Quantum Steering on IBMQ

We use contemporary quantum computers to experimentally investigate quantum steering ofan open quantum system by measurements on its environment. On three IBMQ processors wedistinguish a qubit as the open system and perform pairwise interactions with multiple environmentancillas, following a collision model approach. Different measurement strategies on the ancillaslead to different state ensembles of the open system, which are reconstructed by employing statetomography. The amount of steering within the resulting assemblages is quantified with the help of asemidefinite program. We successfully observe the presence of quantum steering in our experimentalsimulations, and can discriminate the different performance qualities and noise levels of the selectedquantum devices

Distinct Genetic Risk Profile of the Rapidly Progressing Diffuse-Trickling Subtype of Geographic Atrophy in Age-Related Macular Degeneration (AMD)

PURPOSE. To genetically characterize a subphenotype of geographic atrophy (GA) in AMD associated with rapid progression and a diffuse-trickling appearance on fundus autofluorescence imaging. METHODS. Patients from the Fundus Autofluorescence in Age-Related Macular Degeneration Study were phenotyped for diffuse-trickling GA (dt-GA; n = 44). DNA was analyzed for 10 known AMD-associated genetic variants. A genetic risk score (GRS) was calculated and compared with patients with nondiffuse-trickling GA (ndt-GA; n = 311) and individuals from the 1000 genomes project (1000G; n = 267). Given the phenotypic overlap between diffuse trickling and late-onset retinal degeneration (LORD), all C1QTNF5 exons and their exon/ intron boundaries were sequenced. RESULTS. A statistically significant difference in allele frequencies between dt-GA and ndt-GA were found for CFH: rs1061170 and CFH: rs800292 (P-corrected = 0.03). The ARMS2 variant rs10490924 was significantly more frequent in dt-GA than in 1000G individuals (P-corrected < 0.01). The GRS of dt-GA patients was in-between the score of the 1000G individuals and that of patients with ndt-GA, significantly differing from both (P-corrected < 0.01). Sequencing of C1QTNF5 revealed 28 unique variants although none showed a statistically significant association with dt-GA when compared with 1000G individuals. CONCLUSIONS. The dt-GA phenotype shows a remarkably different genetic risk profile from other GA phenotypes secondary to AMD. Disease-associated C1QTNF5 mutations were not identified. Together, these results suggest that the dt-GA phenotype is associated with a genetic background substantially different from other GA phenotypes and underlines the necessity to refine the clinical phenotyping, specifically when aiming for individualized therapies in AMD

The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease.

Lung disease accounts for every sixth death globally. Profiling the molecular state of all lung cell types in health and disease is currently revolutionizing the identification of disease mechanisms and will aid the design of novel diagnostic and personalized therapeutic regimens. Recent progress in high-throughput techniques for single-cell genomic and transcriptomic analyses has opened up new possibilities to study individual cells within a tissue, classify these into cell types, and characterize variations in their molecular profiles as a function of genetics, environment, cell-cell interactions, developmental processes, aging, or disease. Integration of these cell state definitions with spatial information allows the in-depth molecular description of cellular neighborhoods and tissue microenvironments, including the tissue resident structural and immune cells, the tissue matrix, and the microbiome. The Human Cell Atlas consortium aims to characterize all cells in the healthy human body and has prioritized lung tissue as one of the flagship projects. Here, we present the rationale, the approach, and the expected impact of a Human Lung Cell Atlas.Supported by the Helmholtz Association and the German Center for Lung Research (DZL) (H.B.S.); the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement 753039 (L.M.S.); U.K. Medical Research Council grant G0900424 (E.L.R.); National Institutes of Health (NIH) grants ES013995, HL071643, and AG049665, and Veterans Administration grant BX000201 and Department of Defense grant PR141319 (G.R.S.B.); NIH grants HL135124 and AI135964 and Department of Defense grant PR141319 (A.V.M.); NIH grants R01HL141852, R01HL127349, UHHL3123886, U01HL122626, and UG3TR002445, and Department of Defence grant PR151124 (N.K.); and the Netherlands Lung Foundation grants 5.1.14.020 and 4.1.18.226 (M.C.N.)

Setting up the water balance simulation model WaSiM for the assessment of climate change impacts in Chiba basin, Tunisia

The project CLIMB (Climate Induced Changes on the Hydrology of Mediterranean Basins – Reducing Uncertainty and Quantifying Risk through an Integrated Monitoring and Modeling System, www.climb-fp7.eu) investigates the impacts of climate change on hydrological quantities and the occurrence of extreme events for the Mediterranean Region and neighboring countries. This study gives insights into setting up the “Water balance Simulation Model” WaSiM in Chiba basin, situated in the north-east of Tunisia. Besides that, the intended climate change impact assessment framework for this region is presented which also includes uncertainty information within the climate and hydrological modeling chain. Finally, some preliminary results are presented which indicate a considerable decline of total available water and associated risks in the study area between the reference (1971-2000) and scenario period (2041-2070)

Quantifying and reducing uncertainty in the assessment of water-related risks in southern Europe and neighbouring Countries

The project CLIMB (Climate Induced Changes on the Hydrology of Mediterranean Basins – Reducing Uncertainty and Quantifying Risk through an Integrated Monitoring and Modelling System, www.climb-fp7.eu) aims to investigate present and future climate induced changes in the hydrological budgets and extremes for Mediterranean and neighbouring countries. We provide a concept for an integrated modelling and assessment set-up to tackle the challenge of quantifying parameter related uncertainties and associated risks with the water balance simulation model ETH (WaSiM-ETH) for the cultivation of tomatoes in Chiba basin, Tunisia, which is a test site within the CLIMB project. This study indicates that it is already delicate to cultivate tomatoes in the watershed under rain-fed conditions with a deteriorating trend in the future. This is associated with considerable yield reduction for tomatoes and thus economic impacts for local farmers

Quantum steering on IBM quantum processors

We use contemporary quantum computers to experimentally investigate quantum steering of an open quantum system by measurements on its environment. On three IBM quantum processors we distinguish a qubit as the open system and perform pairwise interactions with multiple environment ancillas, following a collision model approach. Different measurement strategies on the ancillas lead to different state ensembles of the open system, which are reconstructed by employing state tomography. The amount of steering within the resulting assemblages is quantified with the help of a semidefinite program. We successfully observe the presence of quantum steering in our experimental simulations and can discriminate the different performance qualities and noise levels of the selected quantum devices.</p

Towards automated forest-type mapping - a service within GSE Forest Monitoring based on SPOT-5 and IKONOS data

Object-based semi-automated segmentation and classification approaches have gained importance in the analysis of remote sensing data over the last few years. Particularly when it comes to operational processing of multi-seasonal input data, independent and robust algorithms are needed. At the German Aerospace Center (DLR) a new method for forest type classification has been developed, covering all processing steps for object-based classification. An automatic adaptation of scenespecific feature values for the classification is implemented, based on automated extraction of feasible ground data. Therefore, no manual sampling of training data is necessary. For classification of mixed forests on the basis of IKONOS data, a special algorithm was developed that can be adapted to any kind of mixed forest definition. Forest age classes are derived based on a digital surface model. The developed method can be used for area-wide forest-type classification on the basis of high and very high-resolution satellite data