93 research outputs found

    Neanderthal teeth from Lezetxiki (Arrasate, Iberian Peninsula): New insights and reassessment

    Get PDF
    Objectives: We reassess the taxonomic assignment and stratigraphic context of a permanent upper first molar and a permanent lower third premolar recovered from the archeological site of Lezetxiki in the North of the Iberian Peninsula. Materials and Methods: We assessed the external and internal morphology of the teeth using qualitative descriptions, crown diameters, dental tissue proportions, and geometric morphometrics. The teeth from Lezetxiki were compared with Middle Pleistocene specimens, Neanderthals, Upper Paleolithic modern humans, and recent modern humans. Results: Both teeth were consistent with a Neanderthal classification. The upper first molar shows taurodontism, and its cusp proportions and overall morphology match those of Neanderthals. Geometric morphometric analyses of occlusal anatomy classify this molar as a Neanderthal with a posterior probability of 76%. The lower third premolar, which was originally classified as a lower fourth premolar, also shows a Neanderthal morphology. This premolar is classified as a Neanderthal with a posterior probability of 60%. Discussion: These teeth represent the only adult Neanderthal teeth from the Western Pyrenees region found to date. The teeth were found at a stratigraphic level (designated Level III) that marks the transition level from Mousterian to Aurignacian, and are among the most recent Neanderthal remains from the north of the Iberian Peninsula

    Deliberative Context-Aware Ambient Intelligence System for Assisted Living Homes

    Full text link
    Monitoring wellbeing and stress is one of the problems covered by ambient intelligence, as stress is a significant cause of human illnesses directly affecting our emotional state. The primary aim was to propose a deliberation architecture for an ambient intelligence healthcare application. The architecture provides a plan for comforting stressed seniors suffering from negative emotions in an assisted living home and executes the plan considering the environment's dynamic nature. Literature was reviewed to identify the convergence between deliberation and ambient intelligence and the latter's latest healthcare trends. A deliberation function was designed to achieve context-aware dynamic human-robot interaction, perception, planning capabilities, reactivity, and context-awareness with regard to the environment. A number of experimental case studies in a simulated assisted living home scenario were conducted to demonstrate the approach's behavior and validity. The proposed methods were validated to show classification accuracy. The validation showed that the deliberation function has effectively achieved its deliberative objectives

    ZONACIÓN DE LA VEGETACIÓN HALÓFILA A LO LARGO DE UN GRADIENTE DE EXPOSICIÓN MAREAL Y PROCESOS ASOCIADOS

    Get PDF
    The zonation of vegetation in the salt-marsh of Mundaka-Gemika (Bay of Biscay, N. Spain) is studied along a small scale topographic gradient. Species distribution appears closely linked to abiotic factors deriving from topographical level, such as organic matter, pH, moisture and conductivity. The redox potential and the compactness of the soil vary in other ways, thus increasing the heterogeneity of the habitat. There is a critica1 elevation, close to MHW level, after which coexistence processes give way to dominance by the best equipped species. A model of the zonation is given. In this model the degree of overlap decreases towards the top area, where there is competitive exclusion and segregation of interior species to the most exposed area. It can not be concluded that the marked segregation of the species along the gradient is exclusively due to physiological requirements of the plants. Tidal dispersal probably plays an important role on the distributional pattem of the annual species Salicornia and Suaeda, but a minor role on the species with vegetative expansion, Spartina maritima, Arthrocnemum perenne, Halimioneportulacoides, and Arthrocnemumfr.uticosum. Plant zonation can only be explained bearing in mind associated processes such as physical disturbance and interspecific competition. As other authors found in higher latitudes, these processes will need to be considered in relation to edaphic factors in elucidating the underlying mechanisms of salt marsh plant zonation. Experimental work in field and laboratory is needed to determine the niche position of each species in the salt marshes in this part of the Atlantic Coast.Se ha estudiado la zonación de la vegetación a lo largo de un gradiente topográfico a pequeña escala en la marisma de Mundaka-Gemika (Norte de España, Golfo de Vizcaya). La distribución de las especies aparece estrechamente ligada a los factores derivados de la topografía, como son la materia orgánica, el pH, la humedad y la conductividad. El potencial redox y la compactación del suelo varían independientemente, aumentando la heterogeneidad del hábitat. La altura media de las pleamares es el nivel a partir del cual los procesos de coexistencia dan paso a la dominancia de las especies competidoras. Se plantea un modelo de zonación. En este modelo, el grado de solapamiento disminuye hacia tierra adentro, donde se produce una competencia y una segregación de las especies inferiores hacia los lugares más expuestos. No se puede concluir que la marcada segregación de las especies a lo largo del gradiente sea debida exclusivamente a los requerimientos fisiológicos de las plantas. La dispersión mareal juega probablemente un importante papel en la distribución de las anuales Salicornia y Suaeda, pero escaso en las especies con crecimiento vegetativo, Spartina maritima, Arthrocnemum perenne, Halimione portuhcoides, y Arthiocnemum fruticosum. La zonación de las plantas debe ser explicada teniendo en cuenta procesos asociados como la perturbación física y la competencia interespecífica, que deben ser considerados en relación con los factores edáficos, para explicar los mecanismos subyacentes de tal zonación. Es necesario el trabajo en el campo y en el laboratorio para determinar el nicho de estas especies en las marismas de esta parte de la Costa Atlántica

    CD30-positive primary cutaneous lymphoproliferative disorders: molecular alterations and targeted therapies

    Get PDF
    Primary cutaneous CD30-positive T-cell lymphoproliferative disorders are the second most common subgroup of cutaneous T-cell lymphomas. They include two clinically different entities with some overlapping features and borderline cases: lymphomatoid papulosis and primary cutaneous anaplastic large cell lymphoma. Molecular studies of primary cutaneous anaplastic large cell lymphoma reveal an increasing level of heterogeneity that is associated with histological and immunophenotypic features of the cases and their response to specific therapies. Here, we review the most significant genetic, epigenetic and molecular alterations described to date in primary cutaneous CD30-positive T-cell lymphoproliferative disorders, and their potential as therapeutic targets

    DUSP22-rearranged anaplastic lymphomas are characterized by specific morphological features and a lack of cytotoxic and JAK/STAT surrogate markers

    Full text link
    This work was supported by grants from the Instituto de Salud Carlos III (ISCIII) of the Spanish Ministry of Economy and Competence (MINECO, RTICC ISCIII and CIBERONC) (SAF2013-47416- R, RD06/0020/0107-RD012/0036/0060 and Plan Nacional I+D+I: PI16/01294 and PIE15/0081), AECC and the Madrid Autonomous Community

    e-Tourism: a tourist recommendation and planning application

    Full text link
    e-Tourism is a tourist recommendation and planning application to assist users on the organization of a leisure and tourist agenda. First, a recommender system offers the user a list of the city places that are likely of interest to the user. This list takes into account the user demographic classification, the user likes in former trips and the preferences for the current visit. Second, a planning module schedules the list of recommended places according to their temporal characteristics as well as the user restrictions; that is the planning system determines how and when to realize the recommended activities. Having the list of recommended activities organized as an agenda (i.e. an executable plan), is a relevant characteristic that most recommender systems lack.This work has been partially funded by Consolider Ingenio 2010 CSD2007-00022 project, by the Spanish Government MICINN TIN2008-6701-C03-01 project and by the Valencian Government GVPRE/2008/384 project. We thank J. Benton for having provided us with the system Sapa to execute our experiments.Sebastiá Tarín, L.; García García, I.; Onaindia De La Rivaherrera, E.; Gúzman Álvarez, CA. (2009). e-Tourism: a tourist recommendation and planning application. International Journal on Artificial Intelligence Tools. 18(5):717-738. https://doi.org/10.1142/S0218213009000378S71773818

    FMAP: Distributed Cooperative Multi-Agent Planning

    Full text link
    This paper proposes FMAP (Forward Multi-Agent Planning), a fully-distributed multi-agent planning method that integrates planning and coordination. Although FMAP is specifically aimed at solving problems that require cooperation among agents, the flexibility of the domain-independent planning model allows FMAP to tackle multi-agent planning tasks of any type. In FMAP, agents jointly explore the plan space by building up refinement plans through a complete and flexible forward-chaining partial-order planner. The search is guided by h D T G , a novel heuristic function that is based on the concepts of Domain Transition Graph and frontier state and is optimized to evaluate plans in distributed environments. Agents in FMAP apply an advanced privacy model that allows them to adequately keep private information while communicating only the data of the refinement plans that is relevant to each of the participating agents. Experimental results show that FMAP is a general-purpose approach that efficiently solves tightly-coupled domains that have specialized agents and cooperative goals as well as loosely-coupled problems. Specifically, the empirical evaluation shows that FMAP outperforms current MAP systems at solving complex planning tasks that are adapted from the International Planning Competition benchmarks.This work has been partly supported by the Spanish MICINN under projects Consolider Ingenio 2010 CSD2007-00022 and TIN2011-27652-C03-01, the Valencian Prometeo project II/2013/019, and the FPI-UPV scholarship granted to the first author by the Universitat Politecnica de Valencia.Torreño Lerma, A.; Onaindia De La Rivaherrera, E.; Sapena Vercher, O. (2014). FMAP: Distributed Cooperative Multi-Agent Planning. Applied Intelligence. 41(2):606-626. https://doi.org/10.1007/s10489-014-0540-2S606626412Benton J, Coles A, Coles A (2012) Temporal planning with preferences and time-dependent continuous costs. In: Proceedings of the 22nd international conference on automated planning and scheduling (ICAPS). AAAI, pp 2–10Borrajo D. (2013) Multi-agent planning by plan reuse. In: Proceedings of the 12th international conference on autonomous agents and multi-agent systems (AAMAS). IFAAMAS, pp 1141–1142Boutilier C, Brafman R (2001) Partial-order planning with concurrent interacting actions. J Artif Intell Res 14(105):136Brafman R, Domshlak C (2008) From one to many: planning for loosely coupled multi-agent systems. In: Proceedings of the 18th international conference on automated planning and scheduling (ICAPS). AAAI, pp 28–35Brenner M, Nebel B (2009) Continual planning and acting in dynamic multiagent environments. J Auton Agents Multiagent Syst 19(3):297–331Bresina J, Dearden R, Meuleau N, Ramakrishnan S, Smith D, Washington R (2002) Planning under continuous time and resource uncertainty: a challenge for AI. In: Proceedings of the 18th conference on uncertainty in artificial intelligence (UAI). Morgan Kaufmann, pp 77–84Cox J, Durfee E (2009) Efficient and distributable methods for solving the multiagent plan coordination problem. Multiagent Grid Syst 5(4):373–408Crosby M, Rovatsos M, Petrick R (2013) Automated agent decomposition for classical planning. In: Proceedings of the 23rd international conference on automated planning and scheduling (ICAPS). AAAI, pp 46–54Dimopoulos Y, Hashmi MA, Moraitis P (2012) μ-satplan: Multi-agent planning as satisfiability. Knowl-Based Syst 29:54–62Fikes R, Nilsson N (1971) STRIPS: a new approach to the application of theorem proving to problem solving. Artif Intell 2(3):189–208Gerevini A, Haslum P, Long D, Saetti A, Dimopoulos Y (2009) Deterministic planning in the fifth international planning competition: PDDL3 and experimental evaluation of the planners. Artif Intell 173(5-6):619–668Ghallab M, Nau D, Traverso P (2004) Automated planning. Theory and practice. Morgan KaufmannGünay A, Yolum P (2013) Constraint satisfaction as a tool for modeling and checking feasibility of multiagent commitments. Appl Intell 39(3):489–509Helmert M (2004) A planning heuristic based on causal graph analysis. In: Proceedings of the 14th international conference on automated planning and scheduling ICAPS. AAAI, pp 161–170Hoffmann J, Nebel B (2001) The FF planning system: fast planning generation through heuristic search. J Artif Intell Res 14:253–302Jannach D, Zanker M (2013) Modeling and solving distributed configuration problems: a CSP-based approach. IEEE Trans Knowl Data Eng 25(3):603–618Jonsson A, Rovatsos M (2011) Scaling up multiagent planning: a best-response approach. In: Proceedings of the 21st international conference on automated planning and scheduling (ICAPS). AAAI, pp 114–121Kala R, Warwick K (2014) Dynamic distributed lanes: motion planning for multiple autonomous vehicles. Appl Intell:1–22Koehler J, Ottiger D (2002) An AI-based approach to destination control in elevators. AI Mag 23(3):59–78Kovacs DL (2011) Complete BNF description of PDDL3.1. Technical reportvan der Krogt R (2009) Quantifying privacy in multiagent planning. Multiagent Grid Syst 5(4):451–469Kvarnström J (2011) Planning for loosely coupled agents using partial order forward-chaining. In: Proceedings of the 21st international conference on automated planning and scheduling (ICAPS). AAAI, pp 138–145Lesser V, Decker K, Wagner T, Carver N, Garvey A, Horling B, Neiman D, Podorozhny R, Prasad M, Raja A et al (2004) Evolution of the GPGP/TAEMS domain-independent coordination framework. Auton Agents Multi-Agent Syst 9(1–2):87–143Long D, Fox M (2003) The 3rd international planning competition: results and analysis. J Artif Intell Res 20:1–59Nissim R, Brafman R, Domshlak C (2010) A general, fully distributed multi-agent planning algorithm. In: Proceedings of the 9th international conference on autonomous agents and multiagent systems (AAMAS). IFAAMAS, pp 1323–1330O’Brien P, Nicol R (1998) FIPA - towards a standard for software agents. BT Tech J 16(3):51–59Öztürk P, Rossland K, Gundersen O (2010) A multiagent framework for coordinated parallel problem solving. Appl Intell 33(2):132–143Pal A, Tiwari R, Shukla A (2013) Communication constraints multi-agent territory exploration task. Appl Intell 38(3):357–383Richter S, Westphal M (2010) The LAMA planner: guiding cost-based anytime planning with landmarks. J Artif Intell Res 39(1):127–177de la Rosa T, García-Olaya A, Borrajo D (2013) A case-based approach to heuristic planning. Appl Intell 39(1):184–201Sapena O, Onaindia E (2008) Planning in highly dynamic environments: an anytime approach for planning under time constraints. Appl Intell 29(1):90–109Sapena O, Onaindia E, Garrido A, Arangú M (2008) A distributed CSP approach for collaborative planning systems. Eng Appl Artif Intell 21(5):698–709Serrano E, Such J, Botía J, García-Fornes A (2013) Strategies for avoiding preference profiling in agent-based e-commerce environments. Appl Intell:1–16Smith D, Frank J, Jónsson A (2000) Bridging the gap between planning and scheduling. Knowl Eng Rev 15(1):47–83Such J, García-Fornes A, Espinosa A, Bellver J (2012) Magentix2: a privacy-enhancing agent platform. Eng Appl Artif Intell:96–109Tonino H, Bos A, de Weerdt M, Witteveen C (2002) Plan coordination by revision in collective agent based systems. Artif Intell 142(2):121–145Torreño A, Onaindia E, Sapena O (2012) An approach to multi-agent planning with incomplete information. In: Proceedings of the 20th European conference on artificial intelligence (ECAI), vol 242. IOS Press, pp 762–767Torreño A, Onaindia E, Sapena O (2014) A flexible coupling approach to multi-agent planning under incomplete information. Knowl Inf Syst 38(1):141–178Van Der Krogt R, De Weerdt M (2005) Plan repair as an extension of planning. In: Proceedings of the 15th international conference on automated planning and scheduling (ICAPS). AAAI, pp 161–170de Weerdt M, Clement B (2009) Introduction to planning in multiagent systems. Multiagent Grid Syst 5(4):345– 355Yokoo M, Durfee E, Ishida T, Kuwabara K (1998) The distributed constraint satisfaction problem: formalization and algorithms. IEEE Trans Knowl Data Eng 10(5):673–685Zhang J, Nguyen X, Kowalczyk R (2007) Graph-based multi-agent replanning algorithm. In: Proceedings of the 6th international joint conference conference on autonomous agents and multiagent systems (AAMAS). IFAAMAS, pp 798–80

    A Better-response Strategy for Self-interested Planning Agents

    Full text link
    [EN] When self-interested agents plan individually, interactions that prevent them from executing their actions as planned may arise. In these coordination problems, game-theoretic planning can be used to enhance the agents¿ strategic behavior considering the interactions as part of the agents¿ utility. In this work, we define a general-sum game in which interactions such as conflicts and congestions are reflected in the agents¿ utility. We propose a better-response planning strategy that guarantees convergence to an equilibrium joint plan by imposing a tax to agents involved in conflicts. We apply our approach to a real-world problem in which agents are Electric Autonomous Vehicles (EAVs). The EAVs intend to find a joint plan that ensures their individual goals are achievable in a transportation scenario where congestion and conflicting situations may arise. Although the task is computationally hard, as we theoretically prove, the experimental results show that our approach outperforms similar approaches in both performance and solution quality.This work is supported by the GLASS project TIN2014-55637-C2-2-R of the Spanish MINECO and the Prometeo project II/2013/019 funded by the Valencian Government.Jordán, J.; Torreño Lerma, A.; De Weerdt, M.; Onaindia De La Rivaherrera, E. (2018). A Better-response Strategy for Self-interested Planning Agents. Applied Intelligence. 48(4):1020-1040. https://doi.org/10.1007/s10489-017-1046-5S10201040484Aghighi M, Bäckström C (2016) A multi-parameter complexity analysis of cost-optimal and net-benefit planning. In: Proceedings of the Twenty-Sixth International Conference on International Conference on Automated Planning and Scheduling. AAAI Press, London, pp 2–10Bercher P, Mattmüller R (2008) A planning graph heuristic for forward-chaining adversarial planning. In: ECAI, vol 8, pp 921–922Brafman RI, Domshlak C, Engel Y, Tennenholtz M (2009) Planning games. In: IJCAI 2009, Proceedings of the 21st international joint conference on artificial intelligence, pp 73–78Bylander T (1994) The computational complexity of propositional strips planning. Artif Intell 69(1):165–204Chen X, Deng X (2006) Settling the complexity of two-player nash equilibrium. In: 47th annual IEEE symposium on foundations of computer science, 2006. FOCS’06. IEEE, pp 261–272Chien S, Sinclair A (2011) Convergence to approximate nash equilibria in congestion games. Games and Economic Behavior 71(2):315–327de Cote EM, Chapman A, Sykulski AM, Jennings N (2010) Automated planning in repeated adversarial games. In: 26th conference on uncertainty in artificial intelligence (UAI 2010), pp 376–383Dunne PE, Kraus S, Manisterski E, Wooldridge M (2010) Solving coalitional resource games. Artif Intell 174(1):20–50Fabrikant A, Papadimitriou C, Talwar K (2004) The complexity of pure nash equilibria. In: Proceedings of the thirty-sixth annual ACM symposium on theory of computing, STOC ’04, pp 604–612Friedman JW, Mezzetti C (2001) Learning in games by random sampling. J Econ Theory 98(1):55–84Ghallab M, Nau D, Traverso P (2004) Automated planning: theory & practice. ElsevierGoemans M, Mirrokni V, Vetta A (2005) Sink equilibria and convergence. In: Proceedings of the 46th annual IEEE symposium on foundations of computer science, FOCS ’05, pp 142–154Hadad M, Kraus S, Hartman IBA, Rosenfeld A (2013) Group planning with time constraints. Ann Math Artif Intell 69(3):243–291Hart S, Mansour Y (2010) How long to equilibrium? the communication complexity of uncoupled equilibrium procedures. Games and Economic Behavior 69(1):107–126Helmert M (2003) Complexity results for standard benchmark domains in planning. Artif Intell 143(2):219–262Helmert M (2006) The fast downward planning system. J Artif Intell Res 26(1):191–246Jennings N, Faratin P, Lomuscio A, Parsons S, Wooldrige M, Sierra C (2001) Automated negotiation: prospects, methods and challenges. Group Decis Negot 10(2):199–215Johnson DS, Papadimtriou CH, Yannakakis M (1988) How easy is local search? J Comput Syst Sci 37 (1):79–100Jonsson A, Rovatsos M (2011) Scaling up multiagent planning: a best-response approach. In: Proceedings of the 21st international conference on automated planning and scheduling, ICAPSJordán J, Onaindía E (2015) Game-theoretic approach for non-cooperative planning. In: 29th AAAI conference on artificial intelligence (AAAI-15), pp 1357–1363McDermott D, Ghallab M, Howe A, Knoblock C, Ram A, Veloso M, Weld D, Wilkins D (1998) PDDL: the planning domain definition language. Yale Center for Computational Vision and Control, New HavenMilchtaich I (1996) Congestion games with player-specific payoff functions. Games and Economic Behavior 13(1):111–124Monderer D, Shapley LS (1996) Potential games. Games and Economic Behavior 14(1):124–143Nigro N, Welch D, Peace J (2015) Strategic planning to implement publicly available ev charching stations: a guide for business and policy makers. Tech rep, Center for Climate and Energy SolutionsNisan N, Ronen A (2007) Computationally feasible vcg mechanisms. J Artif Intell Res 29(1):19–47Nisan N, Roughgarden T, Tardos E, Vazirani VV (2007) Algorithmic game theory. Cambridge University Press, New YorkPapadimitriou CH (1994) On the complexity of the parity argument and other inefficient proofs of existence. J Comput Syst Sci 48(3):498–532Richter S, Westphal M (2010) The LAMA planner: guiding cost-based anytime planning with landmarks. J Artif Intell Res 39(1):127–177Rosenthal RW (1973) A class of games possessing pure-strategy nash equilibria. Int J Game Theory 2(1):65–67Shoham Y, Leyton-Brown K (2009) Multiagent systems: algorithmic, game-theoretic, and logical foundations. Cambridge University PressTorreño A, Onaindia E, Sapena Ó (2014) A flexible coupling approach to multi-agent planning under incomplete information. Knowl Inf Syst 38(1):141–178Torreño A, Onaindia E, Sapena Ó (2014) FMAP: distributed cooperative multi-agent planning. Appl Intell 41(2):606– 626Torreño A, Sapena Ó, Onaindia E (2015) Global heuristics for distributed cooperative multi-agent planning. In: ICAPS 2015. 25th international conference on automated planning and scheduling. AAAI Press, pp 225–233Von Neumann J, Morgenstern O (2007) Theory of games and economic behavior. Princeton University Pressde Weerdt M, Bos A, Tonino H, Witteveen C (2003) A resource logic for multi-agent plan merging. Ann Math Artif Intell 37(1):93–130Wooldridge M, Endriss U, Kraus S, Lang J (2013) Incentive engineering for boolean games. Artif Intell 195:418–43

    Prevalence of Systemic Lupus Erythematosus in Spain: Higher than Previously Reported in other Countries?

    Get PDF
    [Abstract] Objectives: Prevalence of SLE varies among studies, being influenced by study design, geographical area and ethnicity. Data about the prevalence of SLE in Spain are scarce. In the EPISER2016 study, promoted by the Spanish Society of Rheumatology, the prevalence estimate of SLE in the general adult population in Spain has been updated and its association with sociodemographic, anthropometric and lifestyle variables has been explored. Methods: Population-based multicentre cross-sectional study, with multistage stratified and cluster random sampling. Participants were contacted by telephone to carry out a questionnaire for the screening of SLE. Investigating rheumatologists evaluated positive results (review of medical records and/or telephone interview, with medical visit if needed) to confirm the diagnosis. To calculate the prevalence and its 95% CI, the sample design was taken into account and weighing was calculated considering age, sex and geographic origin. Multivariate logistic regression models were defined to analyse which sociodemographic, anthropometric and lifestyle variables included in the telephone questionnaire were associated with the presence of SLE. Results: 4916 subjects aged 20 years or over were included. 16.52% (812/4916) had a positive screening result for SLE. 12 cases of SLE were detected. The estimated prevalence was 0.21% (95% CI: 0.11, 0.40). SLE was more prevalent in the rural municipalities, with an odds ratio (OR) = 4.041 (95% CI: 1.216, 13.424). Conclusion: The estimated prevalence of SLE in Spain is higher than that described in most international epidemiological studies, but lower than that observed in ethnic minorities in the United States or the United Kingdom
    corecore