Mediative fuzzy logic: a new approach for contradictory knowledge management

In this paper we are proposing a novel fuzzy method that can handle imperfect knowledge in a broader way than Intuitionistic (in the sense of Atanassov) fuzzy logic does (IFL). This fuzzy method can manage non- contradictory, doubtful, and contradictory information provided by experts, providing a mediated solution, so we called it Mediative Fuzzy Logic (MFL). We are comparing results of MFL, with IFL and traditional Fuzzy logic (FL).     

A partially supervised classification approach to dominant and recessive human disease gene prediction

The discovery of the genes involved in genetic diseases is a very important step towards the understanding of the nature of these diseases. In-lab identification is a difficult, time-consuming task, where computational methods can be very useful. In silico identification algorithms can be used as a guide in future studies. Previous works in this topic have not taken into account that no reliable sets of negative examples are available, as it is not possible to ensure that a given gene is not related to any genetic disease. In this paper, this feature of the nature of the problem is considered, and identification is approached as a partially supervised classification problem. In addition, we have performed a more specific method to identify disease genes by classifying, for the first time, genes causing dominant and recessive diseases independently. We base this separation on previous results that show that these two types of genes present differences in their sequence properties. In this paper, we have applied a new model averaging algorithm to the identification of human genes associated with both dominant and recessive Mendelian diseases.     

Network convergence and QoS for future multimedia services in the VISION project

The emerging use of real-time 3D-based multimedia applications imposes strict quality of service (QoS) requirements on both access and core networks. These requirements and their impact to provide end-to-end 3D videoconferencing services have been studied within the Spanish-funded VISION project, where different scenarios were implemented showing an agile stereoscopic video call that might be offered to the general public in the near future. In view of the requirements, we designed an integrated access and core converged network architecture which provides the requested QoS to end-to-end IP sessions. Novel functional blocks are proposed to control core optical networks, the functionality of the standard ones is redefined, and the signaling improved to better meet the requirements of future multimedia services. An experimental test-bed to assess the feasibility of the solution was also deployed. In such test-bed, set-up and release of end-to-end sessions meeting specific QoS requirements are shown and the impact of QoS degradation in terms of the user perceived quality degradation is quantified. In addition, scalability results show that the proposed signaling architecture is able to cope with large number of requests introducing almost negligible delay.     

N‐Lauroylation during the Expression of Recombinant N‐Myristoylated Proteins: Implications and Solutions

Incorporation of myristic acid onto the N terminus of a protein is a crucial modification that promotes membrane binding and correct localization of important components of signaling pathways. Recombinant expression of N‐myristoylated proteins in Escherichia coli can be achieved by co‐expressing yeast N‐myristoyltransferase and supplementing the growth medium with myristic acid. However, undesired incorporation of the 12‐carbon fatty acid lauric acid can also occur (leading to heterogeneous samples), especially when the available carbon sources are scarce, as it is the case in minimal medium for the expression of isotopically enriched samples. By applying this method to the brain acid soluble protein 1 and the 1–185 N‐terminal region of c‐Src, we show the significant, and protein‐specific, differences in the membrane binding properties of lauroylated and myristoylated forms. We also present a robust strategy for obtaining lauryl‐free samples of myristoylated proteins in both rich and minimal media.     

Impact of Prematurity and Perinatal Antibiotics on the Developing Intestinal Microbiota: A Functional Inference Study

Background: The microbial colonization of the neonatal gut provides a critical stimulus for normal maturation and development. This process of early microbiota establishment, known to be affected by several factors, constitutes an important determinant for later health. Methods: We studied the establishment of the microbiota in preterm and full-term infants and the impact of perinatal antibiotics upon this process in premature babies. To this end, 16S rRNA gene sequence-based microbiota assessment was performed at phylum level and functional inference analyses were conducted. Moreover, the levels of the main intestinal microbial metabolites, the short-chain fatty acids (SCFA) acetate, propionate and butyrate, were measured by Gas-Chromatography Flame ionization/Mass spectrometry detection. Results: Prematurity affects microbiota composition at phylum level, leading to increases of Proteobacteria and reduction of other intestinal microorganisms. Perinatal antibiotic use further affected the microbiota of the preterm infant. These changes involved a concomitant alteration in the levels of intestinal SCFA. Moreover, functional inference analyses allowed for identifying metabolic pathways potentially affected by prematurity and perinatal antibiotics use. Conclusion: A deficiency or delay in the establishment of normal microbiota function seems to be present in preterm infants. Perinatal antibiotic use, such as intrapartum prophylaxis, affected the early life microbiota establishment in preterm newborns, which may have consequences for later health.     

CCL2 Inhibition of Pro-Resolving Mediators Potentiates Neuroinflammation in Astrocytes

The chemokine CCL2 participates in multiple neuroinflammatory processes, mainly through the recruitment of glial cells. However, CCL2 has also been proven to exert different types of actions on these cells, including the modification of their response to inflammatory stimuli. In the present study we analyzed the effect of CCL2 on the resolution of inflammation in astrocytes. We observed that genetic removal of CCL2 increases the expression of the enzymes responsible for the synthesis of specialized pro-resolving mediators arachidonate 15-lipoxygenase and arachidonate 5-lipoxygenase in the brain cortex of 5xFAD mice. The expression of FPR2 receptor, known to mediate the activity of pro-resolving mediators was also increased in mice lacking CCL2.The downregulation of these proteins by CCL2 was also observed in cultured astrocytes. This suggests that CCL2 inhibition of the resolution of inflammation could facilitate the progression of neuroinflammatory processes. The production of the pro-inflammatory cytokine IL-1beta by astrocytes was analyzed, and allowed us to confirm that CCL2 potentiates the activation of astrocytes trough the inhibition of pro-resolving pathways mediated by Resolvin D1. In addition, the analysis of the expression of TNFalpha, MIP1alpha and NOS2 further confirmed CCL2 inhibition of inflammation resolution in astrocytes.     

State your position

Autonomous vehicles (AVs) andmobile robots are developed to carry out specific tasks autonomously, ideally with no human intervention at all [1], [2]. These kinds of vehicles, whether AVs or mobile robots, has generated great interest in recent years, for instance, because of their capacity to work in remote or harmful environments where humans cannot enter because of the extreme operating conditions [3].We are differentiating amobile robot (designed from scratch for a specific task) from an AV (a commercial vehicle with proper sensory and control systems added so as to be autonomous). However, in the sequel, for the sake of simplicity, we will use indistinctly one or the other term. Several applications are found in the literature, varying from material transportation in a common industrial environment [4] to the exciting exploration of a far planet surface [5], [6].     

Application of a breeder genetic algorithm for filter optimization

In this work we are optimizing an adaptive finite impulse response filter applied to the problem of system identification. We are proposing a breeder genetic algorithm (BGA) for performing the parametric search in highly multimoldal landscapes since in this kind of filters there exits epistiasis. The results of BGA were compared to the traditional genetic algorithm, and we found that the BGA was clearly superior (in accuracy) in most of the cases. We used the statistical least mean squared for validating the results. We suggest to hybridized both methods for real world applications.