Analysis of Alaska Transportation Sectors to Assess Energy Use and Impacts of Price Shocks and Climate Change Legislation

We analyzed the use of energy by Alaska’s transportation sectors to assess the impact of sudden fuel prices changes. We conducted three types of analysis: 1) Development of broad energy use statistics for each transportation sector, including total annual energy and fuel use, carbon emissions, fuel use per ton-mile and passenger-mile, and cost of fuel per ton-mile and passenger-mile. 2) Economic input-output analysis of air, rail, truck, and water transportation sectors. 3) Adjustment of input-output modeling to reflect sudden fuel price changes to estimate the potential impact on industry output and employment. Alaska air transportation used approximately 1.9 billion gallons of fuel annually; 961 million gallons were used for intra-state and exiting Alaska flights. Water transportation used 101.8 million gallons annually, approximately 84.3 million gallons for intra-state and exiting segments. Railroad and truck transportation used 5.1 and 8.8 million gallons annually, respectively. Simulated fuel price increases resulted in an estimated $456.8 million in value-added losses to the Alaska economy through the increase in cost of transportation services, as well as an equivalent loss in income to Alaska household of$26.8 million. A carbon emissions tax would have the greatest impact on the cost of air transportation services followed by water, trucking and rail.309002 DTRT06-G-0011List of Figures / List of Tables / Acknowledgements / Abstract / Executive Summary / Introduction / Background / Research Approach / Findings and Applications / Conclusions / References / Appendix A. Marine Transportation Companies / Appendix B. Barge Fuel Use Calculations / Appendix C. Data Dictionary of Variables and Sources Used for Aviation Fuel Estimates / Appendix D. Glossary of Economic Impact Term

Using ASTER and SRTM DEMs for studying geomorphology and glaciation in high mountain areas

For selected peaks in high mountains of diverse climatic regions (Andes, Hindu Kush, Tien Shan) digital elevation models (DEMs) have been generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data using PCI Geomatica 8.1/8.2 software. Artifacts in the ASTER DEM were eliminated using data from the Space Shuttle Radar Topography Mapping mission (SRTM). For two of the four case studies, accuracy was evaluated by comparison the ASTER/SRTM DEM with DEMs derived from contour maps. Whereas the SRTM DEM shows correct elevations in all altitudes, elevations in the ASTER DEM are slightly to low in higher altitudes and south-exposed aspects. Geomorphic analyses were undertaken using the software ArcInfo, ArcView and SAGA. Cluster analyses including tangetial, vertical curvature and slope combined with spectral information helped identifying debris-covered glaciers and geomorphologic forms and processes. Results show that ASTER/SRTM DEMs are useful for an interpretation of the macro- and mesorelief. The DEM scale sets limits for the level in analysis detail. Whereas SRTM DEMs offer more precise elevations, ASTER DEMs offer more geomorphologic details

Retrieving Multi-Entity Associations: An Evaluation of Combination Modes for Word Embeddings

Word embeddings have gained significant attention as learnable representations of semantic relations between words, and have been shown to improve upon the results of traditional word representations. However, little effort has been devoted to using embeddings for the retrieval of entity associations beyond pairwise relations. In this paper, we use popular embedding methods to train vector representations of an entity-annotated news corpus, and evaluate their performance for the task of predicting entity participation in news events versus a traditional word cooccurrence network as a baseline. To support queries for events with multiple participating entities, we test a number of combination modes for the embedding vectors. While we find that even the best combination modes for word embeddings do not quite reach the performance of the full cooccurrence network, especially for rare entities, we observe that different embedding methods model different types of relations, thereby indicating the potential for ensemble methods.Comment: 4 pages; Accepted at SIGIR'1

HumiR: Web Services, Tools and Databases for Exploring Human microRNA Data

For many research aspects on small non-coding RNAs, especially microRNAs, computational tools and databases are developed. This includes quantification of miRNAs, piRNAs, tRNAs and tRNA fragments, circRNAs and others. Furthermore, the prediction of new miRNAs, isomiRs, arm switch events, target and target pathway prediction and miRNA pathway enrichment are common tasks. Additionally, databases and resources containing expression profiles, e.g., from different tissues, organs or cell types, are generated. This information in turn leads to improved miRNA repositories. While most of the respective tools are implemented in a species-independent manner, we focused on tools for human small non-coding RNAs. This includes four aspects: (1) miRNA analysis tools (2) databases on miRNAs and variations thereof (3) databases on expression profiles (4) miRNA helper tools facilitating frequent tasks such as naming conversion or reporter assay design. Although dependencies between the tools exist and several tools are jointly used in studies, the interoperability is limited. We present HumiR, a joint web presence for our tools. HumiR facilitates an entry in the world of miRNA research, supports the selection of the right tool for a research task and represents the very first step towards a fully integrated knowledge-base for human small non-coding RNA research. We demonstrate the utility of HumiR by performing a very comprehensive analysis of Alzheimer’s miRNAs

NGX-4010, a capsaicin 8% patch, for the treatment of painful HIV-associated distal sensory polyneuropathy: integrated analysis of two phase III, randomized, controlled trials

BACKGROUND HIV-associated distal sensory polyneuropathy (HIV-DSP) is the most frequently reported neurologic complication associated with HIV infection. NGX-4010 is a capsaicin 8% dermal patch with demonstrated efficacy in the treatment of HIV-DSP. Data from two phase III, double-blind studies were integrated to further analyze the efficacy and safety of NGX-4010 and explore the effect of demographic and baseline factors on NGX-4010 treatment in HIV-DSP. METHODS Data from two similarly designed studies in which patients with HIV-DSP received NGX-4010 or a low-concentration control patch (capsaicin 0.04% w/w) for 30 or 60 minutes were integrated. Efficacy assessments included the mean percent change from baseline in Numeric Pain Rating Scale (NPRS) scores to Weeks 2-12. Safety and tolerability assessments included adverse events (AEs) and pain during and after treatment. RESULTS Patients (n = 239) treated with NGX-4010 for 30 minutes demonstrated significantly (p = 0.0026) greater pain relief compared with controls (n = 100); the mean percent change in NPRS scores from baseline to Weeks 2-12 was -27.0% versus -15.7%, respectively. Patients who received a 60-minute application of NGX-4010 (n = 243) showed comparable pain reductions (-27.5%) to patients treated for 30 minutes, but this was not statistically superior to controls (n = 115). NGX-4010 was effective regardless of gender, baseline pain score, duration of HIV-DSP, or use of concomitant neuropathic pain medication, although NGX-4010 efficacy was greater in patients not receiving concomitant neuropathic pain medications. NGX-4010 was well tolerated; the most common AEs were application-site pain and erythema, and most AEs were mild to moderate. The transient increase in pain associated with NGX-4010 treatment decreased the day after treatment and returned to baseline by Day 2. CONCLUSIONS A single 30-minute application of NGX-4010 provides significant pain relief for at least 12 weeks in patients with HIV-DSP and is well tolerated. TRIAL REGISTRATION C107 = NCT00064623; C119 = NCT00321672

Ordering of timescales predicts applicability of quasi-linear theory in unstable flows

We discuss the applicability of quasilinear-type approximations for a turbulent system with a large range of spatial and temporal scales. We consider a paradigm fluid system of rotating convection with a vertical and horizontal temperature gradients. In particular, the interaction of rotating with the horizontal temperature gradient drives a ``thermal wind'' shear flow whose strength is controlled by a horizontal temperature gradient. Varying the parameters systematically alters the ordering of the shearing timescale, the convective timescale, and the correlation timescale. We demonstrate that quasilinear-type approximations work well when the shearing timescale or the correlation timescale is sufficiently short. In all cases, the Generalised Quasilinear approximation (GQL) systematically outperforms the Quasilinear approximation (QL). We discuss the consequences for statistical theories of turbulence interacting with mean gradients. We conclude with comments about the general applicability of these ideas across a wide variety of non-linear physical systems.Comment: 5 pages, 3 figure

Unfrustrated Qudit Chains and their Ground States

We investigate chains of 'd' dimensional quantum spins (qudits) on a line with generic nearest neighbor interactions without translational invariance. We find the conditions under which these systems are not frustrated, i.e. when the ground states are also the common ground states of all the local terms in the Hamiltonians. The states of a quantum spin chain are naturally represented in the Matrix Product States (MPS) framework. Using imaginary time evolution in the MPS ansatz, we numerically investigate the range of parameters in which we expect the ground states to be highly entangled and find them hard to approximate using our MPS method.Comment: 5 pages, 5 figures. Typos correcte