Preserved to preservative free prostaglandin analogues in primary open angle glaucoma

Glaucoma affecting 60 million people all over the world and it will be 80 million till 2020. There are approximately 11.2 million persons aged 40 years and older with glaucoma in India. Primary open angle glaucoma (POAG) is commonest type, affecting 2/3rd of glaucoma patients. POAG is estimated to affect 6.48 million persons. The estimated number with primary angle-closure glaucoma is 2.54 million.POAG develops gradually and take long time to get detected and require long term treatment with topical prostaglandin analogues (PGF2) which is the most common as well as most widely used drugs. These PGF2 analogues need to be taken for longer time and more prone to develop adverse drug reactions. Common ADR seen with PG analogues are irritation on instillation, foreign body sensation, dryness of eyes, pain in eye, increased pigmentation of iris, increased eyelash growth, changes in periorbital sulcus and fat. Some ADRs (Adverse Drug Reaction) are explained by the inherent properties of Prostaglandins and those are not explained are because of preservative used in medication and these ADRs can be minimised by using preservative free drug like Tafluprost which are having same efficacy in decreasing IOP

Mapping wildland-urban interfaces at large scales integrating housing density and vegetation aggregation for fire prevention in the South of France

Every year, more than 50,000 wildland fires affect about 500,000 ha of vegetation in southern European countries, particularly in wildland-urban interfaces (WUI). This paper presents a method to characterize and map WUIs at large scales and over large areas for wildland fire prevention in the South of France. Based on the combination of four types of building configuration and three classes of vegetation structure, 12 interface types were classified. Through spatial analysis, fire ignition density and burned area ratio were linked with the different types of WUI. Among WUI types, isolated WUIs with the lowest housing density represent the highest level of fire risk

Négociation bilatérale par concession : un état de l'art

National audienceConflicts are intrinsic characteristics of multi-agent systems which can be solved by negotiation. This paper presents a state of the art on multi-agent negotiation by focusing on its most elementary variant : bilateral concession-based negotiation. We provide an analysis grid based on : i) the negotiation environment (object, stakeholders, protocol and strategies) ; ii) the expected properties of the outcome ; and iii) those of the process.Les conflits constituent une caractéristique intrinsèque des systèmes multi-agents qui peut être résolu par la négociation. Cet article présente un état de l'art de la négociation multi-agents en mettant l'accent sur sa variante la plus élémentaire : la négociation bilatérale par concession. Nous fournissons ici une grille d'analyse qui distingue : i) l'environnement de négociation (objectifs, parties prenantes, protocole et stratégies) ; ii) les propriétés attendues du résultat ; et iii) celles du processus

The hedgehog and the fox An argumentation-based decision support system

Nous présentons dans cet article un Système d'Aide à la Décision (SDA). À cette intention, nous proposons un cadre d'argumentation pour le raisonnement pratique. Celui-ci s'appuie sur un langage logique qui sert de stucture de données concrète afin de représenter les connaisances, les buts et les décisions possibles. Différentes priorités y sont associées afin de de représenter la fiabilité des connaisances, les préférences de l'utilisateur, et l'utilité espérée des alternatives. Ces structures de données constitue l'épine dorsale des arguments. De part la nature abductive du raisonnement pratique, les arguments sont construits à partir des conclusions. De plus, nous les défi- nissons comme des structures arborescentes. De cette manière, notre SDA suggère à l'utilisateur les meilleures solutions et propose une explication interactive et compréhensible de ce choix. We present here a Decision Support System (DSS). For this purpose, we propose an Argumentation Framework for practical reasoning. A logic language is used as a concrete data structure for holding the statements like knowledge, goals, and actions. Different priorities are attached to these items corresponding to the reliability of the knowledge, the preferences between goals, and the expected utilities of alternatives. These concrete data structures consist of information providing the backbone of arguments. Due to the abductive nature of practical reasoning, we build arguments by reasoning backwards. Moreover, arguments are defined as tree-like structures. In this way, our DSS suggests some solutions and provides an interactive and intelligible explanation of the choices. Decision making is the cognitive process leading to the selection of a course of action among alternatives based on estimates of the values of those alternatives. Indeed, when a human identifies her needs and specifies them with high-level and abstract terms, there should be a way to select an existing solution. Decision Support Systems (DSS) are computer-based systems that support decision making activities including expert systems and Multi-Criteria Decision Analysis (MCDA). In this paper, we propose a DSS which suggests some solutions and provides an interactive and intelligible explanation of the choices. In this paper, we present our Decision Support System (DSS). This computer system is built upon an Argumentation Framework (AF) for decision making. For this purpose, we consider practical reasoning as the vehicle of decision making, which is a knowledge-based, goal-oriented, and action-related reasoning. A logic language is used as a concrete data structure for holding the statements like knowledge, goals, and actions. Different priorities are attached to these items corresponding to the reliability of the knowledge, the preferences between goals, and the expected utilities of alternatives. These concrete data structures consist of information providing the backbone of arguments. Due to the abductive nature of practical reasoning, arguments are built by reasoning backwards. Moreover, arguments are defined as tree-like structures. In this way, our DS

Cadre d'argumentation bayésien

International audienc

Assumption-Based Argumentation for the Minimal Concession Strategy

Several recent works in the area of Artificial Intelligence focus on computational models of argumentation-based negotiation. However, even if computational models of arguments are used to encompass the reasoning of interacting agents, this logical approach does not come with an effective strategy for agents engaged in negotiations. In this paper we propose a realisation of the Minimal Concession (MC) strategy which has been theoretically validated. The main contribution of this paper is the integration of this intelligent strategy in a practical application by means of assumption-based argumentation. We claim here that the outcome of negotiations, which are guaranteed to terminate, is an optimal agreement (when possible) if the agents adopt the MC strategy

Auto-adaptation dans l'architecture V3A par une argumentation sur les motivations propres

10 pagesInternational audienc

Extraction automatique d'objets nécessaires à la cartographie des interfaces habitat-forêt en région française méditerranéenne

[Departement_IRSTEA]GT [TR1_IRSTEA]SET / RICOMEDIn the french mediterranean region, forest fire risk increases because of dynamics of land cover: fuel load accumulation due to agricultural fallows and non exploited forest, urbanisation expansion. Urbanization joined to the forest extension phenomenon, generates new spatial configurations called wildland urban interfaces (WUI) (Jappiot et al., 2002; Lampin et al., 2006). WUI concerns integrate "natural" vegetation connected to urban systems which bring out both components of forest fire risk: hazard (breaking out probability, distribution) and vulnerability (Blanchi et al., 2002). As these interfaces should extend in the next years, assessing forest fire risk in the WUI is a need for wildfire prevention and land management. To characterize wildland urban interfaces, satellite images allow us to work on large and spectral homogeneous areas that was not possible on aerial photos. Traditional classifications per-pixel were adapted to high resolution images (10 m) but do not let working on textural information appearing on very high resolution satellite images. Characterizing and mapping WUI need to extract involved shapes like houses or roads for urban features, but also involved textures like scrublands or forest with different densities of trees for natural features. A lot of papers uses feature extraction or segmentation programs on homogeneous areas to detect specific objects: man-made (Sithole and Vosselman, 2006), burnt area (Mitri and Gitas, 2004) or fuel mapping (Gitas, 2006). In our case, we need to extract these objects in heterogeneous contexts where natural, agricultural and artificial features are interconnected. This paper presents a methodology, using remote sensing in pre-fire planning: automated feature extraction to map an accurate and reliable land cover required to characterize WUI at a large scale. The study area is located in the Meyreuil district near Aix en Provence (South of France). A Quickbird image taken in June 2006 was acquired. A principal component merge between 0.6 panchromatic and 2.4 multispectral Quickbird images was done to retain the spectral information of the four Quickbird MS bands. A feature extraction program, Feature Analyst 4.1® for Erdas Imagine®, was tested in the framework of the FireParadox European research program. Using multiple spatial attributes (size, shape, texture, pattern, spatial association) with spectral information, this software improves considerably automated detection of involved land cover structures. Vegetation classes integrate the texture of the objects: arrangement of pixels with different radiometry, shadows, etc. Mineral objects can be easily identified only if they have a specific shape (that is not the case of roads here), otherwise it is difficult as algorithms used by Feature Analyst® are unknown