Multilayer perceptron neural networks model for meteosat second generation SEVIRI daytime cloud masking

A multilayer perceptron neural network cloud mask for Meteosat Second Generation SEVIRI (Spinning Enhanced Visible and Infrared Imager) images is introduced and evaluated. The model is trained for cloud detection on MSG SEVIRI daytime data. It consists of a multi-layer perceptron with one hidden sigmoid layer, trained with the error back-propagation algorithm. The model is fed by six bands of MSG data (0.6, 0.8, 1.6, 3.9, 6.2 and 10.8 μm) with 10 hidden nodes. The multiple-layer perceptrons lead to a cloud detection accuracy of 88.96%, when trained to map two predefined values that classify cloud and clear sky. The network was further evaluated using sixty MSG images taken at different dates. The network detected not only bright thick clouds but also thin or less bright clouds. The analysis demonstrated the feasibility of using machine learning models of cloud detection in MSG SEVIRI imagery

Sea ice melt pond bathymetry reconstructed from aerial photographs using photogrammetry: a new method applied to MOSAiC data

Melt ponds are a core component of the summer sea ice system in the Arctic, increasing the uptake of solar energy and impacting the ice-associated ecosystem. They were thus one of the key topics during the 1-year drift campaign Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in the Transpolar Drift 2019/2020. Pond depth is a dominating factor in describing the surface meltwater volume; it is necessary to estimate budgets and used in model parameterization to simulate pond coverage evolution. However, observational data on pond depth are spatially and temporally strongly limited to a few in situ measurements. Pond bathymetry, which is pond depth spatially fully resolved, remains unexplored. Here, we present a newly developed method to derive pond bathymetry from aerial images. We determine it from a photogrammetric multi-view reconstruction of the summer ice surface topography. Based on images recorded on dedicated grid flights and facilitated assumptions, we were able to obtain pond depth with a mean deviation of 3.5 cm compared to manual in situ observations. The method is independent of pond color and sky conditions, which is an advantage over recently developed radiometric airborne retrieval methods. It can furthermore be implemented in any typical photogrammetry workflow. We present the retrieval algorithm, including requirements for the data recording and survey planning, and a correction method for refraction at the air–pond interface. In addition, we show how the retrieved surface topography model synergizes with the initial image data to retrieve the water level of individual ponds from the visually determined pond margins. We use the method to give a profound overview of the pond coverage on the MOSAiC floe, on which we found unexpected steady pond coverage and volume. We were able to derive individual pond properties of more than 1600 ponds on the floe, including their size, bathymetry, volume, surface elevation above sea level, and temporal evolution. We present a scaling factor for single in situ depth measurements, discuss the representativeness of in situ pond measurements and the importance of such high-resolution data for new satellite retrievals, and show indications for non-rigid pond bottoms. The study points out the great potential to derive geometric properties of the summer sea ice surface emerging from the increasingly available visual image data recorded from uncrewed aerial vehicles (UAVs) or aircraft, allowing for an integrated understanding and improved formulation of the thermodynamic and hydrological pond system in models.</p

Empirical comparison of high gradient achievement for different metals in DC and pulsed mode

For the SwissFEL project, an advanced high gradient low emittance gun is under development. Reliable operation with an electric field, preferably above 125 MV/m at a 4 mm gap, in the presence of an UV laser beam, has to be achieved in a diode configuration in order to minimize the emittance dilution due to space charge effects. In the first phase, a DC breakdown test stand was used to test different metals with different preparation methods at voltages up to 100 kV. In addition high gradient stability tests were also carried out over several days in order to prove reliable spark-free operation with a minimum dark current. In the second phase, electrodes with selected materials were installed in the 250 ns FWHM, 500 kV electron gun and tested for high gradient breakdown and for quantum efficiency using an ultra-violet laser.Comment: 25 pages, 13 figures, 5 tables. Follow up from FEL 2008 conference (Geyongju Korea 2008) New Title in JVST A (2010) : Vacuum breakdown limit and quantum efficiency obtained for various technical metals using DC and pulsed voltage source

Nuclear inclusions of pathogenic ataxin-1 induce oxidative stress and perturb the protein synthesis machinery

Spinocerebellar ataxia type-1 (SCA1) is caused by an abnormally expanded polyglutamine (polyQ) tract in ataxin-1. These expansions are responsible for protein misfolding and self-assembly into intranuclear inclusion bodies (IIBs) that are somehow linked to neuronal death. However, owing to lack of a suitable cellular model, the downstream consequences of IIB formation are yet to be resolved. Here, we describe a nuclear protein aggregation model of pathogenic human ataxin-1 and characterize IIB effects. Using an inducible Sleeping Beauty transposon system, we overexpressed the ATXN1(Q82) gene in human mesenchymal stem cells that are resistant to the early cytotoxic effects caused by the expression of the mutant protein. We characterized the structure and the protein composition of insoluble polyQ IIBs which gradually occupy the nuclei and are responsible for the generation of reactive oxygen species. In response to their formation, our transcriptome analysis reveals a cerebellum-specific perturbed protein interaction network, primarily affecting protein synthesis. We propose that insoluble polyQ IIBs cause oxidative and nucleolar stress and affect the assembly of the ribosome by capturing or down-regulating essential components. The inducible cell system can be utilized to decipher the cellular consequences of polyQ protein aggregation. Our strategy provides a broadly applicable methodology for studying polyQ diseases

KSHV gB associated RGD interactions promote attachment of cells by inhibiting the potential migratory signals induced by the disintegrin-like domain

Background: Kaposi's sarcoma-associated herpesvirus (KSHV) glycoprotein B (gB) is not only expressed on the envelope of mature virions but also on the surfaces of cells undergoing lytic replication. Among herpesviruses, KSHV gB is the only glycoprotein known to possess the RGD (Arg-Gly-Asp) binding integrin domain critical to mediating cell attachment. Recent studies described gB to also possess a disintegrin-like domain (DLD) said to interact with non-RGD binding integrins. We wanted to decipher the roles of two individually distinct integrin binding domains (RGD versus DLD) within KSHV gB in regulating attachment of cells over cell migration

Is Promiscuity Associated with Enhanced Selection on MHC-DQα in Mice (genus Peromyscus)?

Reproductive behavior may play an important role in shaping selection on Major Histocompatibility Complex (MHC) genes. For example, the number of sexual partners that an individual has may affect exposure to sexually transmitted pathogens, with more partners leading to greater exposure and, hence, potentially greater selection for variation at MHC loci. To explore this hypothesis, we examined the strength of selection on exon 2 of the MHC-DQα locus in two species of Peromyscus. While the California mouse (P. californicus) is characterized by lifetime social and genetic monogamy, the deer mouse (P. maniculatus) is socially and genetically promiscuous; consistent with these differences in mating behavior, the diversity of bacteria present within the reproductive tracts of females is significantly greater for P. maniculatus. To test the prediction that more reproductive partners and exposure to a greater range of sexually transmitted pathogens are associated with enhanced diversifying selection on genes responsible for immune function, we compared patterns and levels of diversity at the Class II MHC-DQα locus in sympatric populations of P. maniculatus and P. californicus. Using likelihood based analyses, we show that selection is enhanced in the promiscuous P. maniculatus. This study is the first to compare the strength of selection in wild sympatric rodents with known differences in pathogen milieu

Clinical approach for the classification of congenital uterine malformations

A more objective, accurate and non-invasive estimation of uterine morphology is nowadays feasible based on the use of modern imaging techniques. The validity of the current classification systems in effective categorization of the female genital malformations has been already challenged. A new clinical approach for the classification of uterine anomalies is proposed. Deviation from normal uterine anatomy is the basic characteristic used in analogy to the American Fertility Society classification. The embryological origin of the anomalies is used as a secondary parameter. Uterine anomalies are classified into the following classes: 0, normal uterus; I, dysmorphic uterus; II, septate uterus (absorption defect); III, dysfused uterus (fusion defect); IV, unilateral formed uterus (formation defect); V, aplastic or dysplastic uterus (formation defect); VI, for still unclassified cases. A subdivision of these main classes to further anatomical varieties with clinical significance is also presented. The new proposal has been designed taking into account the experience gained from the use of the currently available classification systems and intending to be as simple as possible, clear enough and accurate as well as open for further development. This proposal could be used as a starting point for a working group of experts in the field

Genetics of self-reported risk-taking behaviour, trans-ethnic consistency and relevance to brain gene expression

Risk-taking behaviour is an important component of several psychiatric disorders, including attention-deficit hyperactivity disorder, schizophrenia and bipolar disorder. Previously, two genetic loci have been associated with self-reported risk taking and significant genetic overlap with psychiatric disorders was identified within a subsample of UK Biobank. Using the white British participants of the full UK Biobank cohort (n = 83,677 risk takers versus 244,662 controls) for our primary analysis, we conducted a genome-wide association study of self-reported risk-taking behaviour. In secondary analyses, we assessed sex-specific effects, trans-ethnic heterogeneity and genetic overlap with psychiatric traits. We also investigated the impact of risk-taking-associated SNPs on both gene expression and structural brain imaging. We identified 10 independent loci for risk-taking behaviour, of which eight were novel and two replicated previous findings. In addition, we found two further sex-specific risk-taking loci. There were strong positive genetic correlations between risk-taking and attention-deficit hyperactivity disorder, bipolar disorder and schizophrenia. Index genetic variants demonstrated effects generally consistent with the discovery analysis in individuals of non-British White, South Asian, African-Caribbean or mixed ethnicity. Polygenic risk scores comprising alleles associated with increased risk taking were associated with lower white matter integrity. Genotype-specific expression pattern analyses highlighted DPYSL5, CGREF1 and C15orf59 as plausible candidate genes. Overall, our findings substantially advance our understanding of the biology of risk-taking behaviour, including the possibility of sex-specific contributions, and reveal consistency across ethnicities. We further highlight several putative novel candidate genes, which may mediate these genetic effects

ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters

Atmospheric correction over inland and coastal waters is one of the major remaining challenges in aquatic remote sensing, often hindering the quantitative retrieval of biogeochemical variables and analysis of their spatial and temporal variability within aquatic environments. The Atmospheric Correction Intercomparison Exercise (ACIX-Aqua), a joint NASA – ESA activity, was initiated to enable a thorough evaluation of eight state-of-the-art atmospheric correction (AC) processors available for Landsat-8 and Sentinel-2 data processing. Over 1000 radiometric matchups from both freshwaters (rivers, lakes, reservoirs) and coastal waters were utilized to examine the quality of derived aquatic reflectances (̂ρw). This dataset originated from two sources: Data gathered from the international scientific community (henceforth called Community Validation Database, CVD), which captured predominantly inland water observations, and the Ocean Color component of AERONET measurements (AERONET-OC), representing primarily coastal ocean environments. This volume of data permitted the evaluation of the AC processors individually (using all the matchups) and comparatively (across seven different Optical Water Types, OWTs) using common matchups. We found that the performance of the AC processors differed for CVD and AERONET-OC matchups, likely reflecting inherent variability in aquatic and atmospheric properties between the two datasets. For the former, the median errors in ̂ρw(560) and ̂ρw(664) were found to range from 20 to 30% for best-performing processors. Using the AERONET-OC matchups, our performance assessments showed that median errors within the 15–30% range in these spectral bands may be achieved. The largest uncertainties were associated with the blue bands (25 to 60%) for best-performing processors considering both CVD and AERONET-OC assessments. We further assessed uncertainty propagation to the downstream products such as near-surface concentration of chlorophyll-a (Chla) and Total Suspended Solids (TSS). Using satellite matchups from the CVD along with in situ Chla and TSS, we found that 20–30% uncertainties in ̂ρw(490 ≤ λ ≤ 743 nm) yielded 25–70% uncertainties in derived Chla and TSS products for topperforming AC processors. We summarize our results using performance matrices guiding the satellite user community through the OWT-specific relative performance of AC processors. Our analysis stresses the need for better representation of aerosols, particularly absorbing ones, and improvements in corrections for sky- (or sun-) glint and adjacency effects, in order to achieve higher quality downstream products in freshwater and coastal ecosystems

Meta-analysis of the detection of plant pigment concentrations using hyperspectral remotely sensed data

Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550–560nm) and red edge (680–750nm) regions; chlorophyll b on the red, (630–660nm), red edge (670–710nm) and the near-infrared (800–810nm); carotenoids on the 500–580nm region; and anthocyanins on the green (550–560nm), red edge (700–710nm) and near-infrared (780–790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a