L'aporie ou l'expérience métaphysique de la dualité dans le "Peri Archôn" de Damaskios

Le traité Apories et résolutions touchant les premiers principes , rédigé en langue grecque par Damaskios (Damas, 462 AD (?) (?)), dernier Diadoque de l école néoplatonicienne d Athènes, nous permet de penser que nous touchons ici à l apogée de la pensée de cet auteur et à la cime jamais atteinte par la philosophie grecque elle-même. Damaskios développe dans ce traité une véritable voie aporétique, héritier en cela d une longue tradition philosophique. Mais que faut-il entendre sous ce terme d aporie ? Bien plus que des pièges où tombe la pensée humaine, elles sont les limites éprouvées de celle-ci. Ce n est pas tant le fait brut de l aporie qui taraude ce métaphysicien, mais la raison de leur présence. Quelle est la source des apories concernant les premiers principes ? Le traité de Damaskios nous semble être le lieu privilégié où convergent deux interrogations fondamentales : Pourquoi la pensée éprouve-t-elle des difficultés à penser les principes premiers ? Et comment franchir les limites de notre pensée ? Ce qui revient à se demander ce que signifient exactement pour nous ces limites. La question qui surgit derrière chaque aporie est au fond celle des conditions de possibilités de la pensée humaine . Au moyen de multiples apories, nous montrerons que Damaskios cherche à nous faire éprouver ce que l on pourrait appeler une expérience métaphysique de la dualité , en vue d établir une connaissance à la fois de nous-mêmes et de la distance qui nous sépare des Principes suprêmes. Notre intention est donc de saisir le sens et de comprendre le rôle de la notion d aporie dans la métaphysique damaskienne.The work entitled Aporias and resolutions concerning the first principles , written in Greek language by Damaskios (Damas, 462 (?) AD (?)), the last Diadoch of the Neoplatonic Athenian School, allows us to think that we reach here not only the peak of the thought of this author, but also the peak never attained by Greek philosophy before. In this treatise, he develops a real aporetical way, based on a long philosophical tradition. But how to understand this term aporia ? Much more than traps where falls human thought, aporias are the limits of thought itself. It is not the very presence of aporias that annoys this metaphysician, but the reason of their presence. What is the source of aporias concerning the first principles? The work of Damaskios seems to be the privileged place where two fundamental questionings converge: Why is thought always in difficulties while attempting to grasp the first principles? And how to cross or exceed the limits of human thought? That means wondering what those limits mean exactly for us. The question which appears behind every aporia is really that about the conditions of possibilities of human thought. By means of the numerous aporias of the treatise, we are going to show that Damaskios invites us to perceive a metaphysical experience of duality, to be aware of ourselves and to understand the reason of the distance which separates us from the supreme Principles. Our intention is thus to grasp the role of the central notion of aporia and its positive signification in Damaskios metaphysics.PARIS-EPHE-Sciences religieuses (751052336) / SudocSudocFranceF

Insect interaction analysis based on object detection and CNN

International audienceDirect observation to study biodiversity can be time consuming, however, other methods often provide indirect measurements and are possibly biased. To solve these problems, images can be a useful tool and ecologists have started to rely more and more on images as a source of data and on automated image analysis. However, the existing methods mostly perform image classification. In this paper we present an efficient method based on object detection to access deeper information the content of an image. Using high resolution images, we built a pipeline to slice the original images, perform detections and later refine these observations. We illustrate the interest of this pipeline by using it on-field images taken in agroforestery banana-coffee systems to study invertebrate communities around the banana pests Cosmopolites sodidus and Metamasius sp. and the interactions between the different animals within this community. Experimental results show that our pipeline reaches 87.8% F1-score and allows us to successfully detect and identify 23 species and ant castes. These 23 species are divided into 7 super-classes, but the ant super-class, that shows more individuals and interactions is described more precisely. We are then able to study the interaction network between different species of this community and identify major predators of banana pests within this ecosystem

Hierarchical Classification of Very Small Objects: Application to the Detection of Arthropod Species

International audienceAutomated image analysis and deep learning tools such as object detection models are being used increasingly by biologists. However, biological datasets often have constraints that are challenging for the use of deep learning. Classes are often imbalanced, similar, or too few for robust learning. In this paper we present a robust method relying on hierarchical classification to perform very small object detection. We illustrate our results on a custom dataset featuring 22 classes of arthropods used to study biodiversity. This dataset shows several constraints that are frequent when using deep learning on biological data with a high class imbalance, some classes learned on only a few training examples and a high similarity between classes. We propose to first perform detection at a super-class level, before performing a detailed classification at a class level. We compare the obtained results with our proposed method to a global detector, trained without hierarchical classification. Our method succeeds in obtaining a mAP of 75 %, while the global detector only achieves a mAP of 48 %. Moreover, our method shows high precision even on classes with the less train examples. Confusions between classes with our method are fewer and are of a lesser impact. We are able achieve a more robust object classification with the use of our proposed method. This method can also enable better control on the model's output which can be particularly valuable when handling ecological, biological or medical data for example

Caught on camera: Field imagery reveals the unexpected importance of vertebrates for biological control of the banana weevil (Cosmopolites sordidus Col. Curculionidae)

International audienceUnderstanding of ecological interactions is necessary for the application of biological control. Banana is the second most produced fruit worldwide and the banana weevil (Cosmopolites sordidus) is the most important pest of banana and plantain. Its biological control remains challenging because of the robustness and cryptic behaviour of the adult and the hidden development of larval stages. Researchers therefore tend to favour conservation biological control of this pest. The commonly used methods for measuring the effects of natural enemies on the regulation of this pest focus on invertebrates and may underestimate the role of vertebrates on biological control. Using cameras, we recorded the predation of sentinel adult weevils in banana plots in La Réunion island that differed in weevil infestation levels and in animal biodiversity. To facilitate image analysis, we used background subtraction to isolate moving parts of image sequences and thus detect predators and predation events. Our cameras recorded only vertebrates as predators of adult banana weevils. The most important predator appeared to be the Asian shrew (Suncus murinus), which was responsible for 67% of the predation events. Other predators included the house mouse (Mus musculus), the oriental garden lizard (Calotes versicolor), and the guttural toad (Sclerophrys gutturalis). The exact time of predation events were determined from the images metadata. It was thus possible to identify predator foraging periods that coincided with activity of adult weevils. Our results confirm that images provide useful information for biological and ecological studies. Along with other recent studies, our results suggest that the role of vertebrates in biological control may be underestimated. Based on these results, we advocate for several management implications such as the installation of hedges, grasslands, and ponds to favour these vertebrate predators of the banana weevil, possibly also favouring other vertebrate and invertebrate natural enemies

Data from: CORIGAN: Assessing multiple species and interactions within images

1.Images are resourceful data for ecologists and can provide a more complete information than other methods to study biodiversity and the interactions between species. Automated image analysis however often relies on extensive datasets, not implementable by small research teams. We are here proposing an object detection method that allows the analysis of high‐resolution images containing many animals interacting in a small dataset. 2.We developed an image analysis pipeline named ‘CORIGAN' to extract the characteristics of animal communities. CORIGAN is based on the YOLOv3 model as the core of object detection. To illustrate potential applications, we use images collected during a sentinel prey experiment. 3.Our pipeline can be used to detect, count and study the physical interactions between various animals. On our example dataset, the model reaches 86.6% precision and 88.9% recall at the species level or even at the caste level for ants. The training set required fewer than 10 h of labelling. Based on the pipeline output it was possible to build the trophic and non‐trophic interactions network describing the studied community. 4.CORIGAN relies on generic properties of the detected animals and can be used for a wide range of studies and supports. Here, we study invertebrates on high‐resolution images, but the same processing can be transferred for the study of larger animals on satellite or aircraft images

Corigan testing dataset

93 images from on-field sentinel experiments. These image files are associated with labelled files. These files have been used to test the Yolov3 detection model (Redmon & Farhadi 2018), which constitutes the core of the CORIGAN pipeline. For more details on data and CORIGAN, see the related manuscript and supplementary materials in Methods in Ecology & Evolution

Corigan training dataset

95 images from on-field sentinel experiments. These image files are associated with labelled files. These files have been used to train the Yolov3 detection model (Redmon & Farhadi 2018), which constitutes the core of the CORIGAN pipeline. For more details on data and CORIGAN, see the related manuscript and supplementary materials in Methods in Ecology & Evolution