Evaluating the summer night sky brightness at a research field site on Lake Stechlin in northeastern Germany

We report on luminance measurements of the summer night sky at a field site on a freshwater lake in northeastern Germany (Lake Stechlin) to evaluate the amount of artificial skyglow from nearby and distant towns in the context of a planned study on light pollution. The site is located about 70 km north of Berlin in a rural area possibly belonging to one of the darkest regions in Germany. Continuous monitoring of the zenith sky luminance between June and September 2015 was conducted utilizing a Sky Quality Meter. With this device, typical values for clear nights in the range of 21.5-21.7 mag$_{SQM}/$arcsec$^2$ were measured, which is on the order of the natural sky brightness during starry nights. On overcast nights, values down to 22.84 mag$_{SQM}/$arcsec$^2$ were obtained, which is about one third as bright as on clear nights. The luminance measured on clear nights as well as the darkening with the presence of clouds indicate that there is very little influence of artificial skyglow on the zenith sky brightness at this location. Furthermore, fish-eye lens sky imaging luminance photometry was performed with a digital single-lens reflex camera on a clear night in the absence of moonlight. The photographs unravel several distant towns as possible sources of light pollution on the horizon. However, the low level of artificial skyglow makes the field site at Lake Stechlin an excellent location to study the effects of skyglow on a lake ecosystem in a controlled fashion.Comment: 20 pages, 8 figures, Journal of Quantitative Spectroscopy and Radiative Transfer 201

Towards an automated estimation of vegetation cover fractions on multiple scales: Examples of Eastern and Southern Africa

Vegetation cover is one of the key parameters for monitoring the state and dynamics of ecosystems. African semi-arid landscapes are especially prone to degradation due to climate change and increased anthropogenic impact on different spatial and temporal scales. In this study, a multiscale method is applied to monitor vegetation cover by deriving sub-pixel percentages of woody vegetation, herbaceous vegetation and soil. The approach is comparatively applied to two semi-arid savannas, one in Namibia and one in Kenya. The results in eastern and southern Africa demonstrate the applicability of the method to different semiarid ecosystems and to different types of remote sensing data. The presented analysis could show that continuous cover mapping is a highly suitable concept for semi-arid ecosystems, as these show gradual transitions rather than distinct borders between land cover types. Different spatial patterns of vegetation cover depending on land use practices and intensities could be revealed

edge2vec: Representation learning using edge semantics for biomedical knowledge discovery

Representation learning provides new and powerful graph analytical approaches and tools for the highly valued data science challenge of mining knowledge graphs. Since previous graph analytical methods have mostly focused on homogeneous graphs, an important current challenge is extending this methodology for richly heterogeneous graphs and knowledge domains. The biomedical sciences are such a domain, reflecting the complexity of biology, with entities such as genes, proteins, drugs, diseases, and phenotypes, and relationships such as gene co-expression, biochemical regulation, and biomolecular inhibition or activation. Therefore, the semantics of edges and nodes are critical for representation learning and knowledge discovery in real world biomedical problems. In this paper, we propose the edge2vec model, which represents graphs considering edge semantics. An edge-type transition matrix is trained by an Expectation-Maximization approach, and a stochastic gradient descent model is employed to learn node embedding on a heterogeneous graph via the trained transition matrix. edge2vec is validated on three biomedical domain tasks: biomedical entity classification, compound-gene bioactivity prediction, and biomedical information retrieval. Results show that by considering edge-types into node embedding learning in heterogeneous graphs, \textbf{edge2vec}\ significantly outperforms state-of-the-art models on all three tasks. We propose this method for its added value relative to existing graph analytical methodology, and in the real world context of biomedical knowledge discovery applicability.Comment: 10 page

Temporal Evolution of the Light Emitted by a Thin, Laser-ionized Plasma Source

We present an experimental and simulation-based investigation of the temporal evolution of light emission from a thin, laser-ionized Helium plasma source. We demonstrate an analytic model to calculate the approximate scaling of the time-integrated, on-axis light emission with the initial plasma density and temperature, supported by the experiment, which enhances the understanding of plasma light measurement for plasma wakefield accelerator (PWFA) plasma sources. Our model simulates the plasma density and temperature using a split-step Fourier code and a particle-in-cell (PIC) code. A fluid simulation is then used to model the plasma and neutral density, and the electron temperature as a function of time and position. We then show the numerical results of the space-and-time-resolved light emission and that collisional excitation is the dominant source of light emission. We validate our model by measuring the light emitted by a laser-ionized plasma using a novel statistical method capable of resolving the nanosecond-scale temporal dynamics of the plasma light using a cost-effective camera with microsecond-scale timing jitter. This method is ideal for deployment in the high radiation environment of a particle accelerator that precludes the use of expensive nanosecond-gated cameras. Our results show that our models can effectively simulate the dynamics of a thin, laser-ionized plasma source and this work is useful to understand the plasma light measurement, which plays an important role in the PWFA.Comment: 12 pages, 11 figure

Design and implementation of an illumination system to mimic skyglow at ecosystem level in a large-scale lake enclosure facility

Light pollution is an environmental stressor of global extent that is growing exponentially in area and intensity. Artificial skyglow, a form of light pollution with large range, is hypothesized to have environmental impact at ecosystem level. However, testing the impact of skyglow at large scales and in a controlled fashion under in situ conditions has remained elusive so far. Here we present the first experimental setup to mimic skyglow at ecosystem level outdoors in an aquatic environment. Spatially diffuse and homogeneous surface illumination that is adjustable between 0.01 and 10 lx, resembling rural to urban skyglow levels, was achieved with white light-emitting diodes at a large-scale lake enclosure facility. The illumination system was enabled by optical modeling with Monte-Carlo raytracing and validated by measurements. Our method can be adapted to other outdoor and indoor skyglow experiments, urgently needed to understand the impact of skyglow on ecosystems

Functional ultrasound imaging for assessment of extracellular matrix scaffolds used for liver organoid formation

A method of 3D functional ultrasound imaging has been developed to enable non-destructive assessment of extracellular matrix scaffolds that have been prepared by decellularization protocols and are intended for recellularization to create organoids. A major challenge in organ decellularization is retaining patent micro-vascular structures crucial for nutrient access and functionality of organoids. The imaging method described here provides statistical distributions of flow rates throughout the tissue volumes, 3D vessel network architecture visualization, characterization of microvessel volumes and sizes, and delineation of matrix from vascular circuits. The imaging protocol was tested on matrix scaffolds that are tissue-specific, but not species-specific, matrix extracts, prepared by a process that preserved >98% of the collagens, collagen-associated matrix components, and matrix-bound growth factors and cytokines. Image-derived data are discussed with respect to assessment of scaffolds followed by proof-of-concept studies in organoid establishment using Hep3B, human hepatoblast-like cells. Histology showed that the cells attached to scaffolds with patent vasculature within minutes, achieved engraftment at near 100%, expressed liver-specific functions within 24h, and yielded evidence of proliferation and increasing differentiation of cells throughout the two weeks of culture studies. This imaging method should prove valuable in analyses of such matrix scaffolds

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Poly lactic-co-glycolic acid controlled delivery of Disulfiram to target liver cancer stem-like cells

Disulfiram (DS), an anti-alcoholism drug, shows very strong cytotoxicity in many cancer types. However its clinical application in cancer treatment is limited by the very short half-life in the bloodstream. In this study, we developed a poly lactic-co-glycolic acid (PLGA)-encapsulated DS protecting DS from the degradation in the bloodstream. The newly developed DS-PLGA was characterized. The DS-PLGA has very satisfactory encapsulation efficiency, drug-loading content and controlled release rate in vitro. PLGA encapsulation extended the half-life of DS from shorter than 2 minutes to 7 hours in serum. In combination with copper, DS-PLGA significantly inhibited the liver cancer stem cell population. CI-isobologram showed a remarkable synergistic cytotoxicity between DS-PLGA and 5-FU or Sorafenib. It also demonstrated very promising anticancer efficacy and antimetastatic effect in liver cancer mouse model. Both DS and PLGA are FDA approved products for clinical application. Our study may lead to repositioning of DS into liver cancer treatment

Riparian Plant Litter Quality Increases With Latitude

Plant litter represents a major basal resource in streams, where its decomposition is partly regulated by litter traits. Litter-trait variation may determine the latitudinal gradient in decomposition in streams, which is mainly microbial in the tropics and detritivore-mediated at high latitudes. However, this hypothesis remains untested, as we lack information on large-scale trait variation for riparian litter. Variation cannot easily be inferred from existing leaf-trait databases, since nutrient resorption can cause traits of litter and green leaves to diverge. Here we present the first global-scale assessment of riparian litter quality by determining latitudinal variation (spanning 107°) in litter traits (nutrient concentrations; physical and chemical defences) of 151 species from 24 regions and their relationships with environmental factors and phylogeny. We hypothesized that litter quality would increase with latitude (despite variation within regions) and traits would be correlated to produce ‘syndromes’ resulting from phylogeny and environmental variation. We found lower litter quality and higher nitrogen:phosphorus ratios in the tropics. Traits were linked but showed no phylogenetic signal, suggesting that syndromes were environmentally determined. Poorer litter quality and greater phosphorus limitation towards the equator may restrict detritivore-mediated decomposition, contributing to the predominance of microbial decomposers in tropical streams