Nodular Posterior Scleritis: Clinico-Sonographic Characteristics and Proposed Diagnostic Criteria

Purpose: To report the clinical and ultrasound features and outcomes of a series of nodular posterior scleritis. / Methods: Retrospective medical record review of 11 consecutive patients with nodular posterior scleritis. Patient demographics, ocular and systemic findings, ultrasound features, and final anatomical and visual outcomes were recorded. / Results: There were 9 females and 2 males (11 eyes) with mean age at presentation of 57 years (range, 30-84 years). Underlying systemic inflammatory disease was present in 73%. Symptoms included pain in 73% and blurred vision in 45%. A solitary amelanotic mass without the presence of lipofuscin was found in all cases. Associated ocular features included retinal pigment epithelial changes (67%), intraocular inflammation (55%), subretinal fluid (50%), macular edema (50%), and choroidal folds (30%). B-mode ultrasound showed a sclerochoroidal mass with high internal reflectivity (100%) of mean elevation of 4.1 mm. There was nodular thickening of the sclera (100%) and fluid in Tenon space or "T" sign (36%). A complete regression of the nodule after the treatment was observed only in 1 patient (11%) and partial regression in 4 patients (44%). / Conclusion: Nodular posterior scleritis should be considered in the differential diagnosis of a single amelanotic choroidal mass showing high internal reflectivity on ultrasound B-scan. It can produce intraocular inflammation in 50% of the cases and may be painless in 25%. It has a high association with a systemic underlying disease

COCAP : a carbon dioxide analyser for small unmanned aircraft systems

Unmanned aircraft systems (UASs) could provide a cost-effective way to close gaps in the observation of the carbon cycle, provided that small yet accurate analysers are available. We have developed a COmpact Carbon dioxide analyser for Airborne Platforms (COCAP). The accuracy of COCAP's carbon dioxide (CO2) measurements is ensured by calibration in an environmental chamber, regular calibration in the field and by chemical drying of sampled air. In addition, the package contains a lightweight thermal stabilisation system that reduces the influence of ambient temperature changes on the CO2 sensor by 2 orders of magnitude. During validation of COCAP's CO2 measurements in simulated and real flights we found a measurement error of 1.2 mu mol mol(-1) or better with no indication of bias. COCAP is a self-contained package that has proven well suited for the operation on board small UASs. Besides carbon dioxide dry air mole fraction it also measures air temperature, humidity and pressure. We describe the measurement system and our calibration strategy in detail to support others in tapping the potential of UASs for atmospheric trace gas measurements.Peer reviewe

Strong radiative effect induced by clouds and smoke on forest net ecosystem productivity in central Siberia

Aerosols produced by wildfires are a common phenomenon in boreal regions. For the Siberian taiga, it is still an open question if the effects of aerosols on atmospheric conditions increase net CO2 uptake or photosynthesis. We investigated the factors controlling forest net ecosystem productivity (NEP) and explored how clouds and smoke modulate radiation as a major factor controlling NEP during fire events in the years 2012 and 2013. To characterize the underlying mechanisms of the NEP response to environmental drivers, Artificial Neural Networks (ANNs) were trained by eddy covariance flux measurements nearby the Zotino Tall Tower Observatory (ZOTTO). Total photosynthetically active radiation, vapour pressure deficit, and diffuse fraction explain at about 54-58% of NEP variability. NEP shows a strong negative sensitivity to VPD, and a small positive to f(dlf). A strong diffuse radiation fertilization effect does not exist at ZOTTO forest due to the combined effects of low light intensity, sparse canopy and low leaf area index. Results suggests that light intensity and canopy structure are important factors of the overall diffuse radiation fertilization effect.Peer reviewe

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

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

Inverse modelling of European CH4 emissions during 2006-2012 using different inverse models and reassessed atmospheric observations

We present inverse modelling (top down) estimates of European methane (CH4) emissions for 2006-2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions.The inverse models infer total CH4 emissions of 26.8 (20.2-29.7) TgCH(4) yr(-1) (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006-2012 from the four inversion experiments. For comparison, total anthropogenic CH4 emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 TgCH(4) yr(-1) (2006) to 18.8 TgCH(4) yr(-1) (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3-8.2) TgCH(4) yr(-1) from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH4 emissions with maxima in summer, while anthropogenic CH4 emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain.Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH4 compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between -40 and 20% at the aircraft profile sites in France, Hungary and Poland.</p

The CO2 record at the Amazon Tall Tower Observatory : A new opportunity to study processes on seasonal and inter-annual scales

High-quality atmospheric CO2 measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2. In this study, we present the first 6 years (2014-2019) of continuous, high-precision measurements of atmospheric CO2 at the Amazon Tall Tower Observatory (ATTO, 2.1 degrees S, 58.9 degrees W). After subtracting the simulated background concentrations from our observational record, we define a CO2 regional signal (Delta CO2obs) that has a marked seasonal cycle with an amplitude of about 4 ppm. At both seasonal and inter-annual scales, we find differences in phase between Delta CO2obs and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of Delta CO2obs. In addition, we present how the 2015-2016 El Nino-induced drought was captured by our atmospheric record as a positive 2 sigma anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of Delta CO2obs together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales.Peer reviewe