The microglial "activation" continuum: from innate to adaptive responses

Microglia are innate immune cells of myeloid origin that take up residence in the central nervous system (CNS) during embryogenesis. While classically regarded as macrophage-like cells, it is becoming increasingly clear that reactive microglia play more diverse roles in the CNS. Microglial "activation" is often used to refer to a single phenotype; however, in this review we consider that a continuum of microglial activation exists, with phagocytic response (innate activation) at one end and antigen presenting cell function (adaptive activation) at the other. Where activated microglia fall in this spectrum seems to be highly dependent on the type of stimulation provided. We begin by addressing the classical roles of peripheral innate immune cells including macrophages and dendritic cells, which seem to define the edges of this continuum. We then discuss various types of microglial stimulation, including Toll-like receptor engagement by pathogen-associated molecular patterns, microglial challenge with myelin epitopes or Alzheimer's β-amyloid in the presence or absence of CD40L co-stimulation, and Alzheimer disease "immunotherapy". Based on the wide spectrum of stimulus-specific microglial responses, we interpret these cells as immune cells that demonstrate remarkable plasticity following activation. This interpretation has relevance for neurodegenerative/neuroinflammatory diseases where reactive microglia play an etiological role; in particular viral/bacterial encephalitis, multiple sclerosis and Alzheimer disease

Agent-based model with asymmetric trading and herding for complex financial systems

Background: For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. Methods: To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. Results: With the model parameters determined for six representative stock-market indices in the world respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. Conclusions: We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries.Comment: 17 pages, 6 figure

Robustness of Random Graphs Based on Natural Connectivity

Recently, it has been proposed that the natural connectivity can be used to efficiently characterise the robustness of complex networks. Natural connectivity quantifies the redundancy of alternative routes in a network by evaluating the weighted number of closed walks of all lengths and can be regarded as the average eigenvalue obtained from the graph spectrum. In this article, we explore the natural connectivity of random graphs both analytically and numerically and show that it increases linearly with the average degree. By comparing with regular ring lattices and random regular graphs, we show that random graphs are more robust than random regular graphs; however, the relationship between random graphs and regular ring lattices depends on the average degree and graph size. We derive the critical graph size as a function of the average degree, which can be predicted by our analytical results. When the graph size is less than the critical value, random graphs are more robust than regular ring lattices, whereas regular ring lattices are more robust than random graphs when the graph size is greater than the critical value.Comment: 12 pages, 4 figure

Design methodology and implementation of fully passive RFID SoC with temperature sensor

Diese Dissertation stellt die Methodik und die Implementierung eines vollständig passiven RFID SoC mit Temperatursensor zur Reduzierung von Versorgungsrauschen für eine hochgenaue drahtlose Temperaturmessung vor. Die Analyse der modernen eigenständigen Temperatursensoren und der drahtlosen RFID Temperatursensoren zeigt eine Design Herausforderung, dass die RFID Sensoren aufgrund der RFID Kommunikation erheblich unter dem Versorgungsrauschen leiden. Um die Sensorgenauigkeit zu verbessern, ohne zu viele Kompromisse einzugehen, stellt diese Dissertation die folgenden wissenschaftlichen Beiträge vor. Zuerst wird ein Zeitdomain Niederspannungs Niederleistungs Temperatursensor vorgeschlagen, um eine hohe Genauigkeit zu erreichen, ohne einen hochkomplexen Sigma Delta ADC mit niedriger Abtastrate zu verwenden. Darüber hinaus wird die Methodik zur Analyse von Versorgungsrauschen für die Erzeugung, Verstärkung und Digitalisierung des Versorgungsrauschens entwickelt. Die Analyseergebnisse zeigen, dass das Versorgungsrauschen über ein breites Frequenzspektrum verteilt ist, während das Rauschen im Kommunikationsfrequenzband durch das Power Management Unit verstärkt wird. Für die Analyse der Rauschdigitalisierung erreicht dieser vorgeschlagene Temperatursensor die beste DC Versorgungsempfindlichkeit seiner Klasse, während er noch unter Wechselstromwelligkeit leidet. Daher wird das durch die RFID Kommunikation erzeugte Versorgungsrauschen die Sensorleistung erheblich beeinflussen. Die abschließende Optimierung auf Systemebene wird durch die Einführung eines seriellen Auslesekommandos erreicht, das das Versorgungsrauschen für die Sensorauslesung deutlich reduziert. Die experimentellen Ergebnisse zeigen, dass dieser vorgeschlagene RFID Temperatursensor die Genauigkeit von ±0.4 °C (3 sigma) von 0 °C bis 125 °C erreicht. Die ist höchste Genauigkeit mit dem größten Arbeitsbereich im Vergleich zu den derzeit berichteten modernen RFID Temperatursensoren. Der neue RFID Befehl verbessert die Auflösung dieses RFID Temperatursensors um den Faktor 16.This dissertation presents the methodology and implementation of a fully passive RFID SoC with temperature sensor to reduce supply noise for high accurate wireless temperature measurement. The analysis of the state-of-the-art stand-alone temperature sensors and the RFID wireless temperature sensors reveals a design challenge that the RFID sensors suffer significantly from the supply noise, due to the RFID communication. In order to improve sensor accuracy without making too many compromises, this dissertation presents the following scientific contributions. First, a time-domain low-voltage low-power temperature sensor is proposed to achieve high accuracy without using a highly complex Sigma Delta ADC with low sampling rate. In addition, the methodology for the analysis of supply noise is developed for the generation, the amplification and the digitization of the supply noise. The analysis results show that the supply noise is distributed over a wide frequency spectrum, while the noise in the communication frequency band is amplified by the power management unit. For the analysis of noise digitization by the sensors, this proposed temperature sensor achieves the best-in-class DC supply sensitivity while it still suffers from AC ripple. Therefore, the supply noise generated by RFID communication will significantly affect the sensor performance. The final optimization at system level is achieved by introducing a serial readout command that significantly reduces the supply noise for the sensor readout. The experimental results show that this proposed RFID temperature sensor achieves ±0.4 °C (3 sigma) from 0 °C to 125 °C, which is the highest accuracy with the largest operational range compared to the currently reported state-of-the-art RFID temperature sensors. The new RFID command improves the resolution of this RFID temperature sensor by a factor of 16