635 research outputs found
Competent Men and Warm Women: Gender Stereotypes and Backlash in Image Search Results
There is much concern about algorithms that underlie
information services and the view of the world they
present. We develop a novel method for examining the
content and strength of gender stereotypes in image
search, inspired by the trait adjective checklist method.
We compare the gender distribution in photos retrieved by
Bing for the query āpersonā and for queries based on 68
character traits (e.g., āintelligent personā) in four regional
markets. Photos of men are more often retrieved for
āperson,ā as compared to women. As predicted, photos of
women are more often retrieved for warm traits (e.g.,
āemotionalā) whereas agentic traits (e.g., ārationalā) are
represented by photos of men. A backlash effect, where
stereotype-incongruent individuals are penalized, is
observed. However, backlash is more prevalent for
ācompetent womenā than āwarm men.ā Results underline
the need to understand how and why biases enter search
algorithms and at which stages of the engineering proces
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Automatic near real-time selection of flood water levels from high resolution Synthetic Aperture Radar images for assimilation into hydraulic models: a case study
Flood extents caused by fluvial floods in urban and rural areas may be predicted by hydraulic models. Assimilation may be used to correct the model state and improve the estimates of the model parameters or external forcing. One common observation assimilated is the water level at various points along the modelled reach. Distributed water levels may be estimated indirectly along the flood extents in Synthetic Aperture Radar (SAR) images by intersecting the extents with the floodplain topography. It is necessary to select a subset of levels for assimilation because adjacent levels along the flood extent will be strongly correlated. A method for selecting such a subset automatically and in near real-time is described, which would allow the SAR water levels to be used in a forecasting model. The method first selects candidate waterline points in flooded rural areas having low slope. The waterline levels and positions are corrected for the effects of double reflections between the water surface and emergent vegetation at the flood edge. Waterline points are also selected in flooded urban areas away from radar shadow and layover caused by buildings, with levels similar to those in adjacent rural areas. The resulting points are thinned to reduce spatial autocorrelation using a top-down clustering approach. The method was developed using a TerraSAR-X image from a particular case study involving urban and rural flooding. The waterline points extracted proved to be spatially uncorrelated, with levels reasonably similar to those determined manually from aerial photographs, and in good agreement with those of nearby gauges
The effects of spatial resolution and dimensionality on modeling regional-scale hydraulics in a multichannel river
As modeling capabilities at regional and global scales improve, questions remain regarding the appropriate process representation required to accurately simulate multichannel river hydraulics. This study uses the hydrodynamic model LISFLOOD-FP to simulate patterns of water surface elevation (WSE), depth, and inundation extent across a ā¼90 km, anabranching reach of the Tanana River, Alaska. To provide boundary conditions, we collected field observations of bathymetry and WSE during a 2 week field campaign in summer 2013. For the first time at this scale, we test a simple, raster-based model's capabilities to simulate 2-D, in-channel patterns of WSE and inundation extent. Additionally, we compare finer resolution (ā¤25 m) 2-D models to four other models of lower dimensionality and coarser resolution (100ā500 m) to determine the effects of simplifying process representation. Results indicate that simple, raster-based models can accurately simulate 2-D, in-channel hydraulics in the Tanana. Also, the fine-resolution, 2-D models produce lower errors in spatiotemporal outputs of WSE and inundation extent compared to coarse-resolution, 1-D models: 22.6 cm versus 56.4 cm RMSE for WSE, and 90% versus 41% Critical Success Index values for simulating inundation extent. Incorporating the anabranching channel network using subgrid representations for smaller channels is important for simulating accurate hydraulics and lowers RMSE in spatially distributed WSE by at least 16%. As a result, better representation of the converging and diverging multichannel network by using subgrid solvers or downscaling techniques in multichannel rivers is needed to improve errors in regional to global-scale models
Comparative flood damage model assessment: towards a European approach
There is a wide variety of flood damage models in use internationally, differing substantially in their approaches and economic estimates. Since these models are being used more and more as a basis for investment and planning decisions on an increasingly large scale, there is a need to reduce the uncertainties involved and develop a harmonised European approach, in particular with respect to the EU Flood Risks Directive. In this paper we present a qualitative and quantitative assessment of seven flood damage models, using two case studies of past flood events in Germany and the United Kingdom. The qualitative analysis shows that modelling approaches vary strongly, and that current methodologies for estimating infrastructural damage are not as well developed as methodologies for the estimation of damage to buildings. The quantitative results show that the model outcomes are very sensitive to uncertainty in both vulnerability (i.e. depthādamage functions) and exposure (i.e. asset values), whereby the first has a larger effect than the latter. We conclude that care needs to be taken when using aggregated land use data for flood risk assessment, and that it is essential to adjust asset values to the regional economic situation and property characteristics. We call for the development of a flexible but consistent European framework that applies best practice from existing models while providing room for including necessary regional adjustments
ALTERED PHOSPHORYLATION STATUS, PHOSPHOLIPID-METABOLISM AND GLUCONEOGENESIS IN THE HOST LIVER OF RATS WITH PROSTATE-CANCER - A P-31 MAGNETIC-RESONANCE SPECTROSCOPY STUDY
31P magnetic resonance spectroscopy (MRS) in vivo and in vitro was used to study modulation of host liver (HL) metabolism in rats bearing the MAT-LyLu variant of the Dunning prostate tumour. Animals were inoculated either with 10(6) or 10(7) MAT-LyLu cells, or with saline to serve as controls. Carcass weight in tumour-bearing (TB) animals decreased despite similar food and water intake in both groups. Absence of metastatic tumour cells from HL of all TB animals was confirmed by histological examination. Twenty-one days after inoculation, 31P MRS showed a 2.5-fold increase in [Pi]/[ATP] ratios in HL in vivo (P < 0.001) which was confirmed by 31P MRS of liver extracts in vitro (P < 0.005). Phosphodiester to ATP ratios were significantly increased (P < 0.05) in HL in vivo, but absolute PDE levels were similar in both groups. Phosphomonoester to ATP ratios did not change, although absolute phosphomonoester levels in HL were reduced by -41% (not significant). In HL extracts in vitro, sharp reductions in the levels of glucose-6-phosphate (P < 0.05), fructose-6-phosphate (P = 0.05), phosphocholine (P < 0.001), glycerophosphocholine (P < 0.001), and glycerophosphoethanolamine (P < 0.001) were observed. Electron microscopy revealed increased amounts and altered distribution of rough endoplasmic reticulum in HL. These findings show that experimental prostate cancer significantly affects hepatic phosphorylation status, phospholipid metabolism, and gluconeogenesis in the host animal, and demonstrate the value of combined MRS in vivo and in vitro in monitoring HL metabolism in cancer
MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset
High-resolution raster hydrography maps are a fundamental data source for many geoscience applications. Here we introduce MERIT Hydro, a new global flow direction map at 3-arc sec resolution (~90 m at the equator) derived from the latest elevation data (MERIT DEM) and water body data sets (G1WBM, Global Surface Water Occurrence, and OpenStreetMap). We developed a new algorithm to extract river networks near automatically by separating actual inland basins from dummy depressions caused by the errors in input elevation data. After a minimum amount of hand editing, the constructed hydrography map shows good agreement with existing quality-controlled river network data sets in terms of flow accumulation area and river basin shape. The location of river streamlines was realistically aligned with existing satellite-based global river channel data. Relative error in the drainage area was <0.05 for 90% of Global Runoff Data Center (GRDC) gauges, confirming the accuracy of the delineated global river networks. Discrepancies in flow accumulation area were found mostly in arid river basins containing depressions that are occasionally connected at high water levels and thus resulting in uncertain watershed boundaries. MERIT Hydro improves on existing global hydrography data sets in terms of spatial coverage (between N90 and S60) and representation of small streams, mainly due to increased availability of high-quality baseline geospatial data sets. The new flow direction and flow accumulation maps, along with accompanying supplementary layers on hydrologically adjusted elevation and channel width, will advance geoscience studies related to river hydrology at both global and local scales
Integrating FATE/critical data studies into data science curricula : where are we going and how do we get there?
There have been multiple calls for integrating topics related to fairness, accountability, transparency, ethics (FATE) and social justice into Data Science curricula, but little exploration of how this might work in practice. This paper presents the findings of a collaborative auto-ethnography (CAE) engaged in by a MSc Data Science teaching team based at University of Sheffield (UK) Information School where FATE/Critical Data Studies (CDS) topics have been a core part of the curriculum since 2015/16. In this paper, we adopt the CAE approach to reflect on our experiences of working at the intersection of disciplines, and our progress and future plans for integrating FATE/CDS into the curriculum. We identify a series of challenges for deeper FATE/CDS integration related to our own competencies and the wider socio-material context of Higher Education in the UK. We conclude with recommendations for ourselves and the wider FATE/CDS orientated Data Science community
AirSWOT measurements of river water surface elevation and slope: Tanana River, AK
Fluctuations in water surface elevation (WSE) along rivers have important implications for water resources, flood hazards, and biogeochemical cycling. However, current in situ and remote sensing methods exhibit key limitations in characterizing spatiotemporal hydraulics of many of the world's river systems. Here we analyze new measurements of river WSE and slope from AirSWOT, an airborne analogue to the Surface Water and Ocean Topography (SWOT) mission aimed at addressing limitations in current remotely sensed observations of surface water. To evaluate its capabilities, we compare AirSWOT WSEs and slopes to in situ measurements along the Tanana River, Alaska. Root-mean-square error is 9.0 cm for WSEs averaged over 1 km2 areas and 1.0 cm/km for slopes along 10 km reaches. Results indicate that AirSWOT can accurately reproduce the spatial variations in slope critical for characterizing reach-scale hydraulics. AirSWOT's high-precision measurements are valuable for hydrologic analysis, flood modeling studies, and for validating future SWOT measurements
The credibility challenge for global fluvial flood risk analysis
Quantifying flood hazard is an essential component of resilience planning, emergency response, and mitigation, including insurance. Traditionally undertaken at catchment and national scales, recently, efforts have intensified to estimate flood risk globally to better allow consistent and equitable decision making. Global flood hazard models are now a practical reality, thanks to improvements in numerical algorithms, global datasets, computing power, and coupled modelling frameworks. Outputs of these models are vital for consistent quantification of global flood risk and in projecting the impacts of climate change. However, the urgency of these tasks means that outputs are being used as soon as they are made available and before such methods have been adequately tested. To address this, we compare multi-probability flood hazard maps for Africa from six global models and show wide variation in their flood hazard, economic loss and exposed population estimates, which has serious implications for model credibility. While there is around 30-40% agreement in flood extent, our results show that even at continental scales, there are significant differences in hazard magnitude and spatial pattern between models, notably in deltas, arid/semi-arid zones and wetlands. This study is an important step towards a better understanding of modelling global flood hazard, which is urgently required for both current risk and climate change projections
Susceptibility amplitude ratio for generic competing systems
We calculate the susceptibility amplitude ratio near a generic higher
character Lifshitz point up to one-loop order. We employ a renormalization
group treatment with independent scaling transformations associated to the
various inequivalent subspaces in the anisotropic case in order to compute the
ratio above and below the critical temperature and demonstrate its
universality. Furthermore, the isotropic results with only one type of
competition axes have also been shown to be universal. We describe how the
simpler situations of -axial Lifshitz points as well as ordinary
(noncompeting) systems can be retrieved from the present framework.Comment: 20 pages, no figure
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