Experimental investigation of hypersonic aerodynamics

An extensive series of ballistic range tests were conducted at the Ames Research Center to determine precisely the aerodynamic characteristics of the Galileo entry probe vehicle. Figures and tables are presented which summarize the results of these ballistic range tests. Drag data were obtained for both a nonablated and a hypothesized ablated Galileo configuration at Mach numbers from about 0.7 to 14 and at Reynolds numbers from 1000 to 4 million. The tests were conducted in air and the experimental results were compared with available Pioneer Venus data since these two configurations are similar in geometry. The nonablated Galileo configuration was also tested with two different center-of-gravity positions to obtain values of pitching-moment-curve slope which could be used in determining values of lift and center-of-pressure location for this configuration. The results indicate that the drag characteristics of the Galileo probe are qualitatively similar to that of Pioneer Venus, however, the drag of the nonablated Galileo is about 3 percent lower at the higher Mach numbers and as much as 5 percent greater at transonic Mach numbers of about 1.0 to 1.5. Also, the drag of the hypothesized ablated configuration is about 3 percent lower than that of the nonablated configuration at the higher Mach numbers but about the same at the lower Mach numbers. Additional tests are required at Reynolds numbers of 1000, 500, and 250 to determine if the dramatic rise in drag coefficient measured for Pioneer Venus at these low Reynolds numbers also occurs for Galileo, as might be expected

Brief communication "Landslide Early Warning System: toolbox and general concepts"

We define landslide Early Warning Systems and present practical guidelines to assist end-users with limited experience in the design of landslide Early Warning Systems (EWSs). <br><br> In particular, two flow chart-based tools coming from the results of the SafeLand project (7th Framework Program) have been created to make them as simple and general as possible and in compliance with a variety of landslide types and settings at single slope scale. We point out that it is not possible to cover all the real landslide early warning situations that might occur, therefore it will be necessary for end-users to adapt the procedure to local peculiarities of the locations where the landslide EWS will be operated

Ruptured Left Subclavian Artery Aneurysm in a 41-Year-Old Woman with Neurofibromatosis Type 1

Abstract Introduction Intrinsic lesions of the arterial wall are important manifestations of Neurofibromatosis type 1. Report A 41-year-old woman with Neurofibromatosis type 1, suffering sudden onset of upper back as well as left shoulder and upper chest pain is addressed to our hospital. The contrast-enhanced thoracic computed tomogram demonstrated a huge hematoma due to ruptured left subclavian artery aneurysm treated with endovascular therapy. Discussion A ruptured left subclavian artery is an uncommon but life threatening manifestation in Neurofibromatosis type 1

Sinkhole monitoring and early warning: An experimental and successful GB-InSAR application

AbstractSinkholes represent a natural risk that may hit catastrophically without clearly detectible precursors. However, they are often overlooked by people and administrators. Therefore sinkhole monitoring and associated early warnings constitute important research topics but, currently, only a few papers about sinkhole prediction can be found. In this paper an experience of sinkhole monitoring and early warning with GB-InSAR is described. The latter is a highly precise instrument that is able to produce displacement maps with metric spatial resolution. The described activities were carried out on Elba Island (central Italy), where karstified limestone set off the occurrence of nine sinkholes since 2008, all within less than 3000m2, causing major damage to an important road and many indirect losses. In 1year of monitoring two deforming areas were detected, and the point where a sinkhole was about to propagate to the street level was predicted, thus permitting the preventive closure of the road. The deformation area was larger than the hole generated by the sinkhole, thus showing a subsidence that continued for a prolonged time even after the cavity was filled up. The occurrence of a 1.5-m-wide sinkhole, undetected by the GB-InSAR, also showed the lower detection limit of the instrument

Clonal variability of several grapevine cultivars (V. vinifera L.) grown in the Emilia-Romagna

Clonal selection has been performed over the past 2 decades by the University of Bologna to maintain the traditional grapevine cultivars grown in the Emilia-Romagna. Around 1980 budwood canes from several biotypes of the cvs Lambrusco di Sorbara, Lambrusco Salamino, Lambrusco Grasparossa, Lambrusco Maestri and Fortana were collected from old vineyards and used to establish a preliminary trial. The vines were tested for their virus status and compared for yield, grape quality, leaf characters and phenological phases in order to evaluate the biotype variability and clonal repeatability within each cultivar. L. Salamino, L. Grasparossa and L. Maestri showed very low degrees of genetic determination for yield and quality, while Fortana and L Sorbara exhibited quite high degrees. The results in both cases were independent on the virus status of the vines. While for cvs L. Salamino, L. Maestri and L. Grasparossa selection can be made only on the basis of virus status, good selection potentials were found with cvs L. Sorbara and Fortana. Fortana also exhibited marked differences in leaf morphology and phenological phases. Further investigations are needed to better characterize the diversity among biotypes of this variety, since the delimitation between cultivars and clones remains questionable

Displacement prediction of step-like landslide by applying a novel kernel extreme learning machine method

Landslide displacement prediction is an essential component for developing landslide early warning systems. In the Three Gorges Reservoir area (TGRA), landslides experience step-like deformations (i.e., periods of stability interrupted by abrupt accelerations) generally from April to September due to the influence of precipitation and reservoir scheduled level variations. With respect to many traditional machine learning techniques, two issues exist relative to displacement prediction, namely the random fluctuation of prediction results and inaccurate prediction when step-like deformations take place. In this study, a novel and original prediction method was proposed by combining the wavelet transform (WT) and particle swarm optimization-kernel extreme learning machine (PSO-KELM) methods, and by considering the landslide causal factors. A typical landslide with a step-like behavior, the Baishuihe landslide in TGRA, was taken as a case study. The cumulated total displacement was decomposed into trend displacement, periodic displacement (controlled by internal geological conditions and external triggering factors respectively), and noise. The displacement items were predicted separately by multi-factor PSO-KELM considering various causal factors, and the total displacement was obtained by summing them up. An accurate prediction was achieved by the proposed method, including the step-like deformation period. The performance of the proposed method was compared with that of the multi-factor extreme learning machine (ELM), support vector regression (SVR), backward propagation neural network (BPNN), and single-factor PSO-KELM. Results show that the PSO-KELM outperforms the other models, and the prediction accuracy can be improved by considering causal factors

Site-fidelity and movement patterns of bottlenose dolphins (<i>Tursiops truncatus</i>) in central Argentina: essential information for effective conservation

The effectiveness of conservation measures such as marine protected areas (MPAs) for the conservation of cetaceans is determined by how well their home range or critical habitat is covered. The present study seeks to provide information on the site-fidelity and movement patterns of individual bottlenose dolphins (Tursiops truncatus) in central Argentina. Between 2007 and 2013, photo-identification data of bottlenose dolphins were collected in four study sites some 90-200km apart from each other along the central Argentinean coast. Results show long-term site-fidelity (over 5years) in one of the study areas. Re-sighting rates further suggest the existence of different sub-populations of bottlenose dolphins, but also confirm some connectivity (with movements over 200-290km) and thus potential for gene flow within the region. Considering the population declines of bottlenose dolphins in Argentina, information on site-fidelity and movement patterns will be of value to improve the effectiveness of existing MPAs for the conservation of the species as well as prioritizing areas for increased research