IMSE-CNM

The existence of a coevolutionary process between avian brood parasites and their hosts predicts a lower intra-clutch variation in egg appearance of host eggs among rejecters as this would favour egg discrimination of parasite eggs by hosts once parasitic egg mimicry had evolved. So far empirical tests of this prediction have ignored the fact that different aspects of host egg phenotypes may differ in the relative role of environmental versus genetic determination, and hence that the role of intra-clutch variation in egg rejection within a population cannot be invariant. Here, we estimated whether the intra-clutch variation in several aspects of host eggshell features is consistently associated to rejection of parasitic foreign eggs across years in a magpie host population parasitized by great spotted cuckoos. We innovatively estimated spottiness by means of the fractal dimension of eggs, which considers the homogeneity of spot pattern complexity in eggshells. Our results show that low intra-clutch variation in the blue-green coloration at the middle area of the eggs associated with a high chance of rejection, but only in one of the three years we conducted the study. In addition, females that rejected foreign eggs presented more homogenous spot patterns in their clutches as estimated by their fractal dimension than females that accepted experimental eggs, independently of the year of study. Finally, intra-clutch variation in egg volume of host eggs was not associated to rejection. Analyses at the individual level revealed that the relative role of genetic versus environmental factors determination egg phenotype would be feature-specific in magpies, females having a characteristic spottiness, but not colour or volume, pattern. Our work stresses the importance of considering a holistic approach including several aspects of variation in host egg phenotype (size, colour, and homogeneity of spot pattern), as some aspects might be more susceptible to selection through egg rejection than others, presumably because they are less influenced by variation in the environmental conditions. Moreover, our study highlights the importance of replication in studies on the adaptive value of host traits in egg rejection.

This paper demonstrates experimentally how to reduce the nonlinearity of some analog and mixed-signal circuits by using the enhanced body effect provided by Fully-Depleted Silicon on Insulator (FD-SOI) CMOS technology. A current-starved CMOS inverter and a Voltage-Controlled Ring Oscillator (VCRO) are considered as case studies. The inverter is configured as a simple amplifier stage in which the harmonic distortion can be reduced and even removed by the combined action of the control voltages applied at the gate and bulk terminals of the current-source transistors. This current-starved inverter is used as the basic building block of a VCRO, where a more linear voltage-to-frequency characteristic can be achieved if the bulk terminal is used as the control voltage of the oscillator. The circuits under study have been designed and fabricated in a 28-nm FD-SOI technology and experimental results are shown to validate the presented approach.

Vascular malformations classification may pose a diagnostic challenge for physicians. In the early stages, they are diagnosed clinically mainly by visual inspection. For a deeper analysis, Doppler ultrasonography is the preferred technique to determine the haemodynamic behaviour of the anomaly. However, this imaging method is not always available and it requires trained operators to acquire and interpret the images. There is a lack of portable and user-friendly systems that may help physicians in the assessment of vascular malformations. We propose a new diagnostic procedure, more affordable and easier to use, based on a portable thermal camera. This technique provides information about temperature, which has been found to be correlated with the flow rate of the lesion. In our study, > 60 vascular malformations of previously diagnosed patients were analysed with a thermal camera to classify them into low-flow and high-flow malformations. The value was 1 for both sensitivity and specificity of this technique.

Latest advances in CMOS technology, neuromorphic computing and flexible electronics are leading the way to a new era of brain implantable devices that promise to provide innovative and more effective treatments for brain disorders. Real-time signal detection and classification, as well as anticipation of brain electrical activity are yet under development. Microelectrode arrays (MEA) arise as a promising technology enabling detection of local fieldpotentials from multiple locations and permitting the acquisition of more information on brain network electrical activity than conventional electrophysiology techniques. However, whereas most of the electrophysiological studies addressing brain activity have focused on events/patterns analysis, no one has so far addressed the features that might be hidden within the signal baseline. Such features might be particularly relevant in the context of epilepsy, as the signal baseline may carry relevant information for seizure prediction. Here, we present a preliminary processing and analysis of signal baseline acquired through MEA in an in vitro model of limbic seizures. The signal conditioning was implemented using an infinite impulse response (IIR) digital filter. After signal preprocessing, we applied an averaging method to 16 baseline sections to find common patterns and to study the frequency spectrum of this type of signal. We have found signal components between 0.5-2 Hz and peaks at 350, 390 and 650 Hz. In addition, the reconstruction of the averaged signal may provide insights into the main baseline wave patterns. These results might be a preliminary step to study the influence of those components on a biological basis. Based on these results, we propose a possible electronic architecture implementation of the signal processing method.