950 research outputs found
A Dynamic Analysis of the Evolution of Conventions in a Public Goods Experiment with Intergenerational Advice
In this paper we analyse contributions to a public good within an inter-generational framework where at the end of each session one generation of subjects leave advice for the succeeding generation via free form messages. Such advice can be private (advice left by one player in generation t is given only to her immediate successor in generation t+1) or public (advice left by players of generation t is made available to all members of generation t+1). We adopt a novel approach to analysing the data by estimating a panel regression model that enables us to understand the dynamics of the process better and to highlight the learning that occurs over time. Our estimation results show that contributions in any period depend crucially on (1) contributions in the previous period and (2) on the group average in the previous period - more specifically whether a subjectĂ¢ââââ¢s own contribution in the previous period fell above or below the group average. We find that in the public advice treatment when a subjectĂ¢ââââ¢s contribution fell below the group average in the previous period there is a tendency on the part of that subject to increase contributions in the next period. This is evidence that the public advice treatment leads to the creation of virtuous norms that help sustain high cooperation and mitigate problems of free riding over time.Voluntary contributions mechanism, Public goods, Experiments, Panel Data, Generations
Al-Based Metal Foams (AMF) as Permanent Cores in Casting: State-of-the-Art and Future Perspectives
Surface Activation and Characterization of Aluminum Alloys for Brazing Optimization
Brazing of Al-alloys is of interest in many application fields (e.g., mechanical and automotive). The surface preparation of substrates and the in depth investigation of the interface reaction between aluminum substrates and brazing materials is fundamental for a proper understanding of the process and for its optimization. The interaction between two aluminum based substrates (Al5182 and Al6016) and two studied brazing materials (pure Zn and for the first time ZAMA alloy) has been studied in simulated brazing condition in order to define the best surface preparation conditions and combination substrate-brazing material to be used in real joining experiments. Three different surface preparations were considered: polishing and cleaning, application of flux and vacuum plasma etching (Ar) followed by sputtering coating with Zn. Macroscopic observation of the samples surface after “brazing”, optical microscopy, and microhardness measurements on the cross-section and XRD measurements on the top surface gave a comprehensive description of the phenomena occurring at the interface between the substrate and the brazing alloy which are of interest to understand the brazing process and for the detection of the best conditions to be used in brazing. Plasma etching (Ar) followed by sputtering coating with Zn resulted a promising solution in case of Al5182 brazed with Zn, while the addition of flux was more effective in case of Al6016 substrate. ZAMA alloy demonstrated good interface reactivity with both Al6016 and Al5182 alloys, particularly on only cleaned surfaces
Stall detection using near-field low frequency pressure modulation in turbomachines
This work investigates on the use of unconventional sensors to measure the near field unsteady pressure on the casing of a fan in a view to detect rotating stall. Rotating stall is an aerodynamic issue with a frequency signature usually half the rotor frequency. In low speed turbomachines, such as industrial fan, this turns in very low frequencies, even lower than 10 Hz.
The authors developed and set-up a measurement system able to acquire low frequency pressure signals using dynamic microphones. Traditional methods use piezoelectric sensors, e.g. pressure transducers or microphones respectively in the near and far-field, to detect instability from the signal patterns with broad frequency ranges. Recently electret microphones have been proposed, but with a cut-off frequency of 20 Hz as such not suitable for signal in infrasound region.
The sensor used in this work, have a narrower frequency range than more advanced technologies.
In this paper the authors developed a measurement chain based on dynamic microphone and pressure transducer in order to create a stall warning system. They tested the system on a low speed axial fan and they validated the work against state of the art acoustic control techniques. For this reason those devices represent candidate solutions for the detection of the patterns typical of rotating stall in turbomachines.This work investigates on the use of unconventional sensors to measure the near field unsteady pressure on the casing of a fan in a view to detect rotating stall. Rotating stall is an aerodynamic issue with a frequency signature usually half the rotor frequency. In low speed turbomachines, such as industrial fan, this turns in very low frequencies, even lower than 10 Hz.
The authors developed and set-up a measurement system able to acquire low frequency pressure signals using dynamic microphones. Traditional methods use piezoelectric sensors, e.g. pressure transducers or microphones respectively in the near and far-field, to detect instability from the signal patterns with broad frequency ranges. Recently electret microphones have been proposed, but with a cut-off frequency of 20 Hz as such not suitable for signal in infrasound region.
The sensor used in this work, have a narrower frequency range than more advanced technologies.
In this paper the authors developed a measurement chai
Stall Detection Using Pseudo-Acoustic Pressure Modulation in Industrial Fans
This work investigates the use of unconventional sensors to measure pressure modulation interpreted as pseudo sound in the near field on the casing of a fan in a view to detect rotating stall. Rotating stall is an aerodynamic issue with a frequency signature usually half the rotor frequency. In low speed turbomachines, such as industrial fans, this turns in very low frequencies, even lower than 10 Hz.Traditional methods use piezoelectric sensors, e.g., pressure transducers or microphones, respectively in the near and far-field, to detect instability from the signal patterns with broad frequency ranges. Recently electret microphones have been proposed, but with a cut-off frequency of 20 Hz as such not suitable for signal in near infrasound region.The sensor used in this work, have a narrower frequency range than more advanced technologies. The authors developed and set-up a measurement system able to acquire low frequency pressure signals using dynamic microphones.In this paper the authors developed a measurement chain based on dynamic microphone and pressure transducer in order to create a stall warning system. They tested the system on a low speed axial fan and they validated the work against state of the art acoustic control techniques. For this reason those devices represent candidate solutions for the detection of the patterns typical of rotating stall in turbomachines
Genetic diversity of Sardinian goat population based on microsatellites
During the last century, the selection for production traits of the main livestock
species has led to a reduction in number of local populations with consequent loss of genetic variability. In
Sardinia, the genetic improvement strategy has been based on selection for the local pure breed in sheep,
whereas in the other species (cattle, swine and goat), an often unplanned crossbreeding with improved breeds
has been applied. In this context, several studies on genetic diversity of these populations have been started
with the final aim of recovering the autochthonous genetic types. The global approach involves different steps:
- characterization of the farming system and typical products; - morphological and productive evaluation of the
animals; - genetic characterization of the populations through molecular DNA analyses (microsatellites, AFLP,
mitochondrial DNA, etc.); - creation of nucleus flocks in public farms and germoplasm banks; - organization of
herd-books involving farmers interested in the safeguard of local breeds and valorisation of traditional products.
A far as the goat population is concerned, Sardinia is the Italian region with the largest goat stock,
(209.000 heads, about 23% of the total national stock). Farms are located in mountains, low hills and even
plans (Macciotta et al., 2002) resulting in a quite large variability (Brandano and Piras, 1978) in terms of feeding
and management techniques; but extensive and semi extensive systems in marginal areas prevail (Carta
et al., 2001; Usai et al., 2004). The current population has been constituted by crossbreeding the autochthonous
animals with other improved Mediterranean breeds,mainly Maltese goat. The aim of this paper is to study the
genetic variability of this population through the analysis of 17 microsatellite markers
A Method to Identify and Analyze Biological Programs through Automated Reasoning.
Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function
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