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Après 35 jours de développement, la résistance membranaire de deux variétés de Soja (Harosoy et Adoc) a été étudiée en mesurant le flux d'électrolytes (par conductiVité) et le flux de phosphate inorganique lors de la réhydratation des disques foliaires préalablement soumis, pendant 4 h, à un choc osmotique (en présence de polyéthylène-glycol). La résistance membranaire étant inversement corrélée aux flux d'ions, il a été ainsi démontré que les plantes de la variété Adoc sont plus résistantes à une sécheresse modérée que celles de la variété Harosoy. L'analyse des lipides foliaires a montré qu'un défi ci t hydrique modéré (-0,9 à -1,1 MPa) provoque une augmentation de la quantité d'acides gras totaux (plus importante chez la variété Adoc) et notamment celle de l'acide linolénique dans les triacylglycérols et les phosphatidylcholines. Relationships among membrane resistance and the leaf lipid compositions oftwo varieties of Soya under hydrie stress After 35 days of development, membrane resistance was determined in two varieties (Harosoy and Adoc) by mesuring ion flux (by conductimety) and inorganique phosphate, during rehydration of foliar disks which had been submitted for 4 hrs to an osmotic shock (in presence of polyethylene glycol). Membrane resistance being inversely related to ion effiux, it has been shown that plants from the Adoc variety were more resistant to moderate drought than those from the Harosoy variety. Analysis ofIeafIipids has shown that moderate water deficit (-0,9 to -1,1 MPa) induced an increase in the quantity of total fatty acids more prononced in Adoc plants than in Harosoy plants. This is accompanied by an increase oflinolenic acid in triacylglycerols and in phosphatidylcholines.

It remains difficult for mobile robots to continue accurate self-localization when they are suddenly teleported to a location that is different from their beliefs during navigation. Incorporating insights from neuroscience into developing a spatial cognition model for mobile robots may make it possible to acquire the ability to respond appropriately to changing situations, similar to living organisms. Recent neuroscience research has shown that during teleportation in rat navigation, neural populations of place cells in the cornu ammonis-3 region of the hippocampus, which are sparse representations of each other, switch discretely. In this study, we construct a spatial cognition model using brain reference architecture-driven development, a method for developing brain-inspired software that is functionally and structurally consistent with the brain. The spatial cognition model was realized by integrating the recurrent state-space model, a world model, with Monte Carlo localization to infer allocentric self-positions within the framework of neuro-symbol emergence in the robotics toolkit. The spatial cognition model, which models the cornu ammonis-1 and -3 regions with each latent variable, demonstrated improved self-localization performance of mobile robots during teleportation in a simulation environment. Moreover, it was confirmed that sparse neural activity could be obtained for the latent variables corresponding to cornu ammonis-3. These results suggest that spatial cognition models incorporating neuroscience insights can contribute to improving the self-localization technology for mobile robots. The project website is https://nakashimatakeshi.github.io/HF-IGL/., Competing Interests: HY was employed by The Whole Brain Architecture Initiative. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Nakashima, Otake, Taniguchi, Maeyama, El Hafi, Taniguchi and Yamakawa.)