Increased temperature in urban ground as source of sustainable energy

This paper is part of the Proceedings of the 10th International Conference on Urban Regeneration and Sustainability (Sustainable City 2015). http://www.witconferences.comDensely urbanized areas are characterized by special microclimatic conditions with typically elevated temperatures in comparison with the rural surrounding. This phenomenon is known as the urban heat island (UHI) effect, but not restricted exclusively to the atmosphere. We also find significant warming of the urban subsurface and shallow groundwater bodies. Here, main sources of heat are elevated ground surface temperatures, direct thermal exploitation of aquifers and heat losses from buildings and other infrastructure. By measuring the shallow groundwater temperature in several European cities, we identify that heat sources and associated transport processes interact at multiple spatial and temporal scales. The intensity of a subsurface UHI can reach the values of above 4 K in city centres with hotspots featuring temperatures up to +20°C. In comparison with atmospheric UHIs, subsurface UHIs represent long-term accumulations of heat in a relatively sluggish environment. This potentially impairs urban groundwater quality and permanently influences subsurface ecosystems. From another point of view, however, these thermal anomalies can also be seen as hidden large-scale batteries that constitute a source of shallow geothermal energy. Based on our measurements, data surveys and estimated physical ground properties, it is possible to estimate the theoretical geothermal potential of the urban groundwater bodies beneath the studied cities. For instance, by decreasing the elevated temperature of the shallow aquifer in Cologne, Germany, by only 2 K, the obtained energy could supply the space-heating demand of the entire city for at least 2.5 years. In the city of Karlsruhe, it is estimated that about 30% of annual heating demand could be sustainably supplied by tapping the anthropogenic heat loss in the urban aquifer. These results reveal the attractive potential of heated urban ground as energy reservoir and storage, which is in place at many places worldwide but so far not integrated in any city energy plans.This work was supported by the Swiss National Science Foundation (SNSF) under grant number 200021L 144288, and the German Research Foundation (DFG), under grant number BL 1015/4-1

Insurance-related instruments for disaster risk reduction (2011 Global Assessment Report on Disaster Risk Reduction)

Strategies and measures for disaster risk reduction (DRR) are not being implemented at the scale called for by the Hyogo Framework of Action. Part of the problem is that, from the perspective of decision makers with resource constraints, it is risky to invest in something that reaps benefits only in the case of a relatively unlikely event (such as a hurricane or a drought). People and institutions are understandably prone to invest in choices that yield less uncertain benefits. DRR, in itself, can be perceived as a risky endeavor - especially from the financial perspective. One way to circumvent this problem is by promoting DRR through incentives and other features embedded in market-based financial instruments, which offer financial stability or reliable access to funds to help cope with the consequences of extreme events. Since not all risks can be cost-effectively reduced, especially those that occur only very rarely, forward-thinking DRR stakeholders tend to seek options for financing the remaining or residual risks. Insurance and other disaster risk sharing approaches can serve households, national governments and humanitarian or development organizations, not only to complement ex ante DRR by ensuring or accelerating financing for post-disaster activities (like relief, recovery and reconstruction), but also as a conduit for ex ante DRR, guiding investment decisions that would result in fewer losses if a disaster materializes in the future. The objective of this paper is to assist disaster risk reduction stakeholders analyze whether - and how - insurance and other market-based risk transfer instruments can help increase resilience to disasters

Antifouling bastadin congeners target blue mussel phenoloxidase and complex copper(II) ions

Synthetically prepared congeners of spongederived bastadin derivatives such as 5,5'-dibromohemibastadin- 1 (DBHB) that suppress the settling of barnacle larvae were identified in this study as strong inhibitors of blue mussel phenoloxidase that is involved in the firm attachment of mussels to a given substrate. The IC50 value of DBHB as the most active enzyme inhibitor encountered in this study amounts to 0.84 mu M. Inhibition of phenoloxidase by DBHB is likely due to complexation of copper(II) ions from the catalytic centre of the enzyme by the a-oxo-oxime moiety of the compound as shown here for the first time by structure activity studies and by X-ray structure determination of a copper(II) complex of DBHB.Biotechnology & Applied MicrobiologyMarine & Freshwater BiologySCI(E)EI0ARTICLE61148-11581

Nanoscale Weibull Statistics

In this paper a modification of the classical Weibull Statistics is developed for nanoscale applications. It is called Nanoscale Weibull Statistics. A comparison between Nanoscale and classical Weibull Statistics applied to experimental results on fracture strength of carbon nanotubes clearly shows the effectiveness of the proposed modification. A Weibull's modulus around 3 is, for the first time, deduced for nanotubes. The approach can treat (also) a small number of structural defects, as required for nearly defect free structures (e.g., nanotubes) as well as a quantized crack propagation (e.g., as a consequence of the discrete nature of matter), allowing to remove the paradoxes caused by the presence of stress-intensifications

Towards Mixed Gr{\"o}bner Basis Algorithms: the Multihomogeneous and Sparse Case

One of the biggest open problems in computational algebra is the design of efficient algorithms for Gr{\"o}bner basis computations that take into account the sparsity of the input polynomials. We can perform such computations in the case of unmixed polynomial systems, that is systems with polynomials having the same support, using the approach of Faug{\`e}re, Spaenlehauer, and Svartz [ISSAC'14]. We present two algorithms for sparse Gr{\"o}bner bases computations for mixed systems. The first one computes with mixed sparse systems and exploits the supports of the polynomials. Under regularity assumptions, it performs no reductions to zero. For mixed, square, and 0-dimensional multihomogeneous polynomial systems, we present a dedicated, and potentially more efficient, algorithm that exploits different algebraic properties that performs no reduction to zero. We give an explicit bound for the maximal degree appearing in the computations