (p < 0.001) among the isolates, with median values of 96.9 and 212.5 μm3 in the exponential and stationary phases, respectively. Our results showed a significantly higher percentage of C (64.0 to 67.5) and H (9.9 to 13.2) but a lower percentage of N (1.86 to 2.16) and S (0.34 to 0.91) in the stationary phase, along with marked variations of C and N fractions among isolates in the exponential phase. The cell C (5.7 to 203.7 pg) and N (0.65 to 6.1 pg) content exhibited a significant (p < 0.001) linear relationship with the cell volume (27.7 to 510 μm3). On further analysis of the relationship across the two growth phases, we found the equation (cell C (pg) = 0.356 × cell volume (μm3) + 20.922) for stationary phase cells more appropriate for C estimation of natural thraustochytrids. This study provides the first experimental evidence of higher cell C density than the current estimate and relatively larger C contribution of thraustochytrids than bacteria to the marine organic pool.

Global Patterns in Culturable Soil Yeast Diversity

Yeasts, broadly defined as unicellular fungi, fulfill essential roles in soil ecosystems as decomposers and nutrition sources for fellow soil-dwellers. Broad-scale investigations of soil yeasts pose a methodological challenge as metagenomics are of limited use on this group of fungi. Here we characterize global soil yeast diversity using fungal DNA barcoding on 1473 yeasts cultured from 3826 soil samples obtained from nine countries in six continents. We identify mean annual precipitation and international air travel as two significant predictors of soil yeast community structure and composition worldwide. Anthropogenic influences on soil yeast communities, directly via travel and indirectly via altered rainfall patterns resulting from climate change, are concerning as we found common infectious yeasts frequently distributed in soil in several countries. Our discovery of 41 putative novel species highlights the need to revise the current estimate of ~1500 recognized yeast species. Our findings demonstrate the continued need for culture-based studies to advance our knowledge of environmental yeast diversity.

Automatic Tempered Posterior Distributions for Bayesian Inversion Problems

We propose a novel adaptive importance sampling scheme for Bayesian inversion problems where the inference of the variables of interest and the power of the data noise are carried out using distinct (but interacting) methods. More specifically, we consider a Bayesian analysis for the variables of interest (i.e., the parameters of the model to invert), whereas we employ a maximum likelihood approach for the estimation of the noise power. The whole technique is implemented by means of an iterative procedure with alternating sampling and optimization steps. Moreover, the noise power is also used as a tempered parameter for the posterior distribution of the the variables of interest. Therefore, a sequence of tempered posterior densities is generated, where the tempered parameter is automatically selected according to the current estimate of the noise power. A complete Bayesian study over the model parameters and the scale parameter can also be performed. Numerical experiments show the benefits of the proposed approach.

Prevalence and associated factors of undernutrition among pregnant women visiting ANC clinics in Silte zone, Southern Ethiopia

Background Maternal undernutrition is highly prevalent in underdeveloped countries. Hence, this study was intended to determine the prevalence and associated factors of undernutrition among pregnant women visiting ANC clinics in Silte Zone. Method Facility-based cross-sectional study was conducted from July to January 2019. Systematic random sampling technique was used to select 422 study participants from 11 randomly selected health facilities. Data was collected by using a structured-interviewer administered questionnaire. Mid upper arm circumference (MUAC) was measured by standard non stretchable MUAC tape. Data was entered into a computer using Epi data 3.1 and edited, cleaned, and analyzed using SPSS version 20. Both bivariate and multiple logistic regression analyses were employed to identify factors associated with maternal undernutrition. Result In this study, the overall prevalence of undernutrition among study subjects was 21.8%. Age greater than 31 years of women (AOR = 0.15; 95% CI: 0.03, 0.93), Birth intervals > 2 years (AOR = 0.18; 95% CI: 0.04, 0.76), good nutritional knowledge (AOR = 0.34; 95% CI: 0.17, 0.67), and having no dietary change as a result of current pregnancy AOR = 6.02; 95% CI: 2.99, 12.14) were significantly associated with undernutrition. Conclusions The prevalence of undernutrition among pregnant women was 21.8%. Current estimate is lower than previously reported in the study area but higher than reported in developed country. Age of women, Birth intervals, and Dietary change as a result of current pregnancy and Nutrition knowledge were important risk factors/ predictors of undernutrition (MUAC < 23 cm). Interventions targeting maternal nutrition education and child spacing with giving special emphasis to adolescent pregnant women are recommended.

Prevalence and associated factors of undernutrition among pregnant women visiting ANC clinics in Silte zone, southern Ethiopia

Background: Maternal undernutrition is highly prevalent in underdeveloped countries. Hence, this study was intended to determine the prevalence and associated factors of undernutrition among pregnant women visiting ANC clinics in Silte Zone..Method: Facility-based cross-sectional study was conducted from July to January 2019. Systematic random sampling technique was used to select 422 study participants from 11 randomly selected health facilities. Data was collected by using a structured-interviewer administered questionnaire. Mid upper arm circumference (MUAC) was measured by standard non stretchable MUAC tape. Data was entered into a computer using Epi data 3.1 and edited, cleaned, and analyzed using SPSS version 20. Both bivariate and multiple logistic regression analyses were employed to identify factors associated with maternal undernutrition.Result: In this study, the overall prevalence of undernutrition among study subjects was 21.8%. Age greater than 31 years of women (AOR=0.15; 95% CI: 0.03, 0.93), Birth intervals > 2 years (AOR= 0.18; 95% CI: 0.04, 0.76), good nutritional knowledge (AOR=0.34; 95% CI: 0.17, 0.67), and having no dietary change as a result of current pregnancy AOR=6.02; 95% CI: 2.99, 12.14) were significantly associated with undernutrition.Conclusions: The prevalence of undernutrition among pregnant women was 21.8 %. Current estimate is lower than previously reported in the study area but higher than reported in developed country. Age of women, Birth intervals, and Dietary change as a result of current pregnancy and Nutrition knowledge were important risk factors/ predictors of undernutrition (MUAC < 23 cm). Interventions targeting maternal nutrition education and child spacing with giving special emphasis to adolescent pregnant women are recommended.

Underreporting of the 5-year tetanus, diphtheria, pertussis and polio booster vaccination in the Danish Vaccination Register

Background In Denmark, vaccination coverage is measured using the Danish Vaccination Register (DDV). In general, the vaccination coverage is high, but for some vaccinations, the coverage is suboptimal with geographical variation. This study aims to validate the vaccination coverage of the 5-year booster and identify overall reasons for non-vaccination in Copenhagen. Methods We validated the coverage of the 5-year tetanus, diphtheria, pertussis and polio booster for children born in 2010 and living in Copenhagen municipality in 2018, an area with low coverage (current estimate: 89%). We identified all children born in 2010 in the Civil Registration System and sent an electronic questionnaire to parents of children without a record of the 5-year booster in the DDV. Results Parents of 692 children were contacted and 49% participated. Of those, 186 (55%) reported that the child was vaccinated: 61% by their general practitioner and 34% abroad. The most common reason for non-vaccination was forgetfulness (31%), 26% did not want their child vaccinated and 17% had migrated from abroad and were not aware of the vaccination schedule. Considering only children with documentation for the vaccination, the corrected vaccination coverage was 91%. Conclusions We conclude that the coverage of the 5-year booster in Copenhagen is currently underestimated and should be adjusted by 2%. We recommend increased awareness from general practitioners and tailored communication about the vaccination programme targeting immigrants in Denmark.