631 research outputs found

    Aging and cognitive control

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    Aging and cognitive control

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    Electron transport in semiconducting carbon nanotubes with hetero-metallic contacts

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    We present an atomistic self-consistent study of the electronic and transport properties of semiconducting carbon nanotube in contact with metal electrodes of different work functions, which shows simultaneous electron and hole doping inside the nanotube junction through contact-induced charge transfer. We find that the band lineup in the nanotube bulk region is determined by the effective work function difference between the nanotube channel and source/drain electrodes, while electron transmission through the SWNT junction is affected by the local band structure modulation at the two metal-nanotube interfaces, leading to an effective decoupling of interface and bulk effects in electron transport through nanotube junction devices.Comment: Higher quality figures available at http://www.albany.edu/~yx15212

    Aging and cognitive control

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    Hidden dependence of spreading vulnerability on topological complexity

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    Many dynamical phenomena in complex systems concern spreading that plays out on top of networks with changing architecture over time -- commonly known as temporal networks. A complex system's proneness to facilitate spreading phenomena, which we abbreviate as its `spreading vulnerability', is often surmised to be related to the topology of the temporal network featured by the system. Yet, cleanly extracting spreading vulnerability of a complex system directly from the topological information of the temporal network remains a challenge. Here, using data from a diverse set of real-world complex systems, we develop the `entropy of temporal entanglement' as a novel and insightful quantity to measure topological complexities of temporal networks. We show that this parameter-free quantity naturally allows for topological comparisons across vastly different complex systems. Importantly, by simulating three different types of stochastic dynamical processes playing out on top of temporal networks, we demonstrate that the entropy of temporal entanglement serves as a quantitative embodiment of the systems' spreading vulnerability, irrespective of the details of the processes. In being able to do so, i.e., in being able to quantitatively extract a complex system's proneness to facilitate spreading phenomena from topology, this entropic measure opens itself for applications in a wide variety of natural, social, biological and engineered systems.Comment: 15 pages, 9 figures, to appear in Phys. Rev.

    Warriors and Peacekeepers: Testing a Biosocial Implicit Leadership Hypothesis of Intergroup Relations Using Masculine and Feminine Faces

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    This paper examines the impact of facial cues on leadership emergence. Using evolutionary social psychology, we expand upon implicit and contingent theories of leadership and propose that different types of intergroup relations elicit different implicit cognitive leadership prototypes. It is argued that a biologically based hormonal connection between behavior and corresponding facial characteristics interacts with evolutionarily consistent social dynamics to influence leadership emergence. We predict that masculine-looking leaders are selected during intergroup conflict (war) and feminine-looking leaders during intergroup cooperation (peace). Across two experiments we show that a general categorization of leader versus nonleader is an initial implicit requirement for emergence, and at a context-specific level facial cues of masculinity and femininity contingently affect war versus peace leadership emergence in the predicted direction. In addition, we replicate our findings in Experiment 1 across culture using Western and East Asian samples. In Experiment 2, we also show that masculine-feminine facial cues are better predictors of leadership than male-female cues. Collectively, our results indicate a multi-level classification of context-specific leadership based on visual cues imbedded in the human face and challenge traditional distinctions of male and female leadership

    Arrival processes in port modeling: insights from a case study

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    This paper investigates the impact of arrival processes on the ship handling process. Two types of arrival processes are considered: controlled and uncontrolled. Simulation results show that uncontrolled arrivals of ships perform worst in terms of both ship delays and required storage capacity. Stock-controlled arrivals perform best with regard to large vessel delays and storage capacity. The combination of stock-controlled arrivals for large vessels and equidistant arrivals for barges also performs better than the uncontrolled process. Careful allocation of ships to the mooring points of a jetty further improves the efficiency

    On the effect of ship arrival processes on jetty and storage capacity

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    Ports provide jetty facilities for ships to load and unload their cargo. Jetty capacity is costly and therefore limited, causing delays for arriving ships. However, ship delays are also costly, so terminal operators attempt to minimize their number and duration. Here, simulation has proved to be a very suitable tool. However, in port simulation models, the impact of the arrival process of ships on the model outcomes tends to be underestimated. This report considers three arrival processes: stock-controlled, equidistant, and uncontrolled. We assess how their deployment in a port simulation model,based on data from a real case study, affects the efficiency of the loading and unloading process, making a case for careful modeling of arrival processes in port simulations. Uncontrolled, which is an assumed arrival process property in many client-oriented simulations, actually performs worst in terms of both ship delays and required storage capacity. Stock-controlled arrivals perform best with regard to large vessel delays and storage capacity. Additional control of the arrival process through the application of a priority scheme in processing ships further impacts efficiency in all three cases

    Quantifying agent impacts on contact sequences in social interactions

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    Human social behavior plays a crucial role in how pathogens like SARS-CoV-2 or fake news spread in a population. Social interactions determine the contact network among individuals, while spreading, requiring individual-to-individual transmission, takes place on top of the network. Studying the topological aspects of a contact network, therefore, not only has the potential of leading to valuable insights into how the behavior of individuals impacts spreading phenomena, but it may also open up possibilities for devising effective behavioral interventions. Because of the temporal nature of interactions - since the topology of the network, containing who is in contact with whom, when, for how long, and in which precise sequence, varies (rapidly) in time - analyzing them requires developing network methods and metrics that respect temporal variability, in contrast to those developed for static (i.e., time-invariant) networks. Here, by means of event mapping, we propose a method to quantify how quickly agents mingle by transforming temporal network data of agent contacts. We define a novel measure called 'contact sequence centrality', which quantifies the impact of an individual on the contact sequences, reflecting the individual's behavioral potential for spreading. Comparing contact sequence centrality across agents allows for ranking the impact of agents and identifying potential 'behavioral super-spreaders'. The method is applied to social interaction data collected at an art fair in Amsterdam. We relate the measure to the existing network metrics, both temporal and static, and find that (mostly at longer time scales) traditional metrics lose their resemblance to contact sequence centrality. Our work highlights the importance of accounting for the sequential nature of contacts when analyzing social interactions
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