207 research outputs found
A Biased Resistor Network Model for Electromigration Failure and Related Phenomena in Metallic Lines
Electromigration phenomena in metallic lines are studied by using a biased
resistor network model. The void formation induced by the electron wind is
simulated by a stochastic process of resistor breaking, while the growth of
mechanical stress inside the line is described by an antagonist process of
recovery of the broken resistors. The model accounts for the existence of
temperature gradients due to current crowding and Joule heating. Alloying
effects are also accounted for. Monte Carlo simulations allow the study within
a unified theoretical framework of a variety of relevant features related to
the electromigration. The predictions of the model are in excellent agreement
with the experiments and in particular with the degradation towards electrical
breakdown of stressed Al-Cu thin metallic lines. Detailed investigations refer
to the damage pattern, the distribution of the times to failure (TTFs), the
generalized Black's law, the time evolution of the resistance, including the
early-stage change due to alloying effects and the electromigration saturation
appearing at low current densities or for short line lengths. The dependence of
the TTFs on the length and width of the metallic line is also well reproduced.
Finally, the model successfully describes the resistance noise properties under
steady state conditions.Comment: 39 pages + 17 figure
Characterization of CMOS Spiral Inductors
In this work "full-wave" simulations of integrated inductors are presented and compared with measurements of fabricated CMOS chips. The good agreement between measurements and simulations demonstrates the accuracy of the tool, which is, hence, a cheaper alternative to experimental characterization. Furthermore, the proposed approach may give precious hints for performance improvements, by making internal device fields and currents available for the VLSI designer and providing compact, most effective, equivalent models
Linear and nonlinear post-processing of numerically forecasted surface temperature
International audienceIn this paper we test different approaches to the statistical post-processing of gridded numerical surface air temperatures (provided by the European Centre for Medium-Range Weather Forecasts) onto the temperature measured at surface weather stations located in the Italian region of Puglia. We consider simple post-processing techniques, like correction for altitude, linear regression from different input parameters and Kalman filtering, as well as a neural network training procedure, stabilised (i.e. driven into the absolute minimum of the error function over the learning set) by means of a Simulated Annealing method. A comparative analysis of the results shows that the performance with neural networks is the best. It is encouraging for systematic use in meteorological forecast-analysis service operations
Thermal Transient Measurements of an Ultra-Low-Power MOX Sensor
This paper describes a system for the simultaneous dynamic control and thermal characterization of the heating of an Ultra Low Power (ULP) micromachined sensor. A Pulse Width Modulated (PWM) powering system has been realized using a microcontroller to characterize the thermal behavior of a device. Objectives of the research were to analyze the relation between the time period and duty cycle of the PWM signal and the operating temperature of such ULP micromachined systems, to observe the thermal time constants of the device during the heating phase and to measure the total thermal conductance. Constant target heater resistance experiments highlighted that an approximately constant heater temperature at regime can only be obtained if the time period of the heating signal is smaller than 50 s. Constant power experiments show quantitatively a thermal time constant that decreases during heating in a range from 2.3 ms to 2 ms as a function of an increasing temperature rise between the ambient and the operating temperature. Moreover, we calculated the total thermal conductance. Finally, repeatability of experimental results was assessed by guaranteeing the standard deviation of the controlled temperature which was within C in worst case conditions
From moths to caterpillars: Ideal conditions for Galleria mellonella rearing for in vivo microbiological studies.
ABSTRACT Galleria mellonella is a well-accepted insect model for the study of pathogen-host interactions and antimicrobial compounds. The main advantages of this model include the low cost of maintenance, the fast life cycle, the possibility of using a large number of caterpillars and the innate immune system, which is evolutionarily conserved relative to mammals. Because of these advantages, different research groups have been working to implement the rearing of G. mellonella in laboratory conditions. This protocol describes our experience in the rearing of G. mellonella caterpillars for experimental infection models and the influence of different artificial diets on developmental and physiological parameters. Here, we suggest a diet composition that benefits the life cycle of G. mellonella by accelerating the larval phase length and increasing the caterpillar weight. This diet also stimulated the immune system of G. mellonella by increasing the hemolymph volume and hemocyte concentration. In addition, our rearing protocol generated caterpillars that are more resistant to infection by Staphylococcus aureus, Escherichia coli and Candida albicans. A standard G. mellonella rearing protocol is fundamental to minimize external influences on the results, and this simple and easy protocol can support researchers starting to rear G. mellonella
Resistance and Resistance Fluctuations in Random Resistor Networks Under Biased Percolation
We consider a two-dimensional random resistor network (RRN) in the presence
of two competing biased percolations consisting of the breaking and recovering
of elementary resistors. These two processes are driven by the joint effects of
an electrical bias and of the heat exchange with a thermal bath. The electrical
bias is set up by applying a constant voltage or, alternatively, a constant
current. Monte Carlo simulations are performed to analyze the network evolution
in the full range of bias values. Depending on the bias strength, electrical
failure or steady state are achieved. Here we investigate the steady-state of
the RRN focusing on the properties of the non-Ohmic regime. In constant voltage
conditions, a scaling relation is found between and , where
is the average network resistance, the linear regime resistance
and the threshold value for the onset of nonlinearity. A similar relation
is found in constant current conditions. The relative variance of resistance
fluctuations also exhibits a strong nonlinearity whose properties are
investigated. The power spectral density of resistance fluctuations presents a
Lorentzian spectrum and the amplitude of fluctuations shows a significant
non-Gaussian behavior in the pre-breakdown region. These results compare well
with electrical breakdown measurements in thin films of composites and of other
conducting materials.Comment: 15 figures, 23 page
Impact of Resistance to Fluconazole on Virulence and Morphological Aspects of Cryptococcus neoformans and Cryptococcus gattii Isolates
Cryptococcus spp. are responsible for around one million cases of meningitis every year. Fluconazole (FLU) is commonly used in the treatment of cryptococcosis, mainly in immunocompromised patients and the resistance is usually reported after long periods of treatment. In this study, the morphological characterization and virulence profile of FLU-susceptible and FLU-resistant clinical and environmental isolates of C. neoformans and C. gattii were performed both in vitro and in vivo using the Galleria mellonella model. FLU-susceptible isolates from C. neoformans were significantly more virulent than the FLU-resistant isolates. FLU-susceptible C. gattii isolates showed a different virulence profile from C. neoformans isolates where only the environmental isolate, CL, was more virulent compared with the resistant isolates. Cell morphology and capsule size were analyzed and the FLU-resistant isolates did not change significantly compared with the most sensitive isolates. Growth at 37°C was also evaluated and in both species, the resistant isolates showed a reduced growth at this temperature, indicating that FLU resistance can affect their growth. Based on the results obtained is possible suggest that FLU resistance can influence the morphology of the isolates and consequently changed the virulence profiles. The most evident results were observed for C. neoformans showing that the adaptation of isolates to antifungal selective pressure influenced the loss of virulence
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