281 research outputs found

    Contribution of water-limited ecoregions to their own supply of rainfall

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    The occurrence of wet and dry growing seasons in water-limited regions remains poorly understood, partly due to the complex role that these regions play in the genesis of their own rainfall. This limits the predictability of global carbon and water budgets, and hinders the regional management of naturalresources. Using novel satellite observations and atmospheric trajectory modelling, we unravel the origin and immediate drivers of growing-season precipitation, and the extent to which ecoregions themselves contribute to their own supply of rainfall. Results show that persistent anomalies in growing-season precipitation—and subsequent biomass anomalies—are caused by a complex interplay of land and ocean evaporation, air circulation and local atmospheric stability changes. For regions such as the Kalahari and Australia, the volumes of moisture recycling decline in dry years, providing a positive feedback that intensifies dry conditions. However, recycling ratios increase up to40%, pointing to the crucial role of these regions in generating their own supply of rainfall; transpiration in periods of water stress allows vegetation to partly offset the decrease in regional precipitation. Findings highlight the need to adequately represent vegetation–atmosphere feedbacks in models to predict biomass changes and to simulate the fate of water-limited regions in our warming climate

    The future of Earth observation in hydrology

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    In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smart-phones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems

    Potential evaporation at eddy-covariance sites across the globe

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    Potential evaporation (Ep) is a crucial variable for hydrological forecasting and drought monitoring. However, multiple interpretations of Ep exist, which reflect a diverse range of methods to calculate it. A comparison of the performance of these methods against field observations in different global ecosystems is urgently needed. In this study, potential evaporation was defined as the rate of terrestrial evaporation (or evapotranspiration) that the actual ecosystem would attain if it were to evaporate at maximal rate for the given atmospheric conditions. We use eddy-covariance measurements from the FLUXNET2015 database, covering 11 different biomes, to parameterise and inter-compare the most widely used Ep methods and to uncover their relative performance. For each of the 107 sites, we isolate days for which ecosystems can be considered unstressed, based on both an energy balance and a soil water content approach. Evaporation measurements during these days are used as reference to calibrate and validate the different methods to estimate Ep. Our results indicate that a simple radiation-driven method, calibrated per biome, consistently performs best against in situ measurements (mean correlation of 0.93; unbiased RMSE of 0.56&thinsp;mm&thinsp;day−1; and bias of −0.02&thinsp;mm&thinsp;day−1). A Priestley and Taylor method, calibrated per biome, performed just slightly worse, yet substantially and consistently better than more complex Penman-based, Penman–Monteith-based or temperature-driven approaches. We show that the poor performance of Penman–Monteith-based approaches largely relates to the fact that the unstressed stomatal conductance cannot be assumed to be constant in time at the ecosystem scale. On the contrary, the biome-specific parameters required by simpler radiation-driven methods are relatively constant in time and per biome type. This makes these methods a robust way to estimate Ep and a suitable tool to investigate the impact of water use and demand, drought severity and biome productivity.</p

    Renal cell carcinoma with a tumor thrombus in the ureter: a case report

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    <p>Abstract</p> <p>Background</p> <p>Renal cell carcinoma (RCCs) is the most common malignancy of the kidney. When RCC progresses, it is known to form tumor thrombus in the renal vein and/or inferior vena cava. However, RCC does not normally form tumor thrombus in the ureter or renal pelvis.</p> <p>Case presentation</p> <p>A 43-year-old man presented to our department for the treatment of a renal tumor with asymptomatic gross hematuria. In a dynamic CT study, contrast enhancement revealed a tumor suspected to be RCC, but atypical finding as a tumor thrombus that filled the renal pelvis and the whole ureter was also observed. Nephroureterectomy was performed, and the tumor was diagnosed histopathologically as RCC.</p> <p>Conclusion</p> <p>We report here a very rare case of RCC with a tumor thrombus in the whole ureter.</p

    A doubly stochastic rainfall model with exponentially decaying pulses

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    We develop a doubly stochastic point process model with exponentially decaying pulses to describe the statistical properties of the rainfall intensity process. Mathematical formulation of the point process model is described along with second-order moment characteristics of the rainfall depth and aggregated processes. The derived second-order properties of the accumulated rainfall at different aggregation levels are used in model assessment. A data analysis using 15 years of sub-hourly rainfall data from England is presented. Models with fixed and variable pulse lifetime are explored. The performance of the model is compared with that of a doubly stochastic rectangular pulse model. The proposed model fits most of the empirical rainfall properties well at sub-hourly, hourly and daily aggregation levels

    Tumoral CD105 is a novel independent prognostic marker for prognosis in clear-cell renal cell carcinoma

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    International audienceBackground: Angiogenesis is essential for tumour growth and metastasis. There are conflicting reports as to whether microvessel density (MVD) using the endothelial marker CD105 (cluster of differentiation molecule 105) in clear-cell renal cell carcinomas (ccRCC) is associated with prognosis. Recently, CD105 has been described as a RCC cancer stem cell marker.Methods: A total of 102 ccRCC were analysed. Representative tumour sections were stained for CD105. Vascularity (endothelial CD105) was quantified by MVD. The immunohistochemistry analysis detected positive (if present) or negative (if absent) CD105 tumoral staining. This retrospective population-based study was evaluated using Kaplan–Meier method, t-test and Cox proportional hazard model.Results: We found that the expression of endothelial CD105 (MVD) negatively correlated with nuclear grade (P<0.001), tumour stage (P<0.001) and Leibovitch score (P<0.001), whereas the expression of tumoral CD105 positively correlated with these three clinicopathological factors (P<0.001). In multivariate analysis, tumoral CD105 was found to be an independent predictor of poor overall survival (P=0.002).Conclusions: We have shown for the first time that tumoral CD105 is an independent predictive marker for death risk and unfavourable prognosis in patients with ccRCC after curative resection

    Перспективи інформаційної економіки

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    Метою доповіді є дослідження впливу інформаційних технологій на розвиток таких категорій сучасності як перехід сучасної економіки до інформаційного етапу, а також становлення інформаційного суспільства на основі сучасного пост промислового суспільства споживання

    Metastatic chromophobe renal cell carcinoma treated with targeted therapies: A Renal Cross Channel Group study

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    Background\textbf{Background} Treatment of non–clear cell renal cell carcinoma (RCC) remains controversial despite several recent prospective studies of targeted therapies (TT). Often Vascular Endothelial growth Factor (VEGF) and Mammalian Target of Rapamycin (mTOR) inhibitors are used, extrapolating the data from use of these agents in clear cell RCC. Methods\textbf{Methods} We performed a retrospective data analysis within the Renal Cross Channel Group to determine metastatic chromophobe RCC (mChRCC) outcomes in the TT era. The end-points were overall response, overall survival (OS) and time to treatment failure (TTF). The two latter were estimated using the Kaplan–Meier method. Results\textbf{Results} 91 mChRCC patients from 26 centres were included. Median follow-up from the date of first metastasis was 6.1 years (range: 0–13.9). Median OS was 37.9 months (95% confidence interval [CI]: 21.4–46.8) from the diagnosis of metastatic disease. Among the 61 patients who received TT, 50 (82%) were treated with anti-angiogenic (AA) and 11 with mTOR inhibitors. Median TTF and OS in patients receiving a first line of AA was 8.7 months (95% CI: 5.2–10.9) and 22.9 months (95% CI: 17.8–49.2) versus 1.9 months (95% CI: 1.0–6.0) and 3.2 months (95% CI: 2.3–not evaluable) with mTOR inhibitors, respectively. A stratified log-rank test was used to compare AA and mTOR inhibitors TT, while controlling the effect of the International Metastatic RCC Database Consortium risk group and no significant difference between AA and mTOR inhibitors was observed for TTF (p = 0.26) or for OS (p = 0.55). Conclusion\textbf{Conclusion} We report the largest retrospective cohort of patients with mChRCC treated with TT and no significant difference between AA and mTOR inhibitors was observed for TTF and OS
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