Attention, predictive learning, and the inverse base-rate effect: Evidence from event-related potentials

We report the first electrophysiological investigation of the inverse base-rate effect (IBRE), a robust non-rational bias in predictive learning. In the IBRE, participants learn that one pair of symptoms (AB) predicts a frequently occurring disease, whilst an overlapping pair of symptoms (AC) predicts a rarely occurring disease. Participants subsequently infer that BC predicts the rare disease, a non-rational decision made in opposition to the underlying base rates of the two diseases. Error-driven attention theories of learning state that the IBRE occurs because C attracts more attention than B. On the basis of this account we predicted and observed the occurrence of brain potentials associated with visual attention: a posterior Selection Negativity, and a concurrent anterior Selection Positivity, for C vs. B in a post-training test phase. Error-driven attention theories further predict no Selection Negativity, Selection Positivity or IBRE, for control symptoms matched on frequency to B and C, but for which there was no shared symptom (A) during training. These predictions were also confirmed, and this confirmation discounts alternative explanations of the IBRE based on the relative novelty of B and C. Further, we observed higher response accuracy for B alone than for C alone; this dissociation of response accuracy (B>C) from attentional allocation (C>B) discounts the possibility that the observed attentional difference was caused by the difference in response accuracy

Tidal controls on trace gas dynamics in a seagrass meadow of the Ria Formosa lagoon (southern Portugal)

Coastal zones are important source regions for a variety of trace gases, including halocarbons and sulfur-bearing species. While salt marshes, macroalgae and phyto-plankton communities have been intensively studied, little is known about trace gas fluxes in seagrass meadows. Here we report results of a newly developed dynamic flux chamber system that can be deployed in intertidal areas over full tidal cycles allowing for highly time-resolved measurements. The fluxes of CO2, methane (CH4) and a range of volatile organic compounds (VOCs) showed a complex dynamic mediated by tide and light. In contrast to most previous studies, our data indicate significantly enhanced fluxes during tidal immersion relative to periods of air exposure. Short emission peaks occurred with onset of the feeder current at the sampling site. We suggest an overall strong effect of advective transport processes to explain the elevated fluxes during tidal immersion. Many emission estimates from tidally influenced coastal areas still rely on measurements carried out during low tide only. Hence, our results may have significant implications for budgeting trace gases in coastal areas. This dynamic flux chamber system provides intensive time series data of community respiration (at night) and net community production (during the day) of shallow coastal systems.German Federal Ministry of Education and Research (BMBF) [03F0611E, 03F0662E]; EU FP7 ASSEMBLE research infrastructure initiative

Don’t make me angry, you wouldn’t like me when I’m angry: volitional choices to act or inhibit are modulated by subliminal perception of emotional faces

Volitional action and self-control—feelings of acting according to one’s own intentions and in being control of one’s own actions—are fundamental aspects of human conscious experience. However, it is unknown whether high-level cognitive control mechanisms are affected by socially salient but nonconscious emotional cues. In this study, we manipulated free choice decisions to act or withhold an action by subliminally presenting emotional faces: In a novel version of the Go/NoGo paradigm, participants made speeded button-press responses to Go targets, withheld responses to NoGo targets, and made spontaneous, free choices to execute or withhold the response for Choice targets. Before each target, we presented emotional faces, backwards masked to render them nonconscious. In Intentional trials, subliminal angry faces made participants more likely to voluntarily withhold the action, whereas fearful and happy faces had no effects. In a second experiment, the faces were made supraliminal, which eliminated the effects of angry faces on volitional choices. A third experiment measured neural correlates of the effects of subliminal angry faces on intentional choice using EEG. After replicating the behavioural results found in Experiment 1, we identified a frontal-midline theta component—associated with cognitive control processes—which is present for volitional decisions, and is modulated by subliminal angry faces. This suggests a mechanism whereby subliminally presented “threat” stimuli affect conscious control processes. In summary, nonconscious perception of angry faces increases choices to inhibit, and subliminal influences on volitional action are deep seated and ecologically embedded

Phase-Noise Degradation of an Optically Distributed Local Oscillator in a Radio Access Network

The experimental evaluation of the phase-noise degradation of an optically distributed opto-electronic oscillator (OEO) signal is presented. The assembled setup is simulating a possible topology for a 5G radio access network (RAN), in which the local oscillator (LO) signal is distributed from the central-office to the base-stations via an existing optical distribution network (ODN). TheOEOin our experiment has a phase noise of -105 dBc/Hz and -124 dBc/Hz at 1 kHz and 10 kHz offsets from the 10.5 GHz carrier, respectively. The degradation of the phase noise of the signal distributed to the base-station within a distance of 20 km is within 4 dB and 6 dB for 1 kHz and 10 kHz offsets from the carrier, respectively. These are promising results for further research and the development of the 5G RAN with a centralized OEO signal distribution

Подготовка медицинских сестер с высшим образованием – важный стратегический шаг в реализации реформ в здравоохранении

Department of Social Medicine and Sanitaty Management, Association of Nursing of the Republic of Moldova, Nicolae Testemitanu State Medical and Pharmaceutical University, Congresul III al Medicilor de Familie din Republica Moldova, 17–18 mai, 2012, Chişinău, Republica Moldova, Conferinţa Naţională „Maladii bronhoobstructive la copii”, consacrată profesorului universitar, doctor habilitat Victor Gheţeul, 27 aprilie, Chişinău, Republica MoldovaIn this article describes the necessity of preparing nurses with high education, which has become a strategic step in implementation of health care reforms. The reforms in primary health care and necessity of optimization of financing health care institutions are arguments for the introduction of such training.B работе описывается необходимость подготовки медицинских сестер с высшим образованием как важный стратегический шаг в реализации медицинских реформ в здравоохранении. Аргументами подготовки являются реформы в сети первичной медицинской помощи и необходимость оптимизации механизмов финансирования учреждений здравоохранения

Country-scale analysis of methane emissions with a high-resolution inverse model using GOSAT and surface observations

We employed a global high-resolution inverse model to optimize the CH4 emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011-2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH4 yr-1 and 232.5 Tg CH4 yr-1, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH4 yr-1, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH4 yr-1), the United States (25.9 ± 8.3 Tg CH4 yr-1), Russia (13.2 ± 9.3 Tg CH4 yr-1), India (12.3 ± 6.4 Tg CH4 yr-1), and Canada (12.2 ± 5.1 Tg CH4 yr-1). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries

Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations

We employed a global high-resolution inverse model to optimize the CH4 emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011–2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH4 yr−1 and 232.5 Tg CH4 yr−1, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH4 yr−1, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH4 yr−1), the United States (25.9 ± 8.3 Tg CH4 yr−1), Russia (13.2 ± 9.3 Tg CH4 yr−1), India (12.3 ± 6.4 Tg CH4 yr−1), and Canada (12.2 ± 5.1 Tg CH4 yr−1). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries

Long-term measurements (2010–2014) of carbonaceous aerosol and carbon monoxide at the Zotino Tall Tower Observatory (ZOTTO) in central Siberia

We present long-term (5-year) measurements of particulate matter with an upper diameter limit of ∼ 10 µm (PM10), elemental carbon (EC), organic carbon (OC), and water-soluble organic carbon (WSOC) in aerosol filter samples collected at the Zotino Tall Tower Observatory in the middle-taiga subzone (Siberia). The data are complemented with carbon monoxide (CO) measurements. Air mass back trajectory analysis and satellite image analysis were used to characterise potential source regions and the transport pathway of haze plumes. Polluted and background periods were selected using a non-parametric statistical approach and analysed separately. In addition, near-pristine air masses were selected based on their EC concentrations being below the detection limit of our thermal–optical instrument. Over the entire sampling campaign, 75 and 48 % of air masses in winter and in summer, respectively, and 42 % in spring and fall are classified as polluted. The observed background concentrations of CO and EC showed a sine-like behaviour with a period of 365 ± 4 days, mostly due to different degrees of dilution and the removal of polluted air masses arriving at the Zotino Tall Tower Observatory (ZOTTO) from remote sources. Our analysis of the near-pristine conditions shows that the longest periods with clean air masses were observed in summer, with a frequency of 17 %, while in wintertime only 1 % can be classified as a clean. Against a background of low concentrations of CO, EC, and OC in the near-pristine summertime, it was possible to identify pollution plumes that most likely came from crude-oil production sites located in the oil-rich regions of Western Siberia. Overall, our analysis indicates that most of the time the Siberian region is impacted by atmospheric pollution arising from biomass burning and anthropogenic emissions. A relatively clean atmosphere can be observed mainly in summer, when polluted species are removed by precipitation and the aerosol burden returns to near-pristine conditions