La notion de résilience

via La notion de résilience


Improving public transportation systems with self-organization: A headway-based model and regulation of passenger alighting and boarding

Complexity Digest

The equal headway instability?the fact that a configuration with regular time intervals between vehicles tends to be volatile?is a common regulation problem in public transportation systems. An unsatisfactory regulation results in low efficiency and possible collapses of the service. Computational simulations have shown that self-organizing methods can regulate the headway adaptively beyond the theoretical optimum. In this work, we develop a computer simulation for metro systems fed with real data from the Mexico City Metro to test the current regulatory method with a novel self-organizing approach. The current model considers overall system?s data such as minimum and maximum waiting times at stations, while the self-organizing method regulates the headway in a decentralized manner using local information such as the passenger?s inflow and the positions of neighboring trains. The simulation shows that the self-organizing method improves the performance over the current one as it adapts to environmental changes at the timescale…

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The Quest for Cognition in Plant Neurobiology

Plant neurobiology1 has emerged in the last few years as a result of the incorporation of new knowledge from well established areas of research such as plant electrophysiology, cell biology, molecular biology, and ecology. The difference between plant neurobiology and other more basic disciplines resides in the target of these interdisciplinary efforts which is the study of the complex patterns of behavior of plants qua information-processing systems.i Despite the youth of plant neurobiology, a body of empirical literature has grown and new results and questions have been reported and formulated.2–3 Very recently, however, a number of researchers sceptical of the overall effort that plant neurobiology represents have teamed up in order to manifest their concern “with the rationale behind” the approach.4 In their view, the newly born discipline does not furnish plant sciences, writ large, with any deeper understanding that is not in principle empirically achievable by, say, plant physiology.

This unnecessary tension between “lower” and “higher” level disciplines is not new to science. In the cognitive sciences, to take a close example, the neuron doctrine (for a review see ref. 5) claims that cognitive activity can be accounted for exclusively by basic neuroscience. Neuronal structure and function, as identified by neurophysiology, neuroanatomy and neurochemistry, furnish us with all we need to appraise the animal mind/brain complex. This approach ignores the integration of basic neuroscience with the rest of the cognitive science disciplines (psychology, linguistics, anthropology, artificial intelligence, and philosophy), an integration that has proved crucial to the understanding of the behavior of animals qua information-processing systems.6 In view of Alpi et al.’s commentary, we run the risk of importing the aforementioned tension into the plant sciences literature. In general, the problem with reductionist approaches is the failure to recognize that the lower-level branches, conceptually speaking, only make sense in a higher-level (tissue, organ, system, social, etc.) context. In this sense, plant neurobiology differs from plant physiology7 in the same way that cognitive neuroscience8 differs from neurophysiology.

In addition, Alpi et al. target a straw man by interpreting plant neurobiology as suggesting that “higher plants have nerves, synapses, the equivalent of a brain localized somewhere in the roots, and an intelligence” (ref. 4, p. 135). And they continue, “there is no evidence for structures such as neurons, synapses or a brain in plants” (p. 136). In particular, Alpi et al. assume on behalf of plant neurobiologists the equation of auxin transport in plant cells with neuronal networks in animals. I do not wish to enter this empirical debate, although see Refs. 9 and 10 for rejoinders. In what follows I shall rather focus upon a conceptual misunderstanding that underlies Alpi et al.’s line of argument, and whose resolution will hopefully allow us to view the controversial topic of plant intelligence under a different lens.




Aspects of plant intelligence.


Intelligence is not a term commonly used when plants are discussed. However, I believe that this is an omission based not on a true assessment of the ability of plants to compute complex aspects of their environment, but solely a reflection of a sessile lifestyle. This article, which is admittedly controversial, attempts to raise many issues that surround this area. To commence use of the term intelligence with regard to plant behaviour will lead to a better understanding of the complexity of plant signal transduction and the discrimination and sensitivity with which plants construct images of their environment, and raises critical questions concerning how plants compute responses at the whole-plant level. Approaches to investigating learning and memory in plants will also be considered.


The minds of plants From the memories of flowers to the sociability of trees, the cognitive capacities of our vegetal cousins are all around us

At first glance, the Cornish mallow (Lavatera cretica) is little more than an unprepossessing weed. It has pinkish flowers and broad, flat leaves that track sunlight throughout the day. However, it’s what the mallow does at night that has propelled this humble plant into the scientific spotlight. Hours before the dawn, it springs into action, turning its leaves to face the anticipated direction of the sunrise. The mallow seems to remember where and when the Sun has come up on previous days, and acts to make sure it can gather as much light energy as possible each morning. When scientists try to confuse mallows in their laboratories by swapping the location of the light source, the plants simply learn the new orientation.

What does it even mean to say that a mallow can learn and remember the location of the sunrise? The idea that plants can behave intelligently, let alone learn or form memories, was a fringe notion until quite recently. Memories are thought to be so fundamentally cognitive that some theorists argue that they’re a necessary and sufficient marker of whether an organism can do the most basic kinds of thinking. Surely memory requires a brain, and plants lack even the rudimentary nervous systems of bugs and worms.

However, over the past decade or so this view has been forcefully challenged. The mallow isn’t an anomaly. Plants are not simply organic, passive automata. We now know that they can sense and integrate information about dozens of different environmental variables, and that they use this knowledge to guide flexible, adaptive behaviour.

For example, plants can recognise whether nearby plants are kin or unrelated, and adjust their foraging strategies accordingly. The flower Impatiens pallida, also known as pale jewelweed, is one of several species that tends to devote a greater share of resources to growing leaves rather than roots when put with strangers – a tactic apparently geared towards competing for sunlight, an imperative that is diminished when you are growing next to your siblings. Plants also mount complex, targeted defences in response to recognising specific predators. The small, flowering Arabidopsis thaliana, also known as thale or mouse-ear cress, can detect the vibrations caused by caterpillars munching on it and so release oils and chemicals to repel the insects.

Plants also communicate with one another and other organisms, such as parasites and microbes, using a variety of channels – including ‘mycorrhizal networks’ of fungus that link up the root systems of multiple plants, like some kind of subterranean internet. Perhaps it’s not really so surprising, then, that plants learn and use memories for prediction and decision-making.



On the Extraordinary Importance of Complexity

Ontonix QCM Blog


Of all physical quantities, energy is probably the most important. Energy expresses the capacity of a body or a system to perform work. Nature works by using energy to transform matter. This is done via processes (physical, chemical, etc.). However, in order to realize these processes it is necessary to have information. Energy on its own is not sufficient. One must know what to do with it and how to do it. This is where information comes into the picture. Information is stored and delivered in a variety of ways. The DNA, for example, encodes biological information.

Information is measured in bits. Shannon’s Information Theory states that entropy is a measure of information:


Entropy, however, has many facets. While it measures the amount of information necessary in order to describe a system, it also quantifies the amount of disorder contained therein. The above equation is of course for a single…

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The Paradox of Music-Evoked Sadness: A Survey of Personality and Reward

Questo studio esplora l’esperienza della tristezza indotta dall’ascolto della musica. La tristezza è comunemente considerata un’emozione negativa e pertanto evitata nella vita quotidiana. Rimane una questione aperta: perché quindi le persone apprezzano la musica triste? Gli Autori presentano i risultati di uno studio condotto online che ha coinvolto 722 partecipanti occidentali e orientali. Lo studio indaga gli effetti gratificanti delle emozioni tristi evocate dalla musica, nonché l’apporto relativo alle caratteristiche dell’ascoltatore e alle situazioni che contribuiscono all’apprezzamento della musica triste. Lo studio esamina inoltre i differenti principi attraverso i quali la tristezza viene evocata dalla musica e la sua interazione con i tratti della personalità.I risultati mostrano quattro diversi aspetti gratificanti della musica triste: l’effetto dell’immaginazione, la regolazione delle emozioni, l’empatia e l’assenza di implicazioni nella vita reale. Inoltre, l’apprezzamento della musica triste segue una modalità congruente con l’umore ed è più grande tra gli individui con maggiore empatia e minore stabilità emotiva. Sorprendentemente la nostalgia piuttosto che la tristezza è l’emozione più frequente evocata dalla musica triste. Di conseguenza, la memoria è stata valutata come il principio più importante attraverso il quale l’emozione viene evocata dalla musica triste. Infine, il tratto di empatia contribuisce all’evocazione della tristezza attraverso il contagio, l’apprezzamento e il coinvolgimento delle funzioni sociali. I presenti risultati indicano che la risposta emotiva alla musica triste è sfaccettata, modulata dall’empatia e collegata a una esperienza multidimensionale del piacere.

Sorgente: The Paradox of Music-Evoked Sadness: A Survey of Personality and Reward

Time is real? I think not

gennaio: 2018
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