Improving reporting of uncertainties in sea level rise assessments

Sea level rise (SLR) assessments are commonly used to identify the extent that coastal populations are at risk to flooding. However, the data and assumptions used to develop these assessments contain numerous sources and types of uncertainty, which limit confidence in the accuracy of modeled results. This study illustrates how the intersection of uncertainty in digital elevation models (DEMs) and SLR lead to a wide range of modeled outcomes. SLR assessments are then reviewed to identify the extent that uncertainty is documented in peer-reviewed articles. The paper concludes by discussing priorities needed to further understand SLR impacts. (PDF contains 4 pages

TWO FORMULAS FOR SMARANDACHE LCM RATIO SEQUENCES

In this paper, a reduction formula for Smarandache LCM ratio sequences SLR(6)and SLR(7) are given

Electron Spin-Lattice Relaxation of doped Yb3+ ions in YBa2Cu3Ox

The electron spin-lattice relaxation (SLR) times T1 of Yb3+‡ ions were measured from the temperature dependence of electron spin resonance linewidth in Y0.99Yb0.01Ba2Cu3Ox with different oxygen contents. Raman relaxation processes dominate the electron SLR. Derived from the temperature dependence of the SLR rate, the Debye temperature (Td) increases with the critical temperature Tc and oxygen content x. Keywords: EPR; ESR; Electron spin-lattice relaxation; Debye temperature; Critical temperatureComment: 5 Pages 4 Figure

Coastal brownfields and adaptation to climate change: Discussions on potential hazards from contaminated groundwater displacement due to saltwater incursion

Toxic-waste associated with coastal brownfield sites can pose serious risks to human and environmental health. In light of anticipated sea-level rise (SLR) due to global climate change, coastal brownfields require heightened attention. The primary intent of this study is to pose questions and encourage discussion of this problem among policy makers. Impacts from SLR on coastal zones are examined within a brownfield policy framework and, current coastal brownfield policy discussions with respect to SLR are also examined. (PDF contains 4 pages

Dual-frequency GPS survey for validation of a regional DTM and for the generation of local DTM data for sea-level rise modelling in an estuarine salt marsh

Global average temperatures have risen by an average of 0.07°C per decade over the last 100 years, with a warming trend of 0.13°C per decade over the last 50 years. Temperatures are predicted to rise by 2°C - 4.4°C by 2100 leading to global average sealevel rise (SLR) of 2 – 6mm per year (20 – 60cms in total) up to 2100 (IPCC 2007) with impacts for protected coastal habitats in Ireland. Estuaries are predominantly sedimentary environments, and are characterised by shallow coastal slope gradients, making them sensitive to even modest changes in sea-level. The Shannon estuary is the largest river estuary in Ireland and is designated as a Special Area of Conservation (SAC) under the EU Habitats Directive (EU 1992) providing protection for listed habitats within it, including estuarine salt marsh. Trends in Shannon estuary tidal data from 1877 – 2004 suggest an average upward SLR trend of 4 - 5mm/yr over this period. A simple linear extension of this historical trend would imply that local SLR will be in the region of 40 - 45cm by 2100. However, this may underestimate actual SLR for the estuary by 2100, since it takes no account of predicted climate-driven global SLR acceleration (IPCC 2007) up to 2100

Video-based Sign Language Recognition without Temporal Segmentation

Millions of hearing impaired people around the world routinely use some variants of sign languages to communicate, thus the automatic translation of a sign language is meaningful and important. Currently, there are two sub-problems in Sign Language Recognition (SLR), i.e., isolated SLR that recognizes word by word and continuous SLR that translates entire sentences. Existing continuous SLR methods typically utilize isolated SLRs as building blocks, with an extra layer of preprocessing (temporal segmentation) and another layer of post-processing (sentence synthesis). Unfortunately, temporal segmentation itself is non-trivial and inevitably propagates errors into subsequent steps. Worse still, isolated SLR methods typically require strenuous labeling of each word separately in a sentence, severely limiting the amount of attainable training data. To address these challenges, we propose a novel continuous sign recognition framework, the Hierarchical Attention Network with Latent Space (LS-HAN), which eliminates the preprocessing of temporal segmentation. The proposed LS-HAN consists of three components: a two-stream Convolutional Neural Network (CNN) for video feature representation generation, a Latent Space (LS) for semantic gap bridging, and a Hierarchical Attention Network (HAN) for latent space based recognition. Experiments are carried out on two large scale datasets. Experimental results demonstrate the effectiveness of the proposed framework.Comment: 32nd AAAI Conference on Artificial Intelligence (AAAI-18), Feb. 2-7, 2018, New Orleans, Louisiana, US

Chemical enrichment of the pre-solar cloud by supernova dust grains

The presence of short-lived radioisotopes (SLRs) in solar system meteorites has been interpreted as evidence that the solar system was exposed to a supernova shortly before or during its formation. Yet results from hydrodynamical models of SLR injection into the proto-solar cloud or disc suggest that gas-phase mixing may not be efficient enough to reproduce the observed abundances. As an alternative, we explore the injection of SLRs via dust grains as a way to overcome the mixing barrier. We numerically model the interaction of a supernova remnant containing SLR-rich dust grains with a nearby molecular cloud. The dust grains are subject to drag forces and both thermal and non-thermal sputtering. We confirm that the expanding gas shell stalls upon impact with the dense cloud and that gas-phase SLR injection occurs slowly due to hydrodynamical instabilities at the cloud surface. In contrast, dust grains of sufficient size (> 1 micron) decouple from the gas and penetrate into the cloud within 0.1 Myr. Once inside the cloud, the dust grains are destroyed by sputtering, releasing SLRs and rapidly enriching the dense (potentially star-forming) regions. Our results suggest that SLR transport on dust grains is a viable mechanism to explain SLR enrichment.Comment: 15 pages, 10 figures, Accepted for publication in MNRAS. Movies can be found here: http://user.physics.unc.edu/~mdgood86/research.htm