745 resultados para Neo-Fuzzy Neuron


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The major cities of the Neo-Assyrian Empire were not only home to impressive palaces and temples, but they were also equipped with strong fortifications. The city walls were not only meant to keep out potential enemies, but by demonstrating Assyria’s power to any approaching person, they served an ideological purpose, as well. However, military efficiency was just as crucial, since, over its entire history, the empire repeatedly faced internal and external threats and could not have afforded to lose any of its urban centers which were essential to maintaining control over the various provinces or geographic regions associated with them. The study of Neo-Assyrian fortifications relies on evidence provided by archaeological excavations, the study of Assyrian reliefs and information from cuneiform texts. Even though these sources help us reconstruct the appearance of the town defenses, the question of why the individual fortification systems were built in a specific way cannot be addressed by these means alone. Remote sensing offers an opportunity to view the course and placement of the city walls within their topographical context. Furthermore, geographical information systems (GIS) offer a tool to illustrate the distribution of the strongly fortified Assyrian towns, thereby allowing us to recognize patterns and functions of regional fortification systems during the Neo-Assyrian period.

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This paper gives an insight into cognitive computing for smart cities, resulting in cognitive cities. Cognitive cities and cognitive computing research with the underlying concepts of knowledge graphs and fuzzy cognitive maps are presented and supported by existing tools (i.e., IBM Watson and Google Now) and intended tools (meta-app). The paper illustrates FCM as a suiting instrument to represent information/knowledge in a city environment driven by human-technology interaction, enforcing the concept of cognitive cities. A proposed paper prototype combines the findings of the paper and shows the next step in the implementation of the proposed meta-app.

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Mechanisms underlying motor neuron subtype-selective endoplasmic reticulum (ER) stress and associated axonal pathology in amyotrophic lateral sclerosis (ALS) remain unclear. Here we show that the molecular environment of the ER between motor neuron subtypes is distinct, with characteristic signatures. We identify cochaperone SIL1, mutated in Marinesco-Sjögren syndrome (MSS), as being robustly expressed in disease-resistant slow motor neurons but not in ER stress-prone fast-fatigable motor neurons. In a mouse model of MSS, we demonstrate impaired ER homeostasis in motor neurons in response to loss of SIL1 function. Loss of a single functional Sil1 allele in an ALS mouse model (SOD1-G93A) enhanced ER stress and exacerbated ALS pathology. In SOD1-G93A mice, SIL1 levels were progressively and selectively reduced in vulnerable fast-fatigable motor neurons. Mechanistically, reduction in SIL1 levels was associated with lowered excitability of fast-fatigable motor neurons, further influencing expression of specific ER chaperones. Adeno-associated virus-mediated delivery of SIL1 to familial ALS motor neurons restored ER homeostasis, delayed muscle denervation and prolonged survival.

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Die Organisation und die strategische Kommunikation von Wahlkämpfen haben sich in den letzten Jahrzehnten in den meisten westeuropäischen Staaten gewandelt, so auch in der Schweiz. Die Kommunikationswissenschaft hat dafür den Begriff der „Professionalisierung“ geprägt und Eigenschaften zusammengetragen, die zu einem „professionalisierten“ Wahlkampf gehören – wie z.B. die Beauftragung von externen Expertinnen und Experten oder die direkte Ansprache von Wählerinnen und Wählern („narrowcasting“). Welche Hintergründe diese Professionalisierung aber hat und wie das Phänomen nicht nur praktisch zu beschreiben, sondern auch theoretisch zu begründen ist, wurde bisher kaum diskutiert. Hier setzt die vorliegende Dissertation an. Basierend auf einer Analyse von 23 Wahlkämpfen aus den Kantonen Aargau, Appenzell Ausserrhoden, Bern, Neuchâtel und Zürich mithilfe der Methode Fuzzy Set Qualitative Comparative Analysis (fsQCA) kommt sie zum Schluss, dass die Professionalisierung der Wahlkämpfe vor dem theoretischen Hintergrund des soziologischen Neo-Institutionalismus als Anpassung von Wahlkämpfen an sich verändernde Bedingungen, Erwartungen und Anforderungen in den wichtigsten Anspruchsgruppen oder „Umwelten“ für den Wahlkampf (Wählerinnen und Wähler, Mitglieder, Medien, andere Parteien) definiert werden kann. Daraus folgt, dass es nicht nur „die“ Professionalisierung gibt, sondern dass jeder Wahlkampf an jene Umwelten angepasst wird, wo diese Anpassung den Wahlkampfverantwortlichen am dringlichsten erscheint. Daher sollte Professionalisierung mit vier einzelnen Messinstrumenten bzw. Professionalisierungsindices – einem pro Umwelt – gemessen werden. Misst man Professionalisierung wie bisher üblich nur mit einem einzigen Messinstrument, gibt der resultierende Wert nur ein ungenaues Bild vom Grad der Professionalisierung des Wahlkampfs wieder und verschleiert, als Anpassung an welche Umwelt die Professionalisierung geschieht. Hat man ermittelt, wie professionalisiert ein Wahlkampf im Hinblick auf jede der vier relevantesten Umwelten ist, können dann auch zuverlässiger die Gründe analysiert werden, die zur jeweiligen Professionalisierung geführt haben. Die empirische Analyse der kantonalen Wahlkämpfe bestätigte, dass hinter der Professionalisierung in Bezug auf jede der vier Umwelten auch tatsächlich unterschiedliche Gründe stecken. Wahlkämpfe werden in Bezug auf die Ansprache der Wähler angepasst („professionalisiert“), wenn sie in urbanen Kontexten stattfinden. Den Wahlkampf im Hinblick auf die Mitglieder zu professionalisieren ist besonders wichtig, wenn die Konkurrenz zwischen den Parteien gross ist oder wenn eine Ansprache der Gesamtwählerschaft für eine Partei wenig gewinnbringend erscheint. Die Professionalisierung des Wahlkampfes in Bezug auf die Medien erfolgt dann, wenn er eine grosse, regional stark verteilte oder aber eine urbane Wählerschaft ansprechen muss. Für die Professionalisierung der Wahlkämpfe gegenüber anderen Parteien kann kein aussagekräftiger Schluss gezogen werden, da nur wenige der untersuchten Kantonalparteien ihre Wahlkämpfe überhaupt im Hinblick auf andere Parteien professionalisierten, indem sie die gegnerischen Wahlkämpfe beobachteten und den eigenen wenn nötig entsprechend anpassten.

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Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.

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The new computing paradigm known as cognitive computing attempts to imitate the human capabilities of learning, problem solving, and considering things in context. To do so, an application (a cognitive system) must learn from its environment (e.g., by interacting with various interfaces). These interfaces can run the gamut from sensors to humans to databases. Accessing data through such interfaces allows the system to conduct cognitive tasks that can support humans in decision-making or problem-solving processes. Cognitive systems can be integrated into various domains (e.g., medicine or insurance). For example, a cognitive system in cities can collect data, can learn from various data sources and can then attempt to connect these sources to provide real time optimizations of subsystems within the city (e.g., the transportation system). In this study, we provide a methodology for integrating a cognitive system that allows data to be verbalized, making the causalities and hypotheses generated from the cognitive system more understandable to humans. We abstract a city subsystem—passenger flow for a taxi company—by applying fuzzy cognitive maps (FCMs). FCMs can be used as a mathematical tool for modeling complex systems built by directed graphs with concepts (e.g., policies, events, and/or domains) as nodes and causalities as edges. As a verbalization technique we introduce the restriction-centered theory of reasoning (RCT). RCT addresses the imprecision inherent in language by introducing restrictions. Using this underlying combinatorial design, our approach can handle large data sets from complex systems and make the output understandable to humans.

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Dieser Artikel bietet einen Überblick über die Entwicklung und Zusammenhänge der einzelnen Elemente der Fuzzy-Logik, wovon Fuzzy-Set-Theorie die Grundlage bildet. Die Grundproblematik besteht in der Handhabung von linguistischen Informationen, die häufig durch Ungenauigkeit gekennzeichnet sind. Die verschiedenen technischen Anwendungen von Fuzzy-Logik bieten eine Möglichkeit, intelligentere Computersysteme zu konstruieren, die mit unpräzisen Informationen umgehen können. Solche Systeme sind Indizien für die Entstehung einer neuen Ära des Cognitive-Computing, di in diesemArtikel ebenfalls zur Sprache kommt. Für das bessere Verständnis wird der Artikel mit einem Beispiel aus der Meteorologie (d. h. Schnee in Adelboden) begleitet.

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Synchronizing mind maps with fuzzy cognitive maps can help to handle complex problems with many involved stakeholders by taking advantage of human creativity. The proposed approach has the capacity to instantiate cognitive cities by including cognitive computing. A use case in the context of decision-finding (concerning a transportation system) is presented to illustrate the approach.

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Amyotrophic lateral sclerosis (ALS) is an adult onset progressive motor neuron disease with no cure. Transgenic mice overexpressing familial ALS associated human mutant SOD1 are a commonly used model for examining disease mechanisms. Presently, it is well accepted that alterations in motor neuron excitability and spinal circuits are pathological hallmarks of ALS, but the underlying molecular mechanisms remain unresolved. Here, we sought to understand whether the expression of mutant SOD1 protein could contribute to altering processes governing motor neuron excitability. We used the conformation specific antibody B8H10 which recognizes a misfolded state of SOD1 (misfSOD1) to longitudinally identify its interactome during early disease stage in SOD1G93A mice. This strategy identified a direct isozyme-specific association of misfSOD1 with Na+/K+ATPase-α3 leading to the premature impairment of its ATPase activity. Pharmacological inhibition of Na+/K+ATPase-α3 altered glutamate receptor 2 expression, modified cholinergic inputs and accelerated disease pathology. After mapping the site of direct association of misfSOD1 with Na+/K+ATPase-α3 onto a 10 amino acid stretch that is unique to Na+/K+ATPase-α3 but not found in the closely related Na+/K+ATPase-α1 isozyme, we generated a misfSOD1 binding deficient, but fully functional Na+/K+ATPase-α3 pump. Adeno associated virus (AAV)-mediated expression of this chimeric Na+/K+ATPase-α3 restored Na+/K+ATPase-α3 activity in the spinal cord, delayed pathological alterations and prolonged survival of SOD1G93A mice. Additionally, altered Na+/K+ATPase-α3 expression was observed in the spinal cord of individuals with sporadic and familial ALS. A fraction of sporadic ALS cases also presented B8H10 positive misfSOD1 immunoreactivity, suggesting that similar mechanism might contribute to the pathology.

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Alien plants provide a unique opportunity to study evolution in novel environments, but relatively little is known about the extent to which they become locally adapted to different environments across their new range. Here, we compare northern and southern populations of the introduced species Senecio squalidus in Britain; S. squalidus has been in southern Britain for approximately 200 years and reached Scotland only about 50 years ago. We conducted common garden experiments at sites in the north and south of the species’ range in Britain. We also conducted glasshouse and growth chamber experiments to test the hypothesis that southern genotypes flower later, are more drought-tolerant, germinate and establish better at warmer temperatures, and are less sensitive to cold stress than their more northern counterparts. Results from the common garden experiments are largely consistent with the hypothesis of rapid adaptive divergence of populations of the species within the introduced range, with genotypes typically showing a home-site advantage. Results from the glasshouse and growth chamber experiments demonstrate adaptive divergence in ability to tolerate drought stress and high temperatures, as well as in phenology. In particular, southern genotypes were more tolerant of dry conditions and high temperatures and they flowered later than northern genotypes. Our results show that rapid local adaptation can occur in alien species, and they have implications for our understanding of the ecological genetics of range expansion of introduced weeds.

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This paper presents a conceptual approach to enhance knowledge management by synchronizing mind maps and fuzzy cognitive maps. The use of mind maps allows taking advantage of human creativity, while the application of fuzzy cognitive maps enables to store information expressed in natural language. By applying cognitive computing, it makes possible to gather and extract relevant information out of a data pool. Therefore, this approach is supposed to give a framework that enhances knowledge management. To demonstrate the potential of this framework, a use case concerning the development of a smart city app is presented.

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Neuronal outgrowth has been proposed in many systems as a mechanism underlying memory storage. For example, sensory neuron outgrowth is widely accepted as an underlying mechanism of long-term sensitization of defensive withdrawal reflexes in Aplysia. The hypothesis is that learning leads to outgrowth and consequently to the formation of new synapses, which in turn strengthen the neural circuit underlying the behavior. However, key experiments to test this hypothesis have never been performed. ^ Four days of sensitization training leads to outgrowth of siphon sensory neurons mediating the siphon-gill withdrawal response in Aplysia . We found that a similar training protocol produced robust outgrowth in tail sensory neurons mediating the tail siphon withdrawal reflex. In contrast, 1 day of training, which effectively induces long-term behavioral sensitization and synaptic facilitation, was not associated with neuronal outgrowth. Further examination of the effect of behavioral training protocols on sensory neuron outgrowth indicated that this structural modification is associated only with the most persistent forms of sensitization, and that the induction of these changes is dependent on the spacing of the training trials over multiple days. Therefore, we suggest that neuronal outgrowth is not a universal mechanism underlying long-term sensitization, but is involved only in the most persistent forms of the memory. ^ Sensory neuron outgrowth presumably contributes to long-term sensitization through formation of new synapses with follower motor neurons, but this hypothesis has never been directly tested. The contribution of outgrowth to long-term sensitization was assessed using confocal microscopy to examine sites of contact between physiologically connected pairs of sensory and motor neurons. Following 4 days of training, the strength of both the behavior and sensorimotor synapse and the number of appositions with follower neurons was enhanced only on the trained side of the animal. In contrast, outgrowth was induced on both sides of the animal, indicating that although sensory neuron outgrowth does appear to contribute to sensitization through the formation of new synapses, outgrowth alone is not sufficient to account for the effects of sensitization. This indicates that key regulatory steps are downstream from outgrowth, possibly in the targeting of new processes and activation of new synapses. ^