Small ICBM Laser Firing Unit (LFU)

The topics are presented in viewgraph form and include the following: history/schedule, LFU development hardware; specifications/features; components; optical layout-arm; optical layout-safe; built in test; and producibility issues

Suncus etruscus (Soricomorpha, Soricidae): A new species for Elba Island (Tuscan Archipelago, Italy)

The following study contains a report regarding the first record of presence of Suncus etruscus on the island of Elba. We considered original and literature data obtained from the analysis of Barn owl (Tyto alba) pellets. Three roosts located in different areas of Elba (Marciana: Colle d'Orano-Patresi; Campo nell'Elba: La Grotta; Portoferraio: Casa Rossa) have been monitored since 1968. The presence of the Pygmy white-toothed shrew has only been observed at one roost (Casa Rossa) since 2004. We performed a biometrical analysis of 15 skull characters on 67 specimens of 'S. etruscus. From the results, we conclude that a colonization of the island by S. etruscus is in progress, but long-term monitoring is needed in order to control the status of the population

Multicommodity formulations for the prize collecting vehicle routing problem in the petrol industry

The Mobile Oil Recovery (MOR) unit is a truck designed to pump marginal oil wells in a petrol field. The MOR optimization Problem (MORP) consists in optimizing both the oil extraction and the travel costs. In this article, we describe several formulations for the MORP using a single vehicle and we propose two formulations to the case where several vehicles are used. We strengthen the proposed formulations by taking advantage of the MORP characteristics, by improving the number of subtour elimination constraints and by using cuts. Computational results are presented for instances close to the reality and optimality is proved for instances with up to 200 nodes

Column generation algorithms for exact modularity maximization in networks

International audienceFinding modules, or clusters, in networks currently attracts much attention in several domains. The most studied criterion for doing so, due to Newman and Girvan [Phys. Rev. E 69, 026113 (2004)], is modularity maximization. Many heuristics have been proposed for maximizing modularity and yield rapidly near optimal solution or sometimes optimal ones but without a guarantee of optimality. There are few exact algorithms, prominent among which is a paper by Xu et al. [Eur. Phys. J. B 60, 231 (2007)]. Modularity maximization can also be expressed as a clique partitioning problem and the row generation algorithm of Grötschel and Wakabayashi [Math. Program. 45, 59 (1989)] applied. We propose to extend both of these algorithms using the powerful column generation methods for linear and non linear integer programming. Performance of the four resulting algorithms is compared on problems from the literature. Instances with up to 512 entities are solved exactly. Moreover, the computing time of previously solved problems are reduced substantially

Developing Effective Measures for Reduction of the Urban Heat Island based on Urban Climate Model Simulations and Stakeholder Cooperation

The climate change projections for the Austrian cities indicate that the observed warming trend, including frequent occurrences of extreme heat events, is expected to continue in the coming decades. Due to the Urban Heat Island (UHI) effect, caused by modification of energy balance in the built-up environment, the cities are warmer than their rural surroundings and therefore more exposed to negative impacts of climate change. During prolonged heat wave events, the excess in heat combined with reduced night-time cooling, decreased ventilation and possible air pollution can cause severe health impacts on the urban population. Developing measures for reduction of the UHI effect is important in the context of sustainable urban development and climate sensitive urban planning. Number of counteracting measures such as increase in vegetation, green open spaces, green roofs, unsealing of paved surfaces, decreasing absorption of solar radiation by increasing the reflectiveness of buildings and paved surfaces, are considered in the scope of climate change adaptation strategies. Nevertheless, the effectiveness of these measures, as well as their applicability in the existing urban structure, especially in the densely-built environments is not well known. Moreover, the expected cooling effects need to be quantified and the possible application should be communicated and appropriately planned with the relevant stakeholders in order to anticipate a large-scale implementation. This study investigates the effective methods for application of climate adaptation measures to reduce the UHI effect in a densely built-up environment on an example of the residential and business district of Jakomini in the city of Graz/Styria. The current local climate conditions are simulated with the urban climate model MUKLIMO_3 of the German Weather Service (DWD) using meteorological, geomorphological and land use data from the city of Graz. The simulations with altered land use characteristics corresponding to application of different UHI counteracting measures are calculated and compared to the reference simulation. The gradual increase in green areas, existing potential for green roofs implementation, modification in reflectivity of roofs and façades as well as unsealing of paved surfaces is considered. The resulting difference in heat load is evaluated as the potential cooling effect for the area of the Jakomini district and its surroundings. Based on the model results, a set of measures with optimal climatic impact is identified in close cooperation with the city’s planning department and in accordance with already existing concepts, plans and projects. This information is communicated with the relevant stakeholder groups both from private and public sectors to get their commitment to definitely undertake measures in the test-district. Considering the respective interests and role of action of different stakeholder groups a set of target measures is selected for further technical, financial and administrative planning of implementation. The study is supported by the Austrian Research Promotion Agency (FFG) and the Climate and Energy Fund (KLIEN) within the Smart Cities project “JACKY_cool_check” (Project Nr. 855554)

Adipose-derived stem cells (ADSC) in the viability of a random pattern dorsal skin flap in rats

PURPOSE:To evaluate the viability of random pattern dorsal skin flaps in rats after injection of adipose-derived stem cells (ADSC).METHODS: Thirty five adult male Wistar EPM rats (weight 250-300 g) were distributed, at random, in two groups. I- Control (flap elevation with injection of saline solution) with fifteen animals and II- Experimental (flap elevation with injection of ADSC ) with fifteen animal. The ADSC were isolated from others five adult male rats. A dorsal skin flap measuring 10x4 cm was raised and a plastic barrier was placed between the flap and its bed in both groups and the injection (cells or saline solution) were perfomed immediately after the surgery. The percentage of flap necrosis was measured on the seventh postoperative day.RESULTS:The ADSC were able to replicate in our culture conditions. We also induced their adipogenic, osteogenic and chondrogenic differentiation to verify their mesenchymal stem cells potentiality in vitro. The results were statistically significant showing that the ADSC decreased the area of necrosis (p<0.05).CONCLUSIONS:The cells demonstrated adipogenic, osteogenic and chondrogenic differentiation potential in vitro. The administration of adipose-derived stem cells was effective to increase the viability of the random random pattern dorsal skin flaps in rats.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Federal University of São Paulo Department of SurgeryUniversidade Estadual de Santa Cruz Department of SurgeryUNIFESPUNIFESP, Department of SurgeryUNIFESPCNPq: 312356/2009-9SciEL

A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm

K-means is undoubtedly the most widely used partitional clustering algorithm. Unfortunately, due to its gradient descent nature, this algorithm is highly sensitive to the initial placement of the cluster centers. Numerous initialization methods have been proposed to address this problem. In this paper, we first present an overview of these methods with an emphasis on their computational efficiency. We then compare eight commonly used linear time complexity initialization methods on a large and diverse collection of data sets using various performance criteria. Finally, we analyze the experimental results using non-parametric statistical tests and provide recommendations for practitioners. We demonstrate that popular initialization methods often perform poorly and that there are in fact strong alternatives to these methods.Comment: 17 pages, 1 figure, 7 table