Observations of OJ 287 from the Geodetic VLBI Archive of the Washington Correlator

We present 27 geodetic VLBI maps of OJ 287 obtained from the archive of the Washington correlator. The observations presented here were made between 1990 October and 1996 December. During this period a sequence of six superluminal components has been identified. We measured the proper motion of these components to be approximately 0.5 mas/yr, which is about twice as high as that seen in previous VLBI observations. These results imply a higher component ejection rate than previously observed, in good agreement with the observed occurrences of radio outbursts. We have examined a possible connection between VLBI components and optical flares in the framework of a binary black hole system.Comment: 9 pages, 5 included figures, emulateapj.sty, accepted to The Astrophysical Journa

On the calculation of the bandgap of periodic solids with MGGA functionals using the total energy

During the last few years, it has become more and more clear that functionals of the meta generalized gradient approximation (MGGA) are more accurate than GGA functionals for the geometry and energetics of electronic systems. However, MGGA functionals are also potentially more interesting for the electronic structure, in particular, when the potential is nonmultiplicative (i.e., when MGGAs are implemented in the generalized Kohn-Sham framework), which may help to get more accurate bandgaps. Here, we show that the calculation of bandgap of solids with MGGA functionals can also be done very accurately in a non-self-consistent manner. This scheme uses only the total energy and can, therefore, be very useful when the self-consistent implementation of a particular MGGA functional is not available. Since self-consistent MGGA calculations may be difficult to converge, the non-self-consistent scheme may also help to speed up the calculations. Furthermore, it can be applied to any other types of functionals, for which the implementation of the corresponding potential is not trivial

Reasoning about norms under uncertainty in dynamic environments

The behaviour of norm-autonomous agents is determined by their goals and the norms that are explicitly represented inside their minds. Thus, they require mechanisms for acquiring and accepting norms, determining when norms are relevant to their case, and making decisions about norm compliance. Up until now the existing proposals on norm-autonomous agents assume that agents interact within a deterministic environment that is certainly perceived. In practise, agents interact by means of sensors and actuators under uncertainty with non-deterministic and dynamic environments. Therefore, the existing proposals are unsuitable or, even, useless to be applied when agents have a physical presence in some real-world environment. In response to this problem we have developed the n-BDI architecture. In this paper, we propose a multi-context graded BDI architecture (called n-BDI) that models norm-autonomous agents able to deal with uncertainty in dynamic environments. The n-BDI architecture has been experimentally evaluated and the results are shown in this paper. © 2014 Elsevier Inc. All rights reserved

Knowledge Acquisition by Networks of Interacting Agents in the Presence of Observation Errors

In this work we investigate knowledge acquisition as performed by multiple agents interacting as they infer, under the presence of observation errors, respective models of a complex system. We focus the specific case in which, at each time step, each agent takes into account its current observation as well as the average of the models of its neighbors. The agents are connected by a network of interaction of Erd\H{o}s-Renyi or Barabasi-Albert type. First we investigate situations in which one of the agents has a different probability of observation error (higher or lower). It is shown that the influence of this special agent over the quality of the models inferred by the rest of the network can be substantial, varying linearly with the respective degree of the agent with different estimation error. In case the degree of this agent is taken as a respective fitness parameter, the effect of the different estimation error is even more pronounced, becoming superlinear. To complement our analysis, we provide the analytical solution of the overall behavior of the system. We also investigate the knowledge acquisition dynamic when the agents are grouped into communities. We verify that the inclusion of edges between agents (within a community) having higher probability of observation error promotes the loss of quality in the estimation of the agents in the other communities.Comment: 10 pages, 7 figures. A working manuscrip

Reasoning about constitutive norms in BDI agents

Software agents can be members of different institutions along their life; they might even belong to different institutions simultaneously. For these reasons, agents need capabilities that allow them to determine the repercussion that their actions would have within the different institutions. This association between the physical word, in which agents' interactions and actions take place, and the institutional world is defined by means of constitutive norms. Currently, the problem of how agents reason about constitutive norms has been tackled from a theoretical perspective only. Thus, there is a lack of more practical proposals that allow the development of software agents capable of reasoning about constitutive norms. In this article we propose an information model, knowledge representation and an inference mechanism to enable Belief-Desire-Intention agents to reason about the consequences of their actions on the institutions and making decisions accordingly. Specifically, the information model, knowledge representation and inference mechanism proposed in this article allows agents to keep track of the institutional state given that they have a physical presence in some real-world environment. Agents have a limited and not fully believable knowledge of the physical world (i.e. they are placed in an uncertain environment). Therefore, our proposal also deals with the uncertainty of the environment. © The Author 2013. Published by Oxford University Press. All rights reserved

SPARC is a new myeloid-derived suppressor cell marker licensing suppressive activities

Myeloid-derived suppressor cells (MDSC) are well-known key negative regulators of the immune response during tumor growth, however scattered is the knowledge of their capacity to influence and adapt to the different tumor microenvironments and of the markers that identify those capacities. Here we show that the secreted protein acidic and rich in cysteine (SPARC) identifies in both human and mouse MDSC with immune suppressive capacity and pro-tumoral activities including the induction of epithelial-to-mesenchymal transition (EMT) and angiogenesis. In mice the genetic deletion of SPARC reduced MDSC immune suppression and reverted EMT. Sparc−/− MDSC were less suppressive overall and the granulocytic fraction was more prone to extrude neutrophil extracellular traps (NET). Surprisingly, arginase-I and NOS2, whose expression can be controlled by STAT3, were not down-regulated in Sparc−/− MDSC, although less suppressive than wild type (WT) counterpart. Flow cytometry analysis showed equal phosphorylation of STAT3 but reduced ROS production that was associated with reduced nuclear translocation of the NF-kB p50 subunit in Sparc−/− than WT MDSC. The limited p50 in nuclei reduce the formation of the immunosuppressive p50:p50 homodimers in favor of the p65:p50 inflammatory heterodimers. Supporting this hypothesis, the production of TNF by Sparc−/− MDSC was significantly higher than by WT MDSC. Although associated with tumor-induced chronic inflammation, TNF, if produced at high doses, becomes a key factor in mediating tumor rejection. Therefore, it is foreseeable that an unbalance in TNF production could skew MDSC toward an inflammatory, anti-tumor phenotype. Notably, TNF is also required for inflammation-driven NETosis. The high level of TNF in Sparc−/− MDSC might explain their increased spontaneous NET formation as that we detected both in vitro and in vivo, in association with signs of endothelial damage. We propose SPARC as a new potential marker of MDSC, in both human and mouse, with the additional feature of controlling MDSC suppressive activity while preventing an excessive inflammatory state through the control of NF-kB signaling pathway

Reasoning about constitutive norms in BDI agents

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Logic Journal of the IGPL following peer review. The definitive publisher-authenticated version: Criado Pacheco, N.; Argente Villaplana, E.; Noriega, P.; Botti Navarro, VJ. (2014). Reasoning about constitutive norms in BDI agents. Logic Journal of the IGPL. 22(1):66-93 is available online at: http://dx.doi.org/1093/jigpal/jzt035Software agents can be members of different institutions along their life; they might even belong to different institutions simultaneously. For these reasons, agents need capabilities that allow them to determine the repercussion that their actions would have within the different institutions. This association between the physical word, in which agents interactions and actions take place, and the institutional world is defined by means of constitutive norms. Currently, the problem of how agents reason about constitutive norms has been tackled from a theoretical perspective only. Thus, there is a lack of more practical proposals that allow the development of software agents capable of reasoning about constitutive norms. In this article we propose an information model, knowledge representation and an inference mechanism to enable Belief-Desire-Intention agents to reason about the consequences of their actions on the institutions and making decisions accordingly. Specifically, the information model, knowledge representation and inference mechanism proposed in this article allows agents to keep track of the institutional state given that they have a physical presence in some real-world environment. Agents have a limited and not fully believable knowledge of the physical world (i.e. they are placed in an uncertain environment). Therefore, our proposal also deals with the uncertainty of the environment.Criado Pacheco, N.; Argente Villaplana, E.; Noriega, P.; Botti Navarro, VJ. (2014). Reasoning about constitutive norms in BDI agents. Logic Journal of the IGPL. 22(1):66-93. doi:10.1093/jigpal/jzt035S6693221Baldi, P., Brunak, S., Chauvin, Y., Andersen, C. A. F., & Nielsen, H. (2000). Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics, 16(5), 412-424. doi:10.1093/bioinformatics/16.5.412Bloch, I. (1996). Information combination operators for data fusion: a comparative review with classification. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 26(1), 52-67. doi:10.1109/3468.477860Casali, A., Godo, L., & Sierra, C. (2011). A graded BDI agent model to represent and reason about preferences. Artificial Intelligence, 175(7-8), 1468-1478. doi:10.1016/j.artint.2010.12.006Criado, N., Julián, V., Botti, V., & Argente, E. (2010). A Norm-Based Organization Management System. Lecture Notes in Computer Science, 19-35. doi:10.1007/978-3-642-14962-7_2Governatori, G., & Rotolo, A. (2008). BIO logical agents: Norms, beliefs, intentions in defeasible logic. Autonomous Agents and Multi-Agent Systems, 17(1), 36-69. doi:10.1007/s10458-008-9030-4Grossi, D., Aldewereld, H., Vázquez-Salceda, J., & Dignum, F. (2006). Ontological aspects of the implementation of norms in agent-based electronic institutions. Computational & Mathematical Organization Theory, 12(2-3), 251-275. doi:10.1007/s10588-006-9546-6Hübner, J. F., Boissier, O., Kitio, R., & Ricci, A. (2009). Instrumenting multi-agent organisations with organisational artifacts and agents. Autonomous Agents and Multi-Agent Systems, 20(3), 369-400. doi:10.1007/s10458-009-9084-yJONES, A. J. I., & SERGOT, M. (1996). A Formal Characterisation of Institutionalised Power. Logic Journal of IGPL, 4(3), 427-443. doi:10.1093/jigpal/4.3.427Rawls, J. (1955). Two Concepts of Rules. The Philosophical Review, 64(1), 3. doi:10.2307/2182230Da Silva, V. T. (2008). From the specification to the implementation of norms: an automatic approach to generate rules from norms to govern the behavior of agents. Autonomous Agents and Multi-Agent Systems, 17(1), 113-155. doi:10.1007/s10458-008-9039-

ON THE APPLICATION OF REMOTE SENSING TIME SERIES ANALYSIS FOR LAND COVER MAPPING: SPECTRAL INDICES FOR CROPS CLASSIFICATION

Abstract. This study aims to introduce a semi-automatic classification workflow for the production of a land use/land cover (LULC) map of the island of Sardinia (Italy) following the CORINE legend schema, and a ground spatial resolution compatible with a scale of 1:25.000. The classification is based on free high-resolution satellite imagery from Sentinel-1 and Sentinel-2 collected in 2020, ancillary data derived from Sardinian Geoportal, Joint Research Centre (JRC) and OpenStreetMap. The LULC map production includes three steps: 1) pixel-based classification, realized with two different approaches, that use i) information derived from existing thematic maps eventually re-coded in case of incoherencies observed between datasets and/or satellite data products, and ii) spectral indices and parameter thresholds defined on the basis of multitemporal analysis; 2) segmentation of Sentinel-1 and 2 annual composites, and pre-labelling of segments with the pixel-based classified map, obtaining the preliminary map; 3) visual inspection procedure in order to confirm, or re-assign, classes to polygons. The accuracy of the preliminary map was tested in a sample area and on specific class of non-irrigated crops through ground truth data collected from a detailed photo-interpretation, estimating 97% of overall accuracy. The results show a great improvement from existing thematic maps in terms of detail, with the possibility of a yearly updating of the map via automatic processes. However, some limitations were found, due to the high fragmentation of Sardinian landscape and the high variety of crop types and agricultural practices, that could affect the efficiency of the classifier