Can the carbon isotopic composition of methane be reconstructed from multi-site firn air measurements?

Methane is a strong greenhouse gas and large uncertainties exist concerning the future evolution of its atmospheric abundance. Analyzing methane atmospheric mixing and stable isotope ratios in air trapped in polar ice sheets helps in reconstructing the evolution of its sources and sinks in the past. This is important to improve predictions of atmospheric CH4 mixing ratios in the future under the influence of a changing climate. The aim of this study is to assess whether past atmospheric δ13C(CH4) variations can be reliably reconstructed from firn air measurements. Isotope reconstructions obtained with a state of the art firn model from different individual sites show unexpectedly large discrepancies and are mutually inconsistent. We show that small changes in the diffusivity profiles at individual sites lead to strong differences in the firn fractionation, which can explain a large part of these discrepancies. Using slightly modified diffusivities for some sites, and neglecting samples for which the firn fractionation signals are strongest, a combined multi-site inversion can be performed, which returns an isotope reconstruction that is consistent with firn data. However, the isotope trends are lower than what has been concluded from Southern Hemisphere (SH) archived air samples and high-accumulation ice core data. We conclude that with the current datasets and understanding of firn air transport, a high precision reconstruction of δ13C of CH4 from firn air samples is not possible, because reconstructed atmospheric trends over the last 50 yr of 0.3–1.5 ‰ are of the same magnitude as inherent uncertainties in the method, which are the firn fractionation correction (up to ~2 ‰ at individual sites), the Kr isobaric interference (up to ~0.8 ‰, system dependent), inter-laboratory calibration offsets (~0.2 ‰) and uncertainties in past CH4 levels (~0.5 ‰).

Probabilistic approach to cloud and snow detection on Advanced Very High Resolution Radiometer (AVHRR) imagery

Derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. Information about a confidence level of provided physical quantities is required to construct an error budget of higher-level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data a common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher-level products and may alter their usability. Within this scope a novel probabilistic cloud mask (PCM) algorithm suited for the 1 km × 1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on the decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve probability estimates from the precomputed look-up tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of intervals. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the invariant coordinate system (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the Polar Platform System (PPS) version 2012 and Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 cloud masks, SYNOP (surface synoptic observations) weather reports, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical feature mask version 3 and to MODIS collection 5 snow mask. The outcomes of conducted analyses proved fine detection skills of the PCM method with results comparable to or better than the reference PPS algorithm.

Segmentation and Recognition of Multi-Food Meal Images for Carbohydrate Counting

In this paper, we propose novel methodologies for the automatic segmentation and recognition of multi-food images. The proposed methods implement the first modules of a carbohydrate counting and insulin advisory system for type 1 diabetic patients. Initially the plate is segmented using pyramidal mean-shift filtering and a region growing algorithm. Then each of the resulted segments is described by both color and texture features and classified by a support vector machine into one of six different major food classes. Finally, a modified version of the Huang and Dom evaluation index was proposed, addressing the particular needs of the food segmentation problem. The experimental results prove the effectiveness of the proposed method achieving a segmentation accuracy of 88.5% and recognition rate equal to 87%

Measurement with the ATLAS detector of multi-particle azimuthal correlations in p+Pb collisions at sqrtsNN=5.02 TeV

In order to study further the long-range correlations ("ridge") observed recently in p+Pb collisions at sqrt(s_NN) =5.02 TeV, the second-order azimuthal anisotropy parameter of charged particles, v_2, has been measured with the cumulant method using the ATLAS detector at the LHC. In a data sample corresponding to an integrated luminosity of approximately 1 microb^(-1), the parameter v_2 has been obtained using two- and four-particle cumulants over the pseudorapidity range |eta|<2.5. The results are presented as a function of transverse momentum and the event activity, defined in terms of the transverse energy summed over 3.1methods, and to predictions from hydrodynamic models of p+Pb collisions. Despite the small transverse spatial extent of the p+Pb collision system, the large magnitude of v_2 and its similarity to hydrodynamic predictions provide additional evidence for the importance of final-state effects in p+Pb reactions.

Lake surface water temperatures of European Alpine lakes (1989–2013) based on the Advanced Very High Resolution Radiometer (AVHRR) 1 km data set

Lake water temperature (LWT) is an important driver of lake ecosystems and it has been identified as an indicator of climate change. Consequently, the Global Climate Observing System (GCOS) lists LWT as an essential climate variable. Although for some European lakes long in situ time series of LWT do exist, many lakes are not observed or only on a non-regular basis making these observations insufficient for climate monitoring. Satellite data can provide the information needed. However, only few satellite sensors offer the possibility to analyse time series which cover 25 years or more. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown as a heritage instrument for almost 35 years. It will be carried on for at least ten more years, offering a unique opportunity for satellite-based climate studies. Herein we present a satellite-based lake surface water temperature (LSWT) data set for European water bodies in or near the Alps based on the extensive AVHRR 1 km data record (1989–2013) of the Remote Sensing Research Group at the University of Bern. It has been compiled out of AVHRR/2 (NOAA-07, -09, -11, -14) and AVHRR/3 (NOAA-16, -17, -18, -19 and MetOp-A) data. The high accuracy needed for climate related studies requires careful pre-processing and consideration of the atmospheric state. The LSWT retrieval is based on a simulation-based scheme making use of the Radiative Transfer for TOVS (RTTOV) Version 10 together with ERA-interim reanalysis data from the European Centre for Medium-range Weather Forecasts. The resulting LSWTs were extensively compared with in situ measurements from lakes with various sizes between 14 and 580 km2 and the resulting biases and RMSEs were found to be within the range of −0.5 to 0.6 K and 1.0 to 1.6 K, respectively. The upper limits of the reported errors could be rather attributed to uncertainties in the data comparison between in situ and satellite observations than inaccuracies of the satellite retrieval. An inter-comparison with the standard Moderate-resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature product exhibits RMSEs and biases in the range of 0.6 to 0.9 and −0.5 to 0.2 K, respectively. The cross-platform consistency of the retrieval was found to be within ~ 0.3 K. For one lake, the satellite-derived trend was compared with the trend of in situ measurements and both were found to be similar. Thus, orbital drift is not causing artificial temperature trends in the data set. A comparison with LSWT derived through global sea surface temperature (SST) algorithms shows lower RMSEs and biases for the simulation-based approach. A running project will apply the developed method to retrieve LSWT for all of Europe to derive the climate signal of the last 30 years. The data are available at doi:10.1594/PANGAEA.831007.

Anamorphic pixels for multi-channel superresolution

Superresolution from plenoptic cameras or camera arrays is usually treated similarly to superresolution from video streams. However, the transformation between the low-resolution views can be determined precisely from camera geometry and parallax. Furthermore, as each low-resolution image originates from a unique physical camera, its sampling properties can also be unique. We exploit this option with a custom design of either the optics or the sensor pixels. This design makes sure that the sampling matrix of the complete system is always well-formed, enabling robust and high-resolution image reconstruction. We show that simply changing the pixel aspect ratio from square to anamorphic is sufficient to achieve that goal, as long as each camera has a unique aspect ratio. We support this claim with theoretical analysis and image reconstruction of real images. We derive the optimal aspect ratios for sets of 2 or 4 cameras. Finally, we verify our solution with a camera system using an anamorphic lens.

Measurement of flow harmonics with multi-particle cumulants in Pb+Pb collisions at √sNN=2.76 TeV with the ATLAS detector

ATLAS measurements of the azimuthal anisotropy in lead–lead collisions at √sNN = 2.76 TeV are shown using a dataset of approximately 7μb−1 collected at the LHC in 2010. The measurements are performed for charged particles with transversemomenta 0.5 < pT < 20 GeV and in the pseudorapidity range |η| < 2.5. The anisotropy is characterized by the Fourier coefficients, vn, of the charged-particle azimuthal angle distribution for n = 2–4. The Fourier coefficients are evaluated using multi-particle cumulants calculated with the generating function method. Results on the transverse momentum, pseudorapidity and centrality dependence of the vn coefficients are presented. The elliptic flow, v2, is obtained from the two-, four-, six- and eight-particle cumulants while higher-order coefficients, v3 and v4, are determined with two- and four-particle cumulants. Flow harmonics vn measured with four-particle cumulants are significantly reduced compared to the measurement involving two-particle cumulants. A comparison to vn measurements obtained using different analysis methods and previously reported by the LHC experiments is also shown. Results of measurements of flow fluctuations evaluated with multiparticle cumulants are shown as a function of transverse momentum and the collision centrality. Models of the initial spatial geometry and its fluctuations fail to describe the flow fluctuations measurements.

Multi-Environment Model Estimation for Motility Analysis of Caernorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

Mechanisms of recognition and binding of α-TTP to the plasma membrane by multi-scale molecular dynamics simulations

We used multiple sets of simulations both at the atomistic and coarse-grained level of resolution to investigate interaction and binding of α-tochoperol transfer protein (α-TTP) to phosphatidylinositol phosphate lipids (PIPs). Our calculations indicate that enrichment of membranes with such lipids facilitate membrane anchoring. Atomistic models suggest that PIP can be incorporated into the binding cavity of α-TTP and therefore confirm that such protein can work as lipid exchanger between the endosome and the plasma membrane. Comparison of the atomistic models of the α-TTP-PIPs complex with membrane-bound α-TTP revealed different roles for the various basic residues composing the basic patch that is key for the protein/ligand interaction. Such residues are of critical importance as several point mutations at their position lead to severe forms of ataxia with vitamin E deficiency (AVED) phenotypes. Specifically, R221 is main residue responsible for the stabilization of the complex. R68 and R192 exchange strong interactions in the protein or in the membrane complex only, suggesting that the two residues alternate contact formation, thus facilitating lipid flipping from the membrane into the protein cavity during the lipid exchange process. Finally, R59 shows weaker interactions with PIPs anyway with a clear preference for specific phosphorylation positions, hinting a role in early membrane selectivity for the protein. Altogether, our simulations reveal significant aspects at the atomistic scale of interactions of α-TTP with the plasma membrane and with PIP, providing clarifications on the mechanism of intracellular vitamin E trafficking and helping establishing the role of key residue for the functionality of α-TTP.

Long-term hydrological dynamics and fire history over the last 2000 years in CE Europe reconstructed from a high-resolution peat archive

Sphagnum peatlands in the oceanic-continental transition zone of Poland are currently influenced by climatic and anthropogenic factors that lead to peat desiccation and susceptibility to fire. Little is known about the response of Sphagnum peatland testate amoebae (TA) to the combined effects of drought and fire. To understand the relationships between hydrology and fire dynamics, we used high-resolution multi-proxy palaeoecological data to reconstruct 2000 years of mire history in northern Poland. We employed a new approach for Polish peatlands – joint TA-based water table depth and charcoal-inferred fire activity reconstructions. In addition, the response of most abundant TA hydrological indicators to charcoal-inferred fire activity was assessed. The results show four hydrological stages of peatland development: moderately wet (from ∼35 BC to 800 AD), wet (from ∼800 to 1390 AD), dry (from ∼1390 to 1700 AD) and with an instable water table (from ∼1700 to 2012 AD). Fire activity has increased in the last millennium after constant human presence in the mire surroundings. Higher fire activity caused a rise in the water table, but later an abrupt drought appeared at the onset of the Little Ice Age. This dry phase is characterized by high ash contents and high charcoal-inferred fire activity. Fires preceded hydrological change and the response of TA to fire was indirect. Peatland drying and hydrological instability was connected with TA community changes from wet (dominance of Archerella flavum, Hyalosphenia papilio, Amphitrema wrightianum) to dry (dominance of Cryptodifflugia oviformis, Euglypha rotunda); however, no clear fire indicator species was found. Anthropogenic activities can increase peat fires and cause substantial hydrology changes. Our data suggest that increased human fire activity was one of the main factors that influenced peatland hydrology, though the mire response through hydrological changes towards drier conditions was delayed in relation to the surrounding vegetation changes.

Quantification of water content across a cement-clay interface using high resolution neutron radiography

In many designs for radioactive waste repositories, cement and clay will come into direct contact. The geochemical contrast between cement and clay will lead to mass fluxes across the interface, which consequently results in alteration of structural and transport properties of both materials that may affect the performance of the multi-barrier system. We present an experimental approach to study cement-clay interactions with a cell to accommodate small samples of cement and clay. The cell design allows both in situ measurement of water content across the sample using neutron radiography and measurement of transport parameters using through-diffusion tracer experiments. The aim of the high- resolution neutron radiography experiments was to monitor changes in water content (porosity) and their spatial extent. Neutron radiographs of several evolving cement-clay interfaces delivered quantitative data which allow resolving local water contents within the sample domain. In the present work we explored the uncertainties of the derived water contents with regard to various input parameters and with regard to the applied image correction procedures. Temporal variation of measurement conditions created absolute uncertainty of the water content in the order of ±0.1 (m3/m3), which could not be fully accounted for by correction procedures. Smaller relative changes in water content between two images can be derived by specific calibrations to two sample regions with different, invariant water contents.

Lake ice phenology from AVHRR data for European lakes: An automated two-step extraction method

Several lake ice phenology studies from satellite data have been undertaken. However, the availability of long-term lake freeze-thaw-cycles, required to understand this proxy for climate variability and change, is scarce for European lakes. Long time series from space observations are limited to few satellite sensors. Data of the Advanced Very High Resolution Radiometer (AVHRR) are used in account of their unique potential as they offer each day global coverage from the early 1980s expectedly until 2022. An automatic two-step extraction was developed, which makes use of near-infrared reflectance values and thermal infrared derived lake surface water temperatures to extract lake ice phenology dates. In contrast to other studies utilizing thermal infrared, the thresholds are derived from the data itself, making it unnecessary to define arbitrary or lake specific thresholds. Two lakes in the Baltic region and a steppe lake on the Austrian–Hungarian border were selected. The later one was used to test the applicability of the approach to another climatic region for the time period 1990 to 2012. A comparison of the extracted event dates with in situ data provided good agreements of about 10 d mean absolute error. The two-step extraction was found to be applicable for European lakes in different climate regions and could fill existing data gaps in future applications. The extension of the time series to the full AVHRR record length (early 1980 until today) with adequate length for trend estimations would be of interest to assess climate variability and change. Furthermore, the two-step extraction itself is not sensor-specific and could be applied to other sensors with equivalent near- and thermal infrared spectral bands.

An automated method for mapping physical soil and water conservation structures on cultivated land using GIS and remote sensing techniques

An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.

High-resolution AMS (super 14) C dating of post-bomb peat archives of atmospheric pollutants.

Peat deposits in Greenland and Denmark were investigated to show that high-resolution dating of these archives of atmospheric deposition can be provided for the last 50 years by radiocarbon dating using the atmospheric bomb pulse. (super 14) C was determined in macrofossils from sequential one cm slices using accelerator mass spectrometry (AMS). Values were calibrated with a general-purpose curve derived from annually averaged atmospheric (super 14) CO (sub 2) values in the northernmost northern hemisphere (NNH, 30 degrees -90 degrees N). We present a through review of (super 14) C bomb-pulse data from the NNH including our own measurements made in tree rings and seeds from Arizona as well as other previously published data. We show that our general-purpose calibration curve is valid for the whole NNH producing accurate dates within 1-2 years. In consequence, (super 14) C AMS can precisely date individual points in recent peat deposits within the range of the bomb-pulse (from the mid-1950s on). Comparing the (super 14) C AMS results with the customary dating method for recent peat profiles by (super 210) Pb, we show that the use of (super 137) Cs to validate and correct (super 210) Pb dates proves to be more problematic than previously supposed. As a unique example of our technique, we show how this chronometer can be applied to identify temporal changes in Hg concentrations from Danish and Greenland peat cores.

Response profiles of murine spiral ganglion neurons on multi-electrode arrays.

OBJECTIVE Cochlear implants (CIs) have become the gold standard treatment for deafness. These neuroprosthetic devices feature a linear electrode array, surgically inserted into the cochlea, and function by directly stimulating the auditory neurons located within the spiral ganglion, bypassing lost or not-functioning hair cells. Despite their success, some limitations still remain, including poor frequency resolution and high-energy consumption. In both cases, the anatomical gap between the electrode array and the spiral ganglion neurons (SGNs) is believed to be an important limiting factor. The final goal of the study is to characterize response profiles of SGNs growing in intimate contact with an electrode array, in view of designing novel CI devices and stimulation protocols, featuring a gapless interface with auditory neurons. APPROACH We have characterized SGN responses to extracellular stimulation using multi-electrode arrays (MEAs). This setup allows, in our view, to optimize in vitro many of the limiting interface aspects between CIs and SGNs. MAIN RESULTS Early postnatal mouse SGN explants were analyzed after 6-18 days in culture. Different stimulation protocols were compared with the aim to lower the stimulation threshold and the energy needed to elicit a response. In the best case, a four-fold reduction of the energy was obtained by lengthening the biphasic stimulus from 40 μs to 160 μs. Similarly, quasi monophasic pulses were more effective than biphasic pulses and the insertion of an interphase gap moderately improved efficiency. Finally, the stimulation with an external electrode mounted on a micromanipulator showed that the energy needed to elicit a response could be reduced by a factor of five with decreasing its distance from 40 μm to 0 μm from the auditory neurons. SIGNIFICANCE This study is the first to show electrical activity of SGNs on MEAs. Our findings may help to improve stimulation by and to reduce energy consumption of CIs and thereby contribute to the development of fully implantable devices with better auditory resolution in the future.