Study made of large amplitude fuel sloshing

Study of resonant oscillations of an ideal fluid in a cylindrical tank is used to obtain a better understanding of fuel sloshing in large liquid booster. More realistic structural design criteria may be formulated when the dynamic response of the liquid in a cylindrical tank can be predicted analytically

An integrated analysis of micro- and macro-habitat features as a tool to detect weather-driven constraints: a case study with cavity nesters

The effects of climate change on animal populations may be shaped by habitat characteristics at both micro- and macro-habitat level, however, empirical studies integrating these two scales of observation are lacking. As analyses of the effects of climate change commonly rely on data from a much larger scale than the microhabitat level organisms are affected at, this mismatch risks hampering progress in developing understanding of the details of the ecological and evolutionary responses of organisms and, ultimately, effective actions to preserve their populations. Cavity nesters, often with a conservation status of concern, are an ideal model because the cavity is a microenvironment potentially different from the macroenvironment but nonetheless inevitably interacting with it. The lesser kestrel (Falco naumanni) is a cavity nester which was until recently classified by as Vulnerable species. Since 2004, for nine years, we collected detailed biotic and abiotic data at both micro- and macro-scales of observation in a kestrel population breeding in the Gela Plain (Italy), a Mediterranean area where high temperatures may reach lethal values for the nest content. We show that macroclimatic features needed to be integrated with both abiotic and biotic factors recorded at a microscale before reliably predicting nest temperatures. Among the nest types used by lesser kestrels, we detected a preferential occupation of the cooler nest types, roof tiles, by early breeders whereas, paradoxically, late breeders nesting with hotter temperatures occupied the overheated nest holes. Not consistent with such a suggested nest selection, the coolest nest type did not host a higher reproductive success than the overheated nests. We discussed our findings in the light of cavity temperatures and nest types deployed within conservation actions assessed by integrating selected factors at different observation scales

Local quasiparticle density of states of superconducting SmFeAsO1−x1-xFxx single crystals: Evidence for spin-mediated pairing

We probe the local quasiparticles density-of-states in micron-sized SmFeAsO$_{1-x}$F$_{x}$ single-crystals by means of Scanning Tunnelling Spectroscopy. Spectral features resemble those of cuprates, particularly a dip-hump-like structure developed at energies larger than the gap that can be ascribed to the coupling of quasiparticles to a collective mode, quite likely a resonant spin mode. The energy of the collective mode revealed in our study decreases when the pairing strength increases. Our findings support spin-fluctuation-mediated pairing in pnictides.Comment: 11 pages, 4 figure

Polaronic signature in the metallic phase of La0.7Ca0.3MnO3 films detected by scanning tunneling spectroscopy

In this work we map tunnel conductance curves with nanometric spatial resolution, tracking polaronic quasiparticle excitations when cooling across the insulator-to-metal transition in La0.7Ca0.3MnO3 films. In the insulating phase the spectral signature of polarons, a depletion of conductance at low bias flanked by peaks, is detected all over the scanned surface. These features are still observed at the transition and persist on cooling into the metallic phase. Polaron-binding energy maps reveal that polarons are not confined to regions embedded in a highly-conducting matrix but are present over the whole field of view both above and below the transition temperature.Comment: 10 pages, 4 figure

INTEGRATED SURVEY AND SMART NAVIGATION OF COMPLEX TERRITORIAL MODELS

Abstract. The study examines the numerous medieval fortified sites that are in ruins throughout the Sicilian territory. Their landscape and historical value is significant, but they are unfortunately abandoned, not in stable conditions and often no metrically reliable graphic representation exists.The methodology we chose required a combined 3D survey campaign and data processing aimed at obtaining 2D and 3D drawings, as well as a virtual reality application to provide knowledge and virtual fruition of the sites.The entire experimental procedure was optimised to provide multi-scalar readings of the sites under investigation, that include their details, the location, territory, and landscape.The article presents the results of a case study carried out on the Maletto Castle in Sicily (Italy)

Controlling Fast Chaos in Delay Dynamical Systems

We introduce a novel approach for controlling fast chaos in time-delay dynamical systems and use it to control a chaotic photonic device with a characteristic time scale of ~12 ns. Our approach is a prescription for how to implement existing chaos control algorithms in a way that exploits the system's inherent time-delay and allows control even in the presence of substantial control-loop latency (the finite time it takes signals to propagate through the components in the controller). This research paves the way for applications exploiting fast control of chaos, such as chaos-based communication schemes and stabilizing the behavior of ultrafast lasers.Comment: 4 pages, 4 figures, to be published in Physical Review Letter

A Comparison of Autonomic Decision Making Techniques

Autonomic computing systems are capable of adapting their behavior and resources thousands of times a second to automatically decide the best way to accomplish a given goal despite changing environmental conditions and demands. Different decision mechanisms are considered in the literature, but in the vast majority of the cases a single technique is applied to a given instance of the problem. This paper proposes a comparison of some state of the art approaches for decision making, applied to a self-optimizing autonomic system that allocates resources to a software application, which provides direct performance feedback at runtime. The Application Heartbeats framework is used to provide the sensor data (feedback), and a variety of decision mechanisms, from heuristics to control-theory and machine learning, are investigated. The results obtained with these solutions are compared by means of case studies using standard benchmarks

SEEC: A Framework for Self-aware Management of Multicore Resources

This paper presents SEEC, a self-aware programming model, designed to reduce programming effort in modern multicore systems. In the SEEC model, application programmers specify application goals and progress, while systems programmers separately specify actions system software and hardware can take to affect an application (e.g. resource allocation). The SEEC runtime monitors applications and dynamically selects actions to meet application goals optimally (e.g. meeting performance while minimizing power consumption). The SEEC runtime optimizes system behavior for the application rather than requiring the application programmer to optimize for the system. This paper presents a detailed discussion of the SEEC model and runtime as well as several case studies demonstrating their benefits. SEEC is shown to optimize performance per Watt for a video encoder, find optimal resource allocation for an application with complex resource usage, and maintain the goals of multiple applications in the face of environmental fluctuations

SEEC: A Framework for Self-aware Computing

As the complexity of computing systems increases, application programmers must be experts in their application domain and have the systems knowledge required to address the problems that arise from parallelism, power, energy, and reliability concerns. One approach to relieving this burden is to make use of self-aware computing systems, which automatically adjust their behavior to help applications achieve their goals. This paper presents the SEEC framework, a unified computational model designed to enable self-aware computing in both applications and system software. In the SEEC model, applications specify goals, system software specifies possible actions, and the SEEC framework is responsible for deciding how to use the available actions to meet the application-specified goals. The SEEC framework is built around a general and extensible control system which provides predictable behavior and allows SEEC to make decisions that achieve goals while optimizing resource utilization. To demonstrate the applicability of the SEEC framework, this paper presents fivedifferent self-aware systems built using SEEC. Case studies demonstrate how these systems can control the performance of the PARSEC benchmarks, optimize performance per Watt for a video encoder, and respond to unexpected changes in the underlying environment. In general these studies demonstrate that systems built using the SEEC framework are goal-oriented, predictable, adaptive, and extensible