Modeling the Effects of Attentional Cueing on Meditators

Training in meditation has been shown to affect functioning of several attentional subsystems, most prominently conflict monitoring, and to some extent orienting. These previous findings described the effects of cueing and manipulating stimulus congruency on response times and accuracies. However, changes in accuracy and response times can arise from several factors. Computational process models can be used to distinguish different factors underlying changes in accuracy and response times. When decomposed by means of the drift diffusion model, a general process model of decision making that has been widely used, both the congruency and cueing effects, is subserved by a change in decision thresholds. Meditators showed a modest overall increase in their decision threshold, which may reflect an ability to wait longer and collect more information before responding

Identification and Characterization of a Bovine Herpesvirus-1 (BHV-1) Glycoprotein gL Which Is Required for Proper Antigenicity, Processing, and Transport of BHV-1 Glycoprotein gH

AbstractDNA sequence analysis of the bovine herpesvirus-1 (BHV-1) genome revealed the presence of an open reading frame named UL1 which exhibited limited homology to glycoprotein gL of herpes simplex virus-1 (S. K. Khattar, S. van Drunen Littel-van den Hurk, L. A. Babiuk, and S. K. Tikoo,Virology213, 28–37). To identify the BHV-1 UL1 protein, rabbit antisera were prepared against two synthetic peptides that were predicted by computer analysis to encompass antigenic epitopes. Sera against both peptides immunoprecipitated a 16- to 17-kDa protein fromin vitrotranslatedin vitrotranscribed mRNA, BHV-1-infected MDBK cells, and purified virions. Enzymatic deglycosylation and lectin binding assays confirmed that the BHV-1 UL1 protein contains only O-linked oligosaccharides and was named glycoprotein gL. Sera against UL22 protein immunoprecipitated a protein of 108 kDa from BHV-1-infected MDBK cells and purified virions, which was modified only by N-linked oligosaccharides and was named glycoprotein gH. Glycoprotein gL expressed by recombinant vaccinia virus was properly processed and secreted into the medium. In contrast glycoprotein gH expressed by recombinant vaccinia virus was found to be retained in the rough endoplasmic reticulum. However, gH coexpressed with gL by recombinant vaccinia viruses was properly processed and transported to the cell surface, suggesting that complex formation between gH and gL is necessary for the proper processing and transport of gH but not gL. In addition gH–gL complex formation is also required for induction of neutralizing antibody response and anchoring of gL to the plasma membrane

Evaluation of European Land Data Assimilation System (ELDAS) products using in site observations

Three land-surface models with land-data assimilation scheme (DA) were evaluated for one growing season using in situ observations obtained across Europe. To avoid drifts in the land-surface state in the models, soil moisture corrections are derived from errors in screen-level atmospheric quantities. With the in situ data it is assessed whether these land-surface schemes produce adequate results regarding the annual range of the soil water content, the monthly mean soil moisture content in the root zone and evaporative fraction (the ratio of evapotranspiration to energy available at the surface). DA considerably reduced bias in net precipitation, while slightly reducing RMSE as well. Evaporative fraction was improved in dry conditions but was hardly affected in moist conditions. The amplitude of soil moisture variations tended to be underestimated. The impact of improved land-surface properties like Leaf Area Index, water holding capacity and rooting depth may be as large as corrections of the DA systems. Because soil moisture memorizes errors in the hydrological cycle of the models, DA will remain necessary in forecast mode. Model improvements should be balanced against improvements of DA per se. Model bias appearing from persistent analysis increments arising from DA systems should be addressed by model improvement

First results of a ferritin‐based blood donor deferral policy in the Netherlands

Algorithms and the Foundations of Software technolog

Increase of Simultaneous Soybean Failures Due To Climate Change

While soybeans are among the most consumed crops in the world, most of its production lies in the US, Brazil, and Argentina. The concentration of soybean growing regions in the Americas renders the supply chain vulnerable to regional disruptions. In 2012, anomalous hot and dry conditions occurring simultaneously in these regions led to low soybean yields, which drove global soybean prices to all-time records. In this study, we explore climate change impacts on simultaneous extreme crop failures as the one from 2012. We develop a hybrid model, coupling a process-based crop model with a machine learning model, to improve the simulation of soybean production. We assess the frequency and magnitude of events with similar or higher impacts than 2012 under different future scenarios, evaluating anomalies both with respect to present day and future conditions to disentangle the impacts of (changing) climate variability from the long-term mean trends. We find long-term trends in mean climate increase the frequency of 2012 analogs by 11–16 times and the magnitude by 4–15% compared to changes in climate variability only depending on the global climate scenario. Conversely, anomalies like the 2012 event due to changes in climate variability show an increase in frequency in each country individually, but not simultaneously across the Americas. We deduce that adaptation of the crop production practice to the long-term mean trends of climate change may considerably reduce the future risk of simultaneous soybean losses across the Americas

Storylines of weather-induced crop failure events under climate change

Unfavourable weather is a common cause for crop failures all over the world. Whilst extreme weather conditions may cause extreme impacts, crop failure commonly is induced by the occurrence of multiple and combined anomalous meteorological drivers. For these cases, the explanation of conditions leading to crop failure is complex, as the links connecting weather and crop yield can be multiple and non-linear. Furthermore, climate change is likely to perturb the meteorological conditions, possibly altering the occurrences of crop failures or leading to unprecedented drivers of extreme impacts. The goal of this study is to identify important meteorological drivers that cause crop failures and to explore changes in crop failures due to global warming. For that, we focus on a historical failure event, the extreme low soybean production during the 2012 season in the midwestern US. We first train a random forest model to identify the most relevant meteorological drivers of historical crop failures and to predict crop failure probabilities. Second, we explore the influence of global warming on crop failures and on the structure of compound drivers. We use large ensembles from the EC-Earth global climate model, corresponding to present-day, pre-industrial +2 and 3 ∘C warming, respectively, to isolate the global warming component. Finally, we explore the meteorological conditions inductive for the 2012 crop failure and construct analogues of these failure conditions in future climate settings. We find that crop failures in the midwestern US are linked to low precipitation levels, and high temperature and diurnal temperature range (DTR) levels during July and August. Results suggest soybean failures are likely to increase with climate change. With more frequent warm years due to global warming, the joint hot–dry conditions leading to crop failures become mostly dependent on precipitation levels, reducing the importance of the relative compound contribution. While event analogues of the 2012 season are rare and not expected to increase, impact analogues show a significant increase in occurrence frequency under global warming, but for different combinations of the meteorological drivers than experienced in 2012. This has implications for assessment of the drivers of extreme impact events

Vitamin D in relation to myocardial structure and function after eight years of follow-up: the Hoorn study.

Background and Aims: To investigate associations between baseline serum 25-hydroxyvitamin D [25(OH)D] levels and myocardial structure and function after 8 years of follow-up in older Dutch subjects. Methods: We included 256 subjects of the Hoorn Study, a population-based cohort. They underwent a standardized 2-dimensional echocardiogram at baseline between 2000 and 2001, and again between 2007 and 2009. We studied the association of 25(OH)D quartiles with echocardiographic measures of the left ventricular mass index (LVMI), left ventricular systolic function and markers of diastolic function using linear regression analyses. Results: At baseline, subjects had a mean age of 67.4 ± 5.2 years and 41.4% had prior cardiovascular disease (CVD). Low serum 25(OH)D levels were only associated with higher LVMI at 8-year follow-up in subjects without prior CVD and in subjects with low kidney function (median estimated glomerular filtration rate ≤77.5 ml/min/1.73

Ferritin trajectories over repeated whole blood donations: results from the FIND+ study

BACKGROUND: Depending on post-donation erythropoiesis, available iron stores, and iron absorption rates, optimal donation intervals may differ between donors. This project aims to define subpopulations of donors with different ferritin trajectories over repeated donations. METHODS: Ferritin levels of 300 new whole blood donors were measured from stored (lookback) samples from each donation over two years in an observational cohort study. Latent classes of ferritin level trajectories were investigated separately using growth mixture models for male and female donors. General linear mixed models assessed associations of ferritin levels with subsequent iron deficiency and/or low hemoglobin. RESULTS: Two groups of donors were identified using group-based trajectory modeling in both genders. Ferritin levels showed rather linear reductions among 42.9% of male donors and 87.7% of female donors. For the remaining groups of donors, steeper declines in ferritin levels were observed. Ferritin levels at baseline and the end of follow-up varied greatly between groups. CONCLUSIONS: Repeated ferritin measurements show depleting iron stores in all-new whole blood donors, the level at which mainly depends on baseline ferritin levels. Tailored, less intensive donation strategies might help to prevent low iron in donors, and could be supported with ferritin monitoring and/or iron supplementation

Seasonal evaluation of the land surface scheme HTESSEL against remote sensing derived energy fluxes of the Transdanubian region in Hungary

The skill of the land surface model HTESSEL is assessed to reproduce evaporation in response to land surface characteristics and atmospheric forcing, both being spatially variable. Evaporation estimates for the 2005 growing season are inferred from satellite observations of the Western part of Hungary and compared to model outcomes. Atmospheric forcings are obtained from a hindcast run with the Regional Climate Model RACMO2. Although HTESSEL slightly underpredicts the seasonal evaporative fraction as compared to satellite estimates, the mean, 10th and 90th percentile of this variable are of the same magnitude as the satellite observations. The initial water as stored in the soil and snow layer does not have a significant effect on the statistical properties of the evaporative fraction. However, the spatial distribution of the initial soil and snow water significantly affects the spatial distribution of the calculated evaporative fraction and the models ability to reproduce evaporation correctly in low precipitation areas in the considered region. HTESSEL performs weaker in dryer areas. In Western Hungary these areas are situated in the Danube valley, which is partly covered by irrigated cropland and which also may be affected by shallow groundwater. Incorporating (lateral) groundwater flow and irrigation, processes that are not included now, may improve HTESSELs ability to predict evaporation correctly. Evaluation of the model skills using other test areas and larger evaluation periods is needed to confirm the results. <br><br> Based on earlier sensitivity analysis, the effect of a number of modifications to HTESSEL has been assessed. A more physically based reduction function for dry soils has been introduced, the soil depth is made variable and the effect of swallow groundwater included. However, the combined modification does not lead to a significantly improved performance of HTESSEL