The liver has a central role in the regulation of systemic glucose and lipid fluxes during feeding and fasting and also relies on these substrates for its own energy needs. These parallel ...requirements are met by coordinated control of carbohydrate and lipid fluxes into and out of the Krebs cycle, which is highly tuned to nutrient availability and heavily regulated by insulin and glucagon. During progression of type 2 diabetes, hepatic carbohydrate and lipid biosynthesis fluxes become elevated, thus contributing to hyperglycaemia and hypertriacylglycerolaemia. Over this interval there are also significant fluctuations in hepatic energy state. To date, it is not known to what extent abnormal glucose and lipid fluxes are causally linked to altered energy states. Recent evidence that the glucose-lowering effects of metformin appear to be mediated by attenuation of hepatic energy generation places an additional spotlight on the interdependence of hepatic biosynthetic and oxidative fluxes. The transition from fasting to feeding results in a significant re-direction of hepatic glucose and lipid fluxes and may also incur a temporary hepatic energy deficit. At present, it is not known to what extent these variables are additionally modified by type 2 diabetes and/or non-alcoholic fatty liver disease. Thus, there is a compelling need to measure fluxes through oxidative, gluconeogenic and lipogenic pathways and determine their relationship with hepatic energy state in both fasting and fed conditions. New magnetic resonance-based technologies allow these variables to be non-invasively studied in animal models and humans. This review summarises a presentation given at the symposium entitled ‘The liver in focus’ at the 2015 annual meeting of the EASD. It is accompanied by two other reviews on topics from this symposium (by Kenneth Cusi, DOI:
10.1007/s00125-016-3952-1
, and by Hannele Yki-Järvinen, DOI:
10.1007/s00125-016-3944-1
) and a commentary by the Session Chair, Michael Roden (DOI:
10.1007/s00125-016-3911-x
).
In order to produce useful hydrologic and aquatic habitat data from the Landsat system, the U.S. Geological Survey has developed the “Dynamic Surface Water Extent” (DSWE) Landsat Science Product. ...DSWE will provide long-term, high-temporal resolution data on variations in inundation extent. The model used to generate DSWE is composed of five decision-rule based tests that do not require scene-based training. To allow its general application, required inputs are limited to the Landsat at-surface reflectance product and a digital elevation model. Unlike other Landsat-based water products, DSWE includes pixels that are only partially covered by water to increase inundation dynamics information content. Previously published DSWE model development included one wetland-focused test developed through visual inspection of field-collected Everglades spectra. A comparison of that test’s output against Everglades Depth Estimation Network (EDEN) in situ data confirmed the expectation that omission errors were a prime source of inaccuracy in vegetated environments. Further evaluation exposed a tendency toward commission error in coniferous forests. Improvements to the subpixel level “partial surface water” (PSW) component of DSWE was the focus of this research. Spectral mixture models were created from a variety of laboratory and image-derived endmembers. Based on the mixture modeling, a more “aggressive” PSW rule improved accuracy in herbaceous wetlands and reduced errors of commission elsewhere, while a second “conservative” test provides an alternative when commission errors must be minimized. Replication of the EDEN-based experiments using the revised PSW tests yielded a statistically significant increase in mean overall agreement (4%, p = 0.01, n = 50) and a statistically significant decrease (11%, p = 0.009, n = 50) in mean errors of omission. Because the developed spectral mixture models included image-derived vegetation endmembers and laboratory spectra for soil groups found across the US, simulations suggest where the revised DSWE PSW tests perform as they do in the Everglades and where they may prove problematic. Visual comparison of DSWE outputs with an unusual variety of coincidently collected images for locations spread throughout the US support conclusions drawn from Everglades quantitative analyses and highlight DSWE PSW component strengths and weaknesses.
First published in 1984, and reissued in a facsimile edition that preserves the formal ingenuity of the original text, Designing Designing contains a crucial and invigorating selection of J. C. ...Jones’ writings on design methodology.
Summary
The aim of this review was to undertake a survey of researchers working with plant‐parasitic nematodes in order to determine a ‘top 10’ list of these pathogens based on scientific and ...economic importance. Any such list will not be definitive as economic importance will vary depending on the region of the world in which a researcher is based. However, care was taken to include researchers from as many parts of the world as possible when carrying out the survey. The top 10 list emerging from the survey is composed of: (1) root‐knot nematodes (Meloidogyne spp.); (2) cyst nematodes (Heterodera and Globodera spp.); (3) root lesion nematodes (Pratylenchus spp.); (4) the burrowing nematode Radopholus similis; (5) Ditylenchus dipsaci; (6) the pine wilt nematode Bursaphelenchus xylophilus; (7) the reniform nematode Rotylenchulus reniformis; (8) Xiphinema index (the only virus vector nematode to make the list); (9) Nacobbus aberrans; and (10) Aphelenchoides besseyi. The biology of each nematode (or nematode group) is reviewed briefly.
This paper constructs a model of saving for retired single people that includes heterogeneity in medical expenses and life expectancies, and bequest motives. We estimate the model using Assets and ...Health Dynamics of the Oldest Old data and the method of simulated moments. Out‐of‐pocket medical expenses rise quickly with age and permanent income. The risk of living long and requiring expensive medical care is a key driver of saving for many higher‐income elderly. Social insurance programs such as Medicaid rationalize the low asset holdings of the poorest but also benefit the rich by insuring them against high medical expenses at the ends of their lives.
Synthetic aperture radar (SAR) sensors represent an indispensable data source for flood disaster planners and responders, given their ability to image the Earth's surface nearly independently of ...weather conditions and time of day. The decision by the European Space Agency (ESA) Copernicus program to open data from its Sentinel-1 SAR satellites to the public marks the first time global, operational SAR data have been made freely available. Combined with the emergence of cloud computing platforms like the Google Earth Engine (GEE), this development presents a tremendous opportunity to the disaster response community, for whom rapid access to analysis-ready data is needed to inform effective flood disaster response interventions and management plans. Here, we present an algorithm that exploits all available Sentinel-1 SAR images in combination with historical Landsat and other auxiliary data sources hosted on the GEE to rapidly map surface inundation during flood events. Our algorithm relies on multi-temporal SAR statistics to identify unexpected floods in near real-time. Additionally, historical Landsat-based surface water class probabilities are used to distinguish unexpected floods from permanent or seasonally occurring surface water. We assessed our algorithm over three recent flood events using coincident very high- spatial resolution imagery and operational flood maps. Using very high resolution optical imagery, we estimated an area-normalized accuracy of 89.8 ± 2.8% (95% c.i.) over Houston, Texas following Hurricane Harvey in late August 2017, representing an improvement of between 1.6% and 9.8% over flood maps derived from a simple backscatter threshold. Additionally, comparison of our results with SAR-derived Copernicus Emergency Management Service (EMS) maps following devastating floods in Thessaly, Greece and Eastern Madagascar in January and March 2018, respectively, yielded overall agreement rates of 98.5% in both cases. Importantly, our algorithm was able to ingest hundreds of SAR and optical images served on the GEE to produce flood maps over affected areas within minutes, circumventing the need for time-consuming data download and pre-processing steps. The flexibility of our algorithm will allow for the rapid processing of future open-access SAR data, including data from future Sentinel-1 missions.
•A new flood detection and monitoring algorithm based on dense Sentinel-1 SAR data is presented.•Temporal backscatter anomalies correct for bias arising from difference in sensor configuration and view angles.•Temporal Z-scores provide an objective measure of change due to flooding.•Integrating Sentinel-1 and Landsat data allow for distinction between seasonal water regimes and new flooding.•Google Earth Engine allows for rapid deployment of algorithm during flood events.
The U.S. Geological Survey is developing new Landsat science products. One, named Dynamic Surface Water Extent (DSWE), is focused on the representation of ground surface inundation as detected in ...cloud-/shadow-/snow-free pixels for scenes collected over the U.S. and its territories. Characterization of DSWE uncertainty to facilitate its appropriate use in science and resource management is a primary objective. A unique evaluation dataset developed from data made publicly available through the Everglades Depth Estimation Network (EDEN) was used to evaluate one candidate DSWE algorithm that is relatively simple, requires no scene-based calibration data, and is intended to detect inundation in the presence of marshland vegetation. A conceptual model of expected algorithm performance in vegetated wetland environments was postulated, tested and revised. Agreement scores were calculated at the level of scenes and vegetation communities, vegetation index classes, water depths, and individual EDEN gage sites for a variety of temporal aggregations. Landsat Archive cloud cover attribution errors were documented. Cloud cover had some effect on model performance. Error rates increased with vegetation cover. Relatively low error rates for locations of little/no vegetation were unexpectedly dominated by omission errors due to variable substrates and mixed pixel effects. Examined discrepancies between satellite and in situ modeled inundation demonstrated the utility of such comparisons for EDEN database improvement. Importantly, there seems no trend or bias in candidate algorithm performance as a function of time or general hydrologic conditions, an important finding for long-term monitoring. The developed database and knowledge gained from this analysis will be used for improved evaluation of candidate DSWE algorithms as well as other measurements made on Everglades surface inundation, surface water heights and vegetation using radar, lidar and hyperspectral instruments. Although no other sites have such an extensive in situ network or long-term records, the broader applicability of this and other candidate DSWE algorithms is being evaluated in other wetlands using this work as a guide. Continued interaction among DSWE producers and potential users will help determine whether the measured accuracies are adequate for practical utility in resource management.
Understanding the factors limiting Li+ charge transfer kinetics in Li-ion batteries is essential in improving the rate performance, especially at lower temperatures. The Li+ charge transfer process ...involved in the lithium intercalation of graphite anode includes the step of de-solvation of the solvated Li+ in the liquid electrolyte and the step of transport of Li+ in the preformed solid electrolyte interphase (SEI) on electrodes until the Li+ accepts an electron at the electrode and becomes a Li in the electrode. Whether the de-solvation process or the Li+ transport through the SEI is a limiting step depends on the nature of the interphases at the electrode and electrolyte interfaces. Several examples involving the electrode materials such as graphite, lithium titanate (LTO), lithium iron phosphate (LFP), lithium nickel cobalt aluminum oxide (NCA) and solid Li+ conductor such as lithium lanthanum titanate or Li-Al-Ti-phosphate are reviewed and discussed to clarify the conditions at which either the de-solvation or the transport of Li+ in SEI is dominating and how the electrolyte components affect the activation energy of Li+ charge transfer kinetics. How the electrolyte additives impact the Li+ charge transfer kinetics at both the anode and the cathode has been examined at the same time in 3-electrode full cells. The resulting impact on Li+ charge transfer resistance, Rct, and activation energy, Ea, at both electrodes are reported and discussed.
With rising levels of CO2 in our atmosphere, technologies capable of converting CO2 into useful products have become more valuable. The field of electrochemical CO2 reduction is reviewed here, with ...sections on mechanism, formate (formic acid) production, carbon monoxide production, reduction to higher products (methanol, methane, etc.), use of flow cells, high pressure approaches, molecular catalysts, non‐aqueous electrolytes, and solid oxide electrolysis cells. These diverse approaches to electrochemical CO2 reduction are compared and contrasted, emphasizing potential processes that would be feasible for large‐scale use. Although the focus is on recent reports, highlights of older reports are also included due to their important contributions to the field, particularly for high‐rate electrolysis.
Accurately quantifying surface water extent in wetlands is critical to understanding their role in ecosystem processes. However, current regional- to global-scale surface water products lack the ...spatial or temporal resolution necessary to characterize heterogeneous or variable wetlands. Here, we proposed a fully automatic classification tree approach to classify surface water extent using Sentinel-1 synthetic aperture radar (SAR) data and training datasets derived from prior class masks. Prior classes of water and non-water were generated from the Shuttle Radar Topography Mission (SRTM) water body dataset (SWBD) or composited dynamic surface water extent (cDSWE) class probabilities. Classification maps of water and non-water were derived over two distinct wetlandscapes: the Delmarva Peninsula and the Prairie Pothole Region. Overall classification accuracy ranged from 79% to 93% when compared to high-resolution images in the Prairie Pothole Region site. Using cDSWE class probabilities reduced omission errors among water bodies by 10% and commission errors among non-water class by 4% when compared with results generated by using the SWBD water mask. These findings indicate that including prior water masks that reflect the dynamics in surface water extent (i.e., cDSWE) is important for the accurate mapping of water bodies using SAR data.
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