From Citizen to Cytizen. How to Escape from Cyberstates?

The Modern Western state is characterized by unmediated individual access to wellness, health, safety and liberal human rights. The Newtonian conception of space and time makes formal room for a discursive public area with the citizen and the public institutes in the margin, while participation and ethical responsibility is a prejudice of good citizenship. It is a necessary condition of consistency and coherence of the nation. To date, global migration and multiculturalism threaten those necessary basic conditions of Western states´ political equilibrium. To challenge the actual global phenomena national states transform into virtual places of fear dominated by cybernetics, digital bureaucracy while citizen’s identity is mirrored by the efficiency and unisexual beauty ideal of cyborgs. The substantive conception of technology is government’s tool box to realize the cyberstate while citizen reduce to “cytizen”.In order to escape from this global grey, we propose a different conception of space and time namely the Leibnizian conception of pluralistic independent participating worlds. Moreover, we modify Leopold’s Land-Ethics by introducing the transpersonal identification claim of Warwick Fox inside the common Land so-called eco-homeland while the care for the foreigner serves as paradigmatic core attitude to all participants of the eco-homeland. So we constitute a common eco-refuge, similar to the ideas of Bookchin´s eco- anarchistic ideas but avoiding his dialectic ideal conception of the Land and its participants

Eco-refuges as Anarchist’s Promised Land or the End of Dialectical Anarchism

Since the early Medieval Time people contested theological legitimation and rational discursive discours on authority as well as retreated to refuges to escape from any secular or ecclesiastical authority. Modern attempts formulated rational legitimation of authority in several ways: pragmatic authority by Monteigne, Bodin and Hobbes, or the contract authority of Locke and Rousseou. However, Enlightened Anarchism, first formulated in 1793 by the English philosopher William Godwin fulminated against all rational restrictions of human freedom and self-determination. However, we do not analyze anarchism by the ‘what’ and the ‘why’, but by looking for the best actual approach of Anarchist’s ‘Promised Land’. Furthermore, we follow the footsteps of Thoreau’s Walden Pond experiment considered as a place of salvation and prototype of 19th century romantic’s extreme individualism towards Leopold’s ethics of the land. Indeed, Thoreau’s and later Muir’s concepts of refuges are tightly connected to territorial and temporal bio-regional constraints and imply an internally organized public area based on mutualism and Hannah Arendt’s agape. From these ideas of refuges, Aldo Leopold formulated his Land-ethics that claimed integrity and autonomy of the ‘Land’. His foundation is a prototype of the eco-centric free space version of eco-anarchism as formulated by Bookchin. In order to formulate a philosophical foundation of eco-anarchism we reject Newtonian homogeneous space-temporal conception, preceding the whole Modern discours about authority and state. On the contrary, we adopt the pluralistic Leibnizian space-time from which thinking-humans do not dissociate themselves, but participate as part of the rational infrastructure of eco-refuges. In eco-refuges, citizen belong to the civil society that stays in equilibrium with the landscape and all forms of biological life. Space is the boundary condition of human activity and determines how borders, environmental organization and institutes are sustained. Space has its proper essence of sustainability, unity and integrity. The individual feelings of security are embedded in a timelike tradition and evolution of the free space, while individual particular conceptions of space and time integrate into the social processes of identification with the refuge. Therefore, the creation of eco-refuges transforms the actual world of national authorities into a world of anarchistic democratic eco-regional homelands

Towards a neural hierarchy of time scales for motor control

Animals show remarkable rich motion skills which are still far from realizable with robots. Inspired by the neural circuits which generate rhythmic motion patterns in the spinal cord of all vertebrates, one main research direction points towards the use of central pattern generators in robots. On of the key advantages of this, is that the dimensionality of the control problem is reduced. In this work we investigate this further by introducing a multi-timescale control hierarchy with at its core a hierarchy of recurrent neural networks. By means of some robot experiments, we demonstrate that this hierarchy can embed any rhythmic motor signal by imitation learning. Furthermore, the proposed hierarchy allows the tracking of several high level motion properties (e.g.: amplitude and offset), which are usually observed at a slower rate than the generated motion. Although these experiments are preliminary, the results are promising and have the potential to open the door for rich motor skills and advanced control

Assessment of post-fire changes in land surface temperature and surface albedo, and their relation with fire-burn severity using multitemporal MODIS imagery

This study evaluates the effects of the large 2007 Peloponnese (Greece) wildfires on changes in broadband surface albedo (a), daytime land surface temperature (LSTd) and night-time LST (LSTn) using a 2-year post-fire time series of Moderate Resolution Imaging Spectroradiometer satellite data. In addition, it assesses the potential of remotely sensed a and LST as indicators for fire-burn severity. Immediately after the fire event, mean a dropped up to 0.039 (standard deviation = 0.012) (P < 0.001), mean LSTd increased up to 8.4 (3.0) K (P < 0.001), and mean LSTn decreased up to -1.2 (1.5) K (P < 0.001) for high-severity plots (P < 0.001). After this initial alteration, fire-induced changes become clearly smaller and seasonality starts governing the a and LST time series. Compared with the fire-induced changes in a and LST, the post-fire NDVI drop was more persistent in time. This temporal constraint restricts the utility of remotely sensed a and LST as indicators for fire-burn severity. For the times when changes in a and LST were significant, the magnitude of changes was related to fire-burn severity, revealing the importance of vegetation as a regulator of land surface energy fluxes

The Properties of Terrestrial Laser System Intensity for Measuring Leaf Geometries: A Case Study with Conference Pear Trees (Pyrus Communis)

Light Detection and Ranging (LiDAR) technology can be a valuable tool for describing and quantifying vegetation structure. However, because of their size, extraction of leaf geometries remains complicated. In this study, the intensity data produced by the Terrestrial Laser System (TLS) FARO LS880 is corrected for the distance effect and its relationship with the angle of incidence between the laser beam and the surface of the leaf of a Conference Pear tree (Pyrus Commmunis) is established. The results demonstrate that with only intensity, this relationship has a potential for determining the angle of incidence with the leaves surface with a precision of ±5° for an angle of incidence smaller than 60°, whereas it is more variable for an angle of incidence larger than 60°. It appears that TLS beam footprint, leaf curvatures and leaf wrinkles have an impact on the relationship between intensity and angle of incidence, though, this analysis shows that the intensity of scanned leaves has a potential to eliminate ghost points and to improve their meshing

Optoelectronic Reservoir Computing

Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing time dependent data. The basic scheme of reservoir computing consists of a non linear recurrent dynamical system coupled to a single input layer and a single output layer. Within these constraints many implementations are possible. Here we report an opto-electronic implementation of reservoir computing based on a recently proposed architecture consisting of a single non linear node and a delay line. Our implementation is sufficiently fast for real time information processing. We illustrate its performance on tasks of practical importance such as nonlinear channel equalization and speech recognition, and obtain results comparable to state of the art digital implementations.Comment: Contains main paper and two Supplementary Material

Information processing using a single dynamical node as complex system

Novel methods for information processing are highly desired in our information-driven society. Inspired by the brain's ability to process information, the recently introduced paradigm known as 'reservoir computing' shows that complex networks can efficiently perform computation. Here we introduce a novel architecture that reduces the usually required large number of elements to a single nonlinear node with delayed feedback. Through an electronic implementation, we experimentally and numerically demonstrate excellent performance in a speech recognition benchmark. Complementary numerical studies also show excellent performance for a time series prediction benchmark. These results prove that delay-dynamical systems, even in their simplest manifestation, can perform efficient information processing. This finding paves the way to feasible and resource-efficient technological implementations of reservoir computing

Reservoir Computing Approach to Robust Computation using Unreliable Nanoscale Networks

As we approach the physical limits of CMOS technology, advances in materials science and nanotechnology are making available a variety of unconventional computing substrates that can potentially replace top-down-designed silicon-based computing devices. Inherent stochasticity in the fabrication process and nanometer scale of these substrates inevitably lead to design variations, defects, faults, and noise in the resulting devices. A key challenge is how to harness such devices to perform robust computation. We propose reservoir computing as a solution. In reservoir computing, computation takes place by translating the dynamics of an excited medium, called a reservoir, into a desired output. This approach eliminates the need for external control and redundancy, and the programming is done using a closed-form regression problem on the output, which also allows concurrent programming using a single device. Using a theoretical model, we show that both regular and irregular reservoirs are intrinsically robust to structural noise as they perform computation